IDEAS home Printed from https://ideas.repec.org/a/eee/renene/v240y2025ics0960148124022122.html
   My bibliography  Save this article

Facilitate the design of residential PV using reliability-based design optimization

Author

Listed:
  • Zhao, Zilong
  • Lv, Guoquan
  • Xu, Yanwen

Abstract

For the first time, the sizing optimization on rooftop PV integrates probabilistic uncertainties and reliability analysis. This study proposes a reliability-based design optimization (RBDO) that treats PV installation angle as a design variable and aims to minimize installation area. Constraints were established to regulate the variable range during the optimization process—the overall power generation ratio, self-use power ratio, and increase of back panel temperature. In the meantime, the environmental variables, including the solar irradiance and ambient temperature, as well as the random variables in PV system, such as the nominal efficiency, are considered with their intrinsic uncertainties. Compared to a deterministic optimization where all input variables are treated as exact values that may lead to non-optimal designs under non-idealized conditions, the RBDO algorithm is proved effective in identifying a design that meets performance requirements and even maintains a high probability of confidence under uncertain conditions. By varying the minimum requirements on power ratios, threshold of back panel temperature limit and probability indices by scenarios, the optimal installation angle and the installation area of PV array are obtained. The results indicated that the uncertainty levels accompanied by the three constraint functions impose a significant influence on the sizing of PV array.

