Renewable and Sustainable Energy Transitions for Countries with Different Climates and Renewable Energy Sources Potentials

energies

Article Renewable and Sustainable Energy Transitions for Countries with Different Climates and Renewable Energy Sources Potentials

Haichao Wang 1,2, Giulia Di Pietro 3, Xiaozhou Wu 1,*, Risto Lahdelma 2, Vittorio Verda 3 and Ilkka Haavisto 4 1 Institute of Building Environment and Facility Engineering, School of Civil Engineering, Dalian University of Technology, Dalian 116024, China; [email protected] or haichao.wang@aalto.fi 2 Department of Mechanical Engineering, Aalto University School of Engineering, P.O. BOX 14100, FI-00076 Aalto, Finland; risto.lahdelma@aalto.fi 3 Dipartimento Energia, Politecnico di Torino, Corso Duca degli Abruzzi 2, 10129 Torino, Italy; [email protected] (G.D.P.); [email protected] (V.V.) 4 Condens Heat Recovery Oy, Puhelinkatu 12, 13110 Hämeenlinna, Finland; ilkka.haavisto@condens.fi * Correspondence: [email protected]

Received: 21 September 2018; Accepted: 10 December 2018; Published: 18 December 2018

Abstract: Renewable energy sources (RES) are playing an increasingly important role in energy markets around the world. It is necessary to evaluate the benefits from a higher level of RES integration with respect to a more active cross-border transmission system. In particular, this paper focuses on the sustainable energy transitions for Finland and Italy, since they have two extreme climate conditions in Europe and quite different profiles in terms of energy production and demand. We developed a comprehensive energy system model using EnergyPLAN with hourly resolution for a reference year for both countries. The models include electricity, heat and transportation sectors. According to the current base models, new scenarios reflecting an RES increase in total fuel consumption have been proposed. The future shares of renewables are based on each nation’s potential. The outcomes of the new scenarios support the future national plans, showing how decarburization in an energy system can occur in relation to the European Roadmap 2030 and 2050. In addition, possible power transmission between Italy and Finland were investigated according to the vision of an integrated European energy system with more efficient cross-border activities.

Keywords: renewable energy sources (RES); energy transition; energy system modelling; optimization

1. Introduction The transition from conventional energy sources towards a renewable and sustainable energy system is currently the subject of much discussion throughout the world [1]. The liberalization of the energy market was introduced in EU at the end of 20th century, and in 2011 the European Commission [2] decided that no member state should remain isolated from electricity and gas networks after the year 2015. European countries should share their natural resources, especially in a complementary manner among neighbors, and act together to achieve lower energy costs. However, the previous century was characterized by centralized and large-scale power plants using traditional fossil fuels to supply power to limited surrounding areas. This paradigm has gradually been superseded by distributed energy systems (DES), which are becoming more popular, especially as the share of renewable energy sources (RES) continually increases in the energy market [3]. New EU targets specify that the share of RES should increase year by year with respect to future energy management, and this is also a reﬂection of the low carbon emission policy, such as the Paris Agreement, which is

Energies 2018, 11, 3523; doi:10.3390/en11123523 www.mdpi.com/journal/energies Energies 2018, 11, 3523 2 of 32 supported by the United Nations Framework Convention on Climate Change (UNFCCC). In addition, RES will play a relevant role in the energy market by affecting electricity prices [4,5]. Each power supplier sells electricity at a marginal cost of production and the market price is set according to the mechanism of merit order [6]. All renewable energies have nearly zero marginal costs; and the other costs, mainly operating costs, are also quite low. RES are the first choice in the ranking of merit order, which helps form a cost-effective electricity market [4,5]. Nowadays, RES account for 23.5% of all electricity and comprise 14% of the energy sector in the EU. The number of installations and investments in RES will increase in the near future, because the EU would like to be the world leader in the utilization of RES [5]. The future energy frameworks for 2030–2050 are based on the development of renewable energies and securing their supply. To achieve this objective, the EU’s Energy 2020 strategies should be fulfilled, with the agreed targets being reached by 2020 [7]. This strategy has always been working according to the already achieved results; in 2012, greenhouse gas emissions were reduced by 18% in comparison to 1990 levels. The share of RES was 13% greater than the total primary energy consumption, bringing 44% of the world’s renewable electricity to the EU. Meanwhile, the energy intensity and carbon density of the EU’s economy decreased by 24% and 28%, respectively [7]. Such progress formed the starting point to defining the 2030 policy framework, where the European Energy market should be able to achieve a 40% reduction in greenhouse gas emissions (also compared to the 1990 level). Meanwhile, renewable energy consumption should account for at least 27% in the total energy structure, and at least 27% in energy savings should be achieved compared to the business-as-usual scenario [7]. Furthermore, the European Commission also set a long-term energy policy via the Energy Roadmap 2050, where the environmental aspect plays a central role. The new scenario is an ambitious one for reducing greenhouse gas emissions by 80%–95%. The year 2050 is presently a timely benchmark for the policies to address this climatic challenge, which could encourage greater low-carbon investments in each sector [8,9]. In light of such developments, the EU Emissions Trading System (EU ETS) is working to combat greenhouse gas emissions by opening a trading market. The system covers 45% of the total greenhouse gas emissions and it is open for all EU members as well as Iceland, Liechtenstein, and Norway [10]. Child and Breyer [11] discussed the definition of transition and transformation in terms of energy systems, and they suggested that changes of physical forms be denoted as transformations, while changes to large socio-technical systems as transitions, when highlighting the ways that society motivates, facilitates, and benefits from the change on a higher level. Energy transition is being discussed more extensively in many countries and regions of the world, not only due to the depletion of fossil fuels, but also because of the challenge of climate change and irreversible pollution [12]. Reducing the use of fossil fuels while promoting RES is crucial for attaining the sustainable development goals [13]. Ruppert-Winkel et al. [14] developed a heuristic three-phase-model (3PM) for regional energy transition simulation, and it was successfully used in three case studies in Germany. They focused on how the transition towards a local, renewable energy-based system could be implemented in Marin County. Lange et al. [15] analyzed the transition to marine renewable energies based on the Irish governance setup and the current capacity. They believed that the situation of the governance setup and power balances across domains should be studied for the energy transition, which is reflected in this research as analyzing the benchmark case and transition scenarios based on the RES potentials. Lind and Espegren [16] showed how the city of Oslo can assume the lead in sustainable energy transition through innovative ideas and solutions. They analyzed various energy and climate measures and their potential to transform Oslo into a low-carbon city. These studies built case specific models for cases, but they mainly focused on the local energy transition in a city level, which cannot reflect the situation of the whole country. Guidolin and Guseo [17] studied some quantitative aspects of the energy transition in Germany. Especially they analyzed the competition and substitution between nuclear power and renewable energies. Anil et al. [18] addressed an hourly model for Turkey’s energy transition until 2050 towards 100% renewable energy considering electricity Energies 2018, 11, 3523 3 of 32 demand development, technical and financial assumptions and resource availability of RES. Mediavilla et al. [19] studied the transition towards renewable forms of energy in Spain. They used a dynamic model to evaluate the depletion patterns of world fossil fuels and their possible replacement by RES. Zakeri et al. [20] proposed a market-based energy system model to simulate Nordic and German energy markets using MATLAB. They examined the impact of integrating a variable renewable energy in Germany with the Nordic power market in terms of power transmission and electricity price. Vidadili et al. [21] explored sustainable development in Azerbaijan through the transition to renewable energy and proposed appropriate measures to shift the country away from oil-based production. Although these studies have provided insights into the proper energy transition in terms of different energy forms, there are also limitations. One is that few studies considered the energy supply and demand data with hourly resolution for the country level when modelling the energy transition. The other is that the energy transition models did not consider the RES potentials in the long run or they were not accurate even reflecting the current energy market as the base case. All these problems will be fixed in this paper to make the long term energy transition model more accurate the reliable. China has also been making intensive efforts to address energy transition and climate change issues because of the huge amount of energy consumption and greenhouse gas emissions. Chai and Zhang [22] highlighted the energy dilemma in China’s modernization process and studied the technological and policy options for making the transition to a sustainable energy system in China using a low carbon energy model (LCEM). They concluded that China needs to take further actions to strengthen the research and development of innovative sustainable energies, to create stronger economic incentives for them, and to improve the integration levels. Sun et al. [23,24] analyzed the role of RES in China’s sustainable energy transition, and presented that renewable energy development is required to reach the Intended Nationally Determined Contribution (INDC) for the post-2020 period. They reviewed the potential of renewable energy in China and how it could be utilized to meet the INDC goals. Eight alternative scenarios with 40% renewable electricity are explored using the EnergyPLAN. The results show that renewables can help reach the 20% share of non-fossil energy in primary energy and 40%–50% share in electricity production. But China still should implement new policies to promote integrated development of wind and solar power. Several other Asian countries, such as India [25,26], Thailand [27], Japan and Korea, are also adopting their own measures to achieve sustainable energy transitions [28]. Mohammad and Khan [29] studied how one of the most non-renewable countries—Saudi Arabia—is acting concerning the global challenge of energy supply vs. resources for energy generation, emphasizing the use of solar energy. In addition, some researchers also tried to evaluate the effects of social and political aspects on the renewable energy transition. Dóci et al. [30] reported that renewable energy communities are grassroots initiatives that contribute to meet consumption needs and environmental goals and thus conduce to the spread of renewables. Therefore they explored the potential of renewable energy communities as social niches to contribute to the energy system transition. For this purpose, they propose three proxies for measuring the transition potential of social niches based on technological innovations from literature. Steg et al. [31] also considered the human dimensions of the sustainable energy transition, and they propose a general framework to understand and encourage sustainable energy behaviors. Dumas et al. [32] however studied the political issues arising from the energy transition and indicated the effects of political competition on the renewable energy transition in the long run. These studies promoted the energy transition studies in Asia, but unfortunately the models did not consider the possible power transmission between neighbouring countries, and the proper aggregation method for energy supply and demand considering different climate zones in each country. Therefore, this study proposed a novel aggregation method which can be used to map the local energy supply and demands to the country level. It was widely acknowledged that the future energy systems should integrate more and more RES to respond to the climate change. This is also the important way to the efficient energy systems, which gradually abandons the fossil fuels. According to the literature review, previous studies usually Energies 2018, 11, 3523 4 of 32 focused on one sector or part of the energy market, however, the energy transition study should consider the energy supplies and demands of the whole energy market. Sometimes it is quite difficult to obtain the detailed energy supply and demand data for several energy sectors in the country level, therefore, this study proposed an aggregation method to scale up the energy profiles based on the typical data of typical cities. Few researchers had considered the energy transition considering the relatively accurate profiles of supplies and demands in hourly resolution as well as RES potentials in the country level. Therefore, this paper tries to bridge the above mentioned gaps by studying the renewable and sustainable energy transition for two countries with different profiles in the supplies and demands, RES potentials as well as the different climates by using the EnergyPLAN. We will define the base scenarios and energy transition scenarios with different RES shares for two countries according to the RES potentials, and to examine whether and how the transitions could happen, and their influences to climate change. The possible interlinks between the two countries are also considered in the energy system modelling in order to examine the possible influences of the energy transmission and more efficient cross-border activities on the energy transition. These are the main new contributions to the existing pool of knowledge in this respect. Since the transition to RES is becoming more extensive, it is necessary to model and simulate the transition for a wider region than just one sector or one country, especially when considering the different climate conditions and different portfolios of energy supply and demand data. Therefore, the objective of this study is to model the actual energy markets for different climate regions, taking Italy and Finland as examples since they have two extreme climate conditions in the EU and very different supply and demand profiles. In addition, Finland is one of the leading countries in RES utilization, while Italy has a larger potential market for integrating RES solutions. This paper analyzes the different energy policies, the energy balances, and the final energy consumption rates for a chosen reference year in both countries considering the different energy transition scenarios. The energy system models were developed using EnergyPLAN, and future possible RES integration scenarios for both countries were introduced by changing the model inputs regarding the share and portfolio of renewables. The impact of the share of RES on the total energy consumption and total CO2 emissions are also analyzed. Moreover, the model can be used to analyze whether the two countries could be complementary in terms of electricity demand and market price in a future European market regarding cross-border power transmission.

2. General Comparison of the Climate Conditions and Populations of Italy and Finland Italy is located in southern Europe and its climate is highly diverse due to the varied terrain. Italy has seven different climatic zones, ranging from humid subtropical, humid continental, oceanic, to warm and temperate Mediterranean, with average winter temperatures varying from 0 ◦C on the Alps to 12 ◦C on the islands, but temperatures can climb up to 30 ◦C in some areas [33]. At the end of 2013, Italy had more than 60.7 million inhabitants and a population density of 202 persons per square kilometer, though not at all equally distributed throughout the country [34]. Finland, which lies in the boreal zone, is one of the world’s northernmost countries, and it is characterized by warm summers and cold winters. The country has two different continental climates: a temperate continental climate, which is inﬂuenced by the moderating effects of the Baltic Sea, and a cool continental climate in the Arctic region of the north. The winter season is long, with snow covering the land until late March or even April, and the temperature can fall to −30 ◦C even in the coastal areas, whereas the average summer temperature remains above 10 ◦C[35]. The population of Finland is currently 5.5 million, mostly concentrated in the southern parts of the country. It has a population density of 18 persons per square kilometer, which is the lowest in the EU [36]. In addition, Finland’s nominal GDP per capita is almost double that of Italy [34,35]. From a European perspective, and when thinking about the integral European energy market, an energy market analysis can be an interesting point of comparison. The differences in climate and Energies 2018, 11, 3523 5 of 32 populations are linked to different heating, cooling, and electricity demands. The different locations affect energy resources and the criteria for choosing a speciﬁc energy transition pathway.

