Cooperative co-evolutionary approach to electricity load and price forecasting in deregulated electricity markets

A. Karsaz, H. R. Mashhadi, R. Eshraghnia
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引用次数: 13

Abstract

Many electric power systems around the world have introduced deregulated markets where suppliers of electricity can freely compete. Deregulation of the electric power industry worldwide raises many challenging issues. Under this environment there will be new tasks to be solved. In the traditional and also new structure of the power industry, accurate short and long term load forecasting have been crucial to the efficient and economic operation of the system. However in the environment of a deregulated power market, various decisions require accurate knowledge of future spot prices for electricity. To buy or sell physical electricity, to offer a transaction to the market, or to analyze security of the network are examples of transactions that can rationally be made only with an idea of future electricity prices. Therefore, forecasting of the market clearing price (MCP) is becoming increasingly relevant to different market players and system operator. This paper introduces a new forecasting method that forecasts the next-day electricity price and the electricity load based on cooperative co-evolutionary (Co-Co) approach. The proposed method is applied to predict the MCP and the load in a real power market. The results of the new method show significant improvement in the load and price forecasting process
解除管制电力市场中电力负荷与价格预测的合作协同进化方法
世界各地的许多电力系统都引入了放松管制的市场,电力供应商可以自由竞争。世界范围内对电力行业的放松管制引发了许多具有挑战性的问题。在这种环境下,将会有新的任务需要解决。无论是在传统的电力工业结构中,还是在新的电力工业结构中,准确的短期和长期负荷预测对系统的高效经济运行至关重要。然而,在放松管制的电力市场环境中,各种决策都需要对未来电力现货价格有准确的了解。购买或出售实物电力,向市场提供交易,或分析网络的安全性,这些交易的例子只有在了解未来电价的情况下才能合理地进行。因此,市场出清价格(MCP)的预测对不同的市场参与者和系统运营商变得越来越重要。本文提出了一种基于协同进化(Co-Co)方法的次日电价和电力负荷预测新方法。将该方法应用于实际电力市场中MCP和负荷的预测。结果表明,新方法在负荷和电价预测过程中有显著改善
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