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Day-ahead AC-DC OPF-based nodal price prediction by artificial neural network (ANN) in a restructured electricity market

机译:重组电力市场中基于人工神经网络(ANN)的基于日间交直流两用OPF的节点价格预测

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摘要

In the last few years, electricity markets have significantly restructured in both developed and developing countries. Accurate prediction of day-ahead electricity nodal price has now become an important activity to address the price volatility in the marketplace. This will facilitate the market participants to estimate the risk and have effective decision-making in formulating bidding strategy. In developing countries, transmission congestion and investment problems have reduced the consumer benefits. Recent trend is to incorporate high voltage direct current (HVDC) transmission in the AC transmission system to gain its techno-economical advantages. This study aims at 1 motivation and relevance of present study 2 presenting AC-DC OPF nodal pricing and formulating ANN-bascd peak day-ahead nodal price prediction using multilayer feed-forward neural network with a back-propagation algorithm 3 the numerical results of IEEE 30-bus system and a real electricity market of India to demonstrate the rationality and feasibility of the proposed methodology.
机译:在过去的几年中,发达国家和发展中国家的电力市场都发生了重大重组。准确预测日间用电节点的价格现在已成为解决市场价格波动的重要活动。这将有助于市场参与者估计风险,并在制定投标策略时做出有效的决策。在发展中国家,传输拥塞和投资问题降低了消费者的利益。最近的趋势是将高压直流(HVDC)传输合并到AC传输系统中,以获取其技术经济优势。这项研究的目的是:1本研究的动机和相关性2提出AC-DC OPF节点定价,并使用带有反向传播算法的多层前馈神经网络制定基于ANN的峰值日前节点价格预测3 IEEE的数值结果30总线系统和印度真实的电力市场,以证明所提出方法的合理性和可行性。

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