3. Energy System Modeling for Italy EnergyPLAN version 11.4 was adopted for energy system modeling, since it was developed to model planning strategies for different energy systems based on technical and economic analyses. Energies 2018, 11, x 5 of 31 The model can be applied on a national level as well as a local one, and it is possible to include a wideThe m varietyodel can of be energy applied technologies on a national and level to as specify well as thea local types one, of and desired it is possible interactions to include between a wide the heatingvariety and of electricityenergy technologies systems [36 and]. The to specify model the implementation types of desired phase interactions starts with between filling outthe inputheating data sheets,and electricity which mainly systems include: [36]. The (1) demand:model implementation the annual demands phase starts for electricity,with filling annual out input productions data sheets, and demandswhich mainly for heating include: and (1) cooling, demand: fuel the consumption annual demands for heating, for electricity, industry, transport,annual productions and non-energy and uses;demands (2) supply: for heating installed and capacitycooling, fuel of each consumption energy technology for heating, for industry, electricity transport, and heat and production, non-energy for centraluses; power(2) suppl plantsy: installed as well capacity as for intermittent of each energy renewable technology sources for electricity and fuel consumptionand heat production, in each plant;for (3)central cost: fuel power costs, plants fixed as and well variable as for intermittent costs for each renewable installed sources technology. and fuel The consumption analysis was in each carried plant; out using(3) cost: an hourly fuel costs, resolution fixed and for variable the chosen costs for reference each installe yeard of technology. 2013. It is possibleThe analysis to choose was carried between out a technicalusing an energy hourly system resolution analysis for the and chosen a market-economic reference year energy of 2013. system It is possible analysis, to andchoose the between last step a has to dotechnical with regulations energy system and analysis final results, and a which market consist-economic of energy energy balances, system analysis, levels of and fuel the consumption, last step has to do with regulations and final results, which consist of energy balances, levels of fuel CO2 emissions, and system cost calculations. consumption, CO2 emissions, and system cost calculations. 3.1. Demand Data 3.1. Demand Data 3.1.1. Electricity Demand 3.1.1. Electricity Demand According to International Energy Agency (IEA), Italy is the fourth largest electricity consumer According to International Energy Agency (IEA), Italy is the fourth largest electricity consumer in Europe after Germany, France, and the UK [33]. In 2013, the electricity demand in Italy was in Europe after Germany, France, and the UK [33]. In 2013, the electricity demand in Italy was 318.5 318.5 TWh, as declared by TERNA (Rete Elettrica Nazionale), the Italian electricity transmission TWh, as declared by TERNA (Rete Elettrica Nazionale), the Italian electricity transmission system system operator [37]. From the website of the European Network of Transmission System Operators operator [37]. From the website of the European Network of Transmission System Operators (ENTSO—E) it is possible to download the country package for the reference year and obtain the (ENTSO—E) it is possible to download the country package for the reference year and obtain the hourly distribution of the electricity demand [38]. The hourly electricity demand of Italy in 2013 is hourly distribution of the electricity demand [38]. The hourly electricity demand of Italy in 2013 is shownshown in Figurein Figure1. This 1. This electricity electricity demand demand also also includes includes electric electric heating heating and cooling. and cooling. The figure The figure shows thatshows the trend that wasthe trend smooth was throughout smooth throughout the year, with the peaksyear, with in the peaks last monthsin the last of the months year becauseof the year of the needbecause for artificial of the need lighting for andartificial during lighting the warmest and during summer the warmest period becausesummer of period the demand because for of coolerthe air,demand most of whichfor cooler was air, satisfied most by of electrical which was technologies. satisfied by The electrical cross-border technologies. exchange The varies cross every-border year, dependingexchange onvaries the nationalevery year, production. depending on the national production.

FigureFigure 1. 1.Hourly Hourly electricityelectricity demand of of Italy Italy in in 2013. 2013.

Energies 2018, 11, 3523 6 of 32

3.1.2. Heat Demand The total heat demand is the sum of the heat demand for individual heating and district heating. Approximately 66% of Italian families use independent heating sources via a type of technology Energies 2018, 11installed, x in their own ﬂat, while only 15% of them use a centralized heating system [39]. Natural gas 6 of 31 and biomass are the preferred energy sources for individual heating, and they account for 83% of analyzed forthe the total production fuel consumption, of domestic as shown hot in Figure water2[ 40(DHW)]. The input [41 data]. Accor for individualding to heatingItalian is National linked Agency for New Technologies,to the annual fuel Energy consumption and (TWh/year) Sustainable for each Economic type of boiler Development technology. Furthermore, (ENEA) [ in42 the], an average individual heating input data sheet, the solar thermal contribution to each type of boiler must be 2 yearly solar analyzedthermal for energy the production density of domesticof 700 kWh/m hot water (DHW) can be [41 chosen]. According as the to Italian base Nationalpoint and Agency the estimated solar thermalfor energy New Technologies, input for Energy individual and Sustainable heating Economic is 2.3 Development TWh/year (ENEA) [41]. [The42], an amount average yearly of heat storage has been chosensolar thermal for one energy day density based of 700 on kWh/m the typical2 can be chosen dimensions as the base of point a water and the tankestimated for solar an individual thermal energy input for individual heating is 2.3 TWh/year [41]. The amount of heat storage has been building [43chosen]. for one day based on the typical dimensions of a water tank for an individual building [43].

Figure 2. Fuel consumption for individual heating in Italy. Figure 2. Fuel consumption for individual heating in Italy. In Italy, district heating is a rather young technology compared to other European countries. In Italy,According district to h theeating annual is report a rather of the Italianyoung Association technology of Urban compared Heating (AIRU), to other 209 grids European were in countries. operation and district heating was active in 179 municipalities throughout the northern regions and in According tocertain the annual parts of centralreport Italy of inthe 2013 Italian [44]. InAssociation 2013, the Italian of districtUrban heating Heating production (AIRU), was 209 10,966 grids were in operation andGWh, district while theheating thermal was energy active needed in to 179 fulfill municipalities the heat demand throughout was 9200 GWh the [44]. no Inrthern addition, regions and in certain partsthe heat of central demand inputItaly data in 2013 sheet requests[44]. In yearly 2013, heat the demand Italian data district both for heating individual production heating and was 10,966 for district heating. It is much more difficult to find reliable data for the total heat demand in Italy as GWh, while the thermal energy needed to fulfill the heat demand was 9200 GWh [44]. In addition, well as in other European countries. However, we can use some aggregated methods to calculate them the heat demandas follows. input data sheet requests yearly heat demand data both for individual heating and for district heating.Italy hasIt is six much major climatemore difficult zones [45], to depending find reliable on the heating data for degree the days total (HDD) heat [46 demand,47] and in Italy as well as in othertundra European climate zone countries. above the tree However, line in the Alps.we can Therefore use itsome is not aggregated easy to study commonmethods heat to calculate demand behavior during the year. The 8000 Italian municipalities are spread across six major climate them as follows.zones. To model the heat demand distribution, one city in each climate zone has been selected as Italy hasshown six major in Table 1climate. Zone A andzones tundra [45] climate, depending zone are so on small the that heating no city wasdegree chosen days for the (HDD model.) [46,47] and tundra climateIn addition, zone thereabove are the few municipalitiestree line in in the Zone Alps. F compared Therefore to Zone it E; is therefore, not easy they to are study included common in heat Zone E in the heat demand calculation. demand behavior during the year. The 8000 Italian municipalities are spread across six major climate zones. To model the heat demand distribution, one city in each climate zone has been selected as shown in Table 1. Zone A and tundra climate zone are so small that no city was chosen for the model. In addition, there are few municipalities in Zone F compared to Zone E; therefore, they are included in Zone E in the heat demand calculation.

Table 1. Classification of the climate zones.

Zone HDD Typical City A <600 / B 601–900 Messina C 901–1400 Napoli D 1401–2100 Rome E 2101–3000 Milan F >3001 /

First, we calculate the heat demand distribution for each typical city using the hourly temperatures (HDD) of that city, and then we obtained the annual heat demand for each person living in the city per year. Therefore we can get the heat demand distribution for the climate zone represented by the city. Finally the total heat demand distribution is calculated by the summation of all heat demand in different climate zones. The hourly temperatures of the reference year for each typical city can be found in Wunderground [48] and other detailed data can be found for Messina

Energies 2018, 11, 3523 7 of 32

Table 1. Classiﬁcation of the climate zones.

Zone HDD Typical City A <600 / B 601–900 Messina C 901–1400 Napoli D 1401–2100 Rome E 2101–3000 Milan F >3001 /

QMessina − Qtap Qcity = × HDDcity + Qtap (1) HDDMessina where Qcity is the annual heat demand for a specific city in MWh/person·year; HDD are the heating degree days for a specific city; Qtap is the heat demand needed for hot water production, usually presumed to be 30% of the heat demand for a specific city [46]. Therefore, the annual heat demand for the typical city in each zone has been calculated and is shown in Table2.

Table 2. Annual heat demands of the typical cities.

Zone City HDD Heat Demand (TWh/Year) B Messina 707 15.34 C Naples 1034 12.64 D Rome 1415 6.8 E Milan 2402 1.0

Hereafter, we can scale up the hourly distribution for each city using the HDD distribution for that particular city and the number of inhabitants in each zone. The same procedure has been applied to estimate the hourly heat demand distribution in Zones D, E, and F. Finally, the annual heat demand for the whole country is the sum of the estimated annual heat demand in each zone, as shown in Figure3. It clearly shows that the heat load is highly dependent on the climate, and in summer time when space heating is not needed, the heat load will maintain a minimum but stable level for the DHW preparation. Energies 2018, 11, x 7 of 31

[49]. It is also possible to deduce the heat demand per person for Naples, Rome, and Milan by using Equation (1) if only hourly temperatures are available: QQ Messina tap QQcity HDD city  tap (1) HDDMessina

where Qcity is the annual heat demand for a specific city in MWh/person·year; HDD are the heating degree days for a specific city; Qtap is the heat demand needed for hot water production, usually presumed to be 30% of the heat demand for a specific city [46]. Therefore, the annual heat demand for the typical city in each zone has been calculated and is shown in Table 2.

Table 2. Annual heat demands of the typical cities.

Zone City HDD Heat demand (TWh/year) B Messina 707 15.34 C Naples 1034 12.64 D Rome 1415 6.8 E Milan 2402 1.0

Hereafter, we can scale up the hourly distribution for each city using the HDD distribution for that particular city and the number of inhabitants in each zone. The same procedure has been applied to estimate the hourly heat demand distribution in Zones D, E, and F. Finally, the annual heat demand for the whole country is the sum of the estimated annual heat demand in each zone, as shown in Figure 3. It clearly shows that the heat load is highly dependent on the climate, and in summer time Energieswhen2018 space, 11, 3523heating is not needed, the heat load will maintain a minimum but stable level for the8 of 32 DHW preparation.

FigureFigure 3. 3.Hourly Hourly heatheat demanddemand distribution in in Italy. Italy.

3.1.3.3.1.3. Cooling Cooling Demand Demand AccordingAccording to to the the National National Institute Institute for for Statistics Statistics (ISTAT), only only one one-third-third of of families families have have air air conditioningconditioning (AC) (AC) systems systems [ 39[39].]. Many Many ofof thethe buildingsbuildings do do not not even even have have an an AC AC system. system. In Ingeneral, general, thethe most most common common AC AC technologies technologies areare heat pumps pumps (HP) (HP) and and ele electricity.ctricity. The The electricity electricity for cooling for cooling is is estimatedestimated to be be equal equal to to 18 18 TWh/year TWh/year in in southern southern Europe Europe [50 [50].]. The The cooling cooling from from district district heating heating involvesinvolves transporting transporting heat heat to to the the users users and and locallylocally producing cooled cooled water water via via absorption absorption HP, HP, driven driven byby hot hot and and superheated superheated water. water. It It is is not not so so popular popular because of of the the high high costs costs for for transport transport and and production,production, limited limited working working times, times, andand thethe lowlow retailretail price. However, However, we we estimate estimate that that the the annual annual coolingcooling production production is is 105 105 GWh, GWh, but but consideringconsidering the losses related related to to the the network, network, 102 102 GWh GWh is isthe the actualEnergiesactual energy2018 energy, 11, inputx input of of the the network network [ 44[44].]. 8 of 31

3.1.4. Industry and Other Fuel Consumption The share of each fuel fuel used used in in the the industry industry is is shown shown in in Figure Figure 4a,4a, and and it ithighlights highlights the the role role of ofnatural natural gas gas in the in Italian the Italian energy energy market market [51]. In [51 addition,]. In addition, various various types of types energy of can energy include can any include fuel anythat fuel has that not hasbeen not accounted been accounted for in industry, for in industry, such as such fuels as forfuels non-energy for non-energy uses, uses, agriculture, agriculture, and andbunkers bunkers [36], [shown36], shown in Figure in Figure 4b. 4b.

