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Performance of off-grid photovoltaic cooling system with two-stage energy storage combining battery and cold water tank. Dengjia Wanga,*, Liang Hua, Yanfeng ...
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Energy (2017) 000–000 574–579 EnergyProcedia Procedia132 00 (2017) www.elsevier.com/locate/procedia

11th Nordic Symposium on Building Physics, NSB2017, 11-14 June 2017, Trondheim, Norway

Performance of off-grid photovoltaic cooling system with two-stage The 15th International Symposium on District Heating and Cooling energy storage combining battery and cold water tank Assessing the feasibility of using the heat demand-outdoor Dengjia Wanga,*, Liang Hua, Yanfeng Liua, Jiaping Liua temperature function for a long-term district heat demand forecast Xi’an University Of Architecture And Technology, No13. Yanta Road, Beilin, Xi'an, 710055 China aa

I. Andrića,b,c*, A. Pinaa, P. Ferrãoa, J. Fournierb., B. Lacarrièrec, O. Le Correc a

IN+ Center for Innovation, Technology and Policy Research - Instituto Superior Técnico, Av. Rovisco Pais 1, 1049-001 Lisbon, Portugal b Veolia Recherche & Innovation, 291 Avenue Dreyfous Daniel, 78520 Limay, France c Département Systèmes Énergétiques et Environnement - IMT Atlantique, 4 rue Alfred Kastler, 44300 Nantes, France

Abstract

This paper proposes an off-grid PV cooling system with TSES combing BS and CWST and investigates the influence of battery efficiency, tank insulation and chiller schedule on system efficiency and storage capacity. TRNSYS is employed to study the specific performance of this system. The results indicate that, in comparison with SBS and SCWST, the proposed TSES can rise Abstract system efficiency by 6.73% and 10.27% under convex cooling load while by 7.16% and 10.50% under ascending one. © 2017 2017 The Authors. Authors. Published Published by by Elsevier Elsevier Ltd. Ltd. © DistrictThe heating networks are commonly addressed in the literature as one of the most effective solutions for decreasing the Peer-review under responsibility of the organizing committee of of the the 11th 11th Nordic Nordic Symposium on on Building Building Physics. Physics. Peer-review responsibility organizing committee greenhouseunder gas emissions from of thethe building sector. These systems require highSymposium investments which are returned through the heat sales. Due the changed climate energy conditions and building renovation heat demand in the future could decrease, Keywords: PV to cooling system; Two-stage storage; Battery storage; Cold waterpolicies, storage; TRNSYS prolonging the investment return period. The main scope of this paper is to assess the feasibility of using the heat demand – outdoor temperature function for heat demand The district of Alvalade, located in Lisbon (Portugal), was used as a case study. The district is consisted of 665 1.forecast. Introduction buildings that vary in both construction period and typology. Three weather scenarios (low, medium, high) and three district renovation scenarios were developed (shallow, intermediate, deep). To estimate the error, obtained heat demand values were Off-grid PV cooling system is an important technology to provide comfortable environment for occupants, compared with results from a dynamic heat demand model, previously developed and validated by the authors. especially for hot remote area, such as isolated island in low latitude, where outside grid is unavailable and electricity The results showed that when only weather change is considered, the margin of error could be acceptable for some applications generated from fuelsdemand is mainly for20% more forHowever, all solar after cooling system, renovation because (the error in annual wassupplied lower than forimportant all weatherfacilities. scenariosHowever, considered). introducing ofscenarios, mismatching between solar radiation and cooling load, energy storage becomes indispensable in this field. BS and the error value increased up to 59.5% (depending on the weather and renovation scenarios combination considered). TS are two optional ways to solve such problem and many researches have been focused on them. The value of slope coefficient increased on average within the range of 3.8% up to 8% per decade, that corresponds to the For off-grid system with BS, modeling, experiment andheating economic optimization investigated by many decrease in the PV number of heating hours of 22-139h during the season (depending have on thebeen combination of weather and renovation considered). other hand, function intercept per an decade (depending on the scholars. Byscenarios using state equationsOn andthenumerical integration methods,increased Illanes etforal.7.8-12.7% [1] modeled off-grid PV systems coupled scenarios). The values suggested could used to modify function parameters and and employed dynamic simulation to test the be coincidence with the experiments. Huang etfor al.the [2]scenarios built an considered, experimental improve the accuracy of heat demand estimations. © 2017 The Authors. Published by Elsevier Ltd. Peer-review under responsibility of the Scientific Committee of The 15th International Symposium on District Heating and * Corresponding author. Tel.: +1-327-945-5510. Cooling. E-mail address: [email protected]

