雾霾条件下光伏发电量预测的迭代优化与经济性分析

doi:10.11930/j.issn.1004-9649.202010098

中国电力 ›› 2021, Vol. 54 ›› Issue (10): 223-230.DOI: 10.11930/j.issn.1004-9649.202010098

• 新能源 • 上一篇

雾霾条件下光伏发电量预测的迭代优化与经济性分析

陈炜, 任静, 武新芳, 于文英, 刘永生

上海电力大学太阳能研究所，上海 200090

收稿日期:2020-10-26 修回日期:2021-08-26 出版日期:2021-10-05 发布日期:2021-10-16
作者简介:陈炜(1994-),男,硕士研究生,从事太阳能电池及光伏系统研究,E-mail:156226453@qq.com;刘永生(1974-),男,通信作者,教授,博士生导师,从事太阳能电池及光伏系统研究,E-mail:ysliu@shiep.edu.cn
基金资助:
国家自然科学基金资助项目(51971128)；上海市优秀学术/技术带头人计划(20XD1401800)；上海市科委项目(19020501000)

Iterative Optimization and Economic Analysis of Photovoltaic Power Generation Forecasting under Haze Conditions

CHEN Wei, REN Jing, WU Xinfang, YU Wenying, LIU Yongsheng

Institute of Solar Energy, Shanghai University of Electric Power, Shanghai 200090, China

Received:2020-10-26 Revised:2021-08-26 Online:2021-10-05 Published:2021-10-16
Supported by:
This work is supported by the National Natural Science Foundation of China (No. 51971128); Program of Shanghai Academic/Technology Research Leader (No.20XD1401800); Science and Technology Commission of Shanghai Municipality (No.19020501000)

摘要/Abstract

摘要： 光伏发电易受温度、辐照度等环境因素的影响，而近年来雾霾（PM_2.5浓度较高）污染严重，大幅降低了光伏系统发电量。因此研究雾霾天气下光伏发电量预测方法对光伏市场的发展具有重要意义。通过采集上海某户用光伏屋顶的全年光伏数据，利用控制变量法及雾霾相似日原理，拟合分析PM_2.5的浓度与发电量损失指数之间的关系，通过迭代原理优化光伏发电量预测算法，并给出雾霾环境下光伏发电量预测公式，修正光伏收益预测模型。结果表明：优化后的光伏预测发电量算法可提高发电量预测结果的精确性和稳定性。通过对3种光伏经济模型进行收益分析，验证了迭代优化算法可有效提高光伏收益预测的精确性。

关键词: 空气污染, 雾霾, PM_2.5, 光伏发电量预测, 迭代优化, 光伏收益预测, 光伏系统设计

Abstract: Photovoltaic power generation is vulnerable to environmental factors such as temperature and irradiance. In recent years, haze (with high concentration of PM_2.5) has caused serious pollution, greatly reducing the power generation of the photovoltaic system. Therefore, it is of great significance for the photovoltaic market to predict the photovoltaic power generation in the haze weather. In this paper, based on the annual photovoltaic data of a household photovoltaic roof in Shanghai, the relationship between the PM_2.5 concentration and the power generation loss index is fitted and analyzed with controlled variables and the similar days for haze analysis. According to the principle of iteration, the algorithm for photovoltaic power generation prediction is optimized, and the formula for photovoltaic power generation prediction under haze is given to modify the photovoltaic revenue prediction model. The results show that the optimized algorithm can improve the accuracy and stability of the prediction results. Through the revenue analysis of three photovoltaic economic models, the iterative optimization algorithm can improve the accuracy of photovoltaic revenue forecast.

Key words: air pollution, haze, PM_2.5, photovoltaic power generation prediction, iterative optimization, photovoltaic revenue forecast, photovoltaic system design

陈炜, 任静, 武新芳, 于文英, 刘永生. 雾霾条件下光伏发电量预测的迭代优化与经济性分析[J]. 中国电力, 2021, 54(10): 223-230.

CHEN Wei, REN Jing, WU Xinfang, YU Wenying, LIU Yongsheng. Iterative Optimization and Economic Analysis of Photovoltaic Power Generation Forecasting under Haze Conditions[J]. Electric Power, 2021, 54(10): 223-230.

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https://www.electricpower.com.cn/CN/Y2021/V54/I10/223

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雾霾条件下光伏发电量预测的迭代优化与经济性分析

Iterative Optimization and Economic Analysis of Photovoltaic Power Generation Forecasting under Haze Conditions

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雾霾条件下光伏发电量预测的迭代优化与经济性分析

Iterative Optimization and Economic Analysis of Photovoltaic Power Generation Forecasting under Haze Conditions

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