Efficient short-term energy management of a renewable energy integrated microgrid using modified manta ray foraging optimization

With recent developments in power electronics devices, today there is increasing interest in renewable energies at the level of distribution networks and close to consumers. However, it is obvious that with the high integration of such resources in the form of distributed generation (DGs), the operation and management of distribution networks will face many challenges. Therefore, it is required to design optimal management systems to properly operate active distribution networks. Proper operation of distribution networks with high integration of DGs is established in the concept of microgrids. This study recommends a day-ahead operation for a microgrid including renewable-based sources such as photovoltaic (PV) and storage systems. Microgrid scheduling has been evaluated in different weather conditions and various output power for the PV system. In order to perform different evaluations, four dissimilar days from the four seasons of the year have been selected to evaluate the amount of radiation of the solar system based on this information. The objective function considered in this work is a single-objective optimization to minimize the total costs of the microgrid. To solve the problem formulation, the modified manta ray foraging optimization (MMRFO) algorithm is applied. To confirm the superiority of the suggested technique, the results of optimization are compared with conventional approaches.