Electricity Price Forecasting Model based on Gated Recurrent Units
Rezaei, N., Rajabi, R. and Estebsari, A. (2022). Electricity Price Forecasting Model based on Gated Recurrent Units. 2022 IEEE International Conference on Environment and Electrical Engineering and 2022 IEEE Industrial and Commercial Power Systems Europe (EEEIC / I&CPS Europe). Prague 28 Jun - 01 Jul 2022 Institute of Electrical and Electronics Engineers (IEEE). https://doi.org/10.1109/EEEIC/ICPSEurope54979.2022.9854746
|Rezaei, N., Rajabi, R. and Estebsari, A.
The participation of consumers and producers in demand response programs has increased in smart grids, which reduces investment and operation costs of power systems. Also, with the advent of renewable energy sources, the electricity market is becoming more complex and unpredictable. To effectively implement demand response programs, forecasting the future price of electricity is very crucial for producers in the electricity market. Electricity prices are very volatile and change under the influence of various factors such as temperature, wind speed, rainfall, intensity of commercial and daily activities, etc. Therefore, considering the influencing factors as dependent variables can increase the accuracy of the forecast. In this paper, a model for electricity price forecasting is presented based on Gated Recurrent Units. The electrical load consumption is considered as an input variable in this model. Noise in electricity price seriously reduces the efficiency and effectiveness of analysis. Therefore, an adaptive noise reducer is integrated into the model for noise reduction. The SAEs are then used to extract features from the de-noised electricity price. Finally, the de-noised features are fed into the GRU to train predictor. Results on real dataset shows that the proposed methodology can perform effectively in prediction of electricity price.
|Institute of Electrical and Electronics Engineers (IEEE)
|Digital Object Identifier (DOI)
|Accepted author manuscript
File Access Level
|28 Jun 2022
|Publication process dates
|30 Jun 2022
Accepted author manuscript
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