Solar and Wind Energy Seasonal Heat

JANAR KALDER

VIIS VIIMAST KAITSMIST

LAGLE HEINMAA FACTORS AFFECTING APPLE JUICE QUALITY AND MYCOTOXIN PATULIN FORMATION ÕUNAMAHLA KVALITEETI JA MÜKOTOKSIINI PATULIINI TEKET MÕJUTAVAD

TEGURID AND SOLAR WIND ENERGY SEASONAL HEAT STORAGE SYSTEMS FOR RESIDENTIAL BUILDINGS IN NORDIC CLIMATE Dotsent Ulvi Moor, professor Eivind Vangdal 31. august 2020

OLEKSANDR KARASOV LANDSCAPE METRICS AND CULTURAL ECOSYSTEM SERVICES: AN SOLAR AND WIND ENERGY SEASONAL HEAT INTEGRATIVE RESOURCE-DRIVEN MAPPING APPROACH FOR LANDSCAPE STORAGE SYSTEMS FOR RESIDENTIAL BUILDINGS HARMONY MAASTIKUMEETRIKA JA ÖKOSÜSTEEMI KULTUURITEENUSED – IN NORDIC CLIMATE RESSURSIPÕHINE INTEGREERIV LÄHENEMINE MAASTIKUHARMOONIA KAARDISTAMISELE Professor Mart Külvik, professor Emeritus Igor Chervanyov 31. august 2020 PÄIKESE- JA TUULEENERGIA SESOONNE RIINU KIIKER SOOJUSSALVESTUS ELAMUTE KÜTTEKS DIVERSITY IN BALTIC POPULATIONS OF POTATO LATE BLIGHT PATHOGEN PHYTOPHTHORA INFESTANS PÕHJAMAISES KLIIMAS KARTULI-LEHEMÄDANIKU TEKITAJA PHYTOPHTHORA INFESTANS BALTIMAADE POPULATSIOONIDE MITMEKESISUS Professor Marika Mänd, dotsent Eve Runno-Paurson 10. september 2020

KAARI REIMUS JANAR KALDER ON-FARM MORTALITY AND RELATED RISK FACTORS IN ESTONIAN DAIRY AND BEEF HERDS SUREMUS FARMIS JA SELLEGA SEOTUD RISKITEGURID EESTI PIIMA- JA LIHAVEISEKARJADES Dotsent Kerli Mõtus, professor Arvo Viltrop A Thesis 16. september 2020 for applying for the degree of Doctor of Philosophy in Engineering Sciences SILLE REBANE EVALUATION OF FOREST MANAGEMENT IN THE CONTEXT OF CARBON FLUXES: EDDY-COVARIANCE METHOD METSADE MAJANDAMISE MÕJU HINDAMINE SÜSINIKU KONTEKSTIS: Väitekiri TURBULENTSE KOVARIATSIOONI MEETOD filosoofiadoktori kraadi taotlemiseks tehnikateaduse erialal Vanemteadur Kalev Jõgiste, vanemteadur Marek Metslaid 9. oktoober 2020

ISSN 2382-7076 Tartu 2020 ISBN 978-9949-698-55-4 (trükis) ISBN 978-9949-698-56-1 (pdf) ! " "#"$%!&!'"

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ORIGINAL PUBLICATIONS Kalder, Janar; Allik, Alo; Hõimoja, Hardi; Jõgi, Erkki; Hovi, Mart; Märss, Maido; Kurnitski, Jarek; Fadejev, Jevgeni; Lill, Heiki; Jasinskas, Algirdas; Annuk, Andres. (2017). Optimal wind/solar energy mix for residential net zero-energy buildings. Rural Development: 8-th International Scientific Conference: Rural Development, 23.- 24.11.2017, Aleksandras Stulginskis University, Kaunas. Ed. A. Raupelienė. Kaunas: Aleksandras Stulginskis University, 1−6.10.15544/RD.2017.020.

Proceedings of the 8th International Scientific Conference Rural Development 2017 Edited by prof. Asta Raupelienė

ISSN 1822-3230 / eISSN 2345-0916 eISBN 978-609-449-128-3

Article DOI: http://doi.org/10.15544/RD.2017.020

OPTIMAL WIND/SOLAR ENERGY MIX FOR RESIDENTIAL NET ZERO-ENERGY BUILDINGS

Janar KALDER, Estonian University of Life Sciences, Institute of Technology, Chair of Energy Application Engineering, Fr.R. Kreutzwaldi 56, 51014 Tartu, Estonia, [email protected] Al o ALLIK, Estonian University of Life Sciences, Institute of Technology, Chair of Energy Application Engineering, Fr.R. Kreutzwaldi 56, 51014 Tartu, Estonia, [email protected] Hardi HÕIMOJA, Estonian University of Life Sciences, Institute of Technology, Chair of Energy Application Engineering, Fr.R. Kreutzwaldi 56, 51014 Tartu, Estonia, [email protected] Erkki JÕGI, Estonian University of Life Sciences, Institute of Technology, Chair of Energy Application Engineering, Fr.R. Kreutzwaldi 56, 51014 Tartu, Estonia, [email protected] Mart HOVI, Estonian University of Life Sciences, Institute of Technology, Chair of Energy Application Engineering, Fr.R. Kreutzwaldi 56, 51014 Tartu, Estonia, [email protected] Maido MÄRS S , Eesti Energia Ldt., Department of Renwable Energy, PV Project manager, Lelle 22, 11318 Tallinn, Estonia, [email protected] Jarek KURNITSKI, Tallinn University of Technology, School of Engineering, Department of Civil Engineering and Architecture, Ehitajate tee 5, 10985 Tallinn, Estonia, [email protected] Jevgeni FADEJEV, Tallinn University of Technology, School of Engineering, Department of Civil Engineering and Architecture, Ehitajate tee 5, 10985 Tallinn, Estonia, [email protected] He i ki LILL, Estonian University of Life Sciences, Tartu Technology College, Fr.R. Kreutzwaldi 56, 51014 Tartu, Estonia, [email protected] Algirdas JAS INS KAS , Aleksandras Stulginskis University, Faculty of Agricultural Engineering, Institute of Agricultural Engineering and Safety, Studentu str. 15, Akademija, LT-53362 Kaunas reg., Lithuania, [email protected] Andres ANNUK, Estonian University of Life Sciences, Institute of Technology, Chair of Energy Application Engineering, Fr.R. Kreutzwaldi 56, 51014 Tartu, Estonia, [email protected] (corresponding author)

The article is concentrated on the energy storage problems arising from microgeneration in private households. The case study involves a small-scale wind and solar electricity production set in a net zero-energy building. Both the net zero-energy building and the microgeneration units are connected to an utility grid. The current article serves to confirm the hypothesis, that the self consumption is at its maximum with the annual 70/30 wind and solar energy mix of in favour of the wind. The maximal self consumption at no additional energy storage in a net zero-energy building is studied as well. Produced and consumed energies are equal, which satisfies the requirements for a net zero-energy building with the utility grid acting as an energy buffer. The consumed energy is used to operate a heat pump, heat up ventilation supply air, run ventilation fans, supplying non-shiftable loads (white goods, TV, lighting etc), heat up domestic hot water via heat pump. To express self consumption, we use the term of supply cover factor, which describes optimally the directly consumed energy in relationship to net consumption or production. In annual scale, the cover factors for a net zero-energy building are equal as the production and consumption are equal as well. Also, seasonal variations in self consumption are studied. According to study results, the annual maximal supply cover factor in a net zero-energy building is 0.375 with 70/30 wind/solar mix. Seasonally, the self consumption is at its maximum in summer when the supply cover factor equals to 0.49.

Keywords: demand response, supply cover factor, load shifting, net zero-energy building, solar energy, wind energy

INTRODUCTION

Net zero-energy building is a building where the energy balance for the end of a year is equal to 0 (Directive…, 2010). Usually, a net zero-energy building is tied to an utility grid. Throughout a year, the utility grid acts as an energy storage medium. Among the renewable energy sources, the solar and wind have the longest historical records with growing acceleration numbers during the recent decades (Kaldellis and Zafirakis, 2011). The wind and solar share in the overall energy mix is growing mainly thanks to the new installations, the micro generation owes much of its popularity to the EU requirements on the net zero-energy buildings (Directive…, 2012). The variance and unpredictability of wind and solar generation is a well-known fact (Allik and Annuk, 2016 ). To compensate the stochastic character of these energy sources, several local demand side management (DSM) technologies are applied. One of the many possibilities is

Copyright © 2017 The Authors. Published by Aleksandras Stulginskis University. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC-BY 4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

51 Proceedings of the 8th International Scientific Conference Rural Development 2017 the application of heat pump loads, discussed in the current paper (Vanhoudt et al., 2014; Elkinton et al., 2009). Previously, only solar-based energy input was considered for net zero-energy buildings (Luthander, 2015). The paper aims to study the share of self consumption in a net zero-energy building under different conditions and at seasonal level. Finally, the conditions for maximal self consumption is found.

MET HO DS

The wind generator and solar panel production graphs were recorded on a building’s roof at coordinates 58°23’19’’ N, 26°41’37’’ E in the city of Tartu, Estonia. The network analyzer Janitza UMG 605 (Janitza…, 2017) with current transformers Circutor P2 TC5 M70312 provided data acquisition (Circutor…., 2017). The recorded data series begin on December 1, 2015 and end on November 30, 2016, covering all four seasons. The energy production data was logged as averaged values at 5-minute intervals, the calculations are based on the sum energies over 5-minute periods. The annual output energy of production units is scaled according to the consumption, being equal to the annual consumption in any circumstance. Figure 1 presents fundamental scheme of the zero energy building with energy supply microdevices and connection to the grid. Non-shiftable loads such as white goods are presented as a separate component.

