Forecasting power generation of solar photovoltaic system based on the combination of grey model and weighted Markov chain

被引：0
|
作者：
Jiang F. [1 ]
Wang Z. [2 ]
Zhang P. [3 ]
机构：
[1] School of Electrical Engineering and Automation, Hefei University of Technology, Hefei
[2] Nanchang Institute of Technology, Nanchang
[3] Feidong Electric Power Company, State Grid Anhui Electric Power Co., Ltd., Hefei
来源：
Dianli Xitong Baohu yu Kongzhi/Power System Protection and Control | 2019年 / 47卷 / 15期
基金：
中国国家自然科学基金;
关键词：
Grey model; Photovoltaic system; Power generation; State transfer probability matrix; Weighted Markov Chain;
D O I：
10.19783/j.cnki.pspc.180634
中图分类号：
学科分类号：
摘要：
One fundamental work of grid-connected photovoltaic (PV) system is to estimate its power generation. This paper introduces weighted Markov Chain estimation theory to build a grey-weighted Markov Chain estimation model after forecasting the overall generation trend of PV by applying the grey model. This model not only takes the advantage of GM(1,1) model when dealing with exponential series into account, but also considers the feature of fluctuation in power generation, which is described by state transfer probability matrix of relative residuals. After applying the model to forecast the generation of one PV power station in Hefei, the results indicate that the combination of grey model and weighted Markov Chain improves the precision when coping with generation data with greater fluctuation, verifying the feasibility and effectiveness of this model. © 2019, Power System Protection and Control Press. All right reserved.
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收藏
页码：55 / 60
页数：5
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