Building a prediction model of solar power generation based on improved Grey Markov Chain

被引：0
|
作者：
Cui, Chongyu [1 ]
Li, Zhaoxia [1 ]
Zhang, Junjie [2 ]
机构：
[1] Tibet Agr & Anim Husb Univ, Nyingchi 86000, Tibet, Peoples R China
[2] State Grid Tibet Elect Power Co Ltd, Elect Power Res Inst, Xizang, Tibet, Peoples R China
来源：
INTERNATIONAL JOURNAL OF GLOBAL ENERGY ISSUES | 2022年 / 44卷 / 2-3期
关键词：
grey Markov chain; solar energy; electricity generation; prediction; charge volatility; power grid; INFEED HVDC; VSC; PARAMETERS; SYSTEMS;
D O I：
10.1504/IJGEI.2022.121396
中图分类号：
X [环境科学、安全科学];
学科分类号：
08 ; 0830 ;
摘要：
In order to improve the prediction ability and reliability management ability of solar power generation, a solar power generation prediction model based on Improved Grey Markov chain is proposed. The constrained parameter model of solar power generation prediction is established, and the disturbance characteristics of solar power generation are analysed. On this basis, the improved grey Markov chain model is applied to the big data fusion analysis of solar power generation, and the reliability prediction of solar power generation is realised. The results show that the prediction accuracy of this method is high, up to 1, which improves the quality and stability of output power, and has certain application value.
引用
收藏
页码：139 / 149
页数：11
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