Keywords: Heat demand; Forecast; Climate change 1876-6102 © 2017 The Authors. Published by Elsevier Ltd. Peer-review under responsibility of the organizing committee of the 11th Nordic Symposium on Building Physics. 1876-6102 © 2017 The Authors. Published by Elsevier Ltd. Peer-review under responsibility of the Scientific Committee of The 15th International Symposium on District Heating and Cooling.

1876-6102 © 2017 The Authors. Published by Elsevier Ltd. Peer-review under responsibility of the organizing committee of the 11th Nordic Symposium on Building Physics 10.1016/j.egypro.2017.09.745

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Nomenclature BS CS CWST Cb Cc Effb Effs

battery storage cold storage cold water storage tank capacity of battery storage, kJ capacity of cold storage, kJ efficiency of battery efficiency of whole system

HWST PCM SBS SCWST TLC TS TSES

hot water storage tank phase change material single battery storage single cold water storage tank tank loss coefficient, W/ (m2∙K) thermal storage two-stage energy storage

system to investigate the running probabilities of PV air conditioner with BS. Moreover, Benmouiza et al. [3] proposed an optimal method of PV and battery sizing for off-grid PV system with classification of hourly solar radiation using fuzzy c-means algorithm. In comparison with BS, TS is usually used in solar heat driven cooling system. For example, Agyenim et al. [4] developed a domestic-scale experimental solar LiBr/H2O absorption cooling system with SCWST and proved the feasibility of such system. Mammoli et al. [5] introduced a solar absorption cooling system with HWST and CWST together and built an experiment to investigate its performance. Similar system of combining hot and cold storage was employed by Allouche et al. [6] who modeled an integrated solar-driven ejector based air conditioner with both HWST and PCM CS. The results indicated that such system could achieve better comfort than the one without CS. Although it is seldom to find a PV cooling system with TS, Wang et al. [7] have introduced such research. In their paper, the systems respectively with battery, ice and other PCMs were compared through primary energy saving ratio. The results from TRNSYS showed that BS generally had a better energy saving than PCM CS. However, there is almost no study about PV cooling system with BS and CS together, especially for off-grid case. Since BS can store nearly 95% energy for one month [8] while CS loses relatively fast but may acquire an efficiency higher than 90% (general Effb from [8]) for energy transfer in one day if CS is well designed [9], it is enlightening to combine two devices together so as to mix advantages and overcome shortcomings. Simultaneously, storage capacity can be reduced because energy can be stored in both of them rather than only one. Therefore, in comparison with single energy storage, the combined energy storage may reach a better performance. This paper will present a simulation work based on TRNSYS to predict the performance of an off-grid PV cooling system with combining battery and CWST. Also SBS and SCWST case will be involved as contrasts. In addition, the influences of cooling load characteristics, chiller schedule, Effb and TLC on storage capacity and Effs will be discussed. 2. Methodology 2.1. System description The proposed off-grid PV cooling system with TSES is shown in Fig. 1a. PV modules, chiller and battery are connected to a power inverter (including battery controller) which functions as a center to charge or discharge battery and convert direct current into alternating one. Then chiller, parallel connected with a CWST, supplies cold water to air conditioners in building via water pipes. For this system, battery can store surplus electricity generated by PV modules and release power when supplied energy is not enough for requirement of chiller. Similarly, when cold water produced by chiller is more than need of building at the same time, CWST will store this excess cooling capacity for future use when cooling load cannot be meet. Different from the cases of SBS and SCWST, it is possible to create a desired operation for chiller in TSES system since battery and CWST can work simultaneously or separately. As shown in Fig. 1b, the curves with different colors respectively represent solar radiation (red), PV power (gold), chiller power (green), chiller load (dark blue) and cooling load (light blue). Besides, the relationships between each curves reveal the regularity of energy conversion in the proposed system. The area below gold and above green is the electric energy that should be stored in battery while the one below dark blue and above light blue is the cold energy which need conserving in CWST. And the ratio of red and gold is the efficiency of PV panels while the one of dark blue and green is COP of chiller. It is obvious that the