Figure 1. Principal diagram of the studied solution where 1 – AC grid connection; 2 – Two way electrical energy meter; 3 – Inverters for solar panels; 4 – Inverters for wind turbine; 5 – HVAC unit consisting: 6 – Heat recovery unit (HRU), 7 – Ground source heat pump (GSHP), 8 – Supply air heating element (HE), 9 – Supply and exhaust fans (SV/EV); 1 0 – Non shiftable loads; 11 – PV panel array; 12 – Wind t urbine; 13 – Zero energy building.

Initial data for this study consist of a typical annual net zero-energy building electrical load (Fig. 2) that includes heat pump compressor, ventilation supply air heat load, fan load and non-shiftable load graphs (lighting, TV, white goods etc). The annual electricity consumptions are Whp=1835 kWh/y for the heat pump, Wvh=1628 kWh/y for ventilation supply air heating, Wvv=1335 kWh/y for operating the fans, Wns=2802 kWh/y for the non-shiftable loads. The total electricity consumption is Wt=7600 kWh/y.

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Figure 2. Consumption curves of net zero energy buiding

The energy balance of the given net zero energy buildings described as:

Whp+Wvh+Wvv +Wns-Wpv-Ww=0, (1) where Wpv – annual solar electricity generation, kWh/y, Ww – annual wind electricity generation, kWh/y.

Figure 3. Production graphs of the wind generator and solar panels

Net zero-energy building was modelled as a two-floor single family house with 143.9 m2 heated area (Fig. 4) located in Tallinn, Estonia. Modelling was performed in IDA-ICE energy simulation environment and MatLab simulation software. Annual energy demand of a heat pump and air handling unit (AHU) supply air heating and fans was obtained in IDA-ICE, where non-shiftable load (Fig. 2) was applied as a reference for internal gains modelling. Climatic conditions in IDA-ICE were defined according to Estonian test reference year (TRY), which consists of outdoor climate data array for indoor climate and energy calculations, collected from the climatic data between 1970 and 2000 all over Estonia and composed according to Estonian standard (EVS…, 2005) or similar requirements (Kalamees and Kurnitski, 2006). MatLab was applied for calculating boilers’ energy balances at every time step, with results presented in Fig ure 5, Figure 6 and Table 1. The current simulation is based on the scaled production graphs of the following electricity microgeneration units: horizontal axis, 3.5 kW, passive yaw control permanent magnet generator (Sonkyo…, 2015), with SMA Sunny Boy 3600TL inverter (SMA…, 2012) and 2.5 kW PV array (DelSolar 250 W D6P250B3A) (Yingli…, 2017), oriented towards South with 40° elevation. A 2.75 kW grid tie inverter (SOLIVIA 2.5 EU G3) (SMA…, 2012) is used for converting DC to AC. Figure 4 presents single family house model placement. The production data for both devices is scaled according to the actual load, which results in peak wind turbine power of 12.78 kW and peak PV power of 2.23 kW. Devices were sized on the 70/30 annual generation mix in favour of the wind turbine (Garalis et al., 2011; Annuk et al., 2011; Annuk et al., 2013). The wind turbine is located in urban conditions with a low capacity factor (ratio between actually generated energy and the theoretical energy if operating continuously at installed power) of CF=0.06, as for PV panels, CF=0.11.

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Figure 4. Single family house model and its orientation in IDA-ICE

The cover factors both express the relationship between locally produced and directly consumed electricity (Allik et al., 2016; Baetens et al., 2012):

(2) where PS is the local power supply and PD the local power demand. The time when PD(t) ≤ PS(t) is denoted as t0…t1, and t1…t2 is the time when PD(t) > PS(t). The supply cover factor YS is a measure for the self-consumption of locally produced renewable energy. Similarly, the demand cover factor YD is defined as ‘the ratio to which the energy demand is covered by the local supply’ and indicates the ‘self-generation’ (Vanhoudt et al., 2014). If production and consumption are equal, the supply and demand cover factors are equal as well (Luthander, 2015). Further, for sake of clarity, we consider only the supply cover factor, as it expresses the ratio of self consumption into the consumed energy and not into the produced energy, described by the demand cover factor..

RESULTS AND DISCUSSION

In case of a net zero energy building with no additional energy storage units applied, one of the possibilities to optimize self consumption is to change the annual wind/solar energy shares. Figure 5 describes the impact of different annual wind/solar electricity production shares on the supply cover factor. According to Figure 5, the supply cover factor peaks at Y=0.375 when annual wind/solar mix is 70/30 in favour of the wind energy. This production mix has been confirmed in a wider scale, as show the similar calculations for Greece (Caralis, 2011) and Estonia (Annuk et al., 2012; Annuk et al.,2011). The cover factors can be augmented with additional energy storage units inside the system.

0,4 0,35 0,3 0,25 0,2 0,15 0,1 Supply cover factor cover Supply 0,05 0 100S 90/10 80/20 70/30 60/40 50/50 40/60 30/70 20/80 10/90 100W

Share of annual PV/wind energy

Figure 5. Impact of different annual wind/solar electricity shares on the cover factor

Figure 6 illustrates the same process at seasonal level. The supply cover factor has its lowest value in winter, when the power generation is maximum at 100/0 wind/solar mix, as 100% of the electricity is supposed to be provided by the wind generator and the net sum of solar irradiation is negligible. However, at seasonal level, the supply cover factor in summer is the highest: higher than 0.5 in very large range of energy mix values. If energy mix were 0/100, i.e. 100% solar, then values for all seasons would be quite apart differing from 0.06 to 0.5. On only wind-powered supply, cover factors are in range of 0.2 in spring to 0.4 in winter. During summer, the supply cover factor has the highest value, when the wind and solar energy productions are more or less equal (Table 1).

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0,60

0,50

0,40

0,30

0,20

Supply cover factor 0,10

0,00 100S 90/10 80/20 70/30 60/40 50/50 40/60 30/70 20/80 10/90 100W

Winter Spring Summer Autumn

Figure 6. Impact of different seasonal wind/solar electricity shares on the supply cover factor

Table 1. Seasonal wind and solar electricity productions at annual wind/solar share of 70/30 Parameters Winter Spring Summer Autumn Solar energy production, kWh 106.4 915.8 894.9 362.9 Wind electricity production, kWh 1931.3 709.7 1233.4 1446.1 Wind/solar mix, % 95/5 43/67 58/42 80/20 Demand, kWh 3082.5 1653.4 1040.2 1825.0 Total production 2037.7 1625.5 2128.3 1809.0 Ys 0.35 0.35 0.49 0.37

Detailed simulation results of 70/30 annual energy mix are presented in Table 1. Highest demand and production appears in winter resulting in supply cover factor of YS=0.35. On the seasonal basis supply cover factor slightly varies in range of 0.35-0.49 with its peak value obtained in summer period. Highest value of supply cover factor in summer can be explained by low demand. Increase in supply cover factors can be obtained with the application of storage devices e.g. battery. For instance, if we use instead of wind generator and PV panels energy source with constant output power, P=0.868 kW, what covered electricity supply 7600 kWh/y, then YS =0.71.

CONCLUSION

The article discusses maximising self consumption in net zero-energy buildings without additional energy storage units. One can claim, that the 70/30 mix is an universal one regardless of latitude and local wind conditions. • At annual wind/solar energy mix of 70%/30% in favour of wind, self consumption reaches its peak resulting in supply cover factor of Y=0.375. • Application of wind power as the only energy source in a net zero-energy building results in supply cover factor of YS =0.323. • Application of 100% PV panels produces supply cover factor of YS =0.234.

ACKNO WLEDGEMENTS The Estonian Centre of Excellence in Zero Energy and Resource Efficient Smart Buildings supported this research and Districts, ZEBE, grant TK146 funded by the European Regional Development Fund.

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56 II Annuk, Andres; Jõgi, Erkki; Kalder, Janar; Allik, Alo (2018). Evaluating Electricity Self-Consumption in Different Renewable Energy Supply Conditions. Proceedings of Engineering for Rural Development: Engineering for Rural Development 2018, Jelgava, 23.-25.05.2018. Jelgava: Latvian University of Life Sciences and Technologies, 1704−1709. ENGINEERING FOR RURAL DEVELOPMENT Jelgava, 23.-25.05.2018.

EVALUATING ELECTRICITY SELF-CONSUMPTION IN DIFFERENT RENEWABLE ENERGY SUPPLY CONDITIONS Andres Annuk, Erkki Jogi, Janar Kalder, Alo Allik Estonian University of Life Sciences, Estonia [email protected], [email protected], [email protected], [email protected]

Abstract. The aim of this article is to detect energy storage problems in dwelling buildings with PV panels and wind generator based electrical energy supply. The focus of the research is to maximise the yield of energy consumed on-site utilising two water heater boilers with equal volumes as energy storage devices and consumption in household devices as white goods, lighting, etc. Energy output from fluctuating sources like PV panels and wind generators is divided by a desired horizontal shaving level on the production curve, separating peaks and stable production. Energy peaks are fed to a pre-heating water boiler and the main part of energy below the shaving level is used in the main boiler and consumption of household devices, maintaining the equalised balance of produced and utilised energy. The observational period is one year with 5-minute averaged data points. Wind generator energy output is calculated according to three different wind conditions, evaluating self-consumption, while retaining PV panel yield on the same level. The produced solar and wind energy ratio is 30 %/70 %. The compared wind conditions result in a capacity factor of 0.055 in the worst case and up to 0.273 in better conditions, while the cover factor increased from 0.6 up to 0.68. If the energy demand is the same, the needed rated capacity of the wind generator can be 5 times smaller in the best conditions.

