Electricity Price Forecasting for the Electric Reliability Council of Texas Using Econometrics Model

In several areas of electrical power firms, short-term electricity price forecasting has been an important factor. Smart metres are critical parts of modern electrical grids, which increase the importance of electricity price and load in the energy management system. Revolutionary developments in modern electrical grids, known as Smart Grids, have implemented smart metres as essential parts of the Smart Grids. In several facets of electrical power companies over the last 15 years, short-term electricity price forecasting has been a prominent factor. Researchers in the field have used a variety of modelling techniques, including fundamental models, reduced-form models, statistical models, and computational intelligence models.The time series models have performed exceptionally well among statistical models. As electricity spot prices exhibit broad deviations, we propose a new market forecasting approach based on SARIMA-GARCH models with the Skew-Normal Distribution in this paper. For the Electric Reliability Council of Texas, the model is designed to simulate and compose the predicted components of the time series model in order to forecast future electricity prices. Finally, the proposed model's obtained results are compared to the Normal Distribution Assumption.Using real electricity price data from the Electric Reliability Council of Texas, the feasibility of the proposed approach is demonstrated. This result demonstrates that the proposed approach can increase forecast accuracy significantly.

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