Increasing the Penetration of Renewable Energy Sources in Isolated Islands Through the Connection of Their Power Systems

Increasing the Penetration of Renewable Energy Sources in Isolated Islands through the Connection of their Power Systems. The Case of Pico and Faial Islands, Azores Márcia Filipa Oliveira Alves [email protected] Instituto Superior Técnico, Universidade de Lisboa, Portugal October 2017 Abstract Anxiety over escalating environmental degradation on the part of governments, non-governmental organizations, companies and populations has reached fever proportions in recent years. In practice, the awareness of this concern has been reflected in a reduction of the consumption of fossil fuels and in an increasing use of renewable energy sources (RES). The implementation of RES in isolated power systems, as is the case of islands, constitutes both a challenge and an opportunity. The RES intermittency originates problems of grid stability, as well as a mismatch between power demand and supply. The connection between isolated power systems can decrease the RES variability and, thereby, to minimize the problems associated with their intermittency. In this work, the endogenous resources of the islands of Pico and Faial were characterized and their power systems were modeled. A scenario considering the connection between the power systems of the two islands is proposed with the objective of increasing the RES penetration in these islands. The proposed scenario comprises a combination of biomass, municipal solid waste, wind, solar, wave and hydro as RES. It is still proposed the use of sodium-sulphur batteries as storage technology of electricity, and fossil fuels to cover the mismatch between demand and supply. The results obtained show that rehabilitating the renewable technologies already installed in the two islands and constructing a biomass power plant and a municipal solid waste valorization plant, the RES penetration in the Islands increases by about 27 pp as compared to the Business as Usual scenario. As a result, the fossil fuels consumption and the corresponding CO2 emissions are reduced by about 25%. The implementation of this scenario represents additional annual costs for both islands of less than 3.5 million euros. In addition, based on the knowledge gained from the present study, measures that may lead, in the long run, to the complete elimination of the use of fossil fuels in all sectors of activity of both islands are presented and discussed. Keywords: Isolated Power Systems; Renewable Energy Sources Intermittency; Renewable Energy Sources Integration; Energy in Islands 1 Introduction Small islands exhibit a high energy dependence on imported fossil fuels, relying on external countries to ensure their normal daily life. This condition not only restricts their ability to be self-reliable but also compromises their economy owing to the very high fuels’ cost in islands [1]. By using the island’s endogenous resources, the renewable energy technologies may be able to tackle these issues. Nevertheless, Renewable Energy Sources (RES) integration in an isolated power system presents limitations. High renewable energy penetration levels create difficulties both in terms of grid stability and mismatch between demand and supply. These issues are associated with the intermittent nature of most of the renewable resources. Therefore, each power system must be carefully designed to obtain an energy mix as broad as possible as well as a reliable backup [1]. The Autonomous Region of the Azores (ARA) is a part of the EU Outermost Regions (OR). The OR are characterized by small land areas, isolation and significant distances to the European continent. The islands have isolated power systems and a dependence on fossil fuels for energy supply. This provides both a challenge and an opportunity for RES integration. ARA is an autonomous territory of the Portuguese Republic and it is constituted by nine islands, divided into three territorial groups: oriental group, central group and occidental group. All nine islands of the archipelago have their own isolated power system, and electricity is provided by the same company, Electricidade Dos Açores (EDA). In 2016, the total electricity demand amounted to 800.77 GWh [2]. The archipelago is considerably dependent on imported fossil fuels, exhibiting an overall RES penetration share of 33% on its electricity production [2]. The RES penetration, however, is rather heterogeneous, with some islands presenting RES penetration shares above 50%, and others of 0 as far as electricity is concern. Most of the archipelago’s renewable energy production is currently originated from the geothermal resource, which was responsible for 19% of the total generated power in 2016 [2]. The wind power generation is the second biggest contributor with a share of 9.1% [2]. Pico and Faial are part of the central group of the archipelago and are rather close to each other, with only 7.5 km separating them. The islands exhibit very similar characteristics. Each island has around 6% of the archipelago’s population. The islands’ main economic activities both focus on the primary sector, and exhibit very little representation of the industry sector. The islands present similar energy needs, with a power consumption of approximately 40 GWh in 2016 [2]. The sectors showing the highest power consumption correspond to the commerce and services sectors and the residential sector. Regarding power production, both islands are very dependent on imported fossil fuels and significant endogenous resources which only a very small part of them are being exploited as a source of energy; indeed, the RES penetration in both islands is only 13% with most of the RES share originated from wind power [2]. The present study is focused on the maximization of the RES penetration in Pico and Faial Islands, Azores, by the year 2030. The main objective is the study is to develop and propose a credible scenario to allow for such maximization, while taking into consideration the economic feasibility of its implementation. The present work concentrates solely on two of the nine islands that constitute the ARA. In particular, the scenario proposed considers the establishment of a novel, common, power system

