IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v14y2022i21p13880-d953200.html

A New Regional Distributed Photovoltaic Power Calculation Method Based on FCM-mRMR and nELM Model

Author

Listed:
  • Honglu Zhu

    (State Key Laboratory of Alternate Electrical Power System with Renewable Energy Sources, North China Electric Power University, Beijing 102206, China
    School of New Energy, North China Electric Power University, Beijing 102206, China)

  • Tingting Jiang

    (State Key Laboratory of Alternate Electrical Power System with Renewable Energy Sources, North China Electric Power University, Beijing 102206, China
    School of New Energy, North China Electric Power University, Beijing 102206, China)

  • Yahui Sun

    (State Key Laboratory of Alternate Electrical Power System with Renewable Energy Sources, North China Electric Power University, Beijing 102206, China
    School of New Energy, North China Electric Power University, Beijing 102206, China)

  • Shuang Sun

    (State Key Laboratory of Alternate Electrical Power System with Renewable Energy Sources, North China Electric Power University, Beijing 102206, China
    School of New Energy, North China Electric Power University, Beijing 102206, China)

Abstract

As the proportion of distributed photovoltaic (DP) increases, improving the accuracy of regional distributed photovoltaic power calculation is crucial to making full use of PV and ensuring the safety of the power system. The calculation of regional power generation is the key to power prediction, performance evaluation, and fault diagnosis. Distributed photovoltaic plants (DPP) are characterized by scattered distribution and small installed capacity, lots of DPPs are not fully monitored, and their real-time output power is difficult to obtain. Therefore, to improve the observability of DPPs and increase the accuracy of calculation, a new method that combines with fuzzy c-means (FCM), Max-Relevance and Min-Redundancy (mRMR) and Extreme Learning Machine(ELM), which can calculate the regional DPP output power without meteorological data is proposed, and validated using actual operational data of regional DPPs in China. The calculations results show good robustness in different months. The innovation of this study is the combination of the benchmark DPP selection method FCM-mRMR and the power calculation method nELM, and the mean absolute error (MAPE) of the proposed method is 0.198 and the coefficient of determination (R2) is 0.996.

