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基于人工智能的电力分配网络的综合核混合可再生能源系统的最佳规划

Samira M Nassar¹, A A Saleh², Ayman A Eisa²

¹Department of Nuclear Safety and Radiological Emergencies, NCRRT, Egyptian Atomic Energy Authority, Cairo, Egypt. Samira.nassar@eaea.org.eg.

Scientific reports

|July 17, 2025

概括

微型核反应堆和可再生能源的整合为电网提供了可持续的解决方案. 核可再生混合能源系统 (N-R HES) 的成本和功率损耗最低,减少了对环境的影响.

科学领域:

电气工程电气工程
可持续能源系统可持续能源系统
优化技术优化技术

背景情况:

随着电力需求的增加,需要可持续的能源替代品.
传统能源带来了环境挑战.
包括微型反应堆在内的小规模核电为现代电网提供了可行的选择.

研究的目的:

开发和优化混合能源系统 (HES) 以改善电力分配.
评估核可再生混合能源系统 (N-R HES) 与其他配置相比.
尽量减少主动功率损耗 (APL) 和净当前成本 (NPC),同时减少温室气体 (GHG) 排放.

主要方法:

使用单个和多目标函数HES的数学建模.
使用白优化算法的优化.
在IEEE 33总线和IEEE 69总线分布网络上使用MATLAB.NET进行模拟和分析.

主要成果:

与化石燃料和可再生化石燃料系统相比,N-R HES在系统效率,成本效益和环境影响方面表现优异.
该N-R HES配置实现了最低的净当前成本 (NPC) 和主动功率损耗 (APL).
优化改进了电压配置,并减少了整体系统损失和排放.

结论:

N-R HES是可持续能源生产和脱碳的最有效解决方案.
微型核反应堆与可再生能源的整合提供了显著的经济和环境效益.
拟议的优化方法提供了一个强大的框架,用于设计高效的HES.

关键词:

核能是核能来源的能源.优化技术的优化技术可再生能源是可再生的能源.

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