基于改进的混乱演变优化算法,风能-光伏-储能混合系统的最佳容量配置
Yingchao Dong1, Xiang Zhou2, Xiguo Cao2
1School of Energy Engineering, Xinjiang Institute of Engineering, Urumqi, 830023, China. dycxju@163.com.
Scientific reports
|February 20, 2026
概括
这项研究优化了风能光伏储能 (WPS) 系统,用于高可再生能源的电网. 改进的混乱进化算法增强了容量规划,提高了成本效益和系统稳定性.
科学领域:
- 可再生能源系统工程可再生能源系统工程
- 优化算法 优化算法
- 电网整合 电网整合
背景情况:
- 高度的可再生能源透率给电网稳定性和经济可行性带来了挑战.
- 风能光伏存储 (WPS) 系统提供了一个有前途的解决方案,但需要最佳容量配置.
- 现有的规划模型与复杂的非线性约束和经济要求作斗争.
研究的目的:
- 为风能光伏储能系统 (WPS) 开发一个最佳容量配置模型.
- 解决高可再生能源电网中的复杂非线性约束和经济因素.
- 提高WPS容量规划的成本效益和稳定性.
主要方法:
- 开发了一种多能源协作容量规划模型.
- 制定了一项能源管理策略,以捕捉风能,光伏和储能之间的相互依存关系.
- 提出了一种改进的混乱进化优化算法 (ICEO),具有自学扰动和自适应局部搜索.
主要成果:
- 与基准函数上的最先进的元启发学相比,ICEO展示了优越的解决方案质量和稳定性.
- 在实践WPS案例研究中的模拟验证了算法的有效性.
- 拟议的方法显著提高了WPS容量规划中的成本效益.
结论:
- 开发的ICEO算法有效地解决了WPS容量规划中的复杂优化问题.
- 综合方法提高了具有高可再生能源份额的电网的经济可行性和可靠性.
- 这项研究为优化混合可再生能源系统提供了一个强大的框架.
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