在微电网中最大限度地储存能量,使用修改后的多层优化器
Qingpu Hu1, Guoxin Zhao1, Jian Hu1
1Department of Electrical Engineering, Yellow River Conservancy Technical Institute, Kaifeng, Henan, 475004, China.
Heliyon
|November 9, 2023
概括
本研究介绍了修订的多元优化算法 (AMVOA),用于设计具有储能功能的经济高效和可靠的微电网. AMVOA方法优化了微电网配置,增强了可再生能源的整合和电力管理.
科学领域:
- 电气工程 电气工程
- 优化算法 优化算法
- 可再生能源系统可再生能源系统
背景情况:
- 微电网为电力网络挑战提供了解决方案,储能对其稳定性至关重要.
- 联合冷却,加热和电源 (CCHP) 系统在传统电网中面临整合困难.
研究的目的:
- 提出一种新的微电网设计方法,使用修订的多元优化算法 (AMVOA) 进行增强的能源存储集成.
- 尽量减少微电网的整体成本,同时确保可靠性和可持续性.
- 为了评估AMVOA与其他最先进的优化算法的性能.
主要方法:
- 开发和应用修订的多元宇宙优化算法 (AMVOA),灵感来自多元宇宙理论.
- 设计和分析微电网的两种混合可再生能源系统 (HRES) 场景:一个是光伏,风能,柴油和电池存储,另一个是光伏,柴油和电池存储.
- 将AMVOA与其他五种优化算法进行比较:进化算法 (EA),修改的虫优化算法 (MGOA),改进的灰狼优化算法 (IGWOA),改进的算术优化算法 (IAOA) 和原始的MVOA.
主要成果:
- 在第1场景 (风力/光伏/DG/BESS) 中,AMVOA算法取得了最佳结果,净当前成本 (NPC) 为299,010美元,能源成本为0.2309美元/kWh.
- 提出的方法成功地集成了84.86%的可再生能源,同时满足了系统限制.
- 在情景2 (PV/DG/BESS) 中,最佳尺寸导致NPC为333,800美元,能源成本为0.3451美元/千瓦时.
- 与其他测试的算法相比,AMVOA表现出优越的融合和高效的电源管理.
结论:
- 基于AMVOA的策略是有效的设计最佳的微电网与储能.
- 提出的方法可以作为一个有价值的决策工具,用于微电网的规划和设计,特别是可再生能源的整合.
- 建议进行进一步的研究,以评估拟议的微电网配置的稳定性,实用性和可靠性.
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