(a) (b)

Figure 4 4.. Fuel consumption for ( a) industry and (b) various energy uses inin Italy. Italy.

3.1.5. Transport According to to the the ENEA ENEA [51 [51], ],energy energy consumption consumption in the in transport the transport sector sector has dropped has dropped by 2% byin 2%comparison in comparison with the with previous the previous year, fromyear, from38.6 to 38.6 37.8 to Mtoe37.8 Mtoe (million (million tons tons of oil of equivalent). oil equivalent). Oil Oildominates dominates the thefuel fuel consumption consumption used used for fortransport, transport, as shown as shown in Figure in Figure 5. 5.

Figure 5. Fuel consumption for transport in Italy.

3.2. Supply Data After having defined the energy demand, we now focus on the supply data and analyze the energy production from different technologies.

3.2.1. Electricity Supply Here we focus on the input data of electricity production from RES and from other conventional technologies, such as condensing plants. During the past decade, renewable energies have changed the Italian energy system drastically, and nowadays Italy is a leading country for producing electricity using RES [51]. In the EU 2020 policy, the gross final energy consumption covered by RES production must reach 17% by 2020 [33]. This part of energy consumption includes the direct use of RES and the part of electricity and heat that is produced from renewables. For the reference year of Energies 2018, 11, x 8 of 31

3.1.4. Industry and Other Fuel Consumption The share of each fuel used in the industry is shown in Figure 4a, and it highlights the role of natural gas in the Italian energy market [51]. In addition, various types of energy can include any fuel that has not been accounted for in industry, such as fuels for non-energy uses, agriculture, and bunkers [36], shown in Figure 4b.

(a) (b)

Figure 4. Fuel consumption for (a) industry and (b) various energy uses in Italy.

3.1.5. Transport According to the ENEA [51], energy consumption in the transport sector has dropped by 2% in comparison with the previous year, from 38.6 to 37.8 Mtoe (million tons of oil equivalent). Oil dominates theEnergies fuel2018 consumption, 11, 3523 used for transport, as shown in Figure 5. 9 of 32

Figure 5. Fuel consumption for transport in Italy. Figure 5. Fuel consumption for transport in Italy. 3.2. Supply Data 3.2. Supply DataAfter having deﬁned the energy demand, we now focus on the supply data and analyze the energy production from different technologies. After having defined the energy demand, we now focus on the supply data and analyze the energy production3.2.1. Electricity from Supplydifferent technologies. Here we focus on the input data of electricity production from RES and from other conventional 3.2.1. Electricitytechnologies, Supply such as condensing plants. During the past decade, renewable energies have changed the Italian energy system drastically, and nowadays Italy is a leading country for producing electricity Here weusing focus RES [on51]. the In the input EU 2020 data policy, of electricity the gross ﬁnal production energy consumption from RES covered and by from RES production other conventional must reach 17% by 2020 [33]. This part of energy consumption includes the direct use of RES and the technologies,part such of electricity as condensing and heat that plants. is produced During from renewables.the past decade, For the reference renewable year of 2013,energies 8.9% washave changed the Italian the energy share covered system by RES-E, drastically, while 10.6% and was nowa covereddays by RES-T Italy [33 ], is which a leading means that country the target for has producing electricity usingalready RES been [ reached.51]. In the In 2013, EU 600,000 2020 policy, RES-E units the were gross recorded final when energy accounting consumption for photovoltaic covered by RES collectors, wind power plants, hydropower plants, and geothermal energy, but the distribution is production must reach 17% by 2020 [33]. This part of energy consumption includes the direct use of irregular along the peninsula depending on different climate conditions and potentials. RES and the part of electricity and heat that is produced from renewables. For the reference year of Solar

At the end of 2013, the total installed capacity of photovoltaic panels was 18,053 MW, and most of those power plants had capacities ranging from 3 kW to 20 kW, while a small proportion of them were large plants with capacities of between 200 kW and 1 MW or greater than 1 MW. The production was 21,589 GWh, which accounted for 19% of the total electricity production from RES-E [33]. Northern Italy installed more photovoltaic panels than the southern part of the country, but it produced less electricity because of the different solar irradiation densities. According to TERNA [52], we can obtain the actual generation ﬁgures for each renewable source for each hour of the reference year. Therefore, the hourly distribution of photovoltaic electricity has been calculated and shown in Figure6a. It is clear that solar production follows the seasonal change, but Italy has a large potential of solar energy even in the winter time, which is quite different with Finland. Energies 2018, 11, x 9 of 31

2013, 8.9% was the share covered by RES-E, while 10.6% was covered by RES-T [33], which means that the target has already been reached. In 2013, 600,000 RES-E units were recorded when accounting for photovoltaic collectors, wind power plants, hydropower plants, and geothermal energy, but the distribution is irregular along the peninsula depending on different climate conditions and potentials.

Solar At the end of 2013, the total installed capacity of photovoltaic panels was 18,053 MW, and most of those power plants had capacities ranging from 3 kW to 20 kW, while a small proportion of them were large plants with capacities of between 200 kW and 1 MW or greater than 1 MW. The production was 21,589 GWh, which accounted for 19% of the total electricity production from RES-E [33]. Northern Italy installed more photovoltaic panels than the southern part of the country, but it produced less electricity because of the different solar irradiation densities. According to TERNA [52], we can obtain the actual generation figures for each renewable source for each hour of the reference year. Therefore, the hourly distribution of photovoltaic electricity has been calculated and shown in Figure 6a. It is clear that solar production follows the seasonal change, but Italy has a large potential of solar energy even in the winter time, which is quite different with Finland. The specific hourly distribution, which means the ratio between hourly production and the total installed capacity, have been calculated and is shown in Figure 6b. This ratio is required by EnergyPLAN, and it shows the amount of real energy produced in comparison with the maximum Energiesthat 2018can , be11, 3523extracted; its value is between 0 and 1. In this case, the ratio is 0.14, which means 10the of 32 equivalent time of actual use of the photovoltaic power plant was 1241 h during the reference year.

(a)

(b)

FigureFigure 6. 6(a. )(a Hourly) Hourly photovoltaic photovoltaic productionproduction trend and ( (b)) specific speciﬁc photovolt photovoltaicaic hourly hourly distribution distribution inin Italy. Italy.

The speciﬁc hourly distribution, which means the ratio between hourly production and the total installed capacity, have been calculated and is shown in Figure6b. This ratio is required by EnergyPLAN, and it shows the amount of real energy produced in comparison with the maximum that can be extracted; its value is between 0 and 1. In this case, the ratio is 0.14, which means the equivalent time of actual use of the photovoltaic power plant was 1241 h during the reference year.

Wind In Italy, there were 1386 wind power plants at the end of 2013. Most of them were small in size, with power outputs of less than 1 MW. The installed capacity was 8561 MW and the production was 14,897 GWh, mostly from large power plants with capacities lager than 10 MW [41]. More wind turbines have been installed in southern Italy and they produce the majority of the wind power in the country. The hourly distributions of wind power can also be obtained from TERNA as shown in Figure7. Like many other countries, the wind energy distribution of Italy seems quite stochastic, but in general the wind speed is a bit higher in winter time. Using the overall capacity and ﬁnal production levels from all installed wind turbines, we can calculate their ratio as being equal to 0.20 for Italy and estimate the average equivalent working hours as being equal to 1793. Moreover, the speciﬁc hourly distribution of wind power can be used in the EnergyPLAN datasheet. Energies 2018, 11, x 10 of 31

Wind In Italy, there were 1386 wind power plants at the end of 2013. Most of them were small in size, with power outputs of less than 1 MW. The installed capacity was 8561 MW and the production was 14,897 GWh, mostly from large power plants with capacities lager than 10 MW [41]. More wind turbines have been installed in southern Italy and they produce the majority of the wind power in the country. The hourly distributions of wind power can also be obtained from TERNA as shown in Figure 7. Like many other countries, the wind energy distribution of Italy seems quite stochastic, but in general the wind speed is a bit higher in winter time. Using the overall capacity and final production levels from all installed wind turbines, we can calculate their ratio as being equal to 0.20 for Italy and estimate the average equivalent working hours as being equal to 1793. Moreover, the Energies 2018, 11, 3523 11 of 32 specific hourly distribution of wind power can be used in the EnergyPLAN datasheet.

(a)

(b)

FigureFigure 7.7. (a) Hourly Hourly wind production trend and (b)) speciﬁcspecific hourly distributiondistribution ofof windwind powerpower inin Italy.Italy.

Geothermal Geothermal production has has not not experienced experienced changes changes in in recent recent years. years. The The installed installed capacity capacity is isabout about 773 773 MW, MW, and and most most of of this this production production is is accounted accounted for for by by small small plants with capacities of of approximately 20 20 MW. MW. The The geothermal geothermal electricity electricity production production was 5659 was GWh 5659 in GWh 2013 in[41 2013]. The [ constant41]. The hourlyconstant distribution hourly distribution was used was in theused EnergyPLAN in the EnergyPLAN database. database. The geothermal The geothermal power station power hasstation the rolehas theof maintaining role of maintaining the grid’s the stability, grid’s stability,and it is consideredand it is considered to be running to be at running base load; at base therefore, load; thetherefore, geothermal the geothermal power plant power does plant not participate does not participate in active regulation. in active regulation. The geothermal The geothermal electricity productionelectricity production is the total is obtained the total whenobtained multiplying when multiplying the capacity, the capacity, the hourly the distribution, hourly distr andibution, the correctionand the correction factor. Once factor. the Once annual the production annual production rate and therate installed and the capacityinstalled were capacity known; were we known; found thewe calculatedfound the calculated correction correction factor to be factor 0.834 to and be the0.834 equivalent and the equivalent hours of work hours 7020. of work 7020.

Nuclear Power Four nuclear power plants have been built in Italy, but none of them have been working since the Fukushima accident in 2011.

Hydropower Italy has about 3250 hydropower plants, with a total installed capacity of 22,009 MW, of which 17,023 MW is from dammed hydropower while the rest is from river hydropower [53]. In 2013, the total hydropower production was 52,773 GWh, most of that coming from plants larger than 10 MW [53]. According to TERNA [53], it is possible to estimate these two levels of productions as the sum of the Energies 2018, 11, x 11 of 31

Nuclear Power Four nuclear power plants have been built in Italy, but none of them have been working since the Fukushima accident in 2011.

Hydropower Italy has about 3250 hydropower plants, with a total installed capacity of 22,009 MW, of which Energies17,0232018 MW, 11, is 3523 from dammed hydropower while the rest is from river hydropower [53]. In 2013, 12the of 32 total hydropower production was 52,773 GWh, most of that coming from plants larger than 10 MW [53]. According to TERNA [53], it is possible to estimate these two levels of productions as the sum hourlyof the distribution hourly distribution for the whole for th referencee whole reference year, as shown year, as in shown Figure 8in. ItFigure can be 8 found. It can the be hydropowerfound the productionhydropower is higher production in summer is higher time. in summer time.

(a)

(b)

FigureFigure 8. 8Hourly. Hourly distribution distribution ofof (aa)) dammed and and ( (bb)) river river hydropower hydropower production production in inItaly. Italy.

AfterAfter analyzing analyzing the the different different contributionscontributions to electricity production production from from the the different different renewable renewable sourcessources installed installed in in Italy, Italy, we we can can calculate calculate their their share of of RES RES electricity electricity production, production, as as shown shown in in FigureFigure9. In9. In 2013, 2013, the the total total amount amount of of electricity electricity producedproduced from RES RES was was 95 95 TWh, TWh, which which was was ca capablepable ofof covering covering 30% 30% of of the the national national electricityelectricity demand during during the the reference reference year. year. Hydropower Hydropower dominates dominates RESRES electricity electricity production production with with a a shareshare ofof 55%,55%, followed by by solar solar power power and and wind, wind, whose whose shares shares are are 23%23% and and 16%, 16%, respectively, respectively, while while geothermal geothermal productionproduction only contributes 6%. 6%.

CondensingCondensing Power Power TheThe condensing condensing power power was was 52,566.752,566.7 MW.MW. According to to TERNA TERNA documentation documentation on on condensing condensing power generation, they were able to produce 94,327.8 GWh during the reference year [53,54]. powerEnergies 2018 generation,, 11, x they were able to produce 94,327.8 GWh during the reference year [53,54]. 12 of 31

FigFigureure 9 9.. RES share in the electrici electricityty sector in Italy.

3.2.2. Combined Heat and Power Supply This input datasheet is devoted to combined heat and power (CHP) plants and the production of heat to fulfill the demands of district heating networks. In Italy, district heating is not a widespread technology; only a small part of the district heating demand is met by CHP. The total CHP installed capacity was 18,632.5 MW, while electricity production was 88,355.2 GWh. According to AIRU [44], the 10.3 TWh of heat produced for the district heating network is associated with: (1) Cogeneration power plants fed by fossil fuels: 851 MW; (2) Cogeneration power plants fed by biomass: 78 MW; (3) Auxiliary boilers fed by fossil fuels: 4726 MW (thermal); (4) Auxiliary boilers fed by biomass: 336 MW (thermal); (5) Geothermal: 240 GWh as heat production; (6) Waste treatments; (7) HPs. The last two production technologies have not played a significant role in total production. For this reason, we consider the heat produced for the district heating network to only be associated with CHP plants and auxiliary boilers.

