Providing an optimal method based on SARIMA In the short-term electricity market considering DER resources

Determining the production arrangement of power plants Is to provide a coherent planning for the operation of power plants in order to determine the entry and exit of power plant units, to determine the production arrangement of power plants and the amount of production of each during the day so that we bear the lowest cost, the investigations show. Optimum exploitation of pumped storage power plants is dependent on accurate prediction of next day energy market behavior and offer of buying and selling energy based on possible market prices. Considering this issue, Increasing the accuracy of forecasting the next day's market prices reduces the unit allocation risk and increases the power plant's profit to the same extent. Therefore, the way to put these joint producers in the circuit with power plants is the basis of an optimization problem for production units, where the goal is to minimize the production cost of power plants by considering various technical and physical limitations and satisfying the load supply condition. In this research paper, a new model for the allocation of storage pump power plant units In the day-ahead market is presented. Considering that the day-ahead market prices are highly volatile and have high uncertainty, seasonal ARIMA or SARIMA time series is used to predict the day-ahead market price. Investigations and simulation results show that SARIMA can predict the next day's daily market prices with acceptable accuracy. It has also been shown that the use of the presented model using the robust optimization method increases the accuracy of the optimal planning of the storage pump power plant and Improves the reliability of the network. The proposed method for planning the participation of units improves the reliability of the network by using the robust optimization method.