Application of an intelligent system based on EPSO and ANFIS to price forecasting

J. Catalão, G. Osório, H. Pousinho
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引用次数: 8

Abstract

This paper proposes evolutionary particle swarm optimization (EPSO) combined with an adaptive-network-based fuzzy inference system (ANFIS) for short-term electricity prices forecasting. In a deregulated framework, producers and consumers require short-term price forecasting to derive their bidding strategies to the electricity market. Accurate forecasting tools are required for producers to maximize their profits and for consumers to maximize their utilities. The accuracy of the price forecasting attained with the proposed intelligent system is thoroughly evaluated, reporting the numerical results from a real-world case study.
基于EPSO和ANFIS的智能系统在价格预测中的应用
本文提出将进化粒子群算法(EPSO)与基于自适应网络的模糊推理系统(ANFIS)相结合用于短期电价预测。在放松管制的框架下,生产者和消费者需要短期价格预测,以获得他们对电力市场的投标策略。生产者要实现利润最大化,消费者要实现效用最大化,都需要准确的预测工具。所提出的智能系统的价格预测的准确性被彻底评估,报告了来自现实世界案例研究的数值结果。
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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