Keywords: wind energy, solar energy, peak shaving, cover factor, demand response.

Introduction Utilisation of solar and wind power has one of the longest historical backgrounds among renewable energy sources. The technological advancement has been in steep ascension during the last decade as modern large scale high output solar and wind power plants are demanding focused research and development on equipment [1]. Rapid developments on the field of small-scale PV and wind technologies have had strong support from the EU legislation that is also related to net zero-energy buildings [2; 3]. It is a known fact that wind turbine and PV panel output is fluctuating and almost non-predictable [4]. To smooth out the output of these primal energy sources, local demand side management (DSM) methods are applied. The most common are different heat-pump-based technologies [5; 6], although chemical batteries [7; 8], pumped-storage hydroelectricity [9; 10], DC loads [11], solar and wind forecast [12], compressed air storage [13] and micro-grid systems [14] are also in use. Another solution to relieve power stochasticity is to store the short peaks of electrical energy production in an additional pre heated water boiler as heat energy [15; 16] and at the same time utilising load shedding and power shifting technologies. This approach allows to store short-lasting energy peaks above the set shaving level without DC/AC alternation allowing smaller inverters with stable output. In the current study, the shaving level is from zero to 100 %, where 0 % is a state, where all the energy is diverted into the pre-heating boiler and 100 % means that no power shaving is exploited. The aim of this study is to evaluate possibilities to increase the self-consumption share under different wind conditions by using production curve peak shaving methods to dividing energy flows to two branches. For energy storage we use two equal volume boilers.

Materials and methods The wind generator used for the modelling and simulation of the parameters is the following: it has a rated power of 10 kW, located in a coastal area (N 59.087694, E 23.591719) and it is produced by TUGE Ltd [16]. The 10 photovoltaic panels have a total rated power of 2.5 kW, located in an urban area (N 58.388458, E 26.694000) and the producer is DelSolar [16]. The measured period covers a time beginning with the 1st of December 2015 and ending with the 30th of November 2016. The year is divided into four periods as follows: winter – December to February, spring – March to May, summer – June to August, autumn – September to November. The production curve is shaved at 5 minute average power levels, whereas the succeeding calculations are based on the corresponding energy portions. The solution for energy storing (Fig. 1) consists of two equal size boilers: a water pre-heating tank (WPHT) with two separate electrical heating elements and the main boiler. The WPHT acts as a

DOI: 10.22616/ERDev2018.17.N239 1704

59 ENGINEERING FOR RURAL DEVELOPMENT Jelgava, 23.-25.05.2018. dump load system for the shaved power peaks, allowing the utilising of both: AC and DC power from the wind generator and from the PV panels due to separate heaters. The system is equipped with an emergency pressure relieve valve that can dump excess hot water into the drainage. The main boiler is designed to consume all of its energy demand below the shaving level, and is equipped with two separate heaters. Both boilers must be able to work separately, because a 0 % shaving level means 100 % utilisation of the pre-heating boiler and vice versa – 100 % shaving level leaves the entire load to the main unit.

Fig. 1. Scheme of proposed systems: 1 – AC grid connection; 2 – cold water main line; 3 – two way electrical energy meter; 4 – water meter; 5 – inverters for solar panels and wind generator; 6 – dump load controllers (DLC) for solar panels and wind generator; 7 – water preheating tank (WPHT) with two separate heating elements; 8 – safety pressure release valve; 9 – conventional water heating tank (CWH); 10 – non-shiftable loads; 11 – Hot water output; 12 – PV panels; 13 – wind generator The current research uses a typical household power demand curve consisting only of non- shiftable loads like white goods etc. and a water heating boiler system. Power demand is measured during a two week period and adjusted for the whole year as consuming habits of people do not change notably [18; 19]. Electrical energy demand during the given period was 3473 kWh per year, which is a value between the Estonian and European Union average values (2957 kWh per year vs 3601 kWh per year) [19; 16]. The PV panels’ and wind generator production curves are similar as given in [17]. Although, the daily average energy used for hot water production is 5.05 ±1.80 kWh [22].. The maximum energy capacity calculated in this case per day of a commercially available 80 l boiler is 5.4 kWh [16]. The annual energy yield of the wind generator and PV system are scaled to be 70 %/30 % [20] in favour of the wind energy [18; 21]. The model for evaluation of the self-consumption is tested with capacity factors (CF) of wind generators ranging from 0.051 to 0.28, at the same time the capacity factor of solar panels CF = 0.11 [16] is constant. We analyse the dependence of rated power according to CF (Fig, 2.) visualising the necessary nominal power output change in different wind conditions. The essence of CF is the ratio of actually produced energy in relation to the theoretically possible energy production during some time period (commonly one year, T = 8760 h). W CF  , (1) Pr t where W – really produced energy in certain period, e.g. one year; Pr – rated power of production device; t – time period (in this case 8760 h).

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Fig. 2 depicts that the relation of the necessary nominal output power of the wind generator to generate the same energy amount is not linear, there is a steep rising slope at CF values lower than 0.15.

As the production is equal to the usage, then the cover factors are also equal YS=YD, so hereafter we discuss only Y, representing the supply cover factor YS.

Fig. 2. Wind generator output power according to capacity factor

The cover factors YS = YD [22; 23] express both locally produced and directly consumed power shares: t t t t 1 P dt  2 P dt 1 P dt  2 P dt t D t S t D t S Y t t 0 1 Y t t 0 1 ( os ... 2 )  t , D ( o ... 2 )  t , (2) 2 P dt 2 P dt t S t D 0 0

where PS – local power supply; PD – local power demand.

The time, when PD(t)  PS(t), is denoted as t0…t1, and t1…t2 is the time, when PD(t) > PS(t). The supply cover factor is a measure for the self-consumption of locally produced renewable energy [6]. Similarly, the demand cover factor is defined as “the ratio to which the energy demand is covered by the local supply” and indicates the “self-generation” [6]. Nevertheless, energy stored into hot water but diverted to drainage is not included into calculation of Y as energy use. In cases, where the production curve depths of peak shaving levels (DPS) are at levels of 20-30 %, the loss is notably increasing as shown in Figure 4. The use of a maximum value of the CF is not feasible, as the losses are also at highest. Energy loss from the boiler is calculated to be 10 % of the whole energy stored, being 184 kWh per year [24]. Yet the heat energy lost through the boiler thermal insulation accounted as the heat source for building thus lowering the energy used for general heating.

Results and discussion Fig. 3 illustrates the cover factor relations to DPS as Y maximums are shifting left, while CF values are lower, while higher CF values are resulting from higher peaks. Minimum Y values are in all cases 0.27, while all the energy is diverted through the pre-heating boiler. The maximum Y value of 0.7 is achieved only with the best wind conditions available. Energy losses due to occasions when the preheating tank is overheating are depending on the DPS level and the CF value that Fig. 4 illustrates and all calculations were done considering the energy amount per boiler 5.4 kWh. Because it is difficult to determine an even temperature in a volume boiler, it was not used as an indicator. The emergency release valve works according to pressure. There are energy losses in the case of three different CF values, being the smallest around a cutting

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61 ENGINEERING FOR RURAL DEVELOPMENT Jelgava, 23.-25.05.2018. limit of 20 %, while CF=0.055. In other cases, the inclination of the curve is less steep, although wasted energy turns to zero in all cases on a shaving depth of 60 %.

Fig. 3. Dependences of cover factor and peak shaving levels on different capacity factors

Fig.4. Wasted energy according to depth of peak (DPS) shaving levels on different capacity factors (CF) Table 1 Results modelling by different wind CF´s

CF (PV) CF (wind) DPS, % Y Pr, kW 0.11 0.055 20 0.6 5.05 0.11 0.190 47 0.63 1.46 0.11 0.273 50 0.68 1.02 Taking for granted the 10 % criteria, the losses are less than 184 ± 10 %. Counted this condition, the results are presented in Table 1. The data are taken from three different CF levels, which means three different wind conditions. To get a certain energy amount during the year, that is the same in all cases, but in different wind conditions, the necessary rated capacities Pr of the wind generators certainly are different. The difference of the rated powers for the wind generators are nearly up to 5 times.

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Thereof it could be concluded that better wind conditions allow increasing the locally consumed energy percentage and usage of a smaller size wind generator, thus shortening the payback period of energy production devices. Although the increase is not drastic (8 %), then an additional effect comes from a smaller wind generator in better wind conditions.

Conclusions 1. The novelty of this research is the determination of the influence on different CF to Y by using production curve peak shaving to increase the self-consumption. The proposed system used two same size boilers, the energy from the peaks is directed to one and the energy under the shaving line is directed to the other. 2. Better wind conditions allow increasing the renewable energy proportion in a dwelling, in this research the CF values were varying in a range of 0.055 to 0.273, and the resulting Y values were changing from 0.6 to 0.68. At the same time it is possible to scale down the wind generator’s rated power up to 5 times, which gives significant economic effect by decreasing expenses to energy production devices. 3. The proposed solution is relatively cheap, because the additional boiler cost is marginal and inverters need only configurational changes concerning the dump load activation value.

