Journal of Shandong University(Engineering Science) ›› 2021, Vol. 51 ›› Issue (4): 118-123.doi: 10.6040/j.issn.1672-3961.0.2020.431

Previous Articles    

Correction method for historical output data of photovoltaic power plant considering spatial correlation based on artificial neural network

YIN Xiaomin1, MENG Xiangjian2, HOU Kunming1, CHEN Yaxiao1, GAO Feng2*   

  1. 1. State Grid Liaocheng Power Supply Company, Liaocheng 252000, Shandong, China;
    2. School of Control Science and Engineering, Shandong University, Jinan 250061, Shandong, China
  • Published:2021-08-18

Abstract: The increase of photovoltaic(PV)system penetration rate brought great challenges to the stable operation of power system. Considering that the accuracy of photovoltaic power prediction was highly dependent on data accuracy, this paper proposed a correction method for historical output data of photovoltaic power plant by taking the advantages of strong ability of artificial neural network in mapping complex nonlinear relations. Person correlation coefficient was employed to select reference PV plants for dimensionality reduction. The inaccurate and missing data of photovoltaic power station could be identified and corrected by taking the spatial correlation characteristics of PV output into consideration based on the output power of reference PV plants, which could solve the problem of PV data inaccuracy caused by human factors or data acquisition system aging. The proposed method was analyzed and verified by the historical output data of Liaocheng City in Shandong Prvoince.

Key words: photovoltaic power, dimensionality reduction, power forecasting, artificial neural network, data correction

CLC Number: 

  • TM615
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