Current political and economic events are placing an emphasis on energy production and consumption more than ever before. This leads to the necessity for continued research with power distribution systems and factors influencing system operation. The Human Social Dynamics Multi Agent System (HSDMAS) is a project contributing to the study of power distribution networks. By examining power failures as a string of related events while incorporating intelligent learning agents representing human factors, the HSDMAS takes a unique approach towards the understanding and prevention of large scale power failures by coupling a probabilistic model of load-dependent cascading failure, CASCADE, with a dynamic power systems model, OPA. The HSDMAS project focuses on improving and optimizing the performance of the CASCADE and OPA models individually, then develops an interactive multi- layer, multi-agent system modeling power transmission and human factors represented by utility optimization.