Acknowledgements The authors would like to thank Tuge Energia Ltd. for making the data of the 10 kW wind generators available for this study. This research was supported by the Estonian Centre of Excellence in Zero Energy and Resource Efficient Smart Buildings and Districts, ZEBE, grant 2014- 2020.4.01.15-0016 funded by the European Regional Development Fund.

References [1] Kaldellis J. K., Zafirakis D. The wind energy (r)evolution: A short review of a long history, Renew. Energy, vol. 36, no. 7, pp. 1887–1901, Jul. 2011. [2] AlFaris F., Juaidi A., Manzano-Agugliaro F. Intelligent homes’ technologies to optimize the energy performance for the net zero energy home, Energy Build., vol. 153, 2017, pp. 262-274. [3] Directive 2012/27/EU of the European Parliament and of the Council of 25 October 2012 on energy efficiency, amending Directives 2009/125/EC and 2010/30/EU and repealing Directives 2004/8/EC and 2006/32/EC Text with EEA relevance, 2012, [online] [19.03.2018] Available at: http://eur-lex.europa.eu/legal-content/EN/TXT/?uri=celex %3A32012L0027 [4] Allik A., Annuk A. Autocorrelations of power output from small scale PV and wind power systems, 2016 IEEE Int. Conf. Renew. Energy Res. Appl. ICRERA 2016, 2017, pp. 279-284. [5] Elkinton M.R., McGowan J.G., J. F. Manwell J.F. Wind power systems for zero net energy housing in the United States, Renew. Energy, vol. 34, no. 5, 2009, pp. 1270-1278. [6] Vanhoudt D., Geysen D., Claessens B., Leemans F., Jespers L., Van Bael J. An actively controlled residential heat pump: Potential on peak shaving and maximization of self- consumption of renewable energy, Renew. Energy, vol. 63, 2014, pp. 531-543. [7] Iqbal M.T. A feasibility study of a zero energy home in Newfoundland, Renew. Energy, vol. 29, no. 2, 2004, pp. 277-289. [8] Qi Z., Lin E. Integrated power control for small wind power system, J. Power Sources, vol. 217, Nov. 2012, pp. 322-328. [9] Foley A.M., Leahy P.G., Li K., McKeogh E.J., A. P. Morrison A.P. A long-term analysis of pumped hydro storage to firm wind power, Appl. Energy, vol. 137, 2015, pp. 638-648. [10] Zoss T., Karklina I., Blumberga D. Power to Gas and Pumped Hydro Storage Potential in Latvia, Energy Procedia, vol. 95, 2016, pp. 528-535. [11] Gabbar H.A. Abdelsalam A.A. Microgrid energy management in grid-connected and islanding modes based on SVC, Energy Convers. Manag., vol. 86, 2014, pp. 964-972. [12] Duda R., Nonparametric techniques, Pattern Classif., vol. 19, 2013, pp. 1387-1389. [13] Petrollese M., Cau G., Cocco D. Use of weather forecast for increasing the self-consumption rate of home solar systems: An Italian case study, Appl. Energy, vol. 212, no. December 2017, 2018, pp. 746-758.

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[14] Ciocan A., Tazerout M., Prisecaru T., Durastanti J.-F. Thermodynamic evaluation for a small scale compressed air energy storage system by integrating renewable energy sources, 2015 Int. Conf. Renew. Energy Res. Appl. ICRERA 2015, 2016, pp. 22-25. [15] Rajesh K.S., Dash S.S., Rajagopal R., Sridhar R. A review on control of ac microgrid, Renew. Sustain. Energy Rev., vol. 71, no. December 2016, 2017. pp. 814-819. [16] Annuk A., Jõgi E., Hovi M., Märss M., Uiga J., Hõimoja H., Peets T., Kalder J., Jasinskas A., Allik A. Increasing self electricity consumption by using double water heating tanks for residential net zero energy buildings, in 6th International Conference on Renewable Energy research and Application, 2017, vol. 6, 2017, pp. 106-110. [17] Kotol M. Survey of occupant behaviour , energy use and indoor air quality in Greenlandic dwellings, Proc. 5th IBPC, Kyoto, Japan, May 28-31, 2012. [18] Energy Savings Trust, Measurement of domestic hot water consumption in dwellings, Energy Savings Trust, 2008, pp. 1-62. [19] World Energy Council, “Electricity use per household”, Electricity Consumption Efficiency 2015. [online] [19.03.2018]Available at: https://www.wec-indicators.enerdata.eu/householdelectricity- use.html [20] Caralis G., Delikaraoglou S., Zervos A. Towards the optimum mix between wind and PV capacity in the Greek power system, Eur. Wind Energy Conf. Exhib., no. November 2014, pp. 75-79. [21] Annuk A., Allik A., Pikk P., Uiga J., Tammoja H., Toom K., Olt J. Increasing renewable fraction by smoothing consumer power charts in grid-connected wind-solar hybrid systems, Oil Shale, vol. 30, no. 2S, 2013, pp. 257-267. [22] Allik A., Märss M., Uiga J., Annuk A. Optimization of the inverter size for grid-connected residential wind energy systems with peak shaving, Renew. Energy, vol. 99, 2016, pp. 1116-1125. [23] Baetens R., De Coninck R., Van Roy J., Verbrugegen B., Driesen J., Helsen L., Saelens D. Assessing electrical bottlenecks at feeder level for residential net zero-energy buildings by integrated system simulation, Appl. Energy, vol. 96, 2012, pp. 74-83. [24] Pourmousavi S.A., Patrick S.N., Nehrir M.H. Real-time demand response through aggregate electric water heaters for load shifting and balancing wind generation, IEEE Trans. Smart Grid, vol. 5, no. 2, 2014, pp. 769-778.

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64 III Kalder, Janar; Annuk, Andres; Allik, Alo; Kokin, Eugen (2018). Increasing Solar Energy Usage for Dwelling Heating, Using Solar Collectors and Medium Sized Vacuum Insulated Storage Tank. Energies, 11 (7), ARTN 1832.10.3390/en11071832. energies

Article Increasing Solar Energy Usage for Dwelling Heating, Using Solar Collectors and Medium Sized Vacuum Insulated Storage Tank

Janar Kalder *, Andres Annuk, Alo Allik and Eugen Kokin Institute of Technology, Estonian University of Life Sciences, Kreutzwaldi 56, EE51006 Tartu, Estonia; [email protected] (A.A.); [email protected] (A.A.); [email protected] (E.K.) * Correspondence: [email protected]; Tel.: +372-5628-2640

Received: 27 June 2018; Accepted: 10 July 2018; Published: 12 July 2018

Abstract: This article describes a method for increasing the solar heat energy share in the heating of a dwelling. Solar irradiation is high in summer, in early autumn, and in spring, but during that same time, the heat demand of dwellings is low. This article describes a solution for storing solar heat energy in summertime as well as the calculations of the heat energy balance of such a storage system. The solar heat energy is stored in a thermally insulated water tank and used in the heating period. The heat is also stored in the ground if necessary, using the ground loop of the heat pump if the water tank’s temperature rises above a certain threshold. The stored heat energy is used directly for heating if the heat carrier temperature inside the tank is sufﬁcient. If the temperature is too low for direct heating, then the heat pump can be used to extract the stored energy. The calculations are based on the solar irradiation measurements and heating demand data of a sample dwelling. The seasonal storing of solar heat energy can increase the solar heat energy usage and decrease the heat pump working time. The long-term storage tank capacity of 15 m3 can increase the direct heating from solar by 41%. The direct heating system efﬁciency is 51%.

Keywords: long-term storage tank; solar heat energy; solar collector

1. Introduction The target of the European energy politics is to increase the renewable energy share to 27% by the year 2030, and thereby reduce CO2 emissions [1]. In addition, by 31 December 2020, all of the new buildings, which need authorization for use, must be nearly zero-energy buildings [2]. Increasing the solar heat energy share for a single-family house heating is difﬁcult, because the solar irradiation is mostly available in warmer periods, when the house heat demand is low. Therefore, is necessary to ﬁnd solutions for storing the solar energy in summertime and using it in the heating period, and thereby decreasing the additional heat energy demand. Solar heating systems with seasonal heat storage for residential districts and also for the single-family houses have been researched for decades. The biggest problem with them is the energy losses from the seasonal storage. Large solar heat seasonal storage systems have been built and researched in Germany. These storages are the rock bed heat storage, the ground/soil storage (borehole storage), and the hot water tank [3]. These storage methods for high temperature heat storing are not a good solution for single-family houses, because the heat losses through the storage walls are too high. The seasonal solar heat storage methods for single family houses has not been studied much, because the ratio of the storage tank wall area and the volume is too small, and therefore the heat losses are high [4]. The higher water temperature in the seasonal storage tank allows more heat energy to be stored or a reduction in the size of the tank, compared with the low temperature tank. For example, the solar heating system with the solar collector area 147.2 m2

