Forecasting peak loads with neural networks

L. Garcia, O. Mohammed
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引用次数: 3

Abstract

This paper presents a new approach to power load forecasting using artificial neural networks (ANN). Based on weather conditions and past history of load consumption, a load forecast is made by the utility companies to deliver the appropriate load to its customers. Power systems operation and planning functions such as unit commitment, security analysis, state estimation, etc. are benefited with an accurate load forecast. Improving the accuracy of the load forecast can save a significant amount of money. Artificial neural networks permit adaptability to climate changes compared to other forecasting methods in use. The results obtained by using ANN have been found to give better results than other conventional techniques.<>
神经网络预测峰值负荷
本文提出了一种利用人工神经网络进行电力负荷预测的新方法。根据天气状况和过去的负荷消耗历史,电力公司进行负荷预测,以便向客户提供适当的负荷。准确的负荷预测有利于电力系统运行和规划功能,如机组承诺、安全分析、状态估计等。提高负荷预测的准确性可以节省大量资金。与其他正在使用的预测方法相比,人工神经网络允许对气候变化的适应性。使用人工神经网络获得的结果比其他传统技术得到的结果更好
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