Electricity Market Clearing Price Forecast Based on Adaptive Kalman Filter

In the competitive electricity market, in order to guarantee generators profits, they usually adopt bidding strategies to participate in the electricity market competition. The forecast of market clearing prices in the electricity market can provide a reference for the quotation behavior of generator companies. This paper develops a new day-ahead electricity price forecasting based on adaptive Kalman filter. Under the condition of unknown prediction model state transition matrix and the statistical characteristics of the observed noise, To estimate the unknown parameters of the prediction model according to the electricity market clearing electricity price data. According to the estimation, the generators will make a quotation with a slightly lower than the predicted market clearing price, ensuring their unit capacity can participate in the market bidding and achieve the goal of maximizing its own profit. The predicted price is applied to the PJM power market to verify its prediction accuracy.