3.2.3. Thermal Plant Supply and Fuel Mix The fuel distribution is divided into coal, oil, natural gas and biomass for condensing, and CHP plants [52]. The auxiliary boilers for district heating production are fed by 90% natural gas and 10% biomass.

3.2.4. CO2 Emission Data One of the final outputs of the EnergyPLAN has to do with total system emissions, hence the CO2 emission intensity of each fuel is needed. In this study, the CO2 content in fuels, measured in kg/GJ, has been modeled following the default values available in the EnergyPLAN database.

3.3. Model Results for the Base Case of Italy We carried out a market exchange analysis after obtaining the required input data. In this case, further input will be needed for the model to identify the market prices and to determine the response of the market prices to the changes of imports and exports. Input is also needed in order to determine the marginal production costs of an individual electricity production unit. Figure 10 shows the hourly market prices [55]. The power prices in Italy are generally higher than in other EU states because of the high level of imports and the predominance of gas-fired, combined-cycle CHP plants. Italy’s dependence on gas imports remains at about 90%.

Energies 2018, 11, 3523 13 of 32

3.2.2. Combined Heat and Power Supply This input datasheet is devoted to combined heat and power (CHP) plants and the production of heat to fulﬁll the demands of district heating networks. In Italy, district heating is not a widespread technology; only a small part of the district heating demand is met by CHP. The total CHP installed capacity was 18,632.5 MW, while electricity production was 88,355.2 GWh. According to AIRU [44], the 10.3 TWh of heat produced for the district heating network is associated with:

(1) Cogeneration power plants fed by fossil fuels: 851 MW; (2) Cogeneration power plants fed by biomass: 78 MW; (3) Auxiliary boilers fed by fossil fuels: 4726 MW (thermal); (4) Auxiliary boilers fed by biomass: 336 MW (thermal); (5) Geothermal: 240 GWh as heat production; (6) Waste treatments; (7) HPs.

The last two production technologies have not played a signiﬁcant role in total production. For this reason, we consider the heat produced for the district heating network to only be associated with CHP plants and auxiliary boilers.

3.2.4. CO2 Emission Data

One of the ﬁnal outputs of the EnergyPLAN has to do with total system emissions, hence the CO2 emission intensity of each fuel is needed. In this study, the CO2 content in fuels, measured in kg/GJ, has been modeled following the default values available in the EnergyPLAN database.

3.3. Model Results for the Base Case of Italy We carried out a market exchange analysis after obtaining the required input data. In this case, further input will be needed for the model to identify the market prices and to determine the response of the market prices to the changes of imports and exports. Input is also needed in order to determine the marginal production costs of an individual electricity production unit. Figure 10 shows the hourly market prices [55]. The power prices in Italy are generally higher than in other EU states because of the high level of imports and the predominance of gas-ﬁred, combined-cycleEnergies 2018, 11 CHP, x plants. Italy’s dependence on gas imports remains at about 90%. 13 of 31

FigureFigure 10. 1Market0. Market electricity electricity priceprice for Italy Italy during during the the year year 2013. 2013.

On the other hand, the maximum import/export capacity between Italy and its neighboring countries is shown in Table 3 [56]. However, we found that the imported electricity is more than the exported for Italy. With higher RES share, the imported electricity is reduced but the exported electricity is increased, and the electricity price is lowered. In EnergyPLAN modeling, EEEP refers to the Exportable Excess Electricity Production and CEEP to Critical Excess Electricity Production. The latter should not be exported because it exceeds the capacity of the transmission line. In fact, such production is not allowed, since it will cause a breakdown in the electricity supply. The model allows for the removal of CEEP, and a balance can be achieved by reducing the CHP and boiler production rates.

Table 3. Maximum import/export capacity between Italy and the neighboring countries.

Country Neighboring countries Maximum import/export (MW) Switzerland 3850 France 2650 Italy Greece 500 Slovenia 430 Austria 220

The main results refer to the balance between consumption and production in both the electricity sector and the heat sector, and an analysis of the different shares from different production plants. The validation of the model and trust in the results have been compared to the annual energy balance for the reference year published by IEA [33], ISTAT [34], and TERNA [53]. In particular, we can obtain the annual production rates for heat and power from different energy resources. For electricity production, we can obtain the following detailed production balance, with the shares being shown in Figure 11. It can be seen that import dependence is at a high level. In the absence of nuclear energy, combustion is the primary electricity production source, which provides more than 58% electricity, followed by the renewables, which contributes 29% electricity. As to the heat, CHP and boilers account for 98%, and the rest are geothermal energy. (1) Electricity consumption: 318.5 TWh [39]; (2) Electricity production: (a) condensing power plants: 94.9 TWh; (b) CHP power plants: 88.52 TWh; (c) RES: 93 TWh; (3) Import: 44.4 TWh; (4) Export: 2.37 TWh.

Energies 2018, 11, 3523 14 of 32

On the other hand, the maximum import/export capacity between Italy and its neighboring countries is shown in Table3[ 56]. However, we found that the imported electricity is more than the exported for Italy. With higher RES share, the imported electricity is reduced but the exported electricity is increased, and the electricity price is lowered. In EnergyPLAN modeling, EEEP refers to the Exportable Excess Electricity Production and CEEP to Critical Excess Electricity Production. The latter should not be exported because it exceeds the capacity of the transmission line. In fact, such production is not allowed, since it will cause a breakdown in the electricity supply. The model allows for the removal of CEEP, and a balance can be achieved by reducing the CHP and boiler production rates.

Table 3. Maximum import/export capacity between Italy and the neighboring countries.

Country Neighboring Countries Maximum Import/Export (MW) Switzerland 3850 France 2650 Italy Greece 500 Slovenia 430 Austria 220

(1) Electricity consumption: 318.5 TWh [39]; (2) Electricity production: (a) condensing power plants: 94.9 TWh; (b) CHP power plants: 88.52 TWh; (c) RES: 93 TWh; (3) Import: 44.4 TWh; (4) Export: 2.37 TWh. Energies 2018, 11, x 14 of 31

(a) (b)

FigureFigure 11.11. Balance ofof the ItalianItalian (aa)) electricityelectricity andand ((bb)) heatingheating marketmarket inin 2013.2013.

FromFrom thethe heatheat productionproduction shownshown onon thethe outputoutput datasheet,datasheet, wewe cancan concludeconclude thethe following:following: (1) District heating Demand: 9.2 TWh [44]; (2) District heating Production: 10.97 TWh [44] (including network losses); (3) CHP Power Plants: 7.52 TWh; (4) Auxiliary Boilers: 3.21 TWh; (5) Geothermal: 0.24 TWh. Other significant results from the base model provided in the EnergyPLAN are as follows: the total fuel consumption including import and export was 1986.29 TWh/year and total CO2 emissions were 402.62 Mt/year, which are quite consistent with the ENEA report for the reference year [51]. Therefore, the model was validated by the real data, and the model results can form the basis for configuring and analyzing future scenarios with higher RES shares.

4. Energy System Modeling for Finland System modeling was also conducted for the Finnish energy market during the reference year following the same procedure with the Italian model.

4.1. Demand Data

4.1.1. Electricity Demand The total electricity demand in Finland was 84 TWh in 2013, as reported by Statistics Finland [57]. Electricity demand is quite variable in Finland, and electricity consumption per capita is the second-highest among IEA member countries after Canada, mainly due to the dark, cold winters and economic activities [35]. Although about half of all space heating is covered by district heating, 13.23 TWh of heating energy are from individual heating, while the total amount of electricity used within the residential sector is growing due to the increasing number of HP [58]. The hourly electricity demand for Finland can be downloaded from NordPool [58], as shown in Figure 12. We found that the electricity demand peaks during the winter because of low outdoor temperatures and limited daylight hours. It is less uniform than the Italian electricity distribution.

Energies 2018, 11, 3523 15 of 32

(1) District heating Demand: 9.2 TWh [44]; (2) District heating Production: 10.97 TWh [44] (including network losses); (3) CHP Power Plants: 7.52 TWh; (4) Auxiliary Boilers: 3.21 TWh; (5) Geothermal: 0.24 TWh.

Other signiﬁcant results from the base model provided in the EnergyPLAN are as follows: the total fuel consumption including import and export was 1986.29 TWh/year and total CO2 emissions were 402.62 Mt/year, which are quite consistent with the ENEA report for the reference year [51]. Therefore, the model was validated by the real data, and the model results can form the basis for conﬁguring and analyzing future scenarios with higher RES shares.

4. Energy System Modeling for Finland System modeling was also conducted for the Finnish energy market during the reference year following the same procedure with the Italian model.

4.1. Demand Data

4.1.1. Electricity Demand The total electricity demand in Finland was 84 TWh in 2013, as reported by Statistics Finland [57]. Electricity demand is quite variable in Finland, and electricity consumption per capita is the second-highest among IEA member countries after Canada, mainly due to the dark, cold winters and economic activities [35]. Although about half of all space heating is covered by district heating, 13.23 TWh of heating energy are from individual heating, while the total amount of electricity used within the residential sector is growing due to the increasing number of HP [58]. The hourly electricity demand for Finland can be downloaded from NordPool [58], as shown in Figure 12. We found that the electricity demand peaks during the winter because of low outdoor temperatures and limited daylight hours.Energies It is2018 less, 11,uniform x than the Italian electricity distribution. 15 of 31

FigureFigure 12. 12.Hourly Hourly electricityelectricity demand for for Finland Finland in in 2013 2013..

4.1.2.4.1.2. Heat Heat Demand Demand BecauseBecause of of its its cold cold climate, climate, Finland’sFinland’s heatheat demand per per capita capita is is among among the the highest highest of ofall allIEA IEA membermember countries countries [35 [35].]. To To the the best best ofof ourour knowledge,knowledge, heating technologies technologies are are strongly strongly related related to to greenhousegreenhouse gas gas emissions; emissions; however, however, Finland Finland doesdoes notnot have a high rate rate of of CO CO2 2emissions.emissions. One One of ofthe the mainmain reasons reasons has has to doto do with with the the important important role role of districtof district heating, heating, which which covers covers almost almost 50% 50% of theof th totale heattotal demand, heat demand, while the while district the district heating heating share inshare Helsinki in Helsinki is 93%. is About93%. About 2.6 million 2.6 million Finns Finns live in live houses in houses heated by district heat. The heat demand of the rest of the population should be modeled as individual heating [59]. The fuel used for individual heating can be found in Figure 13 [60]. It is quite clear that biomass is the most common fuel used for individual heating, while electric heating is still popular in new detached houses because it is easy to use, cost-effective, and does not require high maintenance.

Figure 13. Fuel used for individual heating in Finland.

The share of solar thermal energy has not been modeled, even if solar energy has great potential in Finland, because the main contribution is only in summertime, when the heat demand is quite low. This technology could contribute more to the overall heating production when coupled with long- term heat storage systems. Finnish district heating is mainly based on CHP systems producing heat and electricity. The total produced heat has been modeled as in centralized CHP systems. In 2013, the produced heat was 36.8 TWh and the heat demand was 33.2 TWh considering the network losses [60]. An aggregation procedure similar to the one developed for the Italian model has been followed to obtain the hourly heat demand distribution for Finland, and the results are shown in Figure 14. In this case, the procedure was simpler for two main reasons. The Finnish climate is more uniform and there are not significant differences in HDD between the two climate zones. Moreover, the population is mostly concentrated in the coastal area and mainly around Helsinki. As a consequence, the heat demand can be modeled according to the HDD of Helsinki based on its hourly temperature for the

Energies 2018, 11, x 15 of 31

Figure 12. Hourly electricity demand for Finland in 2013.

4.1.2. Heat Demand Because of its cold climate, Finland’s heat demand per capita is among the highest of all IEA member countries [35]. To the best of our knowledge, heating technologies are strongly related to greenhouse gas emissions; however, Finland does not have a high rate of CO2 emissions. One of the main reasons has to do with the important role of district heating, which covers almost 50% of the total heat demand, while the district heating share in Helsinki is 93%. About 2.6 million Finns live in houses heatedEnergies by2018 district, 11, 3523 heat. The heat demand of the rest of the population should16 ofbe 32 modeled as individual heating [59]. The fuel used for individual heating can be found in Figure 13 [60]. It is quite clear that biomassheated by is district the most heat. The common heat demand fuel of used the rest for of theindividual population heating should be, modeled while electric as individual heating is still heating [59]. The fuel used for individual heating can be found in Figure 13[ 60]. It is quite clear that popular in new detached houses because it is easy to use, cost-effective, and does not require high biomass is the most common fuel used for individual heating, while electric heating is still popular in maintenance.new detached houses because it is easy to use, cost-effective, and does not require high maintenance.

