Demand side management algorithms and modeling in smart grids A customer's behavior based study

This paper presents algorithms and architecture models for a home energy management system. It's based on customers' behavior that is modeled by a decision-making chain, and smart appliances' use for demand side management. The proposed architecture is scalable and extensible to upper levels of smart grid as the development approach used is bottom-up. Once the model is validated for home use, we can go up and apply it for holdings, factories, and micro-grids contexts. Scalability models and strategies are also presented and discussed. Ensuring supply and demand balance at real time is the main problematic of smart grids. The proposed solution meets this objective, because it allows large scale renewable energy resources integration. Hence, it leads to global energy efficiency and demand side management optimization in smart grids.