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Strategy comparison and techno-economic evaluation of a grid-connected photovoltaic-battery system

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  • Ma, Tao
  • Zhang, Yijie
  • Gu, Wenbo
  • Xiao, Gang
  • Yang, Hongxing
  • Wang, Shuxiao

Abstract

The grid-connected distributed photovoltaic system with battery storage system has gathered growing research interest, while the high system model accuracy, grid and battery interaction, and weather prediction consideration are not widely concerned. In this study, the mathematical model of the photovoltaic battery system is developed, and five operation strategies considering battery charging by the grid and simple weather predictions are proposed and compared under various techno-economic indicators. Results show that the battery state of charge is susceptible to battery pre-charging during valley hours. The self-consumption rate (SCR) and self-sufficiency rate (SSR) can be increased by up to 8.8% and 8.5% respectively via purchasing more grid electricity at valley hours. The system with theoretically perfect weather prediction performs better technically than that of solar radiation data of the day before. Besides, it is proved that system economic performance can be improved effectively through the pre-charging battery by the grid at valley hours, resulting in the 8-17-year payback period of five strategies. Moreover, sensitivity analyses on some key factors are conducted, demonstrating that strategies with higher renewable consumption and less grid injection are more sensitive to battery capacity. The SSR and SCR could increase from 45.6% to 40.9%–70.6% and 65.0% as the battery capacity increases, respectively.

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  • Ma, Tao & Zhang, Yijie & Gu, Wenbo & Xiao, Gang & Yang, Hongxing & Wang, Shuxiao, 2022. "Strategy comparison and techno-economic evaluation of a grid-connected photovoltaic-battery system," Renewable Energy, Elsevier, vol. 197(C), pages 1049-1060.
    • Handle: RePEc:eee:renene:v:197:y:2022:i:c:p:1049-1060
    DOI: 10.1016/j.renene.2022.07.114
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    References listed on IDEAS

