A key requirement for success of smart home energy management systems is understanding the user's psychological perception of a smart environments, and the design of control strategies that specifically take into account such dimensions in system operation. We discuss how our research develops psychological models and integrates them with optimization and machine learning techniques to realize social and behavioral aware energy optimization methodologies for smart homes.