An Optimal Approach for Coordinating Scheduling Day-Ahead and Real-Time Energy Market with Risks

Abstract

The trading model consisting of day-ahead market and real-time market exists in most of power markets. The power purchaser must consider how to allocate the specified power energy between the two markets to minimize the purchasing cost and to limit the market risk. This paper firstly analyzes the features of separate clearing energy in day-ahead market and real-time market, then points out this kind of separate clearing mechanism not the most economical. Regarding the load demand as random process, this paper puts forward an optimal model considering risk factors that incorporates day-ahead energy scheduling with real-time energy scheduling to find an optimal day-ahead scheduling scheme so as to achieve the total purchase cost minimum. Monte Carlo simulation algorithm and Hooke and Jeeves pattern search are developed to solve the proposed model. Numerical testing based on a 5-unit system shows that the proposed model with higher economy than the conventional separate energy dispatching approach, and it can consider the market risk.