1 for both islands, which will allow them to share both the power demand and power supply. To accomplish this objective, a complete characterization of Pico’s and Faial’s power systems is made, both in terms of demand and supply. Moreover, the islands’ endogenous energy resources are mapped and their potential is calculated. The baseline scenario is modeled in a well- known energy planning tool, EnergyPLAN. A credible scenario is developed for increasing the penetration of RES in both islands through an undersea connection of their power systems – the proposed scenario includes wind, hydro, solar and biomass and urban waste as RES for the power supply, and an energy storage system; and quantification of the costs associated to the implementation of the proposed scenario. Finally, a presentation and discussion of measures that may lead, in the long run, to the complete elimination of the use of fossil fuels in all sectors of activity of both islands is carried out. 2 Literature review The ARA has been extensively studied in recent years when it comes to renewable energy. A number of studies have been undertaken on the increase of the RES penetration in islands and the feasibility of 100% RES energy systems. Martins et al [3] examined the possibility of increasing the renewable energy penetration in Terceira Island, in Azores, in order to reduce its fossil fuels extreme dependence. The authors conclude that the potential of RES in Terceira can supply almost all the island’s energy needs. Nonetheless, the authors pointed out that it is not possible to completely eliminate fossil fuel usage and achieve total energy independence [3]. Parissis et al [4] evaluated the integration of wind energy for electricity production, and hydrogen production as the energy storage system in Corvo Island, in Azores. They concluded that with the proposed system it is possible to cover 80% of the island’s electricity needs, with a 43% reduction in the power generation cost [4]. Duić et al [5] applied the RenewIslands methodology to the Corvo Island and concluded that a synergy exists for the merging of the electricity and water supply systems. Results showed that the RES penetration can be increased from 25% up to 70% share, without and with energy storage, respectively, without significant additional costs [5]. Cross-Call [1] studied the integration of energy storage in scenarios for increasing the wind energy penetration in S. Miguel, Faial and Flores Islands, in Azores. Results indicated that renewable energy systems coupled with energy storage may produce significant savings in operating costs. The study showed that storage power assumes a higher relevance to achieve cheaper and cleaner energy goals, when compared to storage capacity. Furthermore, the author concluded that islands relying exclusively on wind for power generation, such as Faial Island, will not be able to attain aggressive clean energy goals even with storage integration [1]. The Younicos Company has recently installed a 4 MW battery energy storage system, which allowed for wind and solar energy to unsure the base-load generation in Graciosa Island, in Azores. This allows for up to 100% instantaneous renewable power penetration and a 65% RES penetration share on a yearly basis [6]. The implemented project will reduce the overall energy costs on the island [7]. Bağcı [8] concluded that it was possible to transform Peng Chau Island, in Hong Kong, in a ‘Zero Energy Island’ by producing all of the island’s required electrical energy with the available endogenous resources. The results showed that a combination of two of the RES with the most potential is sufficient to meet the island’s energy demand [8]. Godina et al [9] analyzed the results of the implementation of the first MW-level energy project of a system with wind as the power source and water storage in El Hierro Island, in the Canarias archipelago. The financial data showed that for the system to last its expected lifetime, components with shorter lifetimes will have to be replaced, increasing the project’s costs. The authors conclude that for the first two decades, RES would contribute with more than 75% of the power needs, however there would be a need for new generation facilities to maintain or increase the renewable energy quota [9]. Finally, Gils and Simon [10] presented a scenario pathway to a 100% RES energy system for the entire Canarias archipelago. The results showed that a scenario of smart linkage between the sectors, water supply combined, traditional energy storage technologies and demand side management strategies contribute notably for the integration of intermittent RES generation. Moreover, the results showed that the supply costs decrease when considering sea cables’ connections of all of the archipelago’s islands [10]. 3 Case Study - Pico and Faial Islands As mentioned above, Pico and Faial are two of the islands that constitute the central group of the ARA. Pico is the largest island of the central group, it is located 28º 20’ West and 38º 30’ North. It has a total surface area of 447 km2 [11]. The island has an area of 149.4 km2 of forest, corresponding to 33.6% % of its surface, the highest percentage of the archipelago. 50.3 % of its area is dedicated to agriculture and pasture and 2.2% of the island corresponds to the urban area. Its entire surface is irregular and hilly. Faial is located 28º 42’ West and 38º34’ North. The island has an area of 173.1 km2 and is shaped like an irregular pentagon. Faial’s forest amounts to 17.5% of its area, occupying 30.3 km2; 67.1% of the island is used for agriculture and pasture activities, the highest percentage in the archipelago. The urban and social areas occupy 4.9% of the land. The islands have an average air temperature close to 17 ºC, and maximum and minimum values of 10 to 23 ºC in winter and summer seasons [11]. Relative humidity values are close to 77%. The high humidity and low temperatures on the islands are responsible for the specific vegetation and biodiversity. 3.1 Social- Economic Context Pico’s and Faial’s population has been decreasing for the past few years. The islands’ number of inhabitants was 13,859 and 14,792 in 2016, in Pico and Faial, respectively [12]. Pico’s administrative territory is divided into three municipalities: Madalena, Lajes do Pico and S. Roque do Pico, with a total of 17 parishes. Faial’s administrative territory is composed by a single municipality, Horta, divided into 13 parishes. Pico had a total of 2073 companies in 2015. 37% of these companies work in the primary sector, namely in agriculture, cattle breeding and fishing. The island also relies on its wine industry and touristic activities, such as whale watching. In 2014, the Gross Domestic Product (GDP) of the island was 186 million Euros, 5% of the ARA’s GDP [13]. Despite of its smaller dimension, Faial has almost as much companies as Pico, with 2003 companies, in 2015. The island’s most relevant activities are also agriculture and cattle breeding, with milk and dairy production, and fishing [13]. Faial also depends on tourist activities. The Island had a GDP of 231 million Euros in 2014, 6.2% of the ARA’s GDP [14].

