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Artificial Intelligence Based Price and Load Forecasting of Electrical Energy for Deregulated Power System
Author Name : Mohan Akole, Manisha Kharul
ABSTRACT
The price and load forecasting are an important component in the economic and secure operation of the competitive deregulated power system energy market. This paper presents the use of an artificial intelligence based half hourly ahead load forecasting and half hourly ahead price forecasting application. By using historical weather, load consumption, price and calendar data, a multi-layer feed forward (FF) neural network trained with Back propagation (BP) algorithm was developed for the half hour ahead forecasting. The developed algorithm for half hourly forecasting has been tested with Australian market data. The results of ANN forecasting model is compared with the conventional Multiple Regression (MR) forecasting models.
Keywords: Forecasting, electricity market, Selection of variables, Multiple Regression (MR), and Artificial Neural Network (ANN).