Energies 2018, 11, 1832; doi:10.3390/en11071832 www.mdpi.com/journal/energies 67 Energies 2018, 11, 1832 2of9 and with a seasonal storage tank, with a volume of 1083 m3, is in use in Slatiˇnany, Czech Republic. 2 1 The tank is isolated with mineral wool (thickness of 0.7 m) and has an overall U-value 0.4 W m− K− . The U-value is a measure of the flow of heat through an insulating or building material. The heating system’s operating principle is as follows: if the tank temperature is over 36 ◦C, then the heat energy flows directly from the tank to the house, if the tank temperature is between 12 and 35 ◦C, then the heat energy is extracted using the heat pump. If the tank temperature drops under 12 ◦C, then the building is heated using an electric boiler. The solar fraction for heating in different years is between 63% and 77%. The maximum tank temperature of 52 ◦C was achieved in October 2011 [5]. A disadvantage of such a heating system is the high heat energy loss through the tank walls, which does not allow the water temperature to rise any higher. Therefore, the amount of heat energy for direct heating is lower and the electricity usage for heating, when the heat energy in the tank is depleted, is also higher, in addition to the storage tank volume being higher. Using the storage tank with this U-value for a single-family house is not possible because of the excessive heat loss. To use the seasonal storing of the solar heat energy for a single-family house, it is important to use a storage tank, with a low heat loss. One solution is to use a tank where the working principe is similar to that of thermos. The technique of the vacuum insulated tank with expanded perlite has been previously used for the storage of liquid gases. The vacuum insulated storage tank operational principle is similar. Using vacuum insulation, the thermal resistance is up to 10 times higher compared with conventional insulation materials [6]. The company Hummelsberger Stahl- und Metallbau built the vacuum isolated storage tank with a volume of 16.4 m3 in the year of 2010. The tank has a double-walled steel cylinder construction. The annular gap between the cylinders is filled with expanded perlite and is evacuated [7]. Such thermal insulation has been also investigated by the University of Stuttgart, where the different heat insulation materials are studied in a vacuum [7]. The results are similar to the parameters of the vacuum insulated tank insulation. The tank was put outside in winter and filled with 90 ◦C water. The measurements showed an average temperature 1 loss of 0.23 K day− for a period of 11 weeks in winter [8]. It was found that the tank heat loss 1 3 power is 1.98 W K− [9]. The heating system, with a similar 11 m vacuum storage tank, and the solar collector with an area of 55 m2, is in use in Germany. The entire heating system can be watched in real time [10]. The measurement data shows that the maximum temperature in the storage tank is achieved in May [10]. The share of direct heating is 55% [11]. Also, the climate in Germany is warmer than in Estonia. In Germany, a tank with vacuum panels insulation was also studied, of which the calculated 2 1 U-value was 0.36 W m− K− [12]. The average U-value is high because of joints between the vacuum panels, which are thermal bridges. It possible store solar energy using latent heat storage, where phase change materials are used [13]. These storage systems are more complex compared to conventional storage and the heat insulation that is also needed. Using chemical storage systems are not economically feasible [14]. Nonconventional storage methods are not investigated in this article. The seasonal storage tank for the solar heat energy with vacuum insulation has not been previously investigated in Estonia or in the countries with a similar climate. Using solar energy for dwelling heating is not widely used in Estonia. The vacuum insulation storage technology is novel and allows for storing heat energy for a longer period for small buildings. In Estonia, there are no studies at all about the solar heat energy storage in residential heating systems. This article describes a simplified solution based on calculations of how and how much the vacuum insulated long-term solar heat energy storage tank in the solar heating system will increase the solar heat energy share for a single-family house using direct heating, in Estonian and other countries with a similar climate. Using solar energy to direct heating for dwelling can reduce the demand for other heat energy sources.

2. Materials and Methods The calculations are based on the climate data of 2017 in Tartu, measured by the weather station. The weather station Vantage Pro+ is located on a building’s roof at 58◦2319” N, 26◦4137” E, at the

68 Energies 2018, 11, 1832 3of9 EnergiesEnergies 2018 2018, 11 11, x 3 of 9 heightheight from from ground 25 m. The The m measurementseasurementsss are are taken taken by by step stepssss of 5 min.min. The The y yearlyearly average average −2 temperaturetemperature in in this thiss location location is iss 5.8 ◦°CC and the solarsolars potentialpotential 350350 kWhkWh m m−−2.. The The solar solars collectors collectorss are are facingfacing to towardswardss the the south souths and and the the inclination angle angle is s 60°. 60◦. The The heating heating systemss system simplifieds simplified circuit circuit is iss shownshowns in in Figure Figure 11. . The The systemss system allowss allows for for the the uses use of of different different heating heating modess modes,, which which are are presenteds presented in Tablein Table 1. Th1.is Thiss paper paper describesss describes only only the the solutions solution of solars of solar heat heat energy energy that that iss useds is used for direct for direct heating heating via avia buffer a buffer or long or long-term-term heat heat storages storage tank. tank. The t Theank tank stratifications stratification hass not has been not been taken taken into account. into account. The calculationsThes calculations are baseds are based on the on flow the flow of energy. of energy.

Figure 1. ss FigureFigure 1. 1. SimplifiedSimpliﬁed circuit circuit of of the the heating heating system. system.

Figure 1 showsss alsos a heat pump part, which iss not considereds in detail in thiss paper. Ignoring Figure 1 shows also a heat pump part, which is not considered in detail in this paper. Ignoring the the heat pump part doess not affect the resultsss of the calculations,s becauses thiss article describesss only heat pump part does not affect the results of the calculations, because this article describes only the heat the heat energy from the suns to the direct heating. In the article, only the heat energy iss mentioned, energy from the sun to the direct heating. In the article, only the heat energy is mentioned, which is which iss needed to cover all of the houses’s’s heat energy demand. Thiss heat energy can be extracted needed to cover all of the house’s heat energy demand. This heat energy can be extracted using the usings the heat pump. The amount of the additional heat energy iss useds to calculate the direct heating heat pump. The amount of the additional heat energy is used to calculate the direct heating share. share.s Vacuum isolateds heat s storage tankss [15], s solar s collectors, and buffer tankss with the volume of Vacuum3 isolated heat storage tanks [15], solar collectors, and buffer tanks with the volume of 15 15 m have been selected for the calculations. A prototype of the vacuum insulated tank is showed in m3 have been selecteds for the calculations.s A prototype of the vacuum insulateds tank iss showeds in Figure 2. Figure 2.

(aa) (bb)

Figure 2. Vacuum insulated prototype tank (a) and inner container sketch with pipelines (b)[8]. FigureFigure 2.2. Vacuum insulateds prototype tank (aa) and inner container sketchs with pipeliness (bb) [8].

The solar collectors Ensol ES2H/2.65 S are a ﬂat plate type [16]. The main parameters of the The solars collectorss Ensols ES2H/2.65 S are a flat plate type [16]. The main parameterss of the heating system components and the house are described in Table 2. If the buffer tank temperature heating systemss componentss and the houses are describeds in Table 2. If the buffer tank temperature iss greater than 45 °C, then the heat energy for domestics hot water will be alsos taken into account in the

69 Energies 2018, 11, 1832 4of9

is greater than 45 ◦C, then the heat energy for domestic hot water will be also taken into account in the calculations. The daily hot water consumption is 150 kg and the temperature raise is by 50 K. The demand proﬁle is not used. The calculations are made using steps of 5 min. The single-family houses that have been used in the calculations are two-story and the shape is rectangular. To simplify the calculations, the external border area is summarized. The whole building is shown as one room and the occupancy pattern and lightning pattern are not used. The ventilation 2 1 system is natural. The external border area, with a mean U-value 0.17 W m− K− , was taken in for the 2 calculations. The free heat power (3 W m− ) and dwelling mean U-value were based on the standards in Estonia.

Table 1. The working modes of the heating system.

Heating Mode Open Valves Closed Valves Direct heating using buffer tank. 5, 8 1, 2, 3, 4, 6, 7 Direct heating using vacuum insulated tank. 5, 7 1, 2, 3, 4, 6, 8 Using residual heat from buffer tank to increase heat pump inlet temperature. 1, 3, 6, 7 2, 4, 5, 8 Heat pump is working and input energy delivered from ground loop. 4, 6 1, 2, 3, 5, 7, 8 Overproduced heat energy is stored in to the ground. 1, 2, 7 3, 4, 5, 6, 8

Table 2. The main parameters of components of the heating system.

