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

In this paper, we present a new approach for demand side management in Smart Grid. The Multi Agent Systems (MAS) Technology is actually the most suitable to face its emerging challenges, such as complex management and control, self-healing with necessity of collaboration and communication to solve a local or global problem, and many other problematic aspects. Nowadays, there is no complete environment to simulate MAS. The Agent Oriented Programming is based on multithreading, while the simulation tools don't allow it or causes their instability. Our solution consists on combining these technologies to take benefit from their advantages and strength with available features and characteristics to model and simulate smart grid as a MAS. That leads to demand side management optimization and meets the smart grid objectives and requirements.

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