Multi-objective Optimization of Customers’ Load and Local Energy Resources in order to Increase Profitability and Decrease Pollution of Smart Microgrid

In this study, a new multi-objective method is proposed to optimal manage the local energy resources and customers’ load in a microgrid in the presence of demand response programs. The wind turbine and photovoltaic panel are the renewable energy sources of the microgrid. The time of use and critical peak pricing programs are also used to improve the consumption pattern of customers. Moreover, consumers try to use electrical energy when renewable sources are available. Maximizing the profit of microgrid and minimizing the pollutant gases of the microgrid are the objective functions of the demand side management problem. The multi-objective ant lion optimizer algorithm is used to optimize the indices of the microgrid and create the Pareto front. Then, the fuzzy method is utilized to select the best particle equal to the optimal management plan of the microgrid. Ultimately, the proposed method is evaluated in a sample microgrid. The results demonstrate the high efficiency of the proposed method in improving the performance of the microgrid by optimal managing the local energy sources and customers’ load. The proposed method of energy management increases the profitability of the distribution company and decreases the environmental pollution of the microgrid.