Wind Power Probability Prediction Based on t Location-Scale Distrabution

doi:10.11930/j.issn.1004-9649.2017.01.140.06

Electric Power ›› 2017, Vol. 50 ›› Issue (1): 140-145.DOI: 10.11930/j.issn.1004-9649.2017.01.140.06

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Wind Power Probability Prediction Based on t Location-Scale Distrabution

YANG Mao, DU Gang

College of Electrical Engineering, Northeast Dianli University, Jilin 132012, China

Received:2016-10-20 Online:2017-01-20 Published:2017-01-23
Supported by:
This work is supported by the National Major Basic Research Program (973 Program) (No. 2013CB228201)the National Natural Science Foundation of China(No. 51307017)the Scientific, Technological Planning Project of Jilin Province(No. 20140520129JH)The “12th Five-Year Plan”Scientific and Technological Research Project for Education Department of Jilin Province (Ji Jiao Ke He Zi[2014] No. 474)Industrial Technology Research and Development for Special Project of Jilin Province (No. 2014Y124).

Abstract

Abstract: Wind power forecasting is difficult because of its stochastic variance characteristic. Based on t location-scale distribution function, a wind power forecasting method is proposed. The t location-scale function is adopted to describe probabilistic distribution of wind power prediction error. The prediction is then performed based on the distribution model. The coverage rate and average bandwidth are selected to evaluate prediction accuracy. The historic data of power fluctuation of a wind farm in Jinlin province proves the effectiveness of proposed method.

Key words: wind electricity, wind power, wind abandoning, wind power integration, wind power prediction

CLC Number:

TM615

YANG Mao, DU Gang. Wind Power Probability Prediction Based on t Location-Scale Distrabution[J]. Electric Power, 2017, 50(1): 140-145.

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Wind Power Probability Prediction Based on t Location-Scale Distrabution

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