Description of System Component Symbol Value 2 Solar collector absorber area Ac 2.44 m Solar collector zero lost coefficient a0 0.824 2 1 Solar collector linear loss coefficient a1 2.905 W m− K− 2 1 Solar collector quadratic loss coefficient a2 0.03 W m− K− 2 1 House average heat transmission coefficient U 0.17 W m− K− 2 House surface area Ab 434 m House inside temperature tin 21 ◦C 2 Free heating power Pf 3Wm− 2 House floor area Ahouse 160 m Storage tank volume Vtank 15,000 kg 2 Storage tank surface area Atank 52.4 m 2 1 Storage tank heat transmission coefficient Utank 0.07 W m− K− Storage tank maximum operating temperature top 110 ◦C Buffer tank volume Vbuf 1000 kg 2 Buffer tank surface area Abuf 6m 2 1 Buffer tank heat transmission coefficient Ubuf 0.4 W m− K− Daily hot water energy consumption Q 10.5 kW h water ·

The output power of the solar collector depends on the solar irradiation, collector area, and collector heat losses. The heat loss is related to the collector temperature and the ambient temperature. The higher difference between the solar collector and the ambient temperature causes a bigger heat loss. The solar collector temperature is related to the mean temperatures of the buffer tank and the long-term storage tank. The output power of the solar collector is calculated by the following formula [17]: P = A n G a (T T ) a (T T )2 (1) s c 0· − 1 m − a − 2 m − a where Ps is the collector output power, Ac is the solar collector absorber area, n0 is the zero lost efficiency, G is the solar irradiation, a1 is the first order heat loss coefficient, a2 is the second order heat loss coefficient, Tm is the collector temperature, and Ta is the ambient air temperature. Firstly, the produced heat is directed into the buffer tank. If the temperature in the buffer tank raises over 36 ◦C, then the stored heat energy is used for the house’s direct heating. The house’s heat delivery system is floor heating, for which the supplied temperature is lower compared with the conventional heater [18]. If the temperature is greater than 45 ◦C, then the energy for the domestic hot

70 Energies 2018, 11, 1832 5of9

water will be also taken from the buffer tank. If the temperature raises over 60 ◦C, then the produced heat energy will be directed in to the long-term storage tank. If the long-term storage tank temperature rises over 100 ◦C, then the heat energy is moved in to the heat pump ground loop. In autumn, when the solar irradiation is not enough for the buffer tank temperature to raise over 36 ◦C, the heat energy from the long-term tank is used for the house heating. The following formulas are the basis for calculating the buffer tank and the long-term tank temperature. If tb < 36 ◦C, then the buffer tank temperature changes using the following formula:

(Q Q ) t = t + solar − bloss (2) b bp m c p· p where tb is the buffer tank temperature, tbp is the buffer tank initial temperature, Qsolar is the solar heat energy, Qbloss is the buffer tank heat energy loss, mp is the water mass, and cp is the water speciﬁc heat capacity. If tb > 36 ◦C, then the buffer tank temperature changes using the following formula:

(Q Q Q ) t = t + solar − bloss − house (3) b bp m c p· p where Qhouse is the heat energy consumption of the house. If tb > 45 ◦C then the buffer tank temperature changes, using the following formula:

Qsolar Qbloss Qbuilding Qhw t = t + − − − (4) b bp m c p· p where Qhw is the heat energy for the domestic hot water heating. If tb > 60 ◦C and tt < 36 ◦C, then the storage tank temperature changes, using the following formula: (Q Q ) t = t + solar − tloss (5) t tp m c t· p where tt is the storage tank temperature, ttp is the storage tank initial temperature; Qtloss is the storage tank heat energy loss, and mt is the storage tank water mass. If tb <60 ◦C and tt >36 ◦C, then the storage tank temperature changes, using the following formula:

Qsolar Qtloss Qbuilding t = t + − − (6) t tp m c t· p The heat capacity of the water is 0.001164 kW h kg 1. · − The efﬁciency of the direct heating system depends the stored heat energy and system losses, as follows: ∑ Qdirect ηsys = (7) ∑ Qtloss + ∑ Qbloss + ∑ Qwaste where ηsys is the system efﬁciency, Qdirect is the energy for direct heating, and Qwaste is the energy to heat the pump ground loop. The U-values that are used in this article are calculated using insulation thickness and insulation thermal resistance.

3. Results and Discussion The buffer tank and the long-term storage tank temperature changes are shown on Figure 3. The absorber area, buffer tank, and storage tank volumes are selected experimentally by trying out different parameters (solar collector absorber area, vacuum insulated tank volume, and direct

71 Energies 2018, 11, 1832 6of9 Energies 2018 11 heating share). It was s important that s the direct ss heating share of the s house’ss heat energy demand is over 40% and that the system efﬁciency is over s 50%. The temperature of the s buffer s tank in all three of the analyzed conditions gave similar results, s therefore, s it is showed in one condition. Thes temperature change for the long-term tank depends on the area s of the solar collectors s and the s tank volume. The tank, with a larger volume allows for storing more heat senergy and to use it for a longer period. The time for heating up the long-term storages s tanks depends on the solar collector area. Thes maximum s temperature s s of the long-term s tank is achieved in May and the heating up time difference with different collector areas is small. The produced heat energy s in s the s summertime is mostly used by heating the domestic hot water and s by heating up the ground around the heat pump ground loop. The end of the direct heating for the house is visible in Figure 3, in the place where the long-term tank temperature s drops under 36 ◦C. s s s ss ’s s s In Figure 3, during the time between January and March, thess vacuum insulated tank temperature drops, which is caused by heats s loss from the tank. The tank’s s initial temperature s is taken as 20 s◦C. In Figure3 , the tank temperature in January 2018 shows that s the tank temperature s in all three of the different volumes s is higher than 20 ◦C, which should be a direct s rise inthe heating share. 2 The heat energy balance for the year of 2017, with thes s solar collector s absorber area of s 48.4 m 3 and the long-term storage s s tank with the volume of 15 m , are shown s in Figure 4. s Between the end ofs November and the beginnings of April, ss the heat pump is used for the house heating.s The rest of the time the heat pump iss standing s and the ss heat s energy forss heating the house and the domestic hot water s s is collected from thes sun. The heat loss of the buffer tank and the long-term storage tank will not exceed 10 kW h a day. Most of this heat loss is the heat loss of the buffer tank. The data from Figure 4 · is summarized and shown in Table 3. Table 3.

DescriptionTable 3. Heat energy balance. Heat Energy (kW·h) s Description Heat Energy (kW h) s · House yearly heat energy demand 6023 Produced heat energy from sun s 8560 Solar heat energy for direct heating 2474 Additional heat energy demand (ground source heat pump) 3549 Energy to heat pumps ground loopsss 1903 Buffer sss tank and storage tank losses 2312 Storage losses 4215

FigureFigure 3. 3.The temperatures s of the buffer and long-term storages tank with different settings. ss

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FigureFigure 4.4. The daily energy of heating ss system s components in the year of 2017.

If s also s considering the heat energy that s is directed into the ground s as a heat ss loss, then the direct heating ss system efﬁciency s is 51%. The direct heating s share of the house’ss’s yearly heat energy demand is s41%. The heating system ss efﬁciency for different parts s is s presented s in Table 4 .

TableTable 4. 4. Heating ss system efficiency. Description Efficiency Description Efficiency ss Direct heating system efficiency 51% Solar irradiation to collected heat energy efficiency 20% Direct heating 41% Additional energy demand 59% sssBuffer tank losses 6% sVacuum insulated sss tank losses 21% Heat energy to ground 22%

Comparing the ss results to the s similar ss system, which located in Germany, one can be s say that the ssolar energy s share for the dwelling heating in Germany s is greater (41% s vs. 55%), s because the climate 3 there s is s also warmer [11]. The volume of the tank s is 11m . The overproduced heat energy, which is directed s into the heat pump ground loop in summertime, sshould raise s the temperature s of the ground. A higher ground temperature should reduce s length of the heat pump ground loop and increase the heat s pump inlet temperature in the heating season when storedss solar energy s is s over. Increasing s the inlets temperature of the heat pump will increase the coefﬁcient s of performance (COP). The COP is how many times s the energy cans heat the pump to move the heat pump inlet energy. This is only an assumption s s and will ss need a further investigation. s 4. Conclusions 5. ConclusionsThis paper presents a simpliﬁed method for increasing the share of solar direct heating for a single-familys house. ss The s calculations show the uses of a vacuum s insulated s tank for seasonal heat senergy storage, s which makes s it possible s to increase s the solar heat energys share for the ss direct heating. 3 The results s show that s the maximum ss temperature s of the s long-term storage s tank (15 m ) is achieved in May. ss The shares of the solar energy for direct heating will increase tos a level of 41%. This s can be further increased s by using a s larger long-term storage tank. The s additional heat demand is s 59%. A heat pump s s s s 73 Energies 2018, 11, 1832 8of9 is used for the house’s heating from the beginning of December to the end of March. The solar direct heating and the heating with the heat pump are used together in March. The main conclusions are as follows:

Heating system efﬁciency is 51%. This can be improved to better utilize the energy, which is • directed in to the ground; Heating system storage losses are 27%; and • Share of direct heating is 41%, if using a 15 m3 storage tank. •

Author Contributions: Study conception and design: J.K., A.A. (Andres Annuk), A.A. (Alo Allik), E.K.; Acquisition of data: J.K.; Analysis and interpretation of data: J.K., A.A. (Andres Annuk); Drafting of manuscript: J.K., A.A. (Andres Annuk), A.A. (Alo Allik), E.K.; Critical revision: J.K., A.A. (Andres Annuk), A.A. (Alo Allik), E.K. Funding: This research was funded by the Estonian Centre of Excellence in Zero Energy and Resource Efficient Smart Buildings and Districts, ZEBE, grant 2014-2020.4.01.15-0016, funded by the European Regional Development Fund. Acknowledgments: This research was supported by the Estonian Centre of Excellence in Zero Energy and Resource Efficient Smart Buildings and Districts, ZEBE, grant 2014-2020.4.01.15-0016, funded by the European Regional Development Fund. Conflicts of Interest: The authors declare no conflict of interest.

