Murtza Qamar Hafiz Ghulam, Guo Xiaoqiang, Seif Ghith Ehab, Tlija Mehdi, Siddique Abubakar
Key Laboratory of Power Electronics for Energy Conservation and Motor Drive of Hebei Province, Department of Electrical Engineering, Yanshan University, Qinhuangdao, 066004, China.
Department of Mechatronics, Faculty of Engineering, Ain shams University, Cairo, 11566, Egypt.
Sci Rep. 2025 Jan 5;15(1):863. doi: 10.1038/s41598-024-78153-4.
A hybrid microgrid powered by hydrogen is an energy infrastructure that depends on hydrogen as its primary energy carrier within a localized network. This study proposed a novel bi-level optimization approach to enhance power quality and cost efficiency of the system. In the quest to improve energy management systems (EMS) and enhance power quality, a bi-level optimization approach named Particle swarm optimization-Modified water wave optimization (PSO-MWWO) has been proposed. This method integrates adaptive population size and an adaptive wavelength coefficient to boost its overall effectiveness. It is attractive with specialists in energy management systems (EMS), control systems, and hydrogen technologies can significantly augment the efficiency of coordination endeavours. PSO-MWWO can incorporate environmental considerations, such as minimizing emissions or exploiting the use of renewable energy resources (RESs) in hydrogen production and consumption. This paper thoroughly examines its implementation, operation, and unique features, with a particular emphasis on the power quality of a hydrogen based microgrid. The achieved results and numerical analysis affirm the superiority of the proposed technique compared to other traditional methods like mixed integer linear programming (MILP), HOMER, Variable mesh optimization (VMO), and Cataclysmic genetic algorithm in optimizing component sizing, renewable production, hydrogen production, reliability, cost effective, and overall efficacy. This substantiates its practical utility in real-time applications. The efficacy of this method is empirically demonstrated through the implementation in MATLAB software.
以氢气为动力的混合微电网是一种能源基础设施，在局部网络中依赖氢气作为其主要能量载体。本研究提出了一种新颖的双层优化方法，以提高系统的电能质量和成本效率。在寻求改进能源管理系统（EMS）和提高电能质量的过程中，提出了一种名为粒子群优化-改进水波优化（PSO-MWWO）的双层优化方法。该方法集成了自适应种群大小和自适应波长系数，以提高其整体有效性。它对能源管理系统（EMS）、控制系统和氢能技术领域的专家具有吸引力，能够显著提高协调工作的效率。PSO-MWWO可以纳入环境因素，例如在氢气生产和消耗中尽量减少排放或利用可再生能源（RES）。本文深入研究了其实施、运行和独特特性，特别强调了基于氢气的微电网的电能质量。所取得的结果和数值分析证实了所提出的技术在优化组件尺寸、可再生能源生产、氢气生产、可靠性、成本效益和整体效能方面优于其他传统方法，如混合整数线性规划（MILP）、HOMER、可变网格优化（VMO）和灾变遗传算法。这证实了其在实时应用中的实际效用。通过在MATLAB软件中的实现，实证证明了该方法的有效性。
