Optimal Sizing of Different Energy Sources in an Isolated Hybrid Microgrid Using Turbulent Flow Water-Based Optimization Algorithm

Abstract

This paper proposes a relatively new optimization algorithm namely the Turbulent Flow Water-Based Optimization (TFWO) to find the optimal size of a hybrid isolated microgrid generation. Moreover, validation of the proposed algorithm is proved through a comprehensive comparison with three robust performance and fast convergence algorithms which are the Harris Hawks Optimization (HHO), Whale Optimization Algorithm (WOA) and Jellyfish Search Optimizer (JSO). Two topologies with different renewable sources were considered in studying which are based on the meteorological data of the Zafarana area, a site located on the eastern coast of Egypt. The study minimizes the annual system cost (ASC) and CO₂ emissions of the proposed hybrid system while considering the following constraints: Loss of Power Supply Probability (LPSP), Fraction Renewable (FR) and System Excess Energy Ratio (EER). Violation of constraints is penalized by including a penalty factor into the objective function that varies according to the amount of the violation. Moreover, a sensitivity study is presented at the end of the paper through Load variation, irradiance variation, wind speed variation, and diesel generator efficiency decreasing. Results show not only the robustness and the fast convergence of the TFWO algorithm but also its ability to minimize the annual system cost and emission costs to values better than the aforementioned optimization techniques.