Neural networks approach to forecast several hour ahead electricity prices and loads in deregulated market
Neural networks approach to forecast several hour ahead electricity prices and loads in deregulated market
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DOI：
10.1016/j.enconman.2005.12.008
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发表时间：
2006-09-01
影响因子：
10.4
通讯作者：
Funabashi, Toshihisa
中科院分区：
文献类型：
--
作者：
Mandal, Paras;Senjyu, Tomonobu;Funabashi, Toshihisa
在日常电力市场中，预测电价和负荷是最重要的任务，也是决策的基础。预测市场行为的一种方法是利用历史价格、负荷和其他必要的信息来预测未来的价格和负荷。本文介绍了一种使用人工智能方法（如神经网络模型）预测未来几小时（1-6小时）电价和负荷的方法，该方法使用NEMMCO网站上的公开数据来预测维多利亚州电力市场的电价和负荷。提出了一种选取相似日的方法，利用与预测日相似的日的信息来预测负荷和价格曲线。使用带加权因子的欧几里得范数来选择相似的日期。提出了两种不同的人工神经网络模型，一种用于1 ~ 6小时负荷预测，另一种用于1 ~ 6小时电价预测。MAPE（平均绝对百分比误差）结果随着小时前负荷和价格预测的增加有明显的增加趋势。mape对一小时前价格预测的样本平均值为9.75%。在6小时前的预测中，这一数字仅为20.03%。同样，1到6小时前的负荷预测误差（MAPE）范围仅为0.56%到1.30%。MAPE结果表明，在解除管制的维多利亚州市场中，提前数小时预测电价和负荷具有合理的准确性。(c) 2005 Elsevier Ltd版权所有。
In daily power markets, forecasting electricity prices and loads are the most essential task and the basis for any decision making. An approach to predict the market behaviors is to use the historical prices, loads and other required information to forecast the future prices and loads. This paper introduces an approach for several hour ahead (1-6 h) electricity price and load forecasting using an artificial intelligence method, such as a neural network model, which uses publicly available data from the NEMMCO web site to forecast electricity prices and loads for the Victorian electricity market. An approach of selection of similar days is proposed according to which the load and price curves are forecasted by using the information of the days being similar to that of the forecast day. A Euclidean norm with weighted factors is used for the selection of the similar days. Two different ANN models, one for one to six hour ahead load forecasting and another for one to six hour ahead price forecasting have been proposed. The MAPE (mean absolute percentage error) results show a clear increasing trend with the increase in hour ahead load and price forecasting. The sample average of MAPEs for one hour ahead price forecasts is 9.75%. This figure increases to only 20.03% for six hour ahead predictions. Similarly, the one to six hour ahead load forecast errors (MAPE) range from 0.56% to 1.30% only. MAPE results show that several hour ahead electricity prices and loads in the deregulated Victorian market can be forecasted with reasonable accuracy. (c) 2005 Elsevier Ltd. All rights reserved.