A Game-Theoretic Multi-Level Energy Demand Management for Smart Buildings

The advent of smart grids offers us the opportunity to better manage the electricity grids. One of the most interesting challenges in the modern grids is the consumer demand management. Indeed, the development in information and communication technologies encourages the development of demand-side management systems. This paper introduces two electricity management mechanisms in a smart buildings' context. We first use negotiation and multi-leader-follower game techniques to model the interactions between the electricity providers and the buildings' consumers. Then, we propose a distributed energy demand scheduling approach based on game theory with minimal interactions between consumers to optimize the energy demand cost. This approach aims to reduce the total energy cost and the peak to average consumption ratio, and to maximize the exploitation of renewable energy. We use a multi-agent system to model the system entities. The performance evaluation demonstrates that our distributed approach reduces the total consumption cost as well as each consumer bill.