Suggested Citation

  • Zhao, Zilong & Lv, Guoquan & Xu, Yanwen, 2025. "Facilitate the design of residential PV using reliability-based design optimization," Renewable Energy, Elsevier, vol. 240(C).
    • Handle: RePEc:eee:renene:v:240:y:2025:i:c:s0960148124022122
    DOI: 10.1016/j.renene.2024.122144
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0960148124022122
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.renene.2024.122144?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Zhao, Zilong & Lv, Guoquan & Xu, Yanwen & Lin, Yu-Feng & Wang, Pingfeng & Wang, Xinlei, 2024. "Enhancing ground source heat pump system design optimization: A stochastic model incorporating transient geological factors and decision variables," Renewable Energy, Elsevier, vol. 225(C).
    2. Huang, Lin & Song, Zihao & Dong, Qichang & Song, Ye & Zhao, Xiaoqing & Qi, Jiacheng & Shi, Long, 2024. "Surface temperature and power generation efficiency of PV arrays with various row spacings: A full-scale outdoor experimental study," Applied Energy, Elsevier, vol. 367(C).
    3. Zhao, Zilong & Lin, Yu-Feng & Stumpf, Andrew & Wang, Xinlei, 2022. "Assessing impacts of groundwater on geothermal heat exchangers: A review of methodology and modeling," Renewable Energy, Elsevier, vol. 190(C), pages 121-147.
    4. Zhi, Yuan & Yang, Xudong, 2023. "Scenario-based multi-objective optimization strategy for rural PV-battery systems," Applied Energy, Elsevier, vol. 345(C).
    5. Sengupta, Manajit & Xie, Yu & Lopez, Anthony & Habte, Aron & Maclaurin, Galen & Shelby, James, 2018. "The National Solar Radiation Data Base (NSRDB)," Renewable and Sustainable Energy Reviews, Elsevier, vol. 89(C), pages 51-60.
    6. Tian, Wei & Heo, Yeonsook & de Wilde, Pieter & Li, Zhanyong & Yan, Da & Park, Cheol Soo & Feng, Xiaohang & Augenbroe, Godfried, 2018. "A review of uncertainty analysis in building energy assessment," Renewable and Sustainable Energy Reviews, Elsevier, vol. 93(C), pages 285-301.
    7. Brown, Patrick R. & Williams, Travis & Brown, Maxwell L. & Murphy, Caitlin, 2024. "System-cost-minimizing deployment of PV-wind hybrids in low-carbon U.S. power systems," Applied Energy, Elsevier, vol. 365(C).
    8. Han, Xuejiao & Garrison, Jared & Hug, Gabriela, 2022. "Techno-economic analysis of PV-battery systems in Switzerland," Renewable and Sustainable Energy Reviews, Elsevier, vol. 158(C).
    9. Notton, G. & Lazarov, V. & Stoyanov, L., 2010. "Optimal sizing of a grid-connected PV system for various PV module technologies and inclinations, inverter efficiency characteristics and locations," Renewable Energy, Elsevier, vol. 35(2), pages 541-554.
    10. Kucuksari, Sadik & Khaleghi, Amirreza M. & Hamidi, Maryam & Zhang, Ye & Szidarovszky, Ferenc & Bayraksan, Guzin & Son, Young-Jun, 2014. "An Integrated GIS, optimization and simulation framework for optimal PV size and location in campus area environments," Applied Energy, Elsevier, vol. 113(C), pages 1601-1613.
    11. 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).
    12. Okoye, Chiemeka Onyeka & Solyalı, Oğuz, 2017. "Optimal sizing of stand-alone photovoltaic systems in residential buildings," Energy, Elsevier, vol. 126(C), pages 573-584.
    13. Leimeister, Mareike & Kolios, Athanasios, 2018. "A review of reliability-based methods for risk analysis and their application in the offshore wind industry," Renewable and Sustainable Energy Reviews, Elsevier, vol. 91(C), pages 1065-1076.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Fu, Xueqian & Chen, Haoyong & Cai, Runqing & Yang, Ping, 2015. "Optimal allocation and adaptive VAR control of PV-DG in distribution networks," Applied Energy, Elsevier, vol. 137(C), pages 173-182.
    2. Guan, Bowen & Yang, Haobo & Zhang, Tao & Liu, Xiaohua & Wang, Xinke, 2024. "Technoeconomic analysis of rooftop PV system in elevated metro station for cost-effective operation and clean electrification," Renewable Energy, Elsevier, vol. 226(C).
    3. Le, Son Tay & Nguyen, Tuan Ngoc & Bui, Dac-Khuong & Ngo, Tuan Duc, 2024. "Techno-economic and life cycle analysis of renewable energy storage systems in buildings: The effect of uncertainty," Energy, Elsevier, vol. 307(C).
    4. Khezri, Rahmat & Mahmoudi, Amin & Aki, Hirohisa, 2022. "Optimal planning of solar photovoltaic and battery storage systems for grid-connected residential sector: Review, challenges and new perspectives," Renewable and Sustainable Energy Reviews, Elsevier, vol. 153(C).
    5. Zou, Bin & Peng, Jinqing & Yin, Rongxin & Li, Houpei & Li, Sihui & Yan, Jinyue & Yang, Hongxing, 2022. "Capacity configuration of distributed photovoltaic and battery system for office buildings considering uncertainties," Applied Energy, Elsevier, vol. 319(C).
    6. Lukač, Niko & Seme, Sebastijan & Žlaus, Danijel & Štumberger, Gorazd & Žalik, Borut, 2014. "Buildings roofs photovoltaic potential assessment based on LiDAR (Light Detection And Ranging) data," Energy, Elsevier, vol. 66(C), pages 598-609.
    7. Neupane, Deependra & Kafle, Sagar & Karki, Kaji Ram & Kim, Dae Hyun & Pradhan, Prajal, 2022. "Solar and wind energy potential assessment at provincial level in Nepal: Geospatial and economic analysis," Renewable Energy, Elsevier, vol. 181(C), pages 278-291.
    8. Emrani-Rahaghi, Pouria & Hashemi-Dezaki, Hamed & Ketabi, Abbas, 2023. "Efficient voltage control of low voltage distribution networks using integrated optimized energy management of networked residential multi-energy microgrids," Applied Energy, Elsevier, vol. 349(C).
    9. Gueymard, Christian A. & Bright, Jamie M. & Lingfors, David & Habte, Aron & Sengupta, Manajit, 2019. "A posteriori clear-sky identification methods in solar irradiance time series: Review and preliminary validation using sky imagers," Renewable and Sustainable Energy Reviews, Elsevier, vol. 109(C), pages 412-427.
    10. Zhou, Yuekuan & Zheng, Siqian, 2020. "Uncertainty study on thermal and energy performances of a deterministic parameters based optimal aerogel glazing system using machine-learning method," Energy, Elsevier, vol. 193(C).
    11. Omoyele, Olalekan & Hoffmann, Maximilian & Koivisto, Matti & Larrañeta, Miguel & Weinand, Jann Michael & Linßen, Jochen & Stolten, Detlef, 2024. "Increasing the resolution of solar and wind time series for energy system modeling: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 189(PB).
    12. Vallianos, Charalampos & Candanedo, José & Athienitis, Andreas, 2023. "Application of a large smart thermostat dataset for model calibration and Model Predictive Control implementation in the residential sector," Energy, Elsevier, vol. 278(PA).
    13. Deirdre O’Donnell & Jimmy Murphy & Vikram Pakrashi, 2020. "Damage Monitoring of a Catenary Moored Spar Platform for Renewable Energy Devices," Energies, MDPI, vol. 13(14), pages 1-22, July.
    14. Hung, Duong Quoc & Mithulananthan, N. & Bansal, R.C., 2014. "An optimal investment planning framework for multiple distributed generation units in industrial distribution systems," Applied Energy, Elsevier, vol. 124(C), pages 62-72.
    15. Bracken, Cameron & Voisin, Nathalie & Burleyson, Casey D. & Campbell, Allison M. & Hou, Z. Jason & Broman, Daniel, 2024. "Standardized benchmark of historical compound wind and solar energy droughts across the Continental United States," Renewable Energy, Elsevier, vol. 220(C).
    16. Craig, Michael & Guerra, Omar J. & Brancucci, Carlo & Pambour, Kwabena Addo & Hodge, Bri-Mathias, 2020. "Valuing intra-day coordination of electric power and natural gas system operations," Energy Policy, Elsevier, vol. 141(C).
    17. Zimmerman, Ryan & Panda, Anurag & Bulović, Vladimir, 2020. "Techno-economic assessment and deployment strategies for vertically-mounted photovoltaic panels," Applied Energy, Elsevier, vol. 276(C).
    18. Wang, H.X. & Muñoz-García, M.A. & Moreda, G.P. & Alonso-García, M.C., 2018. "Optimum inverter sizing of grid-connected photovoltaic systems based on energetic and economic considerations," Renewable Energy, Elsevier, vol. 118(C), pages 709-717.
    19. Zhong, Qing & Tong, Daoqin, 2020. "Spatial layout optimization for solar photovoltaic (PV) panel installation," Renewable Energy, Elsevier, vol. 150(C), pages 1-11.
    20. Rong-Ceng Leou, 2022. "A Substation-Based Optimal Photovoltaic Generation System Placement Considering Multiple Evaluation Indices," Energies, MDPI, vol. 15(15), pages 1-18, August.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:renene:v:240:y:2025:i:c:s0960148124022122. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.journals.elsevier.com/renewable-energy .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.