TY  - JOUR
T1  - Demand and Price Forecasting by Artificial Neural Networks (ANNs) in a Deregulated Power Market
AU - Xu, YanBin AU - Nagasaka, Ken 
JO  - International Journal of Electrical and Power Engineering
VL  - 3
IS  - 6
SP  - 268
EP  - 275
PY  - 2009
DA  - 2001/08/19
SN  - 1990-7958
DO  - ijepe.2009.268.275
UR  - https://makhillpublications.co/view-article.php?doi=ijepe.2009.268.275
KW  - Electricity power market
KW  -price forecasting
KW  -demand forecasting
KW  -Artificial Neural networks (ANNs)
KW  -demand
AB  - 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.
ER  -