2 3.2 Energy Sector 3.2.1 Energy Demand Fossil fuels are currently the main sources used for power production in both islands under the responsibility of the islands electricity company, named Electricidade dos Açores (EDA). Fossil fuels are also the main sources used to power internal combustion engines in the transport sector, both private and public. In the residential sector, its usage is mostly related to cooking activities and hot water production. Fossil fuels are also used in primary activities as agriculture and fishing and in tertiary activities of commerce and services. In the industry sector, fossil fuels are used to produce heat and power and oil products. In 2015, a total of 18,843 tons of fossil fuels were sold in Pico and 21,865 tons were sold in Faial [15]. The electricity production sector and the transport sector were the two most demanding sectors regarding fossil fuel consumption in both islands. In 2016, Pico’s yearly electricity consumption amounted to a total of 41.02 GWh, a 1.7% increase in comparison to the previous year [2]. From this value, 76.1% refers to low voltage (LV), while the remaining 23.9% refers to medium voltage (MV), consumed by the 9,647 electricity consumers on the island [2]. Despite its smaller size, Faial’s electricity demand has been lower that of Pico Island’s in the last six years. Specifically, in 2016 the Faial’s electricity demand corresponded to 43.44 GWh, about 2 GWh above Pico’s demand. The structure of such consumption corresponded to 71.3% of LV consumption and 28.7% of MV consumption. These consumption values exceeded the previous year by 1% but the number of consumers in the island remained the same (8036 people). Figures 1 and 2 present the power consumption by sector in the Islands of Pico and Faial, respectively [2]. The commerce and services and residential sectors are the most power demanding sectors in both islands. Note that the self-consumption sector in the figures corresponds to the electricity company’s own consumption. The commerce and services sector include private services as well as public services. The only service that is measured separately is the public lighting.

Figure 1 – Power consumption by sector in Pico in 2016. Figure 2 – Power consumption by sector in Faial in 2016.

3.2.2 Energy Supply For the system’s energy supply, both fossil fuels and electricity were considered as energy carriers. Since fossil fuels are imported by the islands its demand matches its supply whenever fuel is to be used as the final form of energy, e.g. in the transport or residential sectors. Therefore, only electricity production is presented here and the islands’ power systems are analyzed. Table 1 shows the existing generation units currently working in both Pico and Faial Islands. Table 1 – Power units installed in Pico and Faial Islands in 2016 [16], [17].

Installed Commissioning Island Name capacity (kW) Date Pico thermal power plant 16,763 1990 Pico Terras do Canto wind park 2,400 2005 Pico oscillating water column 400 1999 S. Barbara thermal power plant 19,107 1982 Faial Salao wind park 4,250 2013 Varadouro hydro power Plant 320 1967 The existing thermal power plants in S. Roque do Pico and S. Barbara are both fossil fuel-based plants. The wind park of Terras do Canto, in Pico, has eight Enercon E-30 wind turbines of 300 kW each. The wind park of Salao, in Faial, has five Vestas V52 wind turbines of 850 kW each. The wave plant installed in Porto Cachorro uses the oscillating water column (OWC) technology and is equipped with a turbine (Wells) of 400 kW. The Varadouro hydro power plant has a nominal capacity of 320 kW and has a reservoir with 1000 m3 capacity used to support the production. As expected, the electricity production has followed the electricity demand, For the last six years, the production coming from RES has grown. In 2016, power production was 45.85 GWh in Pico and 48.78 GWh in Faial. In Pico, approximately 4.1 MWh were produced from residential solar PV panels and 11.8 MWh were generated by the wave resource. In the same year, 6.15 GWh were produced by wind and the remaining energy was supplied by fossil fuels. In Faial, 5.45 GWh were generated from the wind resource, 2.2 MWh were generated from the hydro resource and the remaining was generated from fossil fuels. This value represents a cutback on hydro production. The hydro plant showed a defective output for the stated year because of a malfunction.

