Artificial Neural Network based Short Term Load Forecasting of Power System

Citation : Salman Quaiyum, Yousuf Ibrahim Khan, Saidur Rahman and Parijat Barman. Article: Artificial Neural Network based Short Term Load Forecasting of Power System. International Journal of Computer Applications 30(4):1-7, September 2011. Published by Foundation of Computer Science, New York, USA

Abstract : Load forecasting is the prediction of future loads of a power system. It is an important component for power system energy management. Precise load forecasting helps to make unit commitment decisions, reduce spinning reserve capacity and schedule device maintenance plan properly. Besides playing a key role in reducing the generation cost, it is also essential to the reliability of power systems. By forecasting, experts can have an idea of the loads in the future and accordingly can make vital decisions for the system. This work presents a study of short-term hourly load forecasting using different types of Artificial Neural Networks.

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