Asim Ahmed M, Awad Ahmed S A, Attia Mahmoud A
Department of Electrical Power and Machines Engineering, Faculty of Engineering, Ain Shams University, Cairo, Egypt.
Department of Electrical and Computer Engineering, University of Windsor, Windsor, ON, N9B 3P4, Canada.
Sci Rep. 2025 Jul 15;15(1):25656. doi: 10.1038/s41598-025-09408-x.
This study presents a novel multi-objective optimization framework supporting nations sustainability 2030-2040 visions by enhancing renewable energy integration, green hydrogen production, and emission reduction. The framework evaluates a range of energy storage technologies, including battery, pumped hydro, compressed air energy storage, and hybrid configurations, under realistic system constraints using the IEEE 9-bus test system. Results show that without storage, renewable penetration is limited to 28.65% with 1538 tCO/day emissions, whereas integrating pumped hydro with battery (PHB) enables 40% penetration, cuts emissions by 40.5%, and reduces total system cost to 570 k$/day (84% of the baseline cost). The framework's scalability is confirmed via simulations on IEEE 30-, 39-, 57-, and 118-bus systems, with execution times ranging from 118.8 to 561.5 s using the HiGHS solver on a constrained Google Colab environment. These findings highlight PHB as the most cost-effective and sustainable storage solution for large-scale renewable integration.
本研究提出了一个新颖的多目标优化框架,通过加强可再生能源整合、绿色氢生产和减排来支持各国2030 - 2040年的可持续发展愿景。该框架在现实系统约束条件下,使用IEEE 9节点测试系统评估了一系列储能技术,包括电池、抽水蓄能、压缩空气储能和混合配置。结果表明,在没有储能的情况下,可再生能源渗透率限制在28.65%,日排放量为1538吨二氧化碳,而将抽水蓄能与电池相结合(PHB)可实现40%的渗透率,减排40.5%,并将系统总成本降至57万美元/天(为基准成本的84%)。通过在IEEE 30节点、39节点、57节点和118节点系统上进行仿真,证实了该框架的可扩展性,在受限的谷歌Colab环境中使用HiGHS求解器时,执行时间为118.8至561.5秒。这些发现突出了PHB是大规模可再生能源整合中最具成本效益和可持续性的储能解决方案。