References

1. European Commission. 2030 Energy Strategy. Available online: https://ec.europa.eu/energy/en/topics/ energy-strategy-and-energy-union/2030-energy-strategy (accessed on 20 December 2017). 2. Directive 2010/31/EU of the European Parliament and of the Council of 19 May 2010 on the Energy Performance of Buildings. Available online: https://eur-lex.europa.eu/LexUriServ/LexUriServ.do?uri=OJ: L:2010:153:0013:0035:EN:PDF (accessed on 3 July 2018). 3. Xu, J.; Wang, R.Z.; Li, Y. A review of available technologies for seasonal thermal energy storage. Sol. Energy 2013, 103, 610–638. [CrossRef] 4. Meissner, R.; Abrecht, S. Sense and Nonsense of Solar Thermal Storage. Available online: http://ritter-xl-solar. com/uploads/media/Sense_and_Nonsense_of_solar_thermal_storage.pdf (accessed on 22 March 2018). 5. Kny, M.; Urban, M. Solar System with Long-term Heat Storage—Analysis and Optimisation. In Proceedings of the 11th REHVA World Congress & 8th International Conference on IAQVEC—Energy Efﬁcient, Smart and Healthy Buildings, Prague, Czech Republic, 16–19 June 2013. 6. Fricke, J.; Schwab, H.; Heinemann, U. Vacuum Insulation Panels—Exciting Thermal Properties and Most Challenging Applications. Int. J. Thermophys. 2006, 27, 1123. [CrossRef] 7. Lang, S.; Gerschitzka, M.; Bauer, D.; Drück, H. Thermal conductivity of vacuum insulation materials for thermal energy stores in solar thermal systems. Energy Procedia 2016, 91, 172–181. [CrossRef] 8. Beikircher, T.; Buttinger, F.; Demharter, M. Super-insulated long-term hot water storage. In Proceedings of the ISES Solar World Congress, Kassel, Germany, 28 August–2 September 2011. 9. Epp, B. Vacuum Super Insulation Reduces Heat Losses at Long-Term Storage. Global Solar Thermal Energy Council, 2013. Available online: http://www.solarthermalworld.org/content/germany-vacuum-super- insulation-reduces-heat-losses-long-term-storage (accessed on 20 December 2017). 10. Visualisierung-WebControl. Available online: http://vakuumpuffer.dyndns.org/heizung.php (accessed on 20 December 2017). 11. Vacuum Storage. Available online: http://vakuum-pufferspeicher.de/installationsbeispiele.html (accessed on 20 December 2017). 12. Benjamin, B.; Hofbecka, K. First Experience in Vacuum Insulated Hot Water Storage with 100 m3. Energy Procedia 2014, 57, 2390–2398. [CrossRef] 13. Sharma, A.; Tyagi, V.V.; Chen, C.R.; Buddhi, D. Review on thermal energy storage with phase change materials and applications. Renew. Sustain. Energy Rev. 2009, 13, 318–345. [CrossRef] 14. Krese, G.; Koželj, R.; Butala, V.; Stritih, U. Thermochemical seasonal solar energy storage for heating and cooling of buildings. Energy Build. 2018, 164, 239–253. [CrossRef]

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15. Vacuum High Power. Available online: http://vacuum-storage.com/series-vacuum-high-power.html (accessed on 20 December 2017). 16. Ensol. Technical Data of the Flat Solar Collectors. Available online: http://ensol.pl/new_ensol/wp-content/ uploads/2016/10/EN-Technical-Data-ES2H265-072015.pdf (accessed on 20 December 2017). 17. ESTIF. Objective Methodology for Simple Calculation of the Energy Delivery of (Small) Solar Thermal System. 2007. Available online: http://www.estif.org/ﬁleadmin/estif/content/policies/downloads/ Simple_Calculation.pdf (accessed on 20 December 2017). 18. Sarbu, I.; Sebarchievici, C. A study of the performances of low-temperature heating systems. Energy Efﬁc. 2015, 8, 609. [CrossRef]

© 2018 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).

75 76 IV Kalder, Janar; Hovi, Mart; Allik, Alo; Annuk, Andres. (2019). Interseasonal heat storage for residential buildings with renewable energy generation. Proceedings of Engineering for Rural Development: Engineering for Rural Development 2018, Jelgava, 22.-24.05.2019. Jelgava: Latvian University of Life Sciences and Technologies, 1484−1489. ENGINEERING FOR RURAL DEVELOPMENT Jelgava, 22.-24.05.2019.

INTERSEASONAL HEAT STORAGE FOR RESIDENTIAL BUILDINGS WITH RENEWABLE ENERGY GENERATION Janar Kalder, Mart Hovi, Alo Allik, Andres Annuk Estonian University of Life Sciences, Estonia [email protected], [email protected], [email protected], [email protected]

Abstract. This article describes the modelling of the energy system for a house, which includes components for heating, electricity production from renewables, energy storage and consuming devices. The electrical energy production devices are not connected to the electrical power supply grid and overproduced energy is stored in along term storage water tank. Batteries are also included in the energy system. The energy production of the PV-panels in spring, summer and early autumn is high but the annual heat energy demand for a house is nearly zero. Therefore, it is sensible to use the power plant in grid connected mode and the grid acts like a storage, where is it possible to sell the overproduced energy. The aim of this research is to investigate a solution that uses as much as possible of the produced energy locally, storing the energy in the vacuum insulated tank as heat, if batteries are full. The energy that is stored in the tank, can be used at the beginning of the heating season. This article is based on modelling of the proposed heating system. The inputs for the model are production data from PV panels and a wind generator, climate data (outside temperature) and the heat and electricity demand of the example house. Storing overproduced energy as heat in the vacuum insulated tank, will increase the share of locally produced energy, and therefore decrease import of electrical and other sources of energy. The results show, if the yearly renewable energy production is 13000 kW·h and the house yearly energy demand is 12981 kW·h, then over 79 % of overall energy demand can be covered from renewable energy sources, if the solar/wind share is 30/70 %. With the solar/wind ratio 70/30 %, the coverage is over 60 %.

Keywords: solar energy, wind energy, long term storage tank, seasonal storage, vacuum insulation.

Introduction Energy from the sun can be used to increase the share of renewable energy for heating of a house. The use of solar energy is widely investigated for heating systems, like the use of solar collectors and different other methods for using it effectively [1], for example, increasing the coefficient of performance (COP) of a heat pump [2]. Solar energy is mostly available in warmer periods, when the heating demand is low. Therefore, it is necessary to use interseasonal storages for heat energy. Previously borehole storages have been investigated [3;5], large tanks and basins and etc. [5]. However, these are large storages or complex technology (phase change materials) [6] and using them for a single family house would not be efficient. For increasing the consumption of electricity, which is produced locally with a wind generator and photovoltaic (PV) panels, also different methods are previously investigated. For example, batteries [7], demand management [8], preheat boilers [9;10] and other systems are used. However, these methods are not feasible to store enough energy for the long term heating of a house. Earlier research for increasing the share of renewable energy for heating a house used only solar collectors and a medium size vacuum insulated tank (VSI tank). The results showed that the direct heating percentage from solar energy for a 160 m2 house can be 41 % in a system with a 15 m3 storage tank [11]. Direct heating means in this case that the energy is used directly, without converting it. The VSI tank contains an outer and an inner tank. The space between these layers is filled with expanded perlite and air is evacuated [12]. The VSI tank U-value is 0.05 W·m-2·K-1 [13] and measurements, in the test period, showed an 0.23 K average temperature drop per day, when placed outdoor [14]. In Nordic countries, the amount of energy used for house heating is high. For covering both, the electricity and heating demands, it is necessary to use both storage systems (interseasonal storage and batteries). The new approach is to use PV-panels, a wind generator, batteries and a VSI tank together to increase the renewable energy share for a single-family house. The remaining energy after covering the demand of electricity for household devices and daily energy for domestic hot water (DHW) is stored in to the VSI tank and used during the heating season. The aim of this research is to investigate how much is it possible to cover from the overall energy demand of a house with renewable energy sources in different wind and solar energy production conditions, when consumption and production are similar. One requirement of this system is that all produced electricity is used locally, in vicinity

DOI: 10.22616/ERDev2019.18.N374 1484

79 ENGINEERING FOR RURAL DEVELOPMENT Jelgava, 22.-24.05.2019. without selling it to the AC grid. The system also is usable in locations without a distribution grid. The system is suitable for nearly zero buildings.

Materials and methods This research is based on a model, which is based on the energy system of a small building. The model is made with spreadsheet software, where all necessary parameters of the heating and consuming systems are used for making calculations. The system overview is shown in Figure 1. The input parameters for the model are the production of wind and solar energy, consumption of household electricity, energy spent for domestic hot water and the energy demand for heating. Production of wind and solar energy is based on the measurements between 01.12. 2015 and 30.11.2016. The rated power of the wind generator is 10 kW, which is located in a coastal area (N 59.087694, E 23.591719) and manufactured by Tuge Ltd. Photovoltaic panels rated power is 2.5 kW, the producer is DelSolar (DelSolar 250 W DP250B3A). In Estonian territory the PV panel capacity factor 0.11 is quite even. The demand of household electricity is based on the measurements conducted during October 2018. The measuring interval was one hour and the data are converted to 5 minute averages. These data are taken 12 times to get the electricity consumption for one year, which is total 4623 kW·h. The energy for heating is based on the calculated two storey house, which floor area is 160 m2 and surface area 434 m2. The average U-value 0.17 W·m-2·K-1, indoor temperature 21 ºC, free heat 3 W·m-2 and the outdoor temperature, measurement step 5 minutes, are taken for calculating the demand of heat energy. The DHW is equal with the energy, which is needed to rise a temperature of 150 l water in the boiler from 5 ºC to 70 ºC. For simplification, the heat capacity of construction materials is not taken into account. For covering deficit of electricity, when renewable energy is not available, energy is taken from the AC grid, using automatic switch between the energy sources.

