Artificial Neural Networks for Spot Electricity Price Forecasting: A Review
S. Vijayalakshmi and
G. P. Girish
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S. Vijayalakshmi: Department of Finance, IBS Hyderabad, IFHE University (a Deemed to-be-University under Section 3 of UGC Act 1956), Hyderabad, Andhra Pradesh, India,
G. P. Girish: Department of Finance, IBS Hyderabad, IFHE University (a Deemed to-be-University under Section 3 of UGC Act 1956), Hyderabad, Andhra Pradesh, India
International Journal of Energy Economics and Policy, 2015, vol. 5, issue 4, 1092-1097
In this study we review literature related to short-term forecasting of spot electricity prices using artificial neural networks (ANN) 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. ANN models may truly be an answer to short-term electricity spot price forecasting viz. time-series econometric models.
Keywords: Artificial Neural Networks; Spot Electricity; Short-term; Forecasting; Power Exchange; Review (search for similar items in EconPapers)
JEL-codes: C01 C22 C53 (search for similar items in EconPapers)
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Persistent link: https://EconPapers.repec.org/RePEc:eco:journ2:2015-04-22
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