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(a)

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(b)

Fig. 1. a) Off-grid PV cooling system with TSES; b) Energy conversion curve in TSES system.

curves of chiller power and load (green and dark blue) are able to be arranged as desire because the lack or excess energy can be solved by either BS or CS. However, since it is more benefit and efficient for chiller to work under stable condition, the curves of chiller power and load are designed as a straight line in this paper. 2.2. Simulation conditions As described in Fig. 2, two cooling load are chosen, namely ascending curve and convex curve which are obtained from a simple building created by TRNBuild with some intended parameters. Simultaneously, since Effb is generally from 0.8 to 0.95 for off-grid PV system [8], this paper chooses 0.75, 0.80, 0.85, 0.90, 0.95 and 1.00 for simulation. Here, 1.00 is selected as an ideal contrast. Besides, briefly calculating through the thermal conductivity of insulation materials from [10], TLC is chosen with 1, 0.5, 0.1, 0.05, 0.01 and 0. Similarly, 0 is selected as an ideal contrast. In addition, chiller schedule is arranged from 7:00-15:00 to 7:00-20:00 and actual chiller load is set 80% of rated capacity. 3. Results and discussion 3.1. System performance in convex cooling load Cb, Cc and Effs for TSES, SBS and SCWST system in convex cooling load is shown in Fig. 3. For TSES case with different Effb and TLC=0.1, Cb, Cc and Effs are as a function of chiller duration that is from 8h to 13h. Shown in Fig. 3a, with duration increasing, Cb is reducing when duration is less than 9h while increasing when more than that. However, Cc is always reducing. This can be explained in Fig.4 that Cb expressed by the area between PV power and chiller power is firstly decreasing and then growing with duration increasing while Cc represented by the area between chiller load and cooling load is lessening all along. Also in Fig. 3a, since the less PV areas, caused by Effs increasing as battery is more efficient, will supply less direct electricity for chiller and lead more Cb to fill the lack, Cb is reducing with Effb decreasing. But, Effb has no influence on Cc because cooling system is somehow independent from PV system when the consumption of chiller can be satisfied all the time. Besides, Effs is a convex shape and decreases with Effb descending in Fig. 3a. The maximum point for each Effb case indicates that there is a balance between Cb and Cc since too much Cb or Cc will both cause a huge energy loss in operation. When such system is running with different TLC and Effb= 0.85 as illustrated in Fig. 3b, the general tendency of Cb, Cc and Effs resembles the results shown in Fig. 3a. However, different from Effb, TLC has both influences on Cb and Cc. Because different TLC leads different efficiency of cooling system, the consumption of chiller will change and then influence PV system as follows. In specific, with higher TLC which causes more cold need for offsetting the loss and more electric need for meeting the consumption to produce such cold, Cb and Cc both have a slight rise while Effs is continuously decreasing. Moreover, growing chiller duration has a concentrated effect on Cc and Effs under different TLC in Fig. 3b while a diffuse trend of Effs is observed under different Effb in Fig. 3a. This phenomenon can

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Fig. 2. Cooling load and cumulative cooling load under different characteristics.

Fig. 3. Cb, Cc and Effs for TSES, SBS and SCWST system in convex cooling load. The results of SBS and SCWST system are plotted as a contrast here. For SBS case, they are as a function of Effb while are as a function of TLC for SCWST case.

be explained by that difference between tank loss in different TLC will not be huge with much less Cc caused by increasing duration. Nevertheless, the case is just contrary for battery in different Effb. For SBS and SCWST cases, the results are also plotted as contrasts with histogram in Fig. 3a and Fig. 3b. Obviously, for SBS case, Cb and Effs is both increasing with Effb growing. However, for SCWST case, with higher TLC, Cc has a slight rise while Effs is continuously decreasing. But Effs in TSES case is higher than in single case under most Effb and TLC, which implies a potential for better performance in the proposed system comparing with single storage case.

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Fig. 4. Energy curve with different schedules in TSES system.

Fig. 5. Cb, Cc and Effs for TSES, SBS and SCWST system in ascending cooling load. The results of SBS and SCWST system are plotted as a contrast here. For SBS case, they are as a function of Effb while are as a function of TLC for SCWST case.