    as
    1. Beck, T. & Kondziella, H. & Huard, G. & Bruckner, T., 2017. "Optimal operation, configuration and sizing of generation and storage technologies for residential heat pump systems in the spotlight of self-consumption of photovoltaic electricity," Applied Energy, Elsevier, vol. 188(C), pages 604-619.
    2. Zhou, Yuekuan & Zheng, Siqian, 2020. "Machine-learning based hybrid demand-side controller for high-rise office buildings with high energy flexibilities," Applied Energy, Elsevier, vol. 262(C).
    3. Ma, Tao & Yang, Hongxing & Lu, Lin, 2014. "Solar photovoltaic system modeling and performance prediction," Renewable and Sustainable Energy Reviews, Elsevier, vol. 36(C), pages 304-315.
    4. Talavera, D.L. & Muñoz-Rodriguez, F.J. & Jimenez-Castillo, G. & Rus-Casas, C., 2019. "A new approach to sizing the photovoltaic generator in self-consumption systems based on cost–competitiveness, maximizing direct self-consumption," Renewable Energy, Elsevier, vol. 130(C), pages 1021-1035.
    5. Petrollese, Mario & Cau, Giorgio & Cocco, Daniele, 2018. "Use of weather forecast for increasing the self-consumption rate of home solar systems: An Italian case study," Applied Energy, Elsevier, vol. 212(C), pages 746-758.
    6. Javed, Muhammad Shahzad & Ma, Tao & Jurasz, Jakub & Canales, Fausto A. & Lin, Shaoquan & Ahmed, Salman & Zhang, Yijie, 2021. "Economic analysis and optimization of a renewable energy based power supply system with different energy storages for a remote island," Renewable Energy, Elsevier, vol. 164(C), pages 1376-1394.
    7. Hannan, M.A. & Lipu, M.S.H. & Hussain, A. & Mohamed, A., 2017. "A review of lithium-ion battery state of charge estimation and management system in electric vehicle applications: Challenges and recommendations," Renewable and Sustainable Energy Reviews, Elsevier, vol. 78(C), pages 834-854.
    8. Litjens, G.B.M.A. & Worrell, E. & van Sark, W.G.J.H.M., 2018. "Assessment of forecasting methods on performance of photovoltaic-battery systems," Applied Energy, Elsevier, vol. 221(C), pages 358-373.
    9. Javed, Muhammad Shahzad & Zhong, Dan & Ma, Tao & Song, Aotian & Ahmed, Salman, 2020. "Hybrid pumped hydro and battery storage for renewable energy based power supply system," Applied Energy, Elsevier, vol. 257(C).
    10. Yan, Xiaohe & Gu, Chenghong & Li, Furong & Xiang, Yue, 2018. "Network pricing for customer-operated energy storage in distribution networks," Applied Energy, Elsevier, vol. 212(C), pages 283-292.
    11. Kazemian, Arash & Salari, Ali & Hakkaki-Fard, Ali & Ma, Tao, 2019. "Numerical investigation and parametric analysis of a photovoltaic thermal system integrated with phase change material," Applied Energy, Elsevier, vol. 238(C), pages 734-746.
    12. Ringkjøb, Hans-Kristian & Haugan, Peter M. & Solbrekke, Ida Marie, 2018. "A review of modelling tools for energy and electricity systems with large shares of variable renewables," Renewable and Sustainable Energy Reviews, Elsevier, vol. 96(C), pages 440-459.
    13. Chaianong, Aksornchan & Bangviwat, Athikom & Menke, Christoph & Breitschopf, Barbara & Eichhammer, Wolfgang, 2020. "Customer economics of residential PV–battery systems in Thailand," Renewable Energy, Elsevier, vol. 146(C), pages 297-308.
    14. Dong, Siyuan & Kremers, Enrique & Brucoli, Maria & Rothman, Rachael & Brown, Solomon, 2020. "Improving the feasibility of household and community energy storage: A techno-enviro-economic study for the UK," Renewable and Sustainable Energy Reviews, Elsevier, vol. 131(C).
    15. Mayer, Martin János & Gróf, Gyula, 2021. "Extensive comparison of physical models for photovoltaic power forecasting," Applied Energy, Elsevier, vol. 283(C).
    16. Schopfer, S. & Tiefenbeck, V. & Staake, T., 2018. "Economic assessment of photovoltaic battery systems based on household load profiles," Applied Energy, Elsevier, vol. 223(C), pages 229-248.
    17. Wang, Zhimin & Gu, Chenghong & Li, Furong, 2018. "Flexible operation of shared energy storage at households to facilitate PV penetration," Renewable Energy, Elsevier, vol. 116(PA), pages 438-446.
    18. Markovics, Dávid & Mayer, Martin János, 2022. "Comparison of machine learning methods for photovoltaic power forecasting based on numerical weather prediction," Renewable and Sustainable Energy Reviews, Elsevier, vol. 161(C).
    19. Yang, Ying & Campana, Pietro Elia & Yan, Jinyue, 2020. "Potential of unsubsidized distributed solar PV to replace coal-fired power plants, and profits classification in Chinese cities," Renewable and Sustainable Energy Reviews, Elsevier, vol. 131(C).
    20. Talent, Orlando & Du, Haiping, 2018. "Optimal sizing and energy scheduling of photovoltaic-battery systems under different tariff structures," Renewable Energy, Elsevier, vol. 129(PA), pages 513-526.
    21. Schram, Wouter L. & Lampropoulos, Ioannis & van Sark, Wilfried G.J.H.M., 2018. "Photovoltaic systems coupled with batteries that are optimally sized for household self-consumption: Assessment of peak shaving potential," Applied Energy, Elsevier, vol. 223(C), pages 69-81.