FigureFigure 13. Fuel 13. Fuel used used for for individual individual heating heating in Finland. in Finland. The share of solar thermal energy has not been modeled, even if solar energy has great potential The sharein Finland, of solar because thermal the main energy contribution has not is been only in modeled, summertime, even when if thesolar heat energy demand has is quite great potential in Finland, becauselow. This technologythe main couldcontribution contribute is more only to thein summertime, overall heating production when the when heat coupled demand with is quite low. long-term heat storage systems. Finnish district heating is mainly based on CHP systems producing This technology could contribute more to the overall heating production when coupled with long- heat and electricity. The total produced heat has been modeled as in centralized CHP systems. In 2013, term heat storagethe produced systems. heat wasFinnish 36.8 TWh district and theheating heat demand is mainly was 33.2based TWh on considering CHP systems the network producing heat and electricity.losses The [60]. total produced heat has been modeled as in centralized CHP systems. In 2013, the produced heat wasAn aggregation 36.8 TWh procedure and the similar heat todemand the one developed was 33.2 for TWh the Italian considering model has the been network followed losses [60]. to obtain the hourly heat demand distribution for Finland, and the results are shown in Figure 14. An aggregationIn this case, theprocedure procedure wassimilar simpler to for the two one main developed reasons. The for Finnish the climate Italian is moremodel uniform has andbeen followed to obtain thethere hourly are not heat signiﬁcant demand differences distribution in HDD between for Finland, the two climate and the zones. results Moreover, are theshown population in Figure 14. In is mostly concentrated in the coastal area and mainly around Helsinki. As a consequence, the heat this case, the procedureEnergies 2018, 11 was, x simpler for two main reasons. The Finnish climate is16 more of 31 uniform and demand can be modeled according to the HDD of Helsinki based on its hourly temperature for the there are not significant differences in HDD between the two climate zones. Moreover, the population referencereference year. year. The population-weighted The population-weighted average average number number of HDD of HDD was was 5000 5000 during during the whole the whole reference is mostly concentratedyear [reference61]. Note year thatin [61the our]. Note calculationscoastal that our area forcalculations the and HDD mainly for for the a FinnishHDD around for city a Finnish differHelsinki. city from differ the As Italianfrom a theconsequence, case Italian because the heat demand canthe be presumedcase modeled because indoor the according presumed temperature indoor to in the temperature Finland HDD is 17 inof ◦FinlandC. Helsinki According is 17 °C. based to According Figure on 14 to ,its theFigure hourly 14, the heat hourlytemperature demand for the heat demand is much higher in winter than summer, and the summer time is much shorter than Italy. is much higher in winter than summer, and the summer time is much shorter than Italy.

FigureFigure 14. 14Hourly. Hourly heat heat demanddemand distribution distribution in inFinland Finland..

4.1.3. Cooling Demand In Finland, district cooling is still a relatively young technology that was only introduced in the 1990s. In 2013, the cooling energy used was only 1.2 TWh, and it has been estimated that the cooling demand will not experience significant growth by 2030 [62]. Therefore, we did not complete this particular input datasheet.

4.1.4. Industry and Other Fuel Consumption The total fuel consumption in the industrial sector of Finland was 105.3 TWh in 2013, and the share of each fuel used is shown in Figure 15 [57]. Again, biomass dominated the fuel consumption in this sector with a 53% share. Finland is among the leading countries in the use of biomass for energy production, and nearly two-thirds of all industrial energy is consumed in wood and paper industry [35].

Figure 15. Industrial fuel consumption in Finland.

4.1.5. Transport Figure 16 shows the fuel used for transport in Finland, although the transport system is based on diesel and gasoline. The share of biofuel is higher than that of gas, and the most commonly used biofuel is biodiesel. Nowadays, all transport fuels distributed in Finland contain bio components, and the bio-ethanol content is increasing to meet environmental targets of 20% for the renewable energy content of fuels for this sector by 2020.

Energies 2018, 11, x 16 of 31

reference year. The population-weighted average number of HDD was 5000 during the whole reference year [61]. Note that our calculations for the HDD for a Finnish city differ from the Italian case because the presumed indoor temperature in Finland is 17 °C. According to Figure 14, the hourly heat demand is much higher in winter than summer, and the summer time is much shorter than Italy.

Figure 14. Hourly heat demand distribution in Finland. Energies 2018, 11, 3523 17 of 32 4.1.3. Cooling Demand 4.1.3.In Finland, Cooling district Demand cooling is still a relatively young technology that was only introduced in the 1990s. In In2013, Finland, the cooling district coolingenergy isused still awas relatively only 1.2 young TWh, technology and it has that been was estimated only introduced that the in thecooling demand1990s. will In 2013,not experience the cooling energysignificant used wasgrowth only 1.2by TWh,2030 and[62]. it Therefore, has been estimated we didthat notthe complete cooling this particulardemand input will datasheet. not experience signiﬁcant growth by 2030 [62]. Therefore, we did not complete this particular input datasheet. 4.1.4. Industry and Other Fuel Consumption 4.1.4. Industry and Other Fuel Consumption The Thetotal total fuel fuel consumption consumption in in the the industrial industrial sector ofof FinlandFinland was was 105.3 105.3 TWh TWh in 2013,in 2013, and and the the shareshare of each of each fuel fuel used used is shown is shown in in Figure Figure 1155 [[57].]. Again,Again, biomass biomass dominated dominated the the fuel fuel consumption consumption in thisin thissector sector with with a 5 a3% 53% share share.. Finland Finland is is among among the leadingleading countries countries in in the the use use of biomassof biomass for for energyenergy production, production, and and nearly nearly two two-thirds-thirds of of all all industrialenergy energy is is consumed consumed in woodin wood and and paper paper industryindustry [35] [.35 ].

FigFigureure 15 15.. IndustrialIndustrial fuel fuel consumption in in Finland. Finland. 4.1.5. Transport 4.1.5. Transport Figure 16 shows the fuel used for transport in Finland, although the transport system is based onFigure diesel 16 and shows gasoline. the fuel The shareused offor biofuel transport is higher in Finland, than that although of gas, and the the transport most commonly system usedis based on dieselbiofuel and is biodiesel.gasoline. Nowadays,The share of all biofuel transport is higher fuels distributed than that inof Finlandgas, and contain the most bio components,commonly used biofueland is the biodiesel. bio-ethanol Nowadays, content isall increasing transport to fuels meet distribut environmentaled in Finland targets contain of 20% forbio thecomponents, renewable and Energiesthe 2018 bioenergy,- ethanol11, x content content of fuels is forincreasing this sector to by meet 2020. environmental targets of 20% for the renewable energy17 of 31 content of fuels for this sector by 2020.

FigureFigure 16. 16.FuelFuel consumption consumption forfor transport transport in Finland.in Finland.

4.2. Supply Data

4.2.1. Electricity Supply The electricity demand is fulfilled partly by condensing power plants and nuclear energy and partly by intermittent renewable energies, such as wind and hydropower. This has to do with the types of resources available in Finland.

Nuclear Power In the late 1980s, the Finnish government made the decision to include nuclear power in the national energy system, and nowadays four reactors are active in two main power plants. Nuclear power plays a large role in the plants’ power production and meets the constant need for base-load power [63]. In 2013, the installed capacity was 2752 MW, with an efficiency level of 0.4 [60]. The share of nuclear power in total electricity production will increase when the fifth reactor is ready for commercial operation. This technology, with high load factors, has a low electricity price, low levels of radioactive emissions, and will help the country achieve low levels of CO2 emissions. The distribution is considered constant because it is a base-load electricity generation technology.

Wind In Finland, many costal sites and coastal waters of the Baltic Sea would be suitable for the generation of wind power, but at the end of 2013 only 211 wind turbine generators were working, mostly along the west coast, and the nominal capacity was 258 MW [60,64]. During the reference year, the total amount of electricity produced from wind turbines was 774 GWh. The hourly distribution used in the model is shown in Figure 17, which shows that the wind production is higher in November and December in Finland.

Figure 17. Hourly wind production in Finland.

Energies 2018, 11, x 17 of 31

Energies 2018, 11, 3523 18 of 32

Figure 16. Fuel consumption for transport in Finland. 4.2. Supply Data 4.2. Supply Data 4.2.1. Electricity Supply 4.2.1. Electricity Supply The electricity demand is fulfilled partly by condensing power plants and nuclear energy and partly byThe intermittent electricity demand renewable is fulfilled energies, partly such by ascondensing wind and power hydropower. plants and This nuclear has to energy do with and the typespartly of resourcesby intermittent available renewable in Finland. energies, such as wind and hydropower. This has to do with the types of resources available in Finland. Nuclear Power Nuclear Power In the late 1980s, the Finnish government made the decision to include nuclear power in the nationalIn energy the late system, 1980s, the and Finnish nowadays government four reactors made arethe activedecision in twoto include main powernuclear plants.power Nuclearin the national energy system, and nowadays four reactors are active in two main power plants. Nuclear power plays a large role in the plants’ power production and meets the constant need for base-load power plays a large role in the plants’ power production and meets the constant need for base-load power [63]. In 2013, the installed capacity was 2752 MW, with an efficiency level of 0.4 [60]. The share of power [63]. In 2013, the installed capacity was 2752 MW, with an efficiency level of 0.4 [60]. The share nuclear power in total electricity production will increase when the fifth reactor is ready for commercial of nuclear power in total electricity production will increase when the fifth reactor is ready for operation. This technology, with high load factors, has a low electricity price, low levels of radioactive commercial operation. This technology, with high load factors, has a low electricity price, low levels emissions, and will help the country achieve low levels of CO2 emissions. The distribution is considered of radioactive emissions, and will help the country achieve low levels of CO2 emissions. The constantdistribution because is considered it is a base-load constant electricity because generationit is a base-load technology. electricity generation technology. Wind Wind InIn Finland, Finland, many many costal costal sites sites and and coastal coastal waters of of the the Baltic Baltic Sea Sea would would be be suitable suitable for for the the generationgeneration of of wind wind power, power, but but at at the the endend ofof 20132013 only 211 wind wind turbine turbine generators generators were were working, working, mostlymostly along along the the west west coast, coast, and and the the nominalnominal capacity was was 258 258 MW MW [60 [60,64,64]. ].During During the the reference reference year, year, thethe total total amount amount of of electricity electricity produced produced fromfrom windwind turbinesturbines was was 774 774 GWh. GWh. The The hourly hourly distribution distribution usedused in the in themodel model is shown is shown in Figure in Figure 17, which 17, which shows shows that the that wind the production wind production is higher is in higher November in andNovember December and in December Finland. in Finland.

FigureFigure 17. 17.Hourly Hourly windwind production in in Finland Finland..

Hydropower Hydropower is the most important form of renewable energy in the Nordic countries, and in Finland it is the second largest source of renewable energy after bioenergy [35]. Approximately 207 hydropower plants were operating in Finland in 2013, including micro, small, and large hydropower plants, most of which were located in the north and center of the country in the vicinity of the lakes. The total capacity recorded for the reference year was 3125 MW [60]. The total annual production was 12.67 TWh. The distribution pattern is shown in Figure 18, which is quite different from Italy’s hydropower distribution, because Finland has two peaks in terms of hydropower production, they are January and February as well as the summer time. Energies 2018, 11, x 18 of 31

Hydropower Hydropower is the most important form of renewable energy in the Nordic countries, and in Finland it is the second largest source of renewable energy after bioenergy [35]. Approximately 207 hydropower plants were operating in Finland in 2013, including micro, small, and large hydropower plants, most of which were located in the north and center of the country in the vicinity of the lakes. The total capacity recorded for the reference year was 3125 MW [60]. The total annual production was 12.67 TWh. The distribution pattern is shown in Figure 18, which is quite different from Italy’s Energieshydropower2018, 11, 3523 distribution, because Finland has two peaks in terms of hydropower production, they19 of 32 are January and February as well as the summer time.

FigureFigure 18. 18Hourly. Hourly distributiondistribution of hydropower production production in in Finland Finland..

SolarSolar TheThe yearly yearly amount amount of of solar solar energy energy producedproduced in Finland amounts amounts to to about about 1000 1000 kWh kWh per per square square meter,meter, and and it variesit varies dramatically dramatically over over a a year.year. Moreover,Moreover, solar energy energy is is not not present present in in large large scales scales and and throughoutthroughout the the energy energy market; market; therefore therefore it it has has notnot beenbeen modeled in in this this study. study.

4.2.2.4.2.2. Combined Combined Heat Heat and and Power Power Supply Supply CHPCHP is is one one of of the the most most important important andand efﬁcientefficient technologie technologiess in in the the whole whole Finnish Finnish energy energy system, system, andand the the development development of of district district heating heating in in particular particular has has progressed progressed in in tandem tandem withwith thethe developmentdevelopment of CHP.of CHP.CHP accounts CHP accounts for about for one-quarter about one-quarter of the total of the electricity total electricity demand demand of the country of the [ country59]. According [59]. to StatisticsAccording Finland to Statistic [60s], Finland the power [60], generationthe power generation capacity at capacity peak load at peak in 2013 load wasin 2013 5830 was MW 5830 for MW CHP, andfor the CHP, capacity and the feeding capacity the feeding district the heating district network heating was network 3500 MW.was 3500 The totalMW. installedThe total capacityinstalled of CHPcapacity can produce of CHP almostcan produce 80% ofalmost the total 80% heat of the produced total heat for produced the network. for the network.