Moreover, in most efficient TSES case under 7:00-16:00, Effb=1 and TLC=0.1, based on SBS case, Cb can achieve a reduction of 73.23% and Effs can acquire an increase of 6.73%. Considering SCWST case, although there is a 10.87% increase for Cc, Effs also rise 10.27%.

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3.2. System performance in ascending cooling load Cb, Cc and Effs for TSES, SBS and SCWST system in ascending cooling load is shown in Fig. 5. However, similar regularity appears as in convex cooling load. Likewise, in most efficient TSES case under 7:00-16:00, Effb=1 and TLC=0.1, based on SBS case, Cb can achieve a reduction of 76.26% and Effs can acquire an increase of 7.16%. Considering SCWST case, although there is an 8.34% increase for Cc, Effs also rise 10.50%. 3.3. Comparison of different cooling load characteristics The influences of convex or ascending cooling load on Effs and storage capacity shows similar regularity. But in specific, the maximum Effs can be obtained in different schedule. As shown in Fig. 3b and Fig. 5b, Effs under TLC= 0.5 reach the maximum value 0.6029 in 7:00-16:00 for convex curve while in ascending one the schedule becomes 7:00-17:00 with the value 0.6038. Although the values are approximate, the schedules differ by 1h. 4. Conclusions To solve mismatching in off-gird PV cooling system, a TSES combining BS and CWST has been present and the influences of cooling load characteristics, Effb, TLC and chiller schedule on its performance, that is Cb, Cc and Effs, has been investigated in TRNSYS. Besides, SBS and SCWST cases are also created to serve as the contrasts. Based on the results discussed in this paper, major conclusions are summarized as follows:  The chiller schedule is the main influence factor for Cb and Cc in TSES system. With duration increasing, Cb firstly descends and then ascends at the turning point that working time is 9h, while Cc constantly declines.  The TSES system exists a maximum efficient point which results from the loss balance between BS and CS. And it is benefit to select this point as the design condition if Effs is the major purpose. In this study, the maximum generally appears under schedule between 7:00-16:00 and 7:00-17:00.  Under most efficient condition in convex cooling load, the TSES system can increase Effs by 6.73% and 10.27% respectively based on the SBS and SCWST cases and reduce Cb by 73.23%. For ascending cooling load, the percentages become 7.16%, 10.50% and 76.26%. Evidently, it is of great meaning to continue further study. Acknowledgements The research was supported by the National Natural Science Foundation of China (Nos. 51590911, 51678468) and National key research and development program (Nos. 2016YFC0700401, 2016YFC0700402). References [1] Illanes R, De Francisco A, Núñez F, et al. Dynamic simulation and modelling of stand-alone PV systems by using state equations and numerical integration methods. Appl Energy 2014;135:440-9. [2] Huang B-J, Hou T-F, Hsu P-C, et al. Design of direct solar PV driven air conditioner. Renew Energy 2016;88:95-101. [3] Benmouiza K, Tadj M, Cheknane A. Classification of hourly solar radiation using fuzzy c-means algorithm for optimal stand-alone PV system sizing. Int J Elec Power 2016;82:233-41. [4] Agyenim F, Knight I, Rhodes M. Design and experimental testing of the performance of an outdoor LiBr/H2O solar thermal absorption cooling system with a cold store. Sol Energy 2010;84:735-44. [5] Mammoli A, Vorobieff P, Barsun H, et al. Energetic, economic and environmental performance of a solar-thermal-assisted HVAC system. Energy Build 2010;42:1524-35. [6] Allouche Y, Varga S, Bouden C, et al. Dynamic simulation of an integrated solar-driven ejector based air conditioning system with PCM cold storage. Appl Energy 2017;190:600-11. [7] Wang X, Dennis M. Influencing factors on the energy saving performance of battery storage and phase change cold storage in a PV cooling system. Energy Build 2015;107:84-92. [8] Yang Jinhuan. Applied technology of solar photovoltaic power generation. 2nd ed. Beijing: Publishing House of Electronics Industry; 2013. [9] Zhao Qingzhu. Cool storage: Technologies and system design. 1st ed. Beijing: China Architecture & Building Press; 2012. [10] Schiavoni S, D'Alessandro F, Bianchi F, et al. Insulation materials for the building sector: A review and comparative analysis. Renew Sustain Energy Rev 2016;62:988-1011.