Research for Short-Term Load Forecasting Based on Linearization Meteorological Factors

Author:

Zhang Shun Hua1

Affiliation:

1. NanChang Institute of Technology

Abstract

With the development of economy in recent years, rapid growth of electricity demand, the cooling and heating load gets more and more big proportion of the total electricity load; the power load is influenced by meteorological factors which become more and more big. This topic will be based on short-term load forecasting in ANN (Artificial Neural Networks), conduct further research on the relationship between meteorological factors and power load, find the impact of the core meteorological factors of power load, and linear core meteorological factor model to establish the suitable for load forecasting based on ANN, make the forecasting to correctly reflect the meteorological conditions, improve the prediction accuracy of short-term load forecasting.

Publisher

Trans Tech Publications, Ltd.

Reference7 articles.

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