Cost optimization in microgrids: A scenario-based analysis by using polar the fox optimization algorithm

Microgrids have come up as a promising solution for ensuring efficient, reliable, and sustainable energy management through the distributed energy resources integration. However, some challenges such as integration of distributed generators, economic efficacy and operational constraints cause the management and operation of microgrids remain as a complex problem. In this work, a comprehensive analysis is realized by using the Polar Fox Optimization algorithm to find solutions to these problems. Four different scenarios are analyzed to examine the effects of operational constraints on system performance and economic costs. In the first case, all distributed energy resources are operated within the specified limits and all power from renewable sources is injected into the microgrid. This scenario results in an operating cost of 269.76 €/day. In the second case, the output power of the renewable distributed energy sources is optimized. This case, a cost reduction of 42.5% is obtained when compared to the first scenario. In the third case, the energy exchange constraint between the grid and the microgrid is removed. Thus, a cost reduction of 74.7% is obtained when compared to the first case. In the fourth case, a detailed battery energy storage system model is added by considering technical parameters such as battery efficiency, state-of-charge limits, and charge/discharge rates. This case an operating cost of €107.08/day is obtained. Thus, a cost reduction of 60.3% is obtained when compared to the first case. The results show that changing the operational constraints significantly affects both system performance and economic efficiency. The proposed approach presents valuable perception for microgrid operators and planners. It points out the importance of the optimization algorithm in achieving economically efficient and reliable energy management.