Event-Triggered Strategy Design for Demand Response Management in Heterogeneous Agent-Based Smart Grids

This paper presents a novel event-triggered approach for regulating energy prices of heterogeneous agent-based demand response including prosumer groups and energy companies. First, a price-based demand response management (PDRM) model is developed using networked evolutionary game theory. Then, a necessary and sufficient criterion is proposed to verify the stabilizability of the controlled PDRM system, significantly reducing iterative complexity compared to existing methods. By utilizing truth matrices, an algorithm is proposed to calculate the event-triggered feedback gain matrices and determine the triggering times. The proposed matrix-based event-triggered control guarantees that the strategies of all participants converge to the target game equilibrium set while reducing the update frequencies of the controller. Finally, the simulation results demonstrate the effectiveness of the proposed method. Note to Practitioners—Existing game-theoretic demand response management models are challenging to analyze quantitatively regarding the decision-making processes within heterogeneous agent-based smart grids. This paper presents a novel PDRM model for heterogeneous agent-based smart grids. The proposed PDRM model effectively simulates the dynamic evolution of decision-making processes for each participant. In addition, this paper presents a matrix-based event-triggered control approach for dynamically regulating energy prices to the desired level. With an arbitrary initial strategy, the proposed control algorithm ensures that the controlled PDRM system converges to the desired energy price, while reducing the number of adjustments required. The proposed method provides flexible adjustments based on actual conditions for demand response scheduling in heterogeneous agent-based smart grids.