Different ANN Models for Short Term Electricity Price Forecasting
K Sarada1, S S Tulasi Ram2
1K Sarada, Department of EEE, Koneru Lakshmaiah Education Foundation, Vaddeswaram, A.P, India.
2S S Tulasi Ram, Department of EEE, JNTUH, Telangana, India.
Manuscript received on 07 August 2019. | Revised Manuscript received on 15 August 2019. | Manuscript published on 30 September 2019. | PP: 6706-6712 | Volume-8 Issue-3 September 2019 | Retrieval Number: C6895098319/2019©BEIESP | DOI: 10.35940/ijrte.C6895.098319
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: In a deregulated electiricity market, price forecasting is gaining demand with application of Artificial Neural Network (ANN). The paper deals with price forecasting with different ANN models.like Back Propagation Neural Network( BPNN), Radial Bias Function Neural Network (RBFNN) and Genectic Algorithm based Neural Network (GANN). A contextual investigation is made with the downloaded data of the day-ahead pool market prices of the California Pool Market using the above four different ANN models and the results are compared.
Keywords: ANN, Genetic Algorithm, Electricity Markets, Market Clearing Price
Scope of the Article: Artificial Intelligent Methods, Models, Techniques