Forecasting method of clearing price in spot market of electric power based on data mining

Clearance prices are vital for deciding on electricity spot market offers. To solve the problem of complex electricity assessment caused by frequent fluctuations in price levels, this paper investigates a data mining-based method for predicting the liquidation price in the electricity spot market. This paper establishes a data mining model to analyze and assess the forecast risk of electricity spot market clearing prices by solving for generalized forecast error parameters. On this basis, the correlation coefficients are solved to complete the design of the data mining-based power spot market liquidation price forecasting method. The experimental results show that under the action of the data mining model, the error level between the predicted and actual values of the electricity spot market clearing price does not exceed 200 yuan, which can effectively suppress the price fluctuation behavior and better solve the problem of complex electricity assessment.