Optimal scheduling model for master-slave game considering demand-side incentives

Abstract

Abstract Global energy saving and emission reduction measures are deeply promoted, and the importance of demand-side resource participation in smart grid response is highlighted. A novel master-slave game model is proposed to address the uncertainty of demand-side response load-shedding capability and the fluctuation of renewable energy output during peak hours; the follower-side incentive mechanism (CBIM) considers the credit index, contribution, and electricity comfort to constrain the amount of declared load shedding, and is modeled with the objective function of maximizing the revenue from electricity consumption; and the real-time dispatch model in the leader's multi-timescale optimal scheduling model considers the wind and light Penalty coefficients and DR incentive mechanism using improved particle swarm algorithm to solve the mathematical model. Encouraging users to feedback load shedding according to their actual capacity can integrate demand-side revenue, as well as flatten the load curve to improve grid stability, enhance new energy consumption, and reduce the cost of grid energy consumption.