Predicting Indian electricity exchange-traded market prices: SARIMA and MLP approach

Gupta, Sonal, Chakrabarti, Deepankar and Kumar, Rupesh (2023) Predicting Indian electricity exchange-traded market prices: SARIMA and MLP approach. OPEC Energy Review. ISSN 1753-0229 (In Press)

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This research investigates the short-term (ST) forecasting performance of the daily prices of the Indian exchange-traded day-ahead (DAM) market, divided into 13 bid areas, each consisting of states with varied fundamentals. Forecasts are built employing SARIMA (seasonal autoregressive integrated moving average) and MLP (multilayer perceptron) methods. Moreover, the robustness and performance of the model is compared using the lowest error and the Diebold–Mariano (DM) test statistic values. The results indicates that the SARIMA model has high prediction accuracy with error values ranging from 1% to 5% with Southern region having the highest error of 4.53% and Northern having the least error of 1.27%. However, validation by the DM test suggests no statistical significant difference between the two models. The power generators, distribution companies, traders, policymakers, strategists and managers could use the findings for effective power management through proper planning.

Item Type: Article
Keywords: Electricity | India | SARIMA | MLP
Subjects: Social Sciences and humanities > Business, Management and Accounting > General Management
JGU School/Centre: Jindal Global Business School
Depositing User: Amees Mohammad
Date Deposited: 17 Jul 2023 05:25
Last Modified: 17 Jul 2023 05:25
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