Research on Short-term Load Prediction Including the Photovoltaic System

被引:1
|
作者
Lei, Yang [1 ]
Zhou, Shiping [2 ]
Xia, Yongjun [1 ]
Hu, Gang [1 ]
Shu, Xin [1 ]
机构
[1] State Grid Hubei Elect Power Res Inst, Xudong Rd 227, Wuhan, Peoples R China
[2] State Grid Hubei Elect Power Co, Wuhan, Peoples R China
来源
ENERGY DEVELOPMENT, PTS 1-4 | 2014年 / 860-863卷
关键词
photovoltaic power generation; power system load; prediction; quantum particle swarm optimization; generalized system load; MODULE;
D O I
10.4028/www.scientific.net/AMR.860-863.135
中图分类号
TE [石油、天然气工业]; TK [能源与动力工程];
学科分类号
0807 ; 0820 ;
摘要
The global energy issues have become increasingly prominent in recent years, photovoltaic power generation as a renewable energy use pattern is widely used, but a large number of photovoltaic power generation to the grid is a big negative impact, it is necessary to predict the output power of the photovoltaic. Power system load forecasting is the reference and safeguard of the power system operation. This article analyzes the main point of the prediction of photovoltaic power system and power load system, then introduces the support vector machine(SVM) based on quantum particle swarm optimization(QPSO) to do the prediction. And then this paper proposes a generalized system load prediction system containing the photovoltaic power system.
引用
收藏
页码:135 / +
页数:2
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