3 3.3 Characterization of the Islands’ RES 3.3.1 Wind Energy The islands’ wind energy potential is evaluated with the aid of data on wind speed from 2016. The wind speeds were measured in the parks of Terras do Canto, in Pico, and Salao, in Faial, at heights of 44 m and 53 m, respectively. These heights correspond to the respective hub heights of the specific installed wind turbines in both islands. Data was recorded every half an hour and was processed in order to allow for estimates of the wind energy potential. The available data presents gaps of information for wind speed at certain hours, so that such gaps had to be filled using the averages of adjacent hourly values. Pico’s average wind speed is approximately 9 m/s. Wind speeds on the island vary largely along the year, from a maximum value of 15.2 m/s observed in January to a minimum of 5.5 m/s in July. This information agrees with the observable seasonal variability, with summer months showing lower wind average speeds. The most frequent wind speed class is between 4 and 5 m/s. Faial’s average wind speed reached a slightly lower value of about 7.9 m/s. The month with the highest average was also January, with 11.8 m/s, and in July average wind speed was at its lowest value, 5 m/s. Faial’s most frequent wind speed class value is below Pico’s value, between 2 and 3 m/s. 3.3.2 Solar Energy Due to both islands’ geographic proximity, the values for the incident radiation are quite similar and, because of this, there are presented together. The global horizontal incident radiation and the sky’s clearness index for Pico and Faial were both monthly averaged over a period of 22 years (1983 to 2005) and retrieved from NASA’s database of surface meteorology and solar energy. The annual average of the daily global horizontal incident radiation is 4.39 kWh/m2/day [18]. As expected, the summer months exhibit the largest values for the incident radiation and for the sky’s clearness index. July has the highest average of incident radiation (6.98 kWh/m2) and a clearness index of 0.618. In addition, August’s incident radiation values are slightly inferior (6.45 kWh/m2) than in July, but sky’s clearness index is slightly higher (0.633) than in July. In contrast, December exhibits the lowest values for both the average incident radiation and the clearness index (1.75 kWh/m2 and 0.43, respectively) [18]. It should be stressed that the solar energy potential strongly depends not only on the available surface area, but also on the deployed technology. 3.3.3 Hydro The data for the magnitude of rain occurrence and intensity in both islands was obtained from the climatologically report of Instituto Português do Mar e da Atmosfera (IPMA). The total amount of rainfall on Pico Island in 2016 was 1082.5 mm, with an average value of 90.2 mm per month. Values range from 15.8 mm of rain in February, with 11 rainy days, to 230 mm in December during 23 days of rain. Faial’s water abundance is somewhat smaller than in Pico. In this island, the total year rainfall was 936.1 mm and the monthly average vale was 80.26 mm. January was the rainiest month, with 209.6 mm of rain in 24 days, and November the one with less rain, with 17.6 mm of rain in 13 days. 3.3.4 Wave Energy Waves offer an abundant and more predictable source of energy. Waves are more energy intensive, which means that the wave energy flux near the surface is more concentrated than the wind energy flux. Furthermore, waves’ intensity can be foreseen with days in advance making it a more predictable resource as compared to both the wind and solar energies. Particularly in islands, where the ratio between the coast line length and the region’s size presents relative very high values, the wave energy constitutes a powerful RES that cannot be disregarded. Moreover, islands of volcanic origin, like the present two islands, have accentuated depths near the shore line, which make them perfect candidates to take advantage of such resource. Nonetheless, wave energy technologies are not mature yet, with no specific technology presenting a clear advantage over the others, so that the future of such technologies is still uncertain. Accordingly, the analysis presented below has a pure theoretical nature and follows the procedure of Bağcı [8]. The total energy per wave and per width is obtained as follows:

1 2 (1) 퐸̅ = 휌푔H 퐿 8 푠 where Hs is the wave significant height, L is the wave length, ρ is the water’s density and g is the gravity’s acceleration constant. The wave length, L, is calculated using the average time period, Tz, as follows:

1 2 (2) 퐿 = 푔푇 2휋 푧

From the monthly average values retrieved from Matos et al [19] ,an annual average significant height and an annual average wave period were calculated. Considering the average wave significant height equal to 1.44 m, and the average wave period equal to 4.51 s, equation (1) yields a value close to 23 Wh/m. In the Island of Pico, the most frequently observed waves are those coming from northwest [19].The conversion efficiency is not evaluated in this section since it depends on the deployed technology. On the account of the islands proximity, the wave climate data presented here may be used to study the potential for both islands. 3.3.5 Biomass The potential of biomass addressed in the present section refers exclusively to forestry biomass. A considerable part of Pico and Faial Islands is occupied by forest, namely 33.6% and 17.5%, respectively. Several species occupy the forestry territory of these islands. Acacia melanoxylon (Acacia negra), Cryptomeria japonica (Criptoméria), Eucalyptus globules (Eucalipto),

4 Morella Faya (Faia das ilhas), Persea indica (Vinhatico), Pinus pinaster (Pinheiro bravo), Pinus tumbergi (Pinheiro japonês), Pittosporum undulatum (Incenso) and Robinea pseudoacacia (Acacia branca) are the hardwood species present on the studied islands. Figures 3 and 4 show the forest species’ distributions across Pico and Faial respectively.

Figure 3 - Forest species’ distribution in the Pico Island [21]. Figure 4 - Forest species’ distribution in the Faial Island [21].

