Multi-objective planning of microgrid based on renewable energy sources and energy storage system

The optimal planning of microgrids in the presence of renewable energy sources (RES) and conventional units is considered in this research. In other words, this study deals with the multi-objective modeling of planning in the microgrid, considering economic aspects and energy management. On the other hand, the relevant limitations and the presence of different energy sources have been considered to present a more realistic one. The production capacity of wind turbines and photovoltaics is very uncertain due to the random nature of wind speed and solar radiation. Using typical distribution performance, the proposed model considers load uncertainty, price, and RES production. The operational procedure incorporates a demand response program with incentives. Making the most of the microgrid demand response program (DRP's) profitability while minimizing producer and transaction costs results in the best possible economic situation. Since the proposed model has several functions that are opposed to each other, several goals based on teaching-learning and fuzzy theory have been proposed to solve it using the developed optimization algorithm. Finally, the proposed model and algorithm have been discussed in different scenarios. Five models have been used to cover the uncertainty caused by renewable sources and electricity prices. By considering the load management program and the simultaneous application of the storage system for the load, it can be seen that the final cost of the system has been reduced acceptably. According to the obtained results, diesel generators operate for 24 h and contribute to the performance of RES. Therefore, the first and third diesel units reduce production when PV provides power.