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

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  • 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
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    References listed on IDEAS

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    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)

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