通过改进的烟花算法优化和运行多能量合微电网 - - 混青跳跃算法.
Xubo Yue1, Jing Zhang2, Junhui Guo2
1Taizhou Hongchuang Group, Taizhou, China.
PeerJ. Computer science
|August 15, 2024
概括
本研究介绍了一种改进的烟花算法 (IFWA) 和混合的青跳跃算法 (SFLA),以优化多能微电网. IFWA-SFLA的方法提高了微电网的稳定性,能源流量管理,并减少了电压波动.
科学领域:
- 电气工程 电气工程
- 可再生能源系统可再生能源系统
- 优化算法 优化算法
背景情况:
- 多能源合微电网面临着优化和运营挑战,影响系统稳定性和可靠性.
- 综合性能源系统需要先进的解决方案,以实现高效的能源管理.
- 现有的算法可能无法充分解决这些系统中复杂的相互依存关系.
研究的目的:
- 提出和验证一个改进的烟花算法 (IFWA) 与混合的青跳跃算法 (SFLA) 集成,用于微电网优化.
- 开发一个多目标优化模型,解决主动电网损失和静电压的问题.
- 提高多能源合微电网的稳定性和可靠性.
主要方法:
- 开发了一种改进的烟花算法 (IFWA),结合了适应性资源分配和社区遗传策略.
- 制定了一个多目标优化模型,考虑了活性电源网络损失和静电压.
- 混合青跳跃算法 (SFLA) 用于解决受约束的多目标优化问题.
主要成果:
- IFWA-SFLA方法在优化微电网稳定性方面表现出卓越的表现.
- 实现了微电网内的电能流的有效管理.
- 通过模拟观察到电压波动的显著减少.
结论:
- 拟议的IFWA-SFLA方法对于优化多能源合微电网是有效的.
- 该方法通过提高稳定性和管理能源流量来提高系统可靠性.
- 基于IFWA的微电网储能逆变器控制策略的进一步调查是有必要的.
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