Suggested Citation

  • Honglu Zhu & Tingting Jiang & Yahui Sun & Shuang Sun, 2022. "A New Regional Distributed Photovoltaic Power Calculation Method Based on FCM-mRMR and nELM Model," Sustainability, MDPI, vol. 14(21), pages 1-20, October.
    • Handle: RePEc:gam:jsusta:v:14:y:2022:i:21:p:13880-:d:953200
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/14/21/13880/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2071-1050/14/21/13880/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Stainsby, Wendell & Zimmerle, Daniel & Duggan, Gerald P., 2020. "A method to estimate residential PV generation from net-metered load data and system install date," Applied Energy, Elsevier, vol. 267(C).
    2. Siyuan Fan & Shengxian Cao & Yanhui Zhang, 2020. "Temperature Prediction of Photovoltaic Panels Based on Support Vector Machine with Pigeon-Inspired Optimization," Complexity, Hindawi, vol. 2020, pages 1-12, December.
    3. Assouline, Dan & Mohajeri, Nahid & Scartezzini, Jean-Louis, 2018. "Large-scale rooftop solar photovoltaic technical potential estimation using Random Forests," Applied Energy, Elsevier, vol. 217(C), pages 189-211.
    4. Niknam, Taher & Firouzi, Bahman Bahmani, 2009. "A practical algorithm for distribution state estimation including renewable energy sources," Renewable Energy, Elsevier, vol. 34(11), pages 2309-2316.
    5. Muhammed Y. Worku, 2022. "Recent Advances in Energy Storage Systems for Renewable Source Grid Integration: A Comprehensive Review," Sustainability, MDPI, vol. 14(10), pages 1-18, May.
    6. Rahim Zahedi & Alireza Zahedi & Abolfazl Ahmadi, 2022. "Strategic Study for Renewable Energy Policy, Optimizations and Sustainability in Iran," Sustainability, MDPI, vol. 14(4), pages 1-29, February.
    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. Bangjian Wang & Lihua Xu & Tianze Chen & Bowen Hou & Jianxun Liu & Yijun Shen & Rao Kuang, 2024. "High-Temperature Mechanical Properties of Basalt Fibers: A Step Towards Fire-Safe Materials for Photovoltaic Applications," Sustainability, MDPI, vol. 16(24), pages 1-13, December.
    2. Gao, Meng & Feng, Yidan & Ni, Pingan & Zheng, Hanjie & Sun, Hongli & Zhang, Yongwang & Qin, Guojin & He, Bao-Jie, 2026. "Solar energy potential evaluation of multi-scale urban building surfaces under complex shading: A multi-dimensional analysis," Renewable Energy, Elsevier, vol. 259(C).
    3. Raihan, Asif & Hasnat, Md Al & Rahman, Syed Masiur & Ridwan, Mohammad & Rahman, Md Masudur & Islam, Md Tasbirul & Sarker, Tapan & Dhar, Bablu Kumar & Bari, ABM Mainul, 2025. "Recent advancements in alternative energies, technological innovations, and optimization strategies for seaport decarbonization," Innovation and Green Development, Elsevier, vol. 4(3).
    4. Moghadam, Saman Salehi & Gholamian, Mohammad Reza & Zahedi, Rahim & Shaqaqifar, Maziar, 2024. "Designing a multi-purpose network of sustainable and closed-loop renewable energy supply chain, considering reliability and circular economy," Applied Energy, Elsevier, vol. 369(C).
    5. Khan, Waqas & Walker, Shalika & Zeiler, Wim, 2022. "Improved solar photovoltaic energy generation forecast using deep learning-based ensemble stacking approach," Energy, Elsevier, vol. 240(C).
    6. Surafel Kifle Teklemariam & Rachele Schiasselloni & Luca Cattani & Fabio Bozzoli, 2025. "Solar Energy Solutions for Healthcare in Rural Areas of Developing Countries: Technologies, Challenges, and Opportunities," Energies, MDPI, vol. 18(15), pages 1-22, July.
    7. Ricardo Raineri, 2025. "Power Shift: Decarbonization and the New Dynamics of Energy Markets," Energies, MDPI, vol. 18(3), pages 1-52, February.
    8. Yong Zeng & Yanpeng Cai & Guohe Huang & Jing Dai, 2011. "A Review on Optimization Modeling of Energy Systems Planning and GHG Emission Mitigation under Uncertainty," Energies, MDPI, vol. 4(10), pages 1-33, October.
    9. Mortazi, Mohammad & Moradi, Ahmad & Khosravi, Mohsen, 2020. "Simultaneous optimization of transformer tap changer and network capacitors to improve the distribution system’s static security considering distributed generation sources," MPRA Paper 109052, University Library of Munich, Germany, revised 01 Jul 2020.
    10. Chen, Hong-Ju & Yang, Min & Wang, Jian-Qiang & He, QingShan & Wei, TianFeng, 2025. "The role of roadside solar photovoltaic systems in achieving global carbon neutrality: Assessing capacity, economic feasibility, and carbon reduction potential," Energy, Elsevier, vol. 339(C).
    11. Amjad Almusaed & Ibrahim Yitmen & Asaad Almssad, 2023. "Reviewing and Integrating AEC Practices into Industry 6.0: Strategies for Smart and Sustainable Future-Built Environments," Sustainability, MDPI, vol. 15(18), pages 1-27, September.
    12. Lonergan, Katherine Emma & Sansavini, Giovanni, 2022. "Business structure of electricity distribution system operator and effect on solar photovoltaic uptake: An empirical case study for Switzerland," Energy Policy, Elsevier, vol. 160(C).
    13. Hui Zhang & Xiaoxi Huang & Zhengwei Wang & Shiyu Jin & Benlin Xiao & Yanyan Huang & Wei Zhong & Aofei Meng, 2024. "An Estimation of the Available Spatial Intensity of Solar Energy in Urban Blocks in Wuhan, China," Energies, MDPI, vol. 17(5), pages 1-26, February.
    14. Hou, Xinyuan & Papachristopoulou, Kyriakoula & Saint-Drenan, Yves-Marie & Kosmopoulos, Panagiotis G. & Psiloglou, Basil E. & Kazadzis, Stelios, 2025. "Effects of clouds, aerosols and shadows on solar energy potential on urban rooftops using earth observation data and digital surface models," Applied Energy, Elsevier, vol. 397(C).
    15. Yu, Zhe & Chen, Cuiying & Lou, Duo & Jiang, Jingjing & Ye, Bin, 2025. "Energy-economy-environment evaluation of building-integrated photovoltaic considering facade factors for representative megacities in China," Applied Energy, Elsevier, vol. 389(C).
    16. Hanshan Qing & Abhinav Kumar Singh & Efstratios Batzelis, 2025. "Review on Distribution System State Estimation Considering Renewable Energy Sources," Energies, MDPI, vol. 18(10), pages 1-20, May.
    17. Sharma, Naveen & Varun, & Siddhartha,, 2012. "Stochastic techniques used for optimization in solar systems: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 16(3), pages 1399-1411.
    18. Mohajeri, Nahid & Perera, A.T.D. & Coccolo, Silvia & Mosca, Lucas & Le Guen, Morgane & Scartezzini, Jean-Louis, 2019. "Integrating urban form and distributed energy systems: Assessment of sustainable development scenarios for a Swiss village to 2050," Renewable Energy, Elsevier, vol. 143(C), pages 810-826.
    19. Mohamed Sami Ben Ali & Alanoud Al‐Maadid & Brahim Bergougui, 2026. "Climate Change and Energy Security Risk: Do Green Patents, Institutional Quality, and Human Capital Make a Difference?," Sustainable Development, John Wiley & Sons, Ltd., vol. 34(1), pages 165-189, February.
    20. Liu, Jiang & Wu, Qifeng & Lin, Zhipeng & Shi, Huijie & Wen, Shaoyang & Wu, Qiaoyu & Zhang, Junxue & Peng, Changhai, 2023. "A novel approach for assessing rooftop-and-facade solar photovoltaic potential in rural areas using three-dimensional (3D) building models constructed with GIS," Energy, Elsevier, vol. 282(C).

    More about this item

    Keywords

    ;
    ;
    ;
    ;

    Statistics

    Access and download statistics

    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:gam:jsusta:v:14:y:2022:i:21:p:13880-:d:953200. 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: MDPI Indexing Manager The email address of this maintainer does not seem to be valid anymore. Please ask MDPI Indexing Manager to update the entry or send us the correct address (email available below). General contact details of provider: https://www.mdpi.com .

    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.