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A stochastic cloud-driven clustering sizing method for a hybrid photovoltaic/battery energy system integrated with electric bus charge station: A case study for China

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  • Lin, Yaoting
  • Zhou, Wei

Abstract

This paper presented a fuzzy multi-objective, cloud-clustering stochastic approach for the optimal sizing of a hybrid photovoltaic, battery storage, and electric bus charging station system that supplies a commercial load in Yangjiang region, China. The proposed multi-objective formulation jointly minimizes project life-span cost and energy supply inadequacy probability and maximizes a socio-technical indicator. In this regard, a multi-objective Improved Newton-Raphson-Based Optimizer was proposed which was driven by Logistic Map chaotic sequence to overcome its premature convergence drawbacks. Three uncertainties involving irradiance, temperature, and load have been considered and modeled using an enhanced Cloud Model which is K-means scenario clustering balanced between representativeness and computational efforts. Three cases were evaluated: Case I (deterministic PV/BESS), Case II (deterministic PV/BESS/EBCS), and Case III representing stochastic PV/BESS/EBCS with the novel CLCSA. This work shows that the incorporation of EBCS improves the techno-economic performance and equity, for example, reducing the cost by 4.78 % and ESIP by 5.22 % and increasing HDI by 2.21 %, while considering the uncertainty can expose more realistic trade-offs, for example, cost increases moderately by 7.36 %, reliability reduces by 11.05 %, and HDI by 3.07 %. CLCSA achieved similar reliability when compared with MCS and scenario-reduced MCS with higher accuracy at remarkably lower runtime. MOINRBO significantly outperformed MONRBO, MOPSO, and MOAOA on Pareto quality metrics such as hypervolume and spacing, confirming its effectiveness. These results confirmed that PV/BESS systems, if integrated with EBCS and sized under the novel CLCSA, offer a practical and scalable pathway to robust planning while considering real-world variability.