The Pittosporum undulatum is clearly dominant in the islands, representing 78% and 58% of the forest territory on Pico and on Faial islands, respectively [20]. The Cryptomeria is the second species with larger occupation. Pittosporum undulatum is an invasive species and its wide spread has been considered a problem. Several studies have been made to identify possible solutions for the species control. Medeiros et al [20] studied the potential of Pittosporum undulatum for biomass production in all nine islands of Azores. The authors calculated the annual wood production for each island considering a 10 years revolution period, a ratio of 13,000 m3 of wood per km2 and a wood density of 0.56 ton/m3. Operational waste corresponds to 20% of the annual biomass production. Cryptomeria is widely used in the forestry exploration and wood industry. The species is of extreme importance for the islands’ forestry sector and is a source of economical income. Therefore, it makes no sense to solely use it as biomass for energy proposes. However, such economic activities produce operational waste, good quality biomass obtained at a lower cost. In Faial, 18 companies work on the forestry sector. Pico is the island with the second most companies working on the forestry industry, with a total of 29 companies [21]. Values for the specie’s annual exploitation were calculated from the exploited area considering an annual volume increase of 2,300 m3/km2 [22] and a density of 0.3 ton/m3 on a dry basis [23]. The byproducts and residues of the sawing industry are 30% of the woody material. Given Pittosporum undulatum’s clear dominance in occupation and Cryptomeria’s dominant use in the Island’s wood industry, these are the only two species considered. Table 2 presents the species’ biomass properties and energy potential. Table 2 – Biomass resource characterization.

2 Total Energy Area (km ) LHV Moisture Ash Volatile Species biomass Potential (MJ/kg) content content matter Pico Faial (ton/year) (GWh/year) Cryptomeria japonica 8.40 8.68 86.32 21 76% 0.6% 99% 0.5 Pittosporum undulatum 117.05 17.57 73,257 20 46% 1% 99% 406.94 3.3.6 Urban Waste In 2014, Pico was responsible for approximately 4% of waste generation of the Azores, with 5,495 tons of urban waste produced, and Faial produced 9,724 tons of urban waste with a 7% share [24]. Faial shows the second highest waste production per capita in the archipelago. To estimate urban waste production, the projection carried out in the Azores’ Strategic Plan for Prevention and Management of Residues [24] are used. These estimates revealed a waste production of 140,604 tons for the present study’ base year (2016) and a value of 141,023 tons for 2020 [24]. Waste production in 2030 is assumed to be the same as in 2020 due to the increase in recycling. Assuming that the islands’ relative contribution remains the same as in 2013 for the years to come, Pico and Faial Islands will generate 5,640.92 tons and 9,871.61 tons of urban waste, respectively, adding up to a total of 15,512.53 tons for both islands. Urban waste LHV may vary between 8 MJ/kg and 12 MJ/kg. Considering a LHV of 9 MJ/kg, according to [25], the estimated total energy potential for both islands is 38.78 GWh for 2020. Following a conservative approach, values for the energy potential are considered to be the same for 2030. 4 Methodology In order to establish a credible scenario, the present work was divided into three phases. Initially, both islands were characterized according to their geography, climate and social-economical contexts. Then, the energy needs were analyzed and quantified according to each activity sector, and the energy supply per technology was identified and also characterized for both islands. Next, the endogenous resources of both islands were detailed identified and characterized. This chapter describes the methodology used throughout this study and helped to establish the scenarios proposed and discussed in chapter 5. All scenarios presented in chapter 5 were modeled using the EnergyPLAN software [26]. The EnergyPLAN is an energy planning simulation tool that also allows for a certain level of optimization, according to the user’s inputs and outputs choices. The model is of deterministic nature, which means that the same input will always lead to the same output. Its mode of operation does not optimize system investments, but optimizes the modeled scenario, i.e. the program provides the best performance for the considered scenario and the user will have to test different scenarios in order to reach the best solution. This study started by modeling the Business as Usual (BaU) scenario using the available data for 2016 for each independent power system of the Islands of Pico and Faial. The annual power production in 2016 for each technology installed in both

5 islands was taken from EDA’s Demand and Supply of Electrical Energy Report [27]. The hourly power production was provided by the Azores Regional Directorate for Energy. The production units correspond to the existing units presented in Table 1. In order to take into account the energy losses through the grid electricity distribution systems, production is modeled as demand. Subsequently, the BaU scenario was modeled for 2030. The demand increase considered follows the EDA‘s presented forecasts [27]. [66]. It is important to point out that the method used in this study followed a differential approach. This means that the BaU scenario served as the baseline case, with the data obtained for all other scenarios being compared with the BaU scenario. Finally, the proposed credible scenario was modeled and the obtained data examined and discussed in detail. The input parameters for this scenario are presented in section 5.2. The outputs are retrieved from EnergyPLAN tool as hourly data sheets for each tested scenario. The selected outputs are the RES share in electricity production, and the Critical Excess Electricity Production (CEEP). To optimize the energy storage capacity, several scenarios with different energy storage capacities, are modeled. RES share in electricity production and CEEP values, for each energy storage capacity, are retrieved from EnergyPLAN. An optimization concerning the cost of the energy storage system is made. The addition of an energy storage system increases investment costs but reduces fuel related and CO2 related costs. Therefore, total cost for each capacity is calculated as the sum of the investment cost for an energy storage system, minus the avoided costs due to the fossil fuel consumption reduction and avoided CO2 emissions. The costs for the entire power system were calculated as differential costs. The presented costs represent the additional costs that would be necessary to ensure the transition from the current power system to the proposed one. The additional annual costs (Addcost) for the total k technologies installed were calculated as follows:

푘 (3)

