Generalized Stochastic Dynamic Aggregative Game for Demand-Side Management in Microgrids with Shared Battery

TL;DR

This paper models demand-side management in microgrids with shared batteries as a stochastic dynamic aggregative game, addressing uncertainties in renewable energy and demand, and analyzes the Nash equilibrium under these conditions.

Contribution

It introduces a generalized stochastic dynamic aggregative game framework with chance constraints for microgrid demand management, considering uncertainties and shared resources.

Findings

Stochastic method outperforms deterministic approaches in simulations.

Analysis of Nash equilibrium existence and uniqueness under uncertainty.

Effect of renewable energy variability on demand management strategies.

Abstract

In this paper, we focus on modeling and analysis of demand-side management in a microgrid where agents utilize grid energy and a shared battery charged by renewable energy sources. We model the problem as a generalized stochastic dynamic aggregative game with chance constraints that capture the effects of uncertainties in the renewable generation and agents' demands. Computing the solution of the game is a complex task due to probabilistic and coupling constraints among the agents through the state of charge of the shared battery. We investigate the Nash equilibrium of this game under uncertainty considering both the uniqueness of the solution and the effect of uncertainty on the solution. Simulation results demonstrate that the presented stochastic method is superior to deterministic methods.