Abstract

The nature of renewable energy resources (RERs), such as wind energy, makes them highly unstable, unpredictable, and intermittent. As a result, they must be optimized to reduce costs and emissions, increase reliability, and also to find the optimal size and location for RERs and energy storage systems (ESSs). Microgrids (MG) can be modified using ESSs to gradually reduce traditional energy use. In order to integrate RERs in a financially viable scheme, ESSs should be sized and operated optimally. The paper presents an enhanced biogeography-driven optimization algorithm for optimizing the operations and sizes of battery ESSs (BESSs) taking into account MGs that experience wind energy penetration in a way that migration rates are adaptively adjusted based on habitat suitability indexes and differential perturbations added to migration operators. An optimization problem was applied to a BESS to determine its depth of discharge and lifespan. This paper considers three different scenarios in using simulations and compares them to existing optimization methods for the purpose of demonstrating the effectiveness of the offered scheme. Out of all the case studies examined, the optimized BESS-linked case study was the least expensive. We also show that a BESS must be of an optimum size to function both economically and healthily. For economic and efficient functioning of MGs, it has been shown that finding the optimum size of the ESS is important and potentially extends battery lifespan. The IBBOA obtained a more precise size for BESS’s volume, and the final outcomes are compared in this paper with other methods.

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