@article{MAKHILLIJEPE20093625200,
    title = {Demand and Price Forecasting by Artificial Neural Networks (ANNs) in a Deregulated Power Market},
    journal = {International Journal of Electrical and Power Engineering},
    volume = {3},
    number = {6},
    pages = {268-275},
    year = {2009},
    issn = {1990-7958},
    doi = {ijepe.2009.268.275},
    url = {https://makhillpublications.co/view-article.php?issn=1990-7958&doi=ijepe.2009.268.275},
    author = {YanBin and},
    keywords = {Electricity power market,price forecasting,demand forecasting,Artificial Neural networks (ANNs),demand},
    abstract = {In a deregulated electricity market, where the electricity is trading among power suppliers and retailers in the pool market. The demand and price forecasting become important and play an important role for the market participants. Accurate forecasting tools are essential for producers to maximize their profits, avowing profit losses over the misjudgment of future price movements and for consumers to maximize their utilities. This study proposes two step forecast model by the Artificial Neural Networks (ANNs) to forecast one hour ahead demand and price of electricity. A three-layer BP (Back-Propagation) model was designed to train the historical data, then it was tested to predict both demand and price of electricity. In this study, the data from Queensland electricity market of Australia is used and promising results were obtained.}
    }