混合微电网的多目标优化用于能源三难题目标,使用粘液模具算法
Alok Kumar Shrivastav1,2, Soham Dutta3,4
1Department of Electrical Engineering, JIS College of Engineering, Kalyani, 741235, India.
Scientific reports
|August 10, 2025
概括
污泥模具算法优化混合微电网,以确保能源安全,可负担性和可持续性. 这种方法可以显著降低能源损耗和成本,同时提高电力可靠性.
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:
- 混合微电网 (HMG) 对于整合多种能源至关重要.
- 在HMG中平衡能源安全,可负担性和可持续性 (能源三难题) 是一个复杂的挑战.
- 现有的优化方法往往不能同时解决所有三难题目标.
研究的目的:
- 使用模算法 (SMA) 呈现HMG的多目标优化.
- 针对能源三难题的目标:能源安全,负担能力和可持续性.
- 评估SMA的性能与传统算法和基准工具相比.
主要方法:
- 使用Slime Mould算法 (SMA) 的多目标优化.
- 将可再生能源,柴油发电机和电动汽车 (EV) 电池作为分布式能源 (DER) 的整合.
- 对电动汽车电池的双向车辆到电网 (V2G) 能力的建模.
主要成果:
- SMA实现了12.3%的功耗损失减少,并提高了9.8%的平衡能源成本 (LCOE).
- 电源损失概率 (LPSP) 降至0.012,超过了HOMER (0.021) 和Salp Swarm算法 (SSA) (0.017).
- 由于其勘探开发平衡,SMA表现出卓越的融合速度和计算效率.
结论:
- 污泥模具算法在优化混合微电网方面非常有效,可以解决能源三难题.
- 双向V2G支持的电动汽车电池的新型集成提高了HMG的性能.
- 未来的研究应该解决实际实施的可扩展性和实时计算需求.
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