    22. Fan, Cheng & Sun, Yongjun & Zhao, Yang & Song, Mengjie & Wang, Jiayuan, 2019. "Deep learning-based feature engineering methods for improved building energy prediction," Applied Energy, Elsevier, vol. 240(C), pages 35-45.
    23. Hua, Haochen & Qin, Yuchao & Hao, Chuantong & Cao, Junwei, 2019. "Optimal energy management strategies for energy Internet via deep reinforcement learning approach," Applied Energy, Elsevier, vol. 239(C), pages 598-609.
    24. Angenendt, Georg & Zurmühlen, Sebastian & Axelsen, Hendrik & Sauer, Dirk Uwe, 2018. "Comparison of different operation strategies for PV battery home storage systems including forecast-based operation strategies," Applied Energy, Elsevier, vol. 229(C), pages 884-899.
    25. Zhang, Yijie & Ma, Tao & Elia Campana, Pietro & Yamaguchi, Yohei & Dai, Yanjun, 2020. "A techno-economic sizing method for grid-connected household photovoltaic battery systems," Applied Energy, Elsevier, vol. 269(C).
    26. Sani Hassan, Abubakar & Cipcigan, Liana & Jenkins, Nick, 2017. "Optimal battery storage operation for PV systems with tariff incentives," Applied Energy, Elsevier, vol. 203(C), pages 422-441.
    27. Ma, Tao & Yang, Hongxing & Lu, Lin, 2015. "Development of hybrid battery–supercapacitor energy storage for remote area renewable energy systems," Applied Energy, Elsevier, vol. 153(C), pages 56-62.
    28. Vijay, Avinash & Hawkes, Adam, 2019. "Demand side flexibility from residential heating to absorb surplus renewables in low carbon futures," Renewable Energy, Elsevier, vol. 138(C), pages 598-609.
    29. Javed, Muhammad Shahzad & Ma, Tao & Jurasz, Jakub & Mikulik, Jerzy, 2021. "A hybrid method for scenario-based techno-economic-environmental analysis of off-grid renewable energy systems," Renewable and Sustainable Energy Reviews, Elsevier, vol. 139(C).
    30. Zou, Bin & Peng, Jinqing & Li, Sihui & Li, Yi & Yan, Jinyue & Yang, Hongxing, 2022. "Comparative study of the dynamic programming-based and rule-based operation strategies for grid-connected PV-battery systems of office buildings," Applied Energy, Elsevier, vol. 305(C).
    31. Olaszi, Balint D. & Ladanyi, Jozsef, 2017. "Comparison of different discharge strategies of grid-connected residential PV systems with energy storage in perspective of optimal battery energy storage system sizing," Renewable and Sustainable Energy Reviews, Elsevier, vol. 75(C), pages 710-718.
    32. Bertsch, Valentin & Geldermann, Jutta & Lühn, Tobias, 2017. "What drives the profitability of household PV investments, self-consumption and self-sufficiency?," Applied Energy, Elsevier, vol. 204(C), pages 1-15.
    33. Zhang, Hao & Cai, Jie & Fang, Kan & Zhao, Fu & Sutherland, John W., 2017. "Operational optimization of a grid-connected factory with onsite photovoltaic and battery storage systems," Applied Energy, Elsevier, vol. 205(C), pages 1538-1547.
    34. Liu, Jia & Chen, Xi & Yang, Hongxing & Shan, Kui, 2021. "Hybrid renewable energy applications in zero-energy buildings and communities integrating battery and hydrogen vehicle storage," Applied Energy, Elsevier, vol. 290(C).
    35. Liu, Jia & Chen, Xi & Yang, Hongxing & Li, Yutong, 2020. "Energy storage and management system design optimization for a photovoltaic integrated low-energy building," Energy, Elsevier, vol. 190(C).
    36. Pillot, Benjamin & de Siqueira, Sandro & Dias, João Batista, 2018. "Grid parity analysis of distributed PV generation using Monte Carlo approach: The Brazilian case," Renewable Energy, Elsevier, vol. 127(C), pages 974-988.
    37. Koskela, Juha & Rautiainen, Antti & Järventausta, Pertti, 2019. "Using electrical energy storage in residential buildings – Sizing of battery and photovoltaic panels based on electricity cost optimization," Applied Energy, Elsevier, vol. 239(C), pages 1175-1189.
    38. Javed, Muhammad Shahzad & Song, Aotian & Ma, Tao, 2019. "Techno-economic assessment of a stand-alone hybrid solar-wind-battery system for a remote island using genetic algorithm," Energy, Elsevier, vol. 176(C), pages 704-717.
    39. Li, Yanxue & Gao, Weijun & Ruan, Yingjun, 2018. "Performance investigation of grid-connected residential PV-battery system focusing on enhancing self-consumption and peak shaving in Kyushu, Japan," Renewable Energy, Elsevier, vol. 127(C), pages 514-523.
    40. Terlouw, Tom & AlSkaif, Tarek & Bauer, Christian & van Sark, Wilfried, 2019. "Multi-objective optimization of energy arbitrage in community energy storage systems using different battery technologies," Applied Energy, Elsevier, vol. 239(C), pages 356-372.
    41. Linssen, Jochen & Stenzel, Peter & Fleer, Johannes, 2017. "Techno-economic analysis of photovoltaic battery systems and the influence of different consumer load profiles," Applied Energy, Elsevier, vol. 185(P2), pages 2019-2025.
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