Cost-Effective Energy Management of a Microgrid Using a Hybrid Yellow Saddle Goatfish Optimization Algorithm

Asadullah Younas; Tahir  Mahmood; Muhammad Mansoor Ashraf

Authors

Asadullah Younas Department of Electrical Engineering, University of Engineering and Technology Taxila, Pakistan
Tahir Mahmood Department of Electrical Engineering, University of Engineering and Technology Taxila, Pakistan
Muhammad Mansoor Ashraf Department of Electrical Engineering, University of Engineering and Technology Taxila, Pakistan

Keywords:

Microgrid, Energy Management, PV, BESS, HYSGA, SQP

Abstract

The increasing integration of renewable energy sources into hybrid Microgrid presents challenges such as power fluctuations, system complexity, and high operational costs. This paper proposes an optimized energy management framework that combines the Hybrid Yellow Saddle Goatfish Optimization Algorithm (HYSGA) with Sequential Quadratic Programming (SQP) to improve system efficiency, stability, and cost-effectiveness. The HYSGA approach efficiently manages energy distribution among solar photovoltaic (PV) systems, Battery Energy Storage Systems (BESS), and the power grid, ensuring reliable and cost-effective operation. HYSGA quickly identifies near-optimal solutions for complex energy management issues, while SQP fine-tunes these solutions to improve precision and convergence speed. Extensive simulations and cost comparisons confirm the framework's performance. In the baseline scenario, the hybrid Microgrid incurs an annual operational cost of $26,900. In Case I, this cost drops to $13,800, achieving 49% savings. Further optimization with HYSGA reduces the cost to $13,430.08, resulting in a 50.118% savings. Additionally, comparative evaluations show that HYSGA outperforms traditional techniques like Mixed-Integer Nonlinear Programming (MINLP) in terms of cost savings, computational efficiency, and solution accuracy. This study provides a detailed analysis of the research methodology, solution approach, and performance evaluation, ensuring clarity. The results demonstrate that the HYSGA framework is a scalable, computationally efficient, and economically viable solution for hybrid Microgrid energy management. The proposed method offers a promising approach for enhancing energy efficiency and reducing costs in modern smart grid applications.

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