Energy Management of Microgrids Using Load Shifting and Multi-agent System

The demand-side management (DSM) has a great significance as it covers economical activities through decreasing demand of electricity during high consumption hours. Meanwhile, the multi-agent system (MAS) is a computational intelligence technique that has been applied to reduce the overall consumers' cost as well as total loads. This paper proposes a hybrid technique based on DSM and MAS to manage the energy in residential, commercial, and industrial microgrids. First, the DSM mechanism based on load shifting technique for managing and coordinating load demand is implemented. Then, according to the resulting scheduled load curve, the MAS is utilized in order to optimally coordinate different renewable sources to cover the demand and allowable energy to exchange between the main grid and microgrids. The problem is formulated as an optimization problem and solved by a powerful Antlion optimizer algorithm with an objective of maximization of load factor and minimization of overall consumers' cost. The validation of the proposed algorithm is achieved via comparative studies with other published works. The results show the prosperity of the proposed technique and its capability of saving energy cost and reducing peak demands.