Prioritizing Consumers in Smart Grid: Energy Management Using Game Theory

TL;DR

This paper introduces a game-theoretic approach to incentivize consumers in smart grids to trade surplus energy, balancing demand and supply while maximizing individual benefits.

Contribution

It proposes a Stackelberg game model for energy trading between consumers and the grid, along with a distributed algorithm to find optimal solutions.

Findings

Optimal energy trading parameters maximize consumer utility.

The distributed algorithm effectively reaches the game’s equilibrium.

Numerical results demonstrate the approach's efficiency.

Abstract

This paper explores an idea of demand-supply balance for smart grids in which consumers are expected to play a significant role. The main objective is to motivate the consumer, by maximizing their benefit both as a seller and a buyer, to trade their surplus energy with the grid so as to balance the demand at the peak hour. To that end, a Stackelberg game is proposed to capture the interactions between the grid and consumers, and it is shown analytically that optimal energy trading parameters that maximize customers utilities are obtained at the solution of the game. A novel distributed algorithm is proposed to reach the optimal solution of the game, and numerical examples are used to assess the properties and effectiveness of the proposed approach.