Addcost = ∑(I0annualizzed + O&푀)푖 + 퐹푢푒푙푐표푠푡푠 − 퐹표푠푠푖푙퐹푢푒푙푑푖푓푓푒푟푒푛푡푖al + CO2differential 푖=1

Where I0annualized is the annualized investment cost and it is calculated considering the discount rate and the life time of the technology, in years. The discount rate considered is 6% [4]. In equation (3), the O&M are the yearly operation and maintenance costs for each technology, the Fuelcosts represent the costs of the fuel supplying all renewable power plants, excluding fossil fuel costs, the FossilFuelDifferential take into consideration the fossil fuel costs in the annual costs’ calculation as a differential quantity (this quantity is calculated as the difference between the costs related to the fossil fuel consumption in the BaU scenario and the costs related to the fossil fuel consumption in the proposed scenario, with increased RES penetration), and the CO2 Differential, which take into account the CO2 related costs, are calculated as the fossil fuel related costs. Finally, a comparison is made between the two separated power systems of Pico and Faial Islands, i.e. a scenario where there is no undersea connection between the two systems and the proposed joint system. Pico’s and Faial’s power systems were modeled separately, using the same resources as in the proposed joint scenario, and the RES penetration and the costs’ variation are compared. This scenario was modeled using smaller installed capacities, on the account of its smaller power demand comparing to the connected power systems 5 Results and Discussion This chapter presents and discusses the results of this study. Section 5.1 presents the inputs and results for the BaU scenario. Section 5.2 presents the inputs and results of the proposed scenario. 5.1 BaU Scenario Table 3 presents the input values for the BaU scenario. EDA forecasts Pico’s energy demand to increase by 0.4% each year and Faial’s energy to increase by 0.1% [27]. This forecast originates the electricity demand for 2030. The minimum grid stabilization share corresponds to the fraction of the power generated by non-intermittent sources, meaning that 70% of the supplied power must originate from stabilizing sources at every modeled hour. Table 3 – Inputs for the BaU scenario.

Pico Faial Power system 2016 2030 2016 2030 Electricity Demand (GWh) 45.84 48.48 48.78 49.46 Wind capacity 2400 4250 RES installed capacity Hydro capacity 0 320 (kW) Solar PV capacity 4.4 0 Wave capacity 400 0 Fossil fuel installed capacity (kW) 16,763 19,107 Minimum grid stabilization share 0.7 The amount of power possible to generate with the existing wind resource and the currently installed wind turbines is calculated, for both wind parks, with the aid of the wind turbines’ power curves. For each hour, the correspondent power is taken for the specific wind speed and multiplied by the number of existing wind turbines. This calculated power is the power that should be generated, each hour, if the installed technology is working properly. Also, in regard to the wind generation, a 30% limit for the hourly wind penetration, in relation to the overall electricity production, is defined. This limit is defined in order to ensure not only the grid stability and the power quality, but also to take into consideration the probability of the sudden loss of all

6 available wind power [28]. Such loss may occur, for instance, due to the activation of the network’s over current protection as a result of existing defaults in the interconnecting lines, voltage problems on the wind turbines or due to lack or excess of wind speed [28]. Table 4 shows the results of the BaU scenario. Table 4 – Results for the BaU scenario. RES share in Fossil fuel consumption Power CO emissions (tons) electricity production (GWh) 2 system 2016 2030 2016 2030 2016 2030 Pico 13.7% 13.5% 99.55 104.84 26,127 27,513 Faial 17.3% 17% 102.52 102.68 26,904 26,946 Pico + Faial 15.5% 15.3% 202.07 207.52 53,031 54,460 5.2 Proposed Credible Scenario Table 5 shows the inputs for the 2030proposed scenario for. The underwater sea cables connection is constructed at the point of the shortest distance possible between the islands, from the west margin of Pico, near Madalena, to the east Margin of Faial, near Horta. Table 5 - Inputs for the proposed scenario for 2030. Power system Pico + Faial Electricity Demand (GWh) 97.94 Wind capacity 6650 Hydro capacity 640 RES installed capacity Solar PV capacity 8.8 (kWe) Wave capacity 400 Biomass capacity 2,000 Urban Waste capacity 1,000 Fossil fuel installed capacity (kW) 35,870 Minimum grid stabilization share 0.7 Wind power was modeled in a similar manner as in the BaU scenario. As previously stated, wind dynamic penetration already exceeds the 30% limit numerous hours during the year so that no more wind capacity is required. The installed OWC technology installed in Pico is not working to its full capacity. The electrical system installed on the plant does not have the ability to keep up with the turbine’s full potential. According to [29], a replacement of the wave power plant’s electrical system, will originate an increase in the power generated. This originates a yearly production of approximately 0.8 GWh. The hydro power plant installed in Faial was first considered to be repaired from its malfunctioning. Moreover, the plant was considered completely repaired and thus it doubled its capacity. Fossil fuel-fired thermal power plants are still a part of the islands’ power system. Although the installed capacity of fossil fuels-based systems does not decrease, the usage of that capacity does, as a result of the increase in RES capacity. 5.2.1 Biomass and Urban Waste Although there is a tremendous biomass potential, the objective is not to shift the power system’s dependence on fossil fuels directly to a dependence on biomass resource. Therefore, only 30% of the total power must be provided by biomass and waste resources combined. This limit allows for the combination of biomass and waste energy production to match wind hourly penetration, making for a more diversified power system. Furthermore, the imposed limit takes into consideration the sustainability of forestry exploration, guaranteeing biomass availability for the plant’s entire lifetime. Firstly, all available urban waste is used for power generation. After, a comparison is made regarding the generated power from waste valorization and the power corresponding to the 30% limit imposed. The difference between these values is produced by the biomass resource. As for the biomass feedstock, all Cryptomeria’s operational waste is used first and afterwards Pittosporum undulatum provides the amount of biomass that is still necessary. The chosen technology for both power plants will be the grate furnace burning technology. The biomass-fired power plant will be a 8.3 MW power plant, with 27% efficiency [20]. The urban waste valorization unit will have 4.3 MW of installed capacity, and a combustion efficiency of 25% [25] .These resemble the currently functioning power plants and supplying on the mainland. In Mortágua, in Viseu district, there is a biomass-fired thermoelectric power plant with 9 MW of installed power. The plant uses forest biomass and burns it in a grate furnace, in similarity to the proposed one [30]. As for the waste power plant, a bigger version of the proposed plant is working with mass burning technology – Valor Sul, in Loures. Valor Sul is responsible for the treatment and valorization of urban waste coming from 19 municipalities of the great Lisbon area and west region [31]. The biomass plant will be constructed in Pico Island, where most of the resource is concentrated. On the other hand, the urban waste valorization plant will be installed in Faial. This allows for each island to have its generation unit in the possibility of an ill functioning of the undersea connection cables. Currently, the urban waste is transported from Faial to Pico where it is processed. This means that urban waste transportation from one island to the other is already happening and only its direction has to be reversed.

