Electricity Price Forecasting Model based on Gated Recurrent Units
- URL: http://arxiv.org/abs/2207.14225v1
- Date: Thu, 28 Jul 2022 16:49:03 GMT
- Title: Electricity Price Forecasting Model based on Gated Recurrent Units
- Authors: Nafise Rezaei, Roozbeh Rajabi, Abouzar Estebsari
- Abstract summary: This paper presents a model for electricity price forecasting based on Gated Recurrent Units.
Noise in electricity price seriously reduces the efficiency and effectiveness of analysis.
The proposed methodology can perform effectively in prediction of electricity price.
- Score: 0.0
- License: http://creativecommons.org/licenses/by/4.0/
- Abstract: 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.
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