一种电力系统短期负荷预测网络信息系统

在应用BP神经网络对电力系统进行短期负荷预测的基础上，设计了基于三层C／S网络信息结构的电力系统短期负荷预测系统，并给出了一种具体的实现方法。该方法使用户可以通过在线方式浏览历史数据，查看预测结果并分析市场走势，通过预测系统，客户能够根据负荷值采取相应措施，最大程度减少损失并获得较高利润，该系统目前用于预测美国加州电力系统负荷，随着国内电力市场的开放，也用于预测山东，浙江等省的负荷，该方案采用的先进计算机技术和体系结构保证了系统的良好性能。

IMPLEMENTATION OF AN INTERNET BASED INFORMATION SYSTEM FOR SHORT-TERM LOAD FORECASTING

On the basis of applying BP artificial neural network to short term load forecasting a three layer C/S information architecture based short term load forecasting system is developed and a concrete implementation method of this system is given. Using this method the consumers can view the historical data in on line mode,examine the result of forecasting and analyze the market trends. With the help of this forecasting system the customers can determine what corresponding measures should be applied to reduce the loss to a minimum and gain profit as much as possible. At present this system is applied in the forecasting the power load of California Electric Power System,USA. With the opening of domestic electricity market it is also applied to forecast the power load in Shandong Province and Zhejiang Province. The performance of this system is ensured by the applied advanced computer technique and architecture.