Electricity price forecasting using a fuzzy system tuned with a Differential Evolution algorithm

Iván Riaño, Oscar E. Perdomo
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引用次数: 2

Abstract

In this paper we present a method which forecast the price of the kW/h for the next hour, this method was developed with an Expansion of Fuzzy Basis Functions (EFBF) and tuned with Differential Evolution (DE) algorithm. It shows a comparison of the validation results for the better individuals when varying the value of two parameters of DE and one parameter of the EFBD. Historical data were supplied by the Company XM belonging to ISA Group.
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采用差分进化算法对模糊系统进行电价预测
本文提出了一种基于模糊基函数(EFBF)展开和差分进化(DE)算法的下一小时电价预测方法。对比了两个DE参数和一个EFBD参数的变化对较优个体的验证结果。历史数据由ISA集团旗下的XM公司提供。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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