7 5.2.2 Energy Storage The energy storage system (EES) selected for this study is batteries, and a sodium-sulphur battery is selected. To study the influence of the energy storage capacity in the performance of the power system, several configurations were modeled. The first configuration had no energy storage capacity and the remaining configurations varied in a 1 MWh steps. The RES share in the produced electricity, CEEP and annual costs were calculated. Figure 5 shows the RES share and CEEP variation with the ESS capacity for the proposed scenario, and Figure 6 shows the annual costs variation with the ESS capacity for the proposed scenario.

% RES Production CEEP 4950 50 30 4900

45 25 4850

40 20 4800

35 15 4750

nnual nnual cost (k€)

A RES RES Share (%)

30 10 CEEP (GWh/year) 4700

25 5 4650 0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 Storage Capacity (MWh) Storage capacity (MWh) Figure 5 – RES share and CEEP variation with the ESS capacity for Figure 6 – Additional annual costs variation with the ESS capacity for the proposed scenario. the proposed scenario.

The energy storage capacity that minimizes the annual costs is 8 MWh. This capacity allows for a RES penetration value close to the one achieved by the configuration with the highest storage capacity. The RES share varied from 42.3% with an 8 MWh storage capacity to 45.8% with a 20 MWh storage capacity. This means that an increase in the energy storage capacity does not correspond to a significant increase in the RES share, since the CEEP values decrease at a much lower rate. 5.2.3 Results

Table 6 presents RES penetration share in electricity production, fossil fuel consumption and CO2 emissions, for the system with no ESS and considering the 8 MWh sodium-sulphur battery. Table 6 – Results for the proposed scenario without and with ESS.

RES share in electricity production Fossil fuel consumption (GWh) CO emissions (tons) Power system 2 Without ESS With ESS Without ESS With ESS Without ESS With ESS Pico + Faial 27.8 % 42.3 % 172.86 154.53 45,364 40,553

Results from the implementation of the proposed scenario show a 12.55 percentage points increase in RES share without considering any ESS, when comparing to the 2030 BaU scenario. The fossil fuel consumed decreases by 16.7%. This reduction is followed by a decrease in CO2 emissions, 20.4%. With the implementation of the ESS in the power system, there is a 14.5 percentage points increase in RES share. This increase results primarily from the increment of wind power injected to the grid that would be, otherwise, curtailed. Accordingly, fossil fuel consumption and CO2 emissions decrease by 10.6% and 6.5%, respectively. Comparing to the BaU 2030 scenario, fossil fuel consumption and CO2 emissions decrease by 25.5%. RES share in the electricity production rises to 42.3%. 5.2.4 Costs Investment costs, fixed operation and maintenance costs, variable operational and maintenance costs, refurbishment costs and the operational lifetime, for each technology. are forecasts for the costs in 2030 and retrieved from [32]. Fuel related costs are considered to be the same in 2030 as in 2016. Biomass costs are the same as the average price paid by the Mortágua power plant [33]. Waste costs are considered to be null since no extra service is needed [34]. 5.2.5 Sensitivity Analysis A sensitivity analysis is presented for the variable with the largest influence in the annual costs variation: the fossil fuels cost. Biomass price and CO2 related costs have negligible influence in the annual costs. Three scenarios were especially interesting to analyze: the BaU costs, that is the fuel costs are as in 2016 (scenario 1); the scenario considering the highest costs for fossil fuels in the last recent years, more specifically 2012 (scenario 2); and, finally, a scenario that would allow for the additional annual costs to be null (scenario 3). Table 7 shows the fuel related costs and the additional annual costs for each considered scenario. Table 7 – Fuel related costs and the additional annual costs for each considered scenario. Fuel costs Annual Costs (€/year) Scenario Fuel Oil Diesel Biomass Waste 1 7.73 €/GJ 20 €/ton 0 3,487,379 2 16.30 €/GJ 20 €/ton 0 2,533,435 3 39.07 €/GJ 20 €/ton 0 0

8 5.3 Not-Connected Power System Analysis Table 8 presents the inputs for the 2030 scenario with the power systems not connected. Table 8 – Inputs for the 2030 scenario with the power systems not connected.