Suggested Citation

  • Lin, Yaoting & Zhou, Wei, 2026. "A stochastic cloud-driven clustering sizing method for a hybrid photovoltaic/battery energy system integrated with electric bus charge station: A case study for China," Energy, Elsevier, vol. 342(C).
    • Handle: RePEc:eee:energy:v:342:y:2026:i:c:s036054422505337x
    DOI: 10.1016/j.energy.2025.139695
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    1. Rathod, Asmita Ajay & S., Balaji, 2024. "Optimization of stand-alone hybrid renewable energy system based on techno-socio-enviro-financial perspective using improved red-tailed hawk algorithm," Applied Energy, Elsevier, vol. 376(PA).
    2. Alghamdi, Ali S., 2024. "Optimizing energy costs and reliability: A multi-objective framework with learning-enhanced manta ray foraging for hybrid PV/battery systems," Energy, Elsevier, vol. 291(C).
    3. Lin, Xing-Min & Kireeva, Natalia & Timoshin, A.V. & Naderipour, Amirreza & Abdul-Malek, Zulkurnain & Kamyab, Hesam, 2021. "A multi-criteria framework for designing of stand-alone and grid-connected photovoltaic, wind, battery clean energy system considering reliability and economic assessment," Energy, Elsevier, vol. 224(C).
    4. Adoum Abdoulaye, Mahamat & Waita, Sebastian & Wabuge Wekesa, Cyrus & Mwabora, Julius Mwakondo, 2024. "Optimal sizing of an off-grid and grid-connected hybrid photovoltaic-wind system with battery and fuel cell storage system: A techno-economic, environmental, and social assessment," Applied Energy, Elsevier, vol. 365(C).
    5. Davoudkhani, Iraj Faraji & Dejamkhooy, Abdolmajid & Nowdeh, Saber Arabi, 2023. "A novel cloud-based framework for optimal design of stand-alone hybrid renewable energy system considering uncertainty and battery aging," Applied Energy, Elsevier, vol. 344(C).
    6. Duan, Fude & Bu, Xiongzhu, 2025. "A new cloud-stochastic framework for optimized deployment of hydrogen storage in distribution network integrated with renewable energy considering hydrogen-based demand response," Energy, Elsevier, vol. 316(C).
    7. Hu, Song & Yang, Hao & Ding, Shunliang & Tian, Zeke & Guo, Bin & Chen, Huabin & Yang, Fuyuan & Xu, Nianfeng, 2025. "Model simulation and multi-objective capacity optimization of wind power coupled hybrid energy storage system," Energy, Elsevier, vol. 319(C).
    8. Yang, Chengying & Zhao, Yao & Li, Xuetao & Zhou, Xiao, 2025. "Electric vehicles, load response, and renewable energy synergy: A new stochastic model for innovation strategies in green energy systems," Renewable Energy, Elsevier, vol. 238(C).
    9. Nihuan Liao & Zhihong Hu & Vedran Mrzljak & Saber Arabi Nowdeh, 2024. "Stochastic Techno-Economic Optimization of Hybrid Energy System with Photovoltaic, Wind, and Hydrokinetic Resources Integrated with Electric and Thermal Storage Using Improved Fire Hawk Optimization," Sustainability, MDPI, vol. 16(16), pages 1-30, August.
    10. Liu, Bingchun & Huo, Xiankai, 2024. "Prediction of Photovoltaic power generation and analyzing of carbon emission reduction capacity in China," Renewable Energy, Elsevier, vol. 222(C).
    11. Wang, Xiaoyang & Sun, Yunlin & Luo, Duo & Peng, Jinqing, 2022. "Comparative study of machine learning approaches for predicting short-term photovoltaic power output based on weather type classification," Energy, Elsevier, vol. 240(C).
    12. Parrado, Cristóbal & Fontalvo, Armando & Ordóñez, Javier & Girard, Aymeric, 2025. "Optimizing dispatch strategies for CSP plants: A Monte Carlo simulation approach to maximize annual revenue in Chile’s renewable energy sector," Energy, Elsevier, vol. 317(C).
    13. Li, Yingjie & Liu, Fang & Chen, Ke & Liu, Yinghui, 2024. "Technical and economic analysis of a hybrid PV/wind energy system for hydrogen refueling stations," Energy, Elsevier, vol. 303(C).
    14. Araoye, Timothy Oluwaseun & Ashigwuike, Evans Chinemezu & Mbunwe, Muncho Josephine & Bakinson, Oladipupo Idris & Ozue, ThankGod Izuchukwu, 2024. "Techno-economic modeling and optimal sizing of autonomous hybrid microgrid renewable energy system for rural electrification sustainability using HOMER and grasshopper optimization algorithm," Renewable Energy, Elsevier, vol. 229(C).
    15. Bayrak, Gökay & Başaran, Kıvanç & Lazaroiu, Alexandra Catalina, 2025. "Integrating hydrogen-powered fuel cell electric buses into grid-forming microgrids: A solution for emergency energy needs," Renewable Energy, Elsevier, vol. 250(C).
    16. Naderipour, Amirreza & Ramtin, Amir Reza & Abdullah, Aldrin & Marzbali, Massoomeh Hedayati & Nowdeh, Saber Arabi & Kamyab, Hesam, 2022. "Hybrid energy system optimization with battery storage for remote area application considering loss of energy probability and economic analysis," Energy, Elsevier, vol. 239(PD).
    17. Wang, Jinjun & Wang, Xinyu & Chen, Heng & Gao, Yue & Chen, Honggang & Liu, Wenyi & Sun, Ying & Zhang, Lei, 2025. "Capacity configuration of a hybrid energy storage system for the fluctuation mitigation and frequency regulation of wind power based on Aquila Optimizer and Variational Mode Decomposition," Energy, Elsevier, vol. 330(C).
    18. El-Sattar, Hoda Abd & Hassan, Mohamed H. & Vera, David & Jurado, Francisco & Kamel, Salah, 2024. "Maximizing hybrid microgrid system performance: A comparative analysis and optimization using a gradient pelican algorithm," Renewable Energy, Elsevier, vol. 227(C).
    19. Yao, Huizong & Zang, Chuanfu, 2021. "The spatiotemporal characteristics of electrical energy supply-demand and the green economy outlook of Guangdong Province, China," Energy, Elsevier, vol. 214(C).
    20. Abdoos, Ali Akbar & Abdoos, Hatef & Kazemitabar, Javad & Mobashsher, Mohammad Mehdi & Khaloo, Hooman, 2023. "An intelligent hybrid method based on Monte Carlo simulation for short-term probabilistic wind power prediction," Energy, Elsevier, vol. 278(PA).
    21. Dufo-López, Rodolfo & Cristóbal-Monreal, Iván R. & Yusta, José M., 2016. "Optimisation of PV-wind-diesel-battery stand-alone systems to minimise cost and maximise human development index and job creation," Renewable Energy, Elsevier, vol. 94(C), pages 280-293.
    22. Naderipour, Amirreza & Kamyab, Hesam & Klemeš, Jiří Jaromír & Ebrahimi, Reza & Chelliapan, Shreeshivadasan & Nowdeh, Saber Arabi & Abdullah, Aldrin & Hedayati Marzbali, Massoomeh, 2022. "Optimal design of hybrid grid-connected photovoltaic/wind/battery sustainable energy system improving reliability, cost and emission," Energy, Elsevier, vol. 257(C).
    23. Li, Xiaoyuan & Tian, Zhe & Wu, Xia & Feng, Wei & Niu, Jide, 2024. "Optimal planning for hybrid renewable energy systems under limited information based on uncertainty quantification," Renewable Energy, Elsevier, vol. 237(PD).
    24. Duan, Fude & Bu, Xiongzhu, 2024. "Stochastic optimization of a hybrid photovoltaic/fuel cell/parking lot system incorporating cloud model," Renewable Energy, Elsevier, vol. 237(PC).
    25. Abu, Sayem M. & Hannan, M.A. & Rahman, S.A. & Ker, Pin Jern & Long, Chua Yaw, 2025. "Optimization algorithms for hybrid energy storage systems based microgrid performance enhancement," Energy, Elsevier, vol. 332(C).
    26. Dong, Xiao-Jian & Shen, Jia-Ni & Ma, Zi-Feng & He, Yi-Jun, 2025. "Stochastic optimization of integrated electric vehicle charging stations under photovoltaic uncertainty and battery power constraints," Energy, Elsevier, vol. 314(C).
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