4.2.3.4.2.3. Thermal Thermal Plant Plant Supply Supply and and Fuel Fuel MixMix AccordingAccording to to Statistics Statistics Finland, Finland, it it is is useful useful to obtain the the rates rates of of fuel fuel consumption consumption for for the the productionproduction of of heat heat and and electricityelectricity with with respect respect to to the the adopted adopted technologies technologies [60]. [The60]. share The shareof the fuel of the fuelunderlines underlines the the importance importance of biomass of biomass in the in national the national energy energy markets, markets, especially especially in relation in relation to CHP to CHPpower power plants. plants. The The heat heat supplied supplied by CHP by CHP plants plants using using biogas biogas and wood and wood has a hashigher a higher feed-in feed-in tariff for tariff an additional bonus for this kind of renewable heat. for an additional bonus for this kind of renewable heat.

4.2.4. CO2 Emission Data 4.2.4. CO2 Emission Data Similarly to the Italian model, the CO2 content in the fuels, as measured in kg/GJ, has been Similarly to the Italian model, the CO2 content in the fuels, as measured in kg/GJ, has been modeled following the default values available in the EnergyPLAN database. modeled following the default values available in the EnergyPLAN database.

4.3. Model Results for the Base Case of Finland

In order to simulate the market economy, other input data include the market price distribution and the maximum import/export transmission capacity. Since Finland is a member of NordPool, it is convenient to extract the price distribution during the reference year from Nordpool’s website. In particular, the Elspot prices shown in Figure 19 represent the results from the day-ahead implicit auction market [60]. The average electricity price for 2013 was 41.16 €/MWh, which was the highest in the NordPool market, due to a higher share of fossil fuels and imports compared to other countries in the NordPool market. Energies 2018, 11, x 19 of 31 Energies 2018, 11, x 19 of 31 4.3. Model Results for the Base Case of Finland 4.3. Model Results for the Base Case of Finland In order to simulate the market economy, other input data include the market price distribution and theIn order maximum to simulate import/export the market transmission economy, othercapacity. input Since data Finland include is the a member market price of NordPool, distribution it is andconvenient the maximum to extract import/export the price distribution transmission during capacity. the referenceSince Finland year is from a member Nordpool’s of NordPool, website it. Inis convenientparticular, theto extract Elspot theprices price shown distribution in Figure during 19 represent the reference the results year fromfrom Nordpool’sthe day-ahead website implicit. In particular,auction market the Elspot [60]. The prices average shown electricity in Figure price 19 representfor 2013 was the 41.16results €/MWh, from the which day was-ahead the implicithighest auctionin the NordPool market [ 60market,]. The dueaverage to a higherelectricity share price of foss foril 2013 fuels was and 41.16 imports €/MWh, compared which to was other the countries highest inEnergiesin thethe NordPoolNordPool2018, 11, 3523 market,market. due to a higher share of fossil fuels and imports compared to other countries20 of 32 in the NordPool market.

Figure 19. Electricity price distribution in Finland during 2013. FigFigureure 19 19.. Electricity price distribution in Finland during 2013 2013.. The maximum net transfer capacity between Finland and the neighboring countries are shown The maximum net transfer capacity between Finland and the neighboring countries are shown in in TableThe 4.maximum net transfer capacity between Finland and the neighboring countries are shown Tablein Table4. 4.

TableTable 4.4. MaximumMaximum import/exportimport/export capacity between Finland and the neighboring countries. Table 4. Maximum import/export capacity between Finland and the neighboring countries. Country Neighboring Countries Maximum Import/Export (MW) Country Neighboring Countries Maximum Import/Export (MW) Country NeighboringSweden (Northern) Countries Maximum Import/Export1500/1100 (MW) SwedenSweden (Northern)Sweden (Northern) (Central) 1500/11001500/11001200/1200 Finland SwedenSweden (Central) (Central) 1200/12001200/1200 Finland Estonia 1016/1000 Finland Estonia 1016/1000 EstoniaRussia 1016/10001100/- RussiaRussia 1100/-1100/- We obtained the energy balances for Finland in the reference year based on the model output data.We Figure obtained 20 shows the the energy share balances of production for Finland from eachin the technology reference for year the based electricity on the and model heat outputsectors. data.We can Figure Figure find 2 20out0 showsshows that condensing the the share share of of powerproduction production is very from limited each in technology Finland, but for theCHP, electricity RES an d and nuclear heat sectors.power Wedominates can ﬁndfind the out electricity that condensing production. power At is the very same limited time, in CHP Finland, also but butproduces CHP, CHP, RES more an and thand nuclear 70% districtpower dominatesheat with higher thethe electricityelectricity energy production. efficiency.production. The At At theresults the same same come time, time, from CHP CHP the also alsomodel produces produces results more morebut than not than 70% from 70% district the district actual heat withheatstatistics. with higher higher energy energy efﬁciency. efficiency. The results The results come from come the from model the resultsmodel butresults not frombut not the from actual the statistics. actual statistics.

(a) (b) (a) (b) FigureFigure 20.20. BalanceBalance of the Finnish (a)) electricityelectricity andand ((bb)) heatingheating marketmarket inin 2013.2013. Figure 20. Balance of the Finnish (a) electricity and (b) heating market in 2013.

The following detailed electricity balance can be found in the model output datasheets:

(1) Electricity demand: 84 TWh [57]; (2) Electricity production: (a) CHP power plants: 23.33 TWh; (b) nuclear: 22.67 TWh; (c) RES: 13.44 TWh; (d) condensing power plants: 8.9 TWh; (3) Import: 17.6 TWh; (4) Export: 1.87 TWh. Energies 2018, 11, 3523 21 of 32

For the heat sector, the detailed balance is as follows: (1) District heating Demand: 33.2 TWh [57]; (2) District heating Production: 36.8 TWh, including: (a) CHP plants produced 26.1 TWh; (b) Auxiliary boilers supplied 10.7 TWh. These balances have been validated by statistics from the Finnish authorities [57,60]. According to the detailed statistic results shown in Table5, the share of condensing power, CHP, RES, import/export, and nuclear power are 10.6%, 27.7%, 16.1%, 18.7% and 27%, which are consistent with the modelled results. In 2013, CHP produced 75.7% of heat while heat only boilers produced 24.3% district heat, which are also close to the model output. Therefore, the proposed EnergyPLAN model has a good accuracy to reﬂect the base case and therefore the cases with higher RES share.

Table 5. Electricity and heat production by production mode in 2013 by Statistic Finland [57].

Electricity Share of Electricity District Heat Share of Heat Item (TWh) Production (%) (TWh) Production (%) Hydro power 12.7 -- Separate 16.1 (RES) Wind power 0.8 - - production of Nuclear power 22.7 27.0 - - electricity Condensing power 8.9 10.6 - - Combined heat and power production 23.3 27.7 26.1 75.7 Separate heat production - - 8.4 24.3 Total production 68.3 81.3 34.5 100 Net imports of electricity 15.7 18.7 - - Total 84 100.0 34.5 100

According to the model output, nuclear power plants help reduce the electricity produced from CHP. They also help produce more heat for district heating. Relevant results from the models for future optimizations are as follows: annual fuel consumption was 348.62 TWh/year and CO2 emissions were 48.85 Mt/year.

5. Model Optimization Results from Different Renewable Energy Sources Scenarios for Energy Transition The scenarios were created by increasing renewable energy production, according to the current national situation and potential and future energy pathways. The sustainable transitions of the energy market point to changes in the national energy structure in the form of a higher RES share. The models of the two actual energy markets formed the starting point (base case) for this analysis. It is possible to devise new scenarios and examine improvements in the energy market as well as the share of RES in the primary energy consumption and carbon emissions in the system by using EnergyPLAN. To reach a higher share of renewables in primary energy consumption, a study on the potential of RES in both countries has to be carried out in order to better understand how this implementation can occur according to national plans.

5.1. Italian Scenarios and Model Results The Italian national energy plan is focused mostly on the following [65]: (1) Improving energy efﬁciency in buildings because of the large number of old houses; (2) Introducing energy savings in industrial processes; (3) Developing the district heating network in all the municipalities in climate Zones E and F; (4) Ensuring the highest share of RES in district heating production, approximately 37%; (5) Increasing the use of biomass throughout the whole system, especially biofuels. This plan does not highlight the role that RES should play, and the Italian government has cut the incentives for PV installations. Nevertheless, RES should increase their share of total energy Energies 2018, 11, x 21 of 31

(1) Improving energy efficiency in buildings because of the large number of old houses; (2) Introducing energy savings in industrial processes; (3) Developing the district heating network in all the municipalities in climate Zones E and F; (4) Ensuring the highest share of RES in district heating production, approximately 37%; (5) Increasing the use of biomass throughout the whole system, especially biofuels. Energies 2018, 11, 3523 22 of 32 This plan does not highlight the role that RES should play, and the Italian government has cut the incentives for PV installations. Nevertheless, RES should increase their share of total energy consumptionconsumption for a moremore sustainablesustainable energy market, especially in a country like Italy, whichwhich has a greatgreat amount of imported energy energy and and high high energy energy prices. prices. For For this this reason, reason, a stu a studydy was was carried carried out out by byEnergoClub EnergoClub to toevaluate evaluate the the potential potential of of renewable renewable energies energies [66 [66] ]in in Italy Italy and and their their role role in future future scenariosscenarios aimedaimed atat reaching aa higherhigher share inin the market as well as scenarios characterized by energy independenceindependence [[6767].]. TheThe analysesanalyses showshow that the potential of various RES technologies and the possible ratesrates ofof productionproduction forfor thethe electricity,electricity, thermal,thermal, andand transporttransport sectors.sectors. We concludeconclude fromfrom thethe analysesanalyses thatthat the the total total potential potential of RES of RES can cover can orcover even or surpass even the surpass current the Italian current rates Italian of actual rates consumption of actual inconsumption each sector. in each sector. TheThe ItalianItalian RESRES potentialpotential formsforms the basisbasis forfor devisingdevising thethe newnew scenariosscenarios that include 35% (near future)future) andand 60%60% (in(in thethe longlong run)run) ofof thethe RESRES share.share. InIn thisthis case,case, thethe twotwo sharesshares chosenchosen forfor thethe futurefuture scenariosscenarios werewere lowerlower thanthan thethe FinnishFinnish scenariosscenarios becausebecause thethe currentcurrent RESRES statusstatus andand RESRES potentialspotentials areare different.different. We foundfound thatthat in thethe basebase model,model, ItalianItalian renewables account for 19% of total energy consumptionconsumption andand thethe chosenchosen shares shares represent represent reasonable reasonable increases increases without without making making drastic drastic changes changes to theto the energy energy systems. systems. ToTo thethe best best ofof ourour knowledge,knowledge, fewfew studiesstudies havehave discusseddiscussed the plannedplanned capacities of RES for differentdifferent sectors sectors in in the the long long run. run. Therefore, we increased the share of each RES according to its its potentialpotential andand thethe actualactual impactimpact ofof thethe sourcesource onon thethe energyenergy systems.systems. The main aims of thethe ItalianItalian energyenergy marketmarket ofof thethe futurefuture areare relatedrelated toto decreasingdecreasing importsimports andand thethe dependence onon naturalnatural gas and reducingreducing thethe electricityelectricity marketmarket price.price. FigureFigure 2121 shows the the modeled modeled fuel fuel consumption consumption in in the the Italian Italian scenario scenario with with a 35% a 35% RES RES share. share. In Inorder order to toreach reach 35% 35% RES RES share, share, the the model model focuses focuses its its attention attention on on solar technologies, wind power plants,plants, andand biomassbiomass in in power power plants plants and and transport, transport, while while the the estimated estimated potential potential of hydropowerof hydropower is not is sonot high. so high. Following Following this this procedure, procedure, total total CO2 COemissions2 emissions account account for 300for 300 Mt, Mt, with with a decrease a decrease of 77 of Mt, 77 comparedMt, compared to the to basethe base model model for thefor the reference reference year. year. When When the the RES RES share share is increased is increased to 60%to 60% shown shown in Figurein Figure 22, 2 the2, the increase increase is mainly is mainly attributable attributable to the to the use use of biomass, of biomas buts, but not not RES-E. RES Oil-E. andOil and natural natural gas havegas have been been decreased decreased by 6% by and 6% 16%, and respectively, 16%, respectively, compared compared to the 35% to RESthe 35% scenario, RES whichscenario, ensures which a relativeensures independencea relative independence from natural from gas natural and a dramaticgas and a reductiondramatic inreduction the imported in the volume.imported With volume. 60% RES,With CO60%2 emissionsRES, CO2 emissions are 184 Mt, are which 184 Mt, is only which 49% is ofonly the 49% 2013 of level. the 2013 level.

FigureFigure 21.21. Fuel consumption in the Italian scenarioscenario withwith 35%35% RES.RES.

Energies 2018, 11, 3523 23 of 32 Energies 2018, 11, x 22 of 31

FigureFigure 22.22. Fuel consumption in the Italian scenario with 60% RES.RES.

