Sodium sulfur batteries allocation in high renewable penetration microgrids using coronavirus herd immunity optimization

Energy storage batteries have been described as an ideal way to solve renewable energy problems, improve self-consumption rate (ScR), and pave the way for further growth in renewables penetration. In this work, an optimization framework is proposed to enhance a grid-connected microgrid performance in three stages. The first stage epitomizes maximization of the ScR of the highly-penetrated renewables hosted in the microgrid considered via sodium sulfur batteries allocation. The second stage epitomizes the minimization of the active power losses. The third stage epitomizes the calculation of the optimal energy management relying on diminishing the overall microgrid’s cost of operation depending on the optimal findings of the earlier two stages. The coronavirus herd immunity optimization algorithm is applied on MATLAB’s platform to solve the engineering problem formulated. Numerous linear and nonlinear constraints have been taken into account. The results have gotten validate the usefulness of the developed solutions and algorithm application.