Fig. 1. Circuit diagram of energy system of house: 1 – AC grid connection; 2 – boiler for DHW; 3 – inverters for solar panels and wind generator; 4 – batteries; 5 – long-term storage tank; 6 – microcontroller controlled switch; 7 – dump load controllers (DLC) for solar panels and the wind generator; 8 – water heater for the heating system; 9, 10 – heating supply switching valves; 11 – floor heating supply; 12 – wind generator; 13 – PV panels The modelling is based on energy amounts of 5 minute intervals. Firstly, the produced renewable energy is used to cover the household’s electricity demand and charge the deep cycle batteries with a

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80 ENGINEERING FOR RURAL DEVELOPMENT Jelgava, 22.-24.05.2019. capacity of 9.6 kW·h (200 Ah, 48 V). Energy from the batteries is used until 36 % depth of discharge (DoD) is reached. The charging current of the batteries is limited to 20 A, which is in accordance with the rule of thumb that the charging current should not exceed 0.2C, where C is the batteries capacity (Ah). The remaining energy is directed to the boiler, after that directly into the heating system of the house and after that to the VSI tank. The energy, which is added to the VSI tank and boiler, causes a temperature change described by formula 1:

Q  Qloss  Qcon t=t p + (1) mw cw where t – water temperature, ºC; tp – previous water temperature, ºC; Qre – renewable energy, kW·h; Qloss – energy losses, kW·h; Qcon – energy consumption, kW·h; mw – water weight, kg; -1 -1 cw – water specific heat, kW·h·kg ·K . From the energy that goes into the boiler the energy of heat loss is taken off and energy for DHW. The AC grid is used for supply of the boiler, when the temperature drops under 40 ºC. This temperature is taken experimentally. If the temperature in the boiler raises over 70 ºC, then energy flows directly to heating the house, if needed, and then remaining energy goes to the VSI tank. From the energy that goes into the VSI tank, the energy of heat loss is taken off and the energy for house heating, if the temperature inside the tank is over 34 ºC. This temperature is the minimum for floor heating supply. The maximum temperature of the VSI tank (15 m3) is 100 ºC, although up to 110 ºC is also acceptable due to higher than atmospheric pressure[13]. Maximum pressure of the VSI tank is 3 bar [13]. The energy loss of the tank is calculated by using the outdoor temperature. The energy for house heating is taken from the AC grid, when the temperature in the tank drops under 34 ºC. The outputs from PV panels and the wind generator are fluctuating and therefore it is necessary to use variable heaters for the boiler, the VSI tank and water heater. This is achieved by using multiple 3 phase heaters and by switching them according to the renewable energy productivity to match the different loads. The outputs of production devices are scaled to get different energy productions in the range of 2- 15 kW·h. The proportions of solar and wind energy are changed between 100:0, 70:30, 50:50, 30:70, 0:100. This enables to research how the productivity of PV-panels and the wind generator affects the energy balance of the house. To get these data, the special program is written, which changes the renewable energy production device scale in the model and collects all necessary output parameters. The output parameters of the model, which are of interest, are: the renewable energy share of the house, direct heating share, energy loss and the renewable energy share of the household’s electricity consumption. Loss of energy contains the unused energy and heat losses from the boiler and VSI tank.

Results and discussion The yearly energy demand of the house is 12981 kW·h, which includes household electricity (4623 kW·h), heat energy (5613 kW·h) and energy for DHW 2745 kW·h. The results of the modelling show that the best result is achievable, when only a wind generator is used (Fig. 2). However, the loss of energy is smallest in a configuration, where the renewable energy share of the house demand is over 0.77 (10000 kW·h·a) and 30 % are produced from wind and 70 % from solar energy (Fig. 4). The share of renewable energy is significantly lower, when using this option, compared with the option, when all energy is produced by the wind generator. The renewable energy share in the household electricity consumption is better, when both energy production devices are used (Fig. 5). In a situation, when the ratio between the renewable energy production and consumption of the house is 1 and the solar/wind share is 30/70 %, the share of directly consumed renewable energy was 79 % (10313 kW·h). Energy losses were in this scenario 21 % (2747 kW·h), of which 2292 kW·h were energy losses from the VSI tank and the boiler. The remaining energy loss (455 kW·h) was

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81 ENGINEERING FOR RURAL DEVELOPMENT Jelgava, 22.-24.05.2019. caused by unused renewable energy and inefficiency of the batteries. The energy from the VSI tank that was used to heatthe house is 3346 kW·h and deficit of energy that was taken from the AC grid, was 2649 kW·h. 1.0 0.9 S100% W0% 0.8 S70% W30% 0.7 S50% W50% 0.6 S30% W70% 0.5 0.4 0.3 0.2 0.1 0.0 Share of renewable energy renewable of Share 0.15 0.19 0.23 0.27 0.31 0.35 0.39 0.42 0.46 0.50 0.54 0.58 0.62 0.65 0.69 0.73 0.77 0.81 0.85 0.89 0.92 0.96 1.00 1.04 1.08 1.12 1.16 Ratio of renewable energy production to house demand

Fig. 2. Share of renewable energy of house electricity supply

1.0 S100% W0% 0.8 S70% W30% S50% W50% 0.6 S30% W70% S0% W100% 0.4

0.2

0.0 Share of renewable energy renewable of Share 0.15 0.19 0.23 0.27 0.31 0.35 0.39 0.42 0.46 0.50 0.54 0.58 0.62 0.65 0.69 0.73 0.77 0.81 0.85 0.89 0.92 0.96 1.00 1.04 1.08 1.12 1.16 Ratio of renewable energy production to house deman d

Fig. 3. Share of renewable energy for direct heating of house

0.6 S100% W0% 0.5 S70% W30% 0.4 S50% W50% S30% W70% 0.3 0.2 0.1 0 Energy loss from production from loss Energy 0.15 0.19 0.23 0.27 0.31 0.35 0.39 0.42 0.46 0.50 0.54 0.58 0.62 0.65 0.69 0.73 0.77 0.81 0.85 0.89 0.92 0.96 1.00 1.04 1.08 1.12 1.16 Ratio of renewable energy production to house demand

Fig. 4. Energy loss of system

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This all in one system is new and actual to supply the house with electrical and heat energy. Also investments for other electrical consuming heating devices, like a ground source heat pump, are not needed, because the energy demand from the AC grid is comparably small (2649 kW·h). 1.0 0.9 0.8 0.7 0.6 0.5 S100% W0% S70% W30% 0.4 0.3 S50% W50% S30% W70% 0.2 S0% W100% 0.1 0.0 Share of household electricity 0.15 0.19 0.23 0.27 0.31 0.35 0.39 0.42 0.46 0.50 0.54 0.58 0.62 0.65 0.69 0.73 0.77 0.81 0.85 0.89 0.92 0.96 1.00 1.04 1.08 1.12 1.16 Produced energy, kW·h

Fig. 5. Renewable energy share for household electricity However, it is necessary take into consideration that the power from the wind generator is fluctuating, which is caused by climatic factors. Therefore, it is advisable to use a system, where 70 % of the energy is generated from the PV panels and 30 % from the wind. This covers directly over 60 % of the overall energy consumption, if the produced amount of renewable energy is 13000 kW·h, which is comparable to the total energy consumption. It is necessary to use renewable energy to meet the nearly zero energy building standard.

Conclusions The following conclusions were made on the basis of the methodology given above: 1. It is possible to cover most of the energy demand of a house from the sun and wind, by using a vacuum insulated tank as long-term heat storage and when the production and demand are similar. Therefore, it is not necessary to build an additional heating system,like a ground source heat pump, because the amount of the purchased electricity isnegligible. 2. The share of directly consumed energy dependson the production of energy from PVpanels and the wind generator and the relationship between these energy amounts. 3. This approach for supplying the house with renewable energy enables to meet the requirements of the standard for nearly zero buildings.

Acknowledgements This research was supported by the Estonian Centre of Excellence in Zero Energy and Resource Efficient Smart Buildings and Districts, ZEBE, grant 2014-2020.4.01.15-0016 funded by the European Regional Development Fund.

References [1] Kalogirou S. A. Solar thermal collectors and applications. Progress in Energy and Combustion Science, vol. 30, 2004, pp. 231-295. [2] Chwieduk D. A. Solar-assisted heat pumps. Comprehensive Renewable Energy, vol. 3, 2012, pp. 495-528. [3] Lanahan M., Tabares-Velasco P. C. Seasonal thermal-energy storage: A critical review on BTES systems, modeling, and system design for higher system efficiency. Energies 2017, 10, 743. [4] Bär K., Rühaak W., Welsch B. etc. Seasonal High Temperature Heat Storage with Medium Deep Borehole Heat Exchangers. Energy Procedia, vol. 76, 2015, pp. 351-360.

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LAGLE HEINMAA FACTORS AFFECTING APPLE JUICE QUALITY AND MYCOTOXIN PATULIN FORMATION ÕUNAMAHLA KVALITEETI JA MÜKOTOKSIINI PATULIINI TEKET MÕJUTAVAD

TEGURID AND SOLAR WIND ENERGY SEASONAL HEAT STORAGE SYSTEMS FOR RESIDENTIAL BUILDINGS IN NORDIC CLIMATE Dotsent Ulvi Moor, professor Eivind Vangdal 31. august 2020

ISSN 2382-7076 Tartu 2020 ISBN 978-9949-698-55-4 (trükis) ISBN 978-9949-698-56-1 (pdf)