Power system Pico Faial Electricity demand (GWh) 48.48 49.46 Wind capacity 2400 4250 RES Hydro capacity 0 640 installed Solar PV capacity 8.8 0 capacity Wave capacity 400 0 (kWe) Biomass capacity 1,000 0 Urban waste capacity 0 1,000 Fossil fuel installed capacity 16,763 19,107 (kW) Minimum grid stabilization share 0.7 Following the same cost optimization strategy as in the connected system scenario, Pico’s selected energy storage capacity is 2 MWh and Faial’s is 6 MWh. Additional annual costs were calculated using 2016 fossil fuel costs, the same biomass and CO2 emissions’ price as in the connected scenario. Results for the proposed scenario are presented in table 9. Table 9 - Results for the proposed the scenario considering isolated power systems. Energy storage RES share in Fossil fuel CO emissions Annual costs Power system 2 capacity (MWh) electricity production consumption (GWh) (tons) (€/year) Pico 2 30.8 % 88.83 23,312 147,387 Faial 6 33 % 99.17 26,025 1,338,889 Pico + Faial 8 31.9 % 188 49,337 1,486,276 The achieved RES penetration is 10.4 percentage points lower, in comparison the scenario considering the power systems connected. Consequently, fossil fuel consumption is larger and CO2 emissions are higher as well. Fuel consumption and CO2 emissions are 21.7% higher than in the scenario where the islands’ power systems are connected. In relation to BaU 2030 scenario, there is an increase in the RES penetration share of 9.4%. Fossil fuels usage decreases by 9.4% and CO2 emissions are 8.7% lower. 6 Conclusions The results show that the implementation of the proposed scenario, even without an ESS, increases RES penetration share in electricity production by 12.55 percentage points. Optimized energy storage capacity is 8 MWh. When considering such capacity, RES penetration share increases to 42.3%. This share is 14.5 percentage points superior to the scenario without considering an ESS and over 27 percentage points superior to the 2030 BaU scenario. Regarding fuel oil consumption and CO2 emissions there is a 25.5% cut back. Fossil fuel associated costs have the largest influence in the annual costs of the system. For fuel oil costs equal to 2016 costs, additional costs are approximately 3.5 million Euros. When considering the fossil fuel costs for 2012, the highest costs observed in the past years, additional annual costs drop by almost one million Euros. Furthermore, it is found that a fuel cost of 39.07€/GJ would compensate for investment making, having no additional annual costs. Considering the islands’ power systems as isolated, achieved RES penetration share is 30.8% in Pico and 33% in Faial. This corresponds to an average penetration close to 32%. This share corresponds to 16.65 percentage points above the BaU 2030 share. In comparison to the scenario in which the islands’ power systems are connected, there are 10 percentage points less of RES penetration. Fossil fuel consumption and CO2 emissions are 21.7% higher. However, the additional annual costs are approximately 1.5 million Euros. From an environmental perspective, the best propose is to connect the islands power systems, allowing for a larger penetration of RES. From an economic point of view, the scenario should be implemented in each island as an isolated power system. RES share is still increased and annual costs are 57% lower than in the scenario that considers the power connection of the islands. Nonetheless, RES penetration is lower, 32% instead of 42.3%. Besides RES penetration share and costs, other variables should be taken into account when evaluating the costs and benefits of connecting of the islands’ power systems. Pico and Faial are not different countries, they are islands of the same country and of the same archipelago. Therefore, measures contributing to increment of social cohesion, such as this one, should be valued. References [1] D. F. Cross-Call, “Matching Energy Storage to Small Island Electricity Systems: A Case Study of the Azores,” Master Thesis, Massashusetts Institute of Technology, 2013. [2] EDA, “Procura e Oferta de Energia Elétrica,” Açores, 2016. [3] R. Martins, G. Krajačić, N. Duić, L. M. Alves, M. G. Carvalho, "Contribution of the Renewable Energy Sources in the Azorean Energy Mix- Applying the H2RES Model to Terceira Island," Proceedings of the 4th Dubrovnik Conference on Sustainable Development of Energy, Water and Environment Systems, Dubrovnik, Croatia; 2007. [4] O. S. Parissis, E. Zoulias, E. Stamatakis, K. Sioulas, L. Alves, R. Martins, A. Tsikalakis, N. Hatziargyriou, G. Caralis, and A. Zervos, “Integration of Wind and Hydrogen Technologies in the Power System of Corvo Island , Azores : A

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