Artificial Neural Networks for Spot Electricity Price Forecasting: A Review
Abstract
In this study we review literature related to short-term forecasting of spot electricity prices using Artificial Neural Networks in deregulated competitive power markets. With accurate price forecasts, power market participants can maximize their profits and meet their power commitments using a proper combination of power purchase agreements, bilateral trade and buying/selling electricity through power exchanges in a judicious, efficient and effective manner. Artificial Neural Network models may truly be an answer to short-term electricity spot price forecasting viz-a-viz time-series econometric models.Keywords: Artificial Neural Networks, Spot Electricity, Short term, Forecasting, Power Exchange, ReviewJEL Classifications: C01; C22; C53Downloads
Download data is not yet available.
Downloads
Published
2015-10-14
How to Cite
S., V., & G.P., G. (2015). Artificial Neural Networks for Spot Electricity Price Forecasting: A Review. International Journal of Energy Economics and Policy, 5(4), 1092–1097. Retrieved from https://econjournals.com./index.php/ijeep/article/view/1446
Issue
Section
Articles