Page 128 - {PDF Title}

Asian Journal of Water, Environment and Pollution. Vol. 22, No. 1 (2025), pp. 122-133.
doi: 10.36922/AJWEP025050030

ORIGINAL RESEARCH ARTICLE

Efficient energy management in microgrid using Zebra
Optimization Algorithm

Dodda Aasha Vardhini * and Jayaram Nakka †
†
Department of Electrical Engineering, National Institute of Technology Andhra Pradesh, Tadepalligudem,
Andhra Pradesh, India
† These authors contributed equally to this work.
(This article belongs to the Special Issue: Renewable Energy Systems and Strategies in Smart Grids and Smart
Cities Development)
*Corresponding author: Dodda Aasha Vardhini (dodda.aashavardhini@gmail.com)

Received: February 1, 2025; Revised: February 28, 2025; Accepted: February 28, 2025; Published Online: March 20, 2025

Abstract: The inherent variability of power output from photovoltaic (PV) systems, wind energy resources, battery
energy storage systems (BESS), and hydrogen (H2) fuel cells presents a significant challenge in efficiently integrating
these technologies into microgrids. This stochastic nature underscores the necessity of accounting for fluctuations
in renewable energy resources (RERs) to optimize energy utilization within the microgrid. This paper proposes a
resource-efficient energy management (REEM) framework for a microgrid interconnected with the main power
system. By dynamically regulating PV generation, wind power output, BESS discharge, and hydrogen fuel cell
operation in response to load variations, the proposed approach enhances energy utilization and grid stability. To
address the complexities associated with REEM, this study employs the zebra optimization algorithm (ZOA), a highly
efficient metaheuristic technique. The primary objectives of this optimization include cost minimization, voltage
profile enhancement, and optimal sizing of RERs. Simulation results demonstrate that the strategic integration of
PV units, wind turbines, grid-connected BESS, and hydrogen fuel cells significantly reduces operational costs while
improving overall system performance. Comparative analysis further reveals that ZOA outperforms the moth-flame
optimization algorithm and stochastic fractal search network in achieving the defined optimization objectives.

Keywords: Energy resources; Photovoltaic system; Wind energy; Zebra Optimization Algorithm; Voltage stability;
Cost function

1. Introduction ultimately contributes to the promotion of decentralized
and sustainable energy systems. Variations in load
The incorporation of a wide variety of renewable demand, the unpredictability of renewable energy
energy sources and the facilitation of power flow in both resources (RERs), the relationship between the grid
directions are two of the most important contributions
that alternating current (AC) microgrids make to the and the microgrid, and the capacity for energy storage
improvement of energy dependability, resilience, and are all factors that influence the functioning of an AC
efficiency. They provide flexibility in the management microgrid. Optimal management takes into account
1-3
of dispersed generation, the reduction of transmission these aspects to achieve a balance between supply and
losses, and the support of grid stability, which demand, guarantee grid stability, and maximize the

Volume 22 Issue 1 (2025) 122 doi: 10.36922/AJWEP025050030