Shaier Ahmed A, Elymany Mahmoud M, Enany Mohamed A, Elsonbaty Nadia A
Electrical Power and Machines Department, Faculty of Engineering, Zagazig University, Zagazig, 44519, Egypt.
Sci Rep. 2025 Jan 7;15(1):1147. doi: 10.1038/s41598-024-84227-0.
This manuscript focuses on optimizing a Hybrid Renewable Energy System (HRES) that integrates photovoltaic (PV) panels, wind turbines (WT), and various energy storage systems (ESS), including batteries, supercapacitors (SCs), and hydrogen storage. The system uses a multi-objective optimization strategy to balance power management, aiming to minimize costs and reduce the likelihood of loss of power supply probability (LPSP). Seven different algorithms are assessed to identify the most efficient one for achieving these objectives, with the goal of selecting the algorithm that best balances cost efficiency and system performance. The system is assessed across three operational scenarios: (1) when energy supply meets demand with help from backup systems, (2) when demand exceeds supply and energy storage systems are depleted, and (3) when energy generation surpasses demand and storage systems are full. The HBA-based optimization effectively manages energy flow and storage, ensuring grid stability and minimizing overcharging risks. This system offers a reliable and sustainable power supply for isolated microgrids, effectively managing energy production, storage, and distribution. The research sets a new benchmark for future studies in decentralized energy systems, particularly in balancing technical efficiency and economic feasibility.
本手稿聚焦于优化一种混合可再生能源系统（HRES），该系统集成了光伏（PV）板、风力涡轮机（WT）以及包括电池、超级电容器（SC）和储氢在内的各种储能系统（ESS）。该系统采用多目标优化策略来平衡功率管理，旨在使成本最小化并降低供电概率损失（LPSP）的可能性。评估了七种不同的算法，以确定实现这些目标的最有效算法，目标是选择能最佳平衡成本效率和系统性能的算法。该系统在三种运行场景下进行评估：（1）当能源供应在备用系统的帮助下满足需求时；（2）当需求超过供应且储能系统耗尽时；（3）当能源发电量超过需求且储能系统已满时。基于HBA的优化有效地管理了能量流动和存储，确保了电网稳定性并将过充风险降至最低。该系统为孤立微电网提供了可靠且可持续的电力供应，有效地管理了能源生产、存储和分配。该研究为分散式能源系统的未来研究设定了新的基准，特别是在平衡技术效率和经济可行性方面。
