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首页> 外文期刊>International journal of Power and energy conversion >Price volatility forecasting using artificial neural networks in emerging electricity markets
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Price volatility forecasting using artificial neural networks in emerging electricity markets

机译:在新兴电力市场中使用人工神经网络进行价格波动预测

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摘要

In the adaptive short-term electricity price forecasting, it may be premature to rely solely on the hourly price forecast. The volatility of electricity price should also be analysed to provide additional insight on price forecasting. This paper proposes a price volatility module to analyse electricity price spikes and study the probability distribution of electricity price. Two methods are used to study the probability distribution of electricity price; the analytical method and the ANN method. Furthermore, ANN method is used to study the impact of line limits, line outages, generator outages, load pattern and bidding strategy on short term price forecasting, in addition to sensitivity analysis to determine the extent to which these factors impact price forecasting. Data used in this study are spot electricity prices from California market in the period which includes the crisis months where extreme volatility was observed.
机译:在自适应短期电价预测中,仅依靠小时电价预测可能为时过早。还应分析电价的波动性,以提供有关价格预测的更多信息。本文提出了一个价格波动模块,用于分析电价的峰值并研究电价的概率分布。研究电价的概率分布有两种方法。分析方法和ANN方法。此外,除了进行敏感性分析以确定这些因素在多大程度上影响价格预测外,ANN方法还用于研究线限值,线中断,发电机中断,负荷模式和投标策略对短期价格预测的影响。本研究中使用的数据是在这段时期内加利福尼亚市场的现货电价,其中包括观察到极端波动的危机月份。

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