5.2.5.2. Finnish Scenarios and Model Results The Finnish national national plan plan for for pro promotingmoting RES RES still still pays pays great great attention attention to biomass, to biomass, wind, wind, and andhydropower hydropower as a asmeans a means of increasing of increasing the share the share of the of existing the existing technology technology on the on actual the actual market. market. The Themain main expectations expectations for 2020 for 2020 are as are follows as follows [68]: [ 68]: (1) Wind(1) Wind power power production production will risewill torise 6 TWh,to 6 TWh, compared compare to 0.7d to TWh 0.7 TWh in 2013; in 2013; (2) Hydropower(2) Hydropower will increasewill increase to 14 to TWh, 14 TWh, compared compared to 12.67 to 12.67 TWh TWh in 2013; in 2013; (3) CHP(3) CHP production production from from wood wood chips chips will bewill equivalent be equivalent to at to least at least 28 TWh 28 TWh of fuel; of fuel; (4) Renewable(4) Renewable energy energy production production by HP by shouldHP should be increased be increased to 8 TWh;to 8 TWh; (5) The(5) useThe ofuse biofuels of biofuels in the in transportthe transport sector sector will will be increased be increased to 7 to TWh 7 TWh and and biogas biogas to 0.7 to 0.7 TWh. TWh.

These aims can be overlookedoverlooked when considering the potential of RES in Finland.Finland. According to Motiva [[6969],], thethe totaltotal hydropowerhydropower potential, potential, in in addition addition to to the the actual actual installed installed capacity, capacity, is estimatedis estimated to beto be more more than than 600 600 MW, MW, but but this this number number could could even even be be higher. higher. Technical Technical Research Research CentreCentre ofof Finland (VTT)(VTT) gavegave aa realisticrealistic wind wind power power scenario scenario that that amounted amounted to to 11,013 11,013 MW MW from from wind wind turbines turbines along along the westthe west coast coast in the in near the future,near future, so that so number that number can also can increase also increase [70]. The [70 bioenergy]. The bioenergy potential potential of Finland of wasFinland estimated was estimated to be 143 to TWh, be 143 including TWh, including 11 TWh for11 TWh biofuels for inbiofuels the transport in the transport sector [71 sector]. Finland [71]. canFinland use more can use solar more technologies, solar technologies, especially especially because becausethe solar the irradiation solar irradiation rate in southern rate in southern Finland hasFinland an annual has an levelannual roughly level roughly equal to equal that to of that central of central Europe. Europe. However, However, matching matching solar energysolar energy with demandwith demand is much is worse much in worse Finland in comparedFinland compared to central toEurope. central A Europe.study reported A study that reported the maximum that the or long-termmaximum potentialor long-term of solar potential energy of in solar Finland energy is 5.5 in TWh Finland for PV is 5.5 panels TWh and for 4–5 PV TWh panels for and solar 4– heating5 TWh solutionsfor solar heating [72]. solutions [72]. In thethe model,model, increasingincreasing thethe electricityelectricity productionproduction from RES meansmeans thatthat conventionalconventional power production shouldshould bebe reduced, andand thus the amount of imported energy will be reduced too. Nuclear power still playsplays the base role in thethe model,model, andand aa maximummaximum export capacity of 2500 MW has been chosen based on the external power market. The share of RES in Finland for the reference year was already 31%31% accordingaccording toto thethe modelled modelled annual annual energy energy balance. balance. On On this this basis, basis, it i wouldt would be be interesting interesting to to increase the share of RES to 50% or even 75% of the total energy consumption and evaluate the increase the share of RES to 50% or even 75% of the total energy consumption and evaluate the CO2 emissionsCO2 emissions from from the whole the whole system. system. The modeling The modeling of the of new the scenarios new scenarios is based is onbased the on demand the demand for the referencefor the reference year, since year, the since total the amount total am ofount energy of consumptionenergy consumption could not could vary not excessively. vary excessively. As can be seen from Figure 2323,, to reach the goal of 50% 50% RES RES share, share, the the capacity capacity increase increase is mainly mainly based on future projections for wind turbines and hydropower. In addition, the share of biomass has notnot reached the maximum potential, but the primary change has mainly affected the transport and heating sectors. The planned capacity for HP was also taken into account. In this case, CO2 emissions heating sectors. The planned capacity for HP was also taken into account. In this case, CO2 emissions were 2929 Mt,Mt, withwith aa decreasedecrease ofof 2020 MtMt comparedcompared toto thethe referencereference case.case. In this scenario,scenario, the share of biomass increased by 37%, while RES-ERES-E accounted for 13%; nuclear and oil still played a large role in the energy market,market, withwith bothboth accountingaccounting forfor 19%19% ofof energyenergy consumption.consumption.

Energies 2018, 11, 3523 24 of 32 Energies 2018,, 11,, xx 23 of 31

FigureFigure 23.23.. Fuel consumption in the FinnishFinnish scenario withwith 50%50% RES.RES..

Figure 2424 showsshows thatthat thethe highhigh potentialpotential ofof biomassbiomass in FinlandFinland can help the country reach a level ofof 75%75% RESRES in in total total energy energy consumption. consumption. Moreover, Moreover, in thisin this scenario scenario the windthe wind and hydroand hydro capacity capacity have alsohave increased also increased based based on their on potential,their potential, especially especially wind wind power. power. The level The level of production of production resulting resulting from PVfrom panels PV panels and solar and heating solar heating systems systems was also was modeled. also modeled. In this scenario, In this scenario, the biomass theshare biomass increased share dramaticallyincreasedincreased dramaticallydramatically from 37% to fromfrom 56%, 337% while to 56%, there while was only there a 6%was increase only a 6% in RES-E increase compared in RES- toE compared the 50% RES to scenario.thethe 50%50% RESRES Nuclear scenario.scenario. energy NuclearNuclear still accounted energyenergy stillstill for accountedaccounted 13% of total forfor energy 13%13% ofof consumption, totaltotal energyenergy consumption,consumption, but the contributions butbut thethe fromcontributions fossil fuels, from namely fossil oil, fuels, natural namely gas, oil, and natural coal, were gas, quite and coal, small. were In this quite way, small. the future In this high way, share the offuture renewable high share energy of renewable use can be energy reached use and can the be total reache COd2 andemissions the total will CO be22 emissions only 11 Mt. will This be valueonly 11 is onlyMt. This 22% value that of is theonly reference 22% that case of the in 2013.reference case in 2013.

FigureFigure 24.24.. Fuel consumption in the Finnish scenario with 75% RES.RES.. 5.3. Results and Discussion 5.3. Results and Discussion In this study, we developed the EnergyPLAN models for Italy and Finland and validated them In this study, we developed the EnergyPLAN models for Italy and Finland and validated them with real statistics. The proposed EnergyPLAN model was proved to have a good accuracy to reﬂect with real statistics. The proposed EnergyPLAN model was proved to have a good accuracy to reflect the base case for the reference year of 2013. In addition, we also analyzed the national RES potential thethe basebase casecase forfor thethe referencereference yearyear ofof 2013.2013. InIn addition,addition, wewe alsoalso analyzedanalyzed thethe nationalnational RESRES potentialpotential of both countries, which will be the input for the higher RES scenarios. According to the European of both countries, which will be the input for the higher RES scenarios. According to the European roadmap for 2030 and 2050, the penetration of RES will increase in the European market, giving rise roadmap for 2030 and 2050, the penetration of RES will increase in the European market, giving rise to a more competitive low-carbon energy supply system. In order to show how it can be possible to toto aa moremore competitivecompetitive lowlow-carbon energy supply system. In order to show how it can be possible to reach this low carbon goal, new scenarios for both countries have been modeled based on existing base reach this low carbon goal, new scenarios for both countries have been modeled based on existing models of the reference year. The results show that biomass is the backbone of RES in Finland, whereas base models of the reference year. The results show that biomass is the backbone of RES in Finland, solar, wind, and hydropower are also well developed in Italy. The future scenarios are based on the whereas solar, wind, and hydropower are also well developed in Italy. The future scenarios are based potential of each RES in both countries. For Italy, the new scenarios are characterized by a share of 35% on the potential of each RES in both countries. For Italy, the new scenarios are characterized by a and 60%, increasing the installed capacity mostly with respect to solar technologies, wind turbines, share of 35% and 60%, increasing the installed capacity mostly with respect to solar technologies, wind turbines, and geothermal power. Biomass and wind power are the sources that allow Finland toto increaseincrease itsits RESRES toto 50%50% andand 75%.75%.

Energies 2018, 11, 3523 25 of 32

Energiesand geothermal 2018, 11, x power. Biomass and wind power are the sources that allow Finland to increase its24 RESof 31 to 50% and 75%. The output results from developed EnergyPLAN model for both countries can be summarized and shown in Figure 2255. It can be found that the total energy consumption and the CO2 emission all decrease when whenwhen RESRES sharesshares increase,increase, however however the the CO CO2 emissions2 emissions reduce reduce more more clearly clearly than than that that of oftotal total energy energy consumption. consumption. In Finland, In Finland, the total the energytotal energy consumption consumption for RES-50% for RES and-50% RES-75% and RES scenario-75% scenarioreduces by reduces 7.5% and by 7.5% 13.0% and respectively 13.0% respectively compared comparedto the base to case. the While base case. in Italy, While the reductionin Italy, the of reductionthe total energy of the consumptiontotal energy consumption is only 1.7% andis only 3.1%, 1.7% mostly and 3.1%, because mostly of the because different of the RES different portfolios RES in portfoliosthese two countries.in these two The countries. CO2 reductions The CO2 for reductio Finlandns arefor 52%Finland and are 82% 52% corresponding and 82% corresponding to the two RES to thescenarios two RES compared scenarios to compared the base case, to the while base for case, Italy while they for are Italy 22% they and 54%.are 22% and 54%.

(a) (b)

FigFigureure 2 25.5. ModeledModeled total total energy energy consumption and CO 2 emissionemission for for ( (aa)) Finland Finland and and ( (bb)) Italy. Italy.

The most importantimportant ﬁndingfinding is is that that the the RES RES energy energy transition transition may may not not dramatically dramatically reduce reduce the total the totalenergy energy consumption, consumption, but it but can it contribute can contribute a lot toa lot the to CO the2 reductionCO2 reduction and helpand help to reach to reach the road the road map maptarget. target. The goal The of goal the European of the European Commission Commission for 2050 is for the 2050 reduction is the of reduction greenhouse of gasgreenhouse emissions gas by emissions80%–90% fromby 80% 1990–90% levels. from At 1 the990 endlevels. of 1990,At the the end total of CO1990,2 emissions the total CO were2 emissions 512.5 Mt andwere 70.3 512.5 Mt Mt for andItaly 70.3 and Mt Finland. for Italy According and Finland. to the According model outputs, to the wemodel found outputs, that a we RES found scenario that of a 60%RES inscenario Italy can of 60%lead in to Italy CO2 canreductions lead to CO of 64%;2 reductions a RES scenario of 64%; a of RES 75% scenario in Finland’s of 75% energy in Finland’s market energy will allow market for 85%will allowCO2 reductions for 85% CO compared2 reductions to 1990 compared levels. to This 1990 can levels. even meetThis can the roadmapeven meet 2050 the roadmap target for 2050 Finland. target for Finland. 6. Possible Power Transmission and Discussion 6. PossiblePower Power transmission Transmission between and areas Discussion makes it possible to minimize the overall productions costs, sincePower power transmission can be produced between in areas areas withmakes the it lowestpossible production to minimize costs theand overall transferred productions to regions costs, sincewhere power the production can be produced cost is higher in areas [73 with]. Although the lowest Finland production and Italy costs are and not neighboringtransferred to countries, regions whereand they the do production not have a cost common is higher transmission [73]. Although grid,it Finland is interesting and Italy to study are not when neighboring transmission countries, can be andbeneﬁcial they do when not consideringhave a common the connectedtransmission EU grid, grids it and is interesting different electricity to study when demands transmission as well as can the bemarket beneficial prices. when Therefore, considering the electricity the connected demand EU trends grids andand marketdifferent prices electricity have been demands analyzed. as well as the marketThe electricity prices. Therefore, demand trendsthe electricity for both demand countries trends are shownand market in Figure prices 26 have, and been the analyzed. behavior of the electricityThe electricity demand demand in the trends reference for both year countries can be compared. are shown in The Figure electricity 26, and demands the behavior have of quite the electricitydifferent ranges demand for the in the two reference countries; year the average can be hourly compared. demands The are electricity 9.56 GWh demands and 36.32 have GWh quite for differentthe Finnish ranges and thefor Italianthe two markets, countries; respectively. the average The hourly trends demands are not compatible;are 9.56 GWh in summer,and 36.32 the GWh Italian for theelectricity Finnish demand and the reaches Italian amarkets, higher value respectively. than in The winter trends because are not of the compatible; cooling load, in summer, as covered the Italianby electric electricity devices, demand whereas reaches the Finnish a higher trend value shows than a decrease. in winter In because this respect, of the the cooling two countries load, as coveredare complementary. by electric devices, whereas the Finnish trend shows a decrease. In this respect, the two countries are complementary.

