基于人工神经网络的短期需求预测

Astha Singh, Kishan Bhushan Sahay
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引用次数: 6

摘要

电力需求预测是保证电力系统高效、经济、可靠、准确运行的一项重要任务,可以为机组调试、检修调度等提供依据。考虑到负荷预测的重要性,提出了不同的电力需求预测模型。人工神经网络是近年来应用最广泛的电力需求预测方法。仿真结果表明,该方法能够有效地预测电力负荷。本文将不同的人工神经网络应用于短期需求预测,即利用MATLAB R14a对电力需求进行一小时前的小时预测。仿真结果表明,提前1小时的负荷预测具有较高的准确性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Short-Term Demand Forecasting by Using ANN Algorithms
Electric power demand prediction is an important task for the efficient, economic, reliable and accurate power system operations which can be unit commitment, maintenance scheduling, etc. Considering importance of load forecasting different models are proposed for power demand forecasting. ANN is the most widely used method for power demand forecast from years. Simulation results obtained show that ANN is capable of forecasting electricity loads effectively. In this paper different ANN has been applied in short-term demand forecasting that is, the one hour-ahead hourly forecast of the electricity power demand using MATLAB R14a. The simulation results have shown highly accurate one hour ahead load forecast.
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