Daily Peak Load Forecasting by Structured Representation on Genetic Algorithms for Non-linear Function Fitting

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  • 構造的ＧＡによるＧＭＤＨを用いた翌日最大電力需要予測
  • コウゾウテキ GA ニ ヨル GMDH オ モチイタ ヨクジツ サイダイ デンリョク ジュヨウ ヨソク

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Abstract

Recently, the independent power producers (IPPs) and the distributed power generations (DGs) are increase on by the electric power system with the power system deregulation. And the power system becomes more complicated. It is necessary to carry out the electric power demand forecasting in order to the power system is operated for the high economical and the high-efficient. For the improvement of electric power demand forecasting, many methods, such as the methods using fuzzy theory, neural network and SDP data, are proposed. <br>In this paper, we proposed the method using STROGANOFF (STructured Re-presentation on Genetic Algorithms for Non-linear Function Fitting) that approximate the value of predictive to the future data by the past data is obtained. Also, the weather condition was considered for the forecasting that is improvement, and the daily peak load forecasting in next day on Chubu district in Japan was carried out, and the effectiveness of proposed method was examined.

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