Day-Ahead and Intraday Economic Optimization Models of the Stackelberg Game Considering Source-Load Uncertainty

Abstract

In order to enhance the demand response rate on the demand side and the wind power accommodation rate on the supply side, as well as to curtail the operational cost effectively, this paper formulates a day-ahead and intraday economic dispatch model predicated on Stackelberg game theory. Within this model, specific attention is given to the influence of source-load uncertainties on energy prices, and the concept of the net load is incorporated during the intraday phase to meticulously calibrate intraday prices. For the purpose of resolving the devised model, an ameliorated lighting attachment procedure optimization algorithm is employed. Via simulation and comparative analysis, the energy pricing strategy proposed herein markedly bolsters the users’ engagement in demand response and the wind power accommodation rate, concomitantly reducing the operational cost. Furthermore, by leveraging the improved Lightning Attachment Procedure Optimization algorithm to address this model, the system cost is decreased by 9.6%, and the iteration speed is increased by 18.75%. This research provides robust support for overcoming the dual conundrums of demand response and wind power accommodation in contemporary energy systems.

Keywords

• Uncertainty
• multi-time scale
• real-time pricing
• Stackelberg game
• demand response