Energies 2018, 11, x 25 of 31 Energies 2018, 11, 3523 26 of 32 Energies 2018, 11, x 25 of 31

Figure 26. Electricity demand trend for Finland and Italy in 2013. FigureFigure 26. 26Electricity. Electricity demanddemand trend for Finland and and Italy Italy in in 2013 2013.. A lack of dependence between the two markets can be proved and estimated via the correlation coefficientA lackA lack and of of dependence the dependence coefficient between between of determination, the the twotwo marketsmarkets starting can befrom be prov proved theed drawing and and estimated estimated of scatter via via the plots the correlation correlation in Figures coefficient and the coefficient of determination, starting from the drawing of scatter plots in Figures coefficient27 and 28. andThe the correlation coefficient coefficient of determination, illustrates starting the linear from relationships the drawing ofbetween scatter plotsthe observed in Figures data 27 27 and 28. The correlation coefficient illustrates the linear relationships between the observed data andvalues: 28. The correlation coefficient illustrates the linear relationships between the observed data values: values: n xy − x y n∑ xy ∑ x ∑ y r = qr  n xy q x  y (2) r  2 22222 2 2 (2) n(nx x)22−( x x)22· nn( yy ) − ( y y) (2) ∑n x ∑  x n  ∑ y    y∑ wherewherewhere nn isisn theisthe the numbernumber number ofof of pairspairs pairs ofof of data.data. data. ItIt canIt can can be be assumed be assumed assumed that that that a correlation a a correlation correlation greater greater greater than than than0.8 can 0.8 0.8 generally can can generally generally be described be be described described as strong, as as strong, whereas strong, awhereas correlationwhereas a a correlation of correlation less than of 0.5 of less is less weak. than than The 0.5 0.5 correlation is is weak. The coefficient correlation correlation for the coefficient coefficient two arrays for for of the electricitythe two two arrays arrays demand of of inelectricity Italyelectricity and demand Finlanddemand in isin Italy 0.39,Italy and and showing Finland Finland a weak isis 0.39,0.39, dependency, showing aa weakweak as shown dependency, dependency, in Figure as as shown27 shown. The in coefficient inFigure Figure 27 .2 of7. determinationTheThe coefficient coefficient is of rof 2determination, determination and it gives the is is r r proportion22,, and and itit givesgives of the the proportionproportion variance of of of one the the variable,variance variance of which of one one variable, can variable, be predicted which which basedcancan be onbe predicted thepredicted other based variable.based on on the Thisthe other other particular variable.variable. variable This particular meansparticular the variable variable percent meansof means the datathe the percent nearpercent the of best ofthe the data fit data line. Thenearnear coefficient the the best best fit isfit line. equal line. The The to 0.15coefficient coefficient in this is study,is equalequal meaning to 0.15 inin that thisthis only study,study, 15% meaning meaning of thetotal that that only variation only 15% 15% of in ofthe the the total Italian total datavariationvariation can be in explainedin the the Italian Italian by data thedata linearcan can bebe relationship explainedexplained by between the linearlinear Finland relationshiprelationship and Italy. between between Likewise, Finland Finlandr2 is theand and measure Ita Italy. ly. ofLikewise, howLikewise, well r2 r theis2 isthe regressionthe measure measure lineof of how how represents well well thethe the regressionregression data; looking lineline representsrepresents at the scatter the the data; plotdata; looking in looking Figure at at27the the, itscatter isscatter clear thatplotplot thein inFigure data Figure do 2 72 not,7 it, itis follow is clear clear athat that well-determined the the data data dodo notnot line. follow aa wellwell--determineddetermined line. line.

Figure 27. Scatter plot of the electricity demand in Finland and Italy. FigureFigure 27.27. Scatter plot of the electricity demand in Finland andand Italy.Italy. The same analysis can be carried out for the market price data. In this case, the two coefficients areTheThe even samesame smaller. analysisanalysis The correlation cancan bebe carriedcarried coefficient outout forfor is thethe equal marketmarket to 0.27 priceprice and data.data.the coefficient In this case, of determination the two coefficientscoefficients only are even smaller. The correlation coefficient is equal to 0.27 and the coefficient of determination only are even smaller. The correlation coefficient is equal to 0.27 and the coefficient of determination only

Energies 2018, 11, 3523 27 of 32 Energies 2018, 11, x 26 of 31

0.07 becausebecause ofof aa great great amount amount of of value value far far from from the the main main concentration concentration area. area. That That underlines underlines thelack the oflack dependence of dependence between between the two the markettwo market prices, prices, as shown as shown in Figure in Figure 28. 28.

FigFigureure 2 28.8. Scatter plot of the market prices in Finland and Italy Italy..

The average market pricesprices areare 62.9762.97 €€/MWh/MWh and and 41.12 41.12 €/MWh€/MWh for for Italy Italy and and Finland, Finland, respectively. respectively. This difference is is related related to to the the market market itself, itself, the the effect effect of of RES, RES, fuel fuel costs, costs, and and the the share share of imports, of imports, all allof which of which have have already already been been analyzed analyzed though though the the ener energygy market market modeling modeling of ofboth both countries. countries. Based on the difference in marketmarket prices and electricityelectricity demand trends, we can conclude that transmissionstransmissions areare possiblepossible ifif aa transmission gridgrid betweenbetween the two countries would exist or if a proper intermediateintermediate transmiss transmissionion line line is is established established via via another another country. country. A study A study on power on power transmission transmission can canbe carried be carried out out by by imagining imagining that that Finland Finland and and Italy Italy are are interconnected interconnected through through the neighboring neighboring countries in the formform ofof aa chain.chain. Power transmission from Finland to Italy would occuroccur whenwhen thethe market price in Finland is lowerlower thanthan thatthat ofof Italy,Italy, asas shownshown inin FigureFigure 2929..

FigureFigure 29.29. Electricity market price trend for Finland and Italy in 2013.2013.

In orderorder toto estimate estimate the the beneﬁt benefit from from this this power power transmission, transmission, the the analysis analysis can can be carriedbe carried out o forut thefor daythe day of highest of highest demand demand in the in Italianthe Italian electricity electricity market, market, shown shown in Figure in Figure 30. During 30. During the reference the reference year, ayear, peak a electricity peak electricity demand demand of 54.37 ofGWh 54.37 occurred GWh occurredon the 26th on of the July 26th between of July 11:00 between in the morning 11:00 in and the noontime.morning and The noontime. Italian electricity The Italian demand electricity is characterized demand isby characterized a well-deﬁned by shape, a well which-defined underlines shape, which underlines the beginning of the day shown in Figure 30a; on the other hand, the Finnish curve is extremely flat. The Finnish market price is lower than the Italian price shown in Figure 30b, so

Energies 2018, 11, 3523 28 of 32 the beginning of the day shown in Figure 30a; on the other hand, the Finnish curve is extremely ﬂat. Energies 2018, 11, x 27 of 31 The Finnish market price is lower than the Italian price shown in Figure 30b, so power transmission frompower Finland transm toission Italy would from Finland be possible to Italy and would meaningful be possible during and this meaningful day. In this during case, this the day. behaviors In this of marketcase, pricesthe behaviors also differ; of market they bothprices have also a differ; peak correspondingthey both have toa peak the high corresponding demand, but to the the high Italian marketdemand, price but shows the Italian a drop market because price of increased shows a drop electricity because production of increased from electricity RES, especially production solar from power duringRES, theespecially midday solar hours. power during the midday hours.

(a) (b)

FigureFigure 30. 30(a. )(a Electricity) Electricity demand demand trendstrends andand ((b)) market prices prices recorded recorded on on the the 26 26 July July 2013 2013 for for Italy Italy andand Finland. Finland.

InIn order order to to estimate estimate the the amount amount of of possiblepossible powerpower transmission, the the import import costs costs and and amount amount of of exportedexported electricity electricity have have been been collected collected andand compared.compared. The The Italian Italian import import rate rate for for the the day day of ofhighest highest demanddemand was was 126.9 126.9 GWh. GWh. If this If this power power transmission transmission brings brings benefits, benefits, then then the Finnish the Finnish market market can export can electricityexport elec to fulfilltricity partto fulfill of the part Italian of the need Italian and need increase and itsincrease electricity its electricity supply to supply cover to part cover of the part Italian of demand.the Italian Finnish demand. electricity Finnish export electricity for thatexport particular for that particular day is recorded day is asrecorded 3.5 GWh. as 3.5 If thisGWh. amount If this is consideredamount is the considered base amount, the base then amount, about 3.3 then GWh about can 3.3 reach GWh the can Italian reach grid the when Italian considering grid when the transmissionconsidering losses the transmission of 5%. We canlosses see of that 5%. the We transmission can see that amountthe transmission is small inamount comparison is small to in the comparison to the amount of total imported electricity. But this is one example to prove the feasibility amount of total imported electricity. But this is one example to prove the feasibility and the benefits of and the benefits of an integrated European electricity market, characterized by one bidding market an integrated European electricity market, characterized by one bidding market and interconnections and interconnections between countries. between countries. As the share of RES increases, new challenges arise, especially in terms of securing the supply As the share of RES increases, new challenges arise, especially in terms of securing the supply of of power. RES in general relies on weather conditions, and sometimes energy production does not power.meet RESthe demand. in general The relies use onof storage weather in conditions,the energy market and sometimes can increase energy flexibility production and reliability. does not meetSo theas demand. not to have The negative use of storage electricity in the prices, energy as happened market can in increaseGermany flexibility last spring, and electricity reliability. storage So as notis a to havesolution negative for electricity unforeseen prices, electricity as happened production in Germany from last RES. spring, Nevertheless, electricity electricity storage is a storage solution fortechnologies unforeseen remain electricity critical production even though from sometimes RES. Nevertheless, the more-expensive electricity than storage additional technologies transmission remain criticalcapacity even and though a good sometimes interconnected the more-expensive infrastructure could than additionalalso decrease transmission the need for capacity them. and a good interconnected infrastructure could also decrease the need for them. 7. Conclusions 7. Conclusions RES are playing an increasingly important role in the European energy market. They are the key to RES future are policies playing and anincreasingly offer a roadmap important for a role more in renewable,the European sustainable, energy market. competitive, They are and the cost key- to futureeffective policies energy and offer market. a roadmap This paper for a studies more renewable, reasonable sustainable, energy transition competitive, by highlighting and cost-effective RES energypenetration, market. especially This paper when studies considering reasonable different energy climate transition conditions by highlighting and different RES portfolios penetration, of especiallyenergy supply when consideringand demand different data. However climate it conditions is quite difficult and different to obtain portfolios the detailed of energy energ supplyy supply and demandand demand data.However data for some it is quiteenergy difficult sectors toin obtainthe country the detailed level, therefore energy supplythis study and firstly demand proposed data for somean aggregation energy sectors method in the to country scale up level, the energy therefore profiles this based study on firstly the data proposed of typical an aggregationcities. In addition, method tofew scale researchers up the energy had considered profiles based the energy on the transition data of using typical the cities. relatively In addition, accurate profiles few researchers of supplies had consideredand demands the energyin hourly transition resolution using as well the as relativelyRES potentials accurate in the profiles country of level. supplies Therefore, and demandsthis paper in hourlybridges resolution these gaps as well by studying as RES potentials the renewable in the countryand sustainable level. Therefore, energy transition this paper for bridges two count theseries gaps bywith studying different the renewableprofiles in andthe supplies sustainable and energy demands, transition RES potentials for two countriesas well as with the different different climates profiles in by using the EnergyPLAN. the supplies and demands, RES potentials as well as the different climates by using the EnergyPLAN. We defined the base scenarios and energy transition scenarios with different RES shares for the two countries according to the RES potentials, and examined whether and how the transitions could

Energies 2018, 11, 3523 29 of 32

We defined the base scenarios and energy transition scenarios with different RES shares for the two countries according to the RES potentials, and examined whether and how the transitions could happen, and their influences to climate change. The results show that biomass is the backbone of RES in Finland, whereas solar power, wind power, and hydropower are also well developed in Italy. The future scenarios are based on the potential of each RES. For Italy, the new scenarios are characterized by a share of 35% and 60%, increasing the installed capacity mostly with respect to solar technologies, wind turbines, and geothermal power. Biomass and wind power are the sources that allow Finland to increase its RES to 50% and 75%. The most important finding is that the RES energy transition may not dramatically reduce the total energy consumption, but it can contribute a lot to the CO2 reduction and help to reach the road map target. Therefore, we concluded that the European aim is concrete and can be achieved if the transition policies obtained in this study are adopted. The possible interlinks between the two countries were also considered in the energy system modelling in order to examine the possible influences of the energy transmission and more efficient cross-border activities on the energy transition. These are the main new contributions to the existing pool of knowledge in this respect. The new modeled scenarios can be considered for future national plans to better understand where to invest and to estimate the decarburization level. Another possible solution can be market coupling; realizing the goal of a single European energy market will make energy production more flexible and reliable. This analysis has focused on the modeling and input/output data related to achieving higher RES shares and reducing the emissions in energy systems. The next step will include cost evaluation and analyzing how the new investments in RES can be profitable in the long-term and how RES could influence market prices. This study can reflect, to some extent, energy transitions in other EU countries. It provides quantitative results on how to reach EU targets and offers an effective pathway towards achieving a low-carbon energy supply.

Author Contributions: H.W., G.D.P. and R.L. conceived and designed the method; X.W., V.V. and I.H. contributed some materials and valuable suggestions; H.W. and G.D.P. analyzed the data and wrote the paper. Funding: This work was supported by the China national key research and development program—China-Finland intergovernmental cooperation in science and technology innovation (Funding No. 2016YFE0114500) and Academy of Finland funding (Grant Number No. 299186). We would also like to thank the “Xinghai” talent project of Dalian University of Technology. Conﬂicts of Interest: The authors declare no conﬂict of interest.

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