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Study on the Method of Enterprise Short-term Load Forecasting Considering Weather and Product Information SCOPUS

Hu Bo, Wang Nan, Di Feng, Song Yundong, Zhang Junyang

보안공학연구지원센터(IJCA) International Journal of Control and Automation Vol.8 No.6 2015.06 pp.307-316

※ 원문제공기관과의 협약기간이 종료되어 열람이 제한될 수 있습니다.

Short-term load forecast plays an important role in the safe and economic operation of power system. Its prediction accuracy affects the power system's security, profit and quality directly. And meteorological factor is one of the key factors that affect the accuracy of load forecasting. In this paper, we put forward enterprise electric load forecasting method combined with grey relational degree algorithm and multivariate linear regression forecasting method. The example shows that this method can get better prediction accuracy.

 
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