期刊文献+

基于高斯-柯西变异帝国竞争算法的微电网优化调度 被引量:1

Optimal Dispatching of Microgrid Based on Gauss-Cauchy Mutation Imperialist Competitive Algorithm
下载PDF
导出
摘要 为提高微电网运行经济性,建立了以微电网综合运行成本最小为目标函数的微电网优化调度模型。利用高斯变异和柯西变异对帝国竞争算法进行改进,采用高斯-柯西帝国竞争算法对微电网优化调度模型进行求解,并与其他优化算法对比分析。结果表明,高斯-柯西帝国竞争算法求解的微电网综合运行成本为4485.62元,低于其他优化算法;调度方案能够优化微电网系统内各分布式电源出力,合理与上级配电网交换电能,使微电网综合运行成本最小。验证了模型的正确性及求解方法的优越性。 In order to improve the operation economy of microgrid,an optimal dispatching model of microgrid was established with the objective function of minimizing the comprehensive operation cost of microgrid.Gaussian mutation and Cauchy mutation were used to improve the imperial competition algorithm,and Gaussian-Cauchy imperial competition algorithm was used to solve the microgrid optimal scheduling model,and the algorithm was compared with other optimization algorithms.The results show that the integrated operation cost of the microgrid solved by the Gauss-Cauchy empire competition algorithm is 4485.62 yuan,which is lower than that by other optimization algorithms.The dispatching scheme can optimize the output of each distributed generation in the microgrid system,reasonably exchange energy with the superior distribution network,and minimize the integrated operation cost of the microgrid.It verifies the correctness of the model and the superiority of the solution method.
作者 陈海旭 余畅文 卢银均 陈磊 马小龙 刘闯 刘炬 Chen Haixu;Yu Changwen;Lu Yinjun;Chen Lei;Ma Xiaolong;Liu Chuang;Liu Ju(College of Electrical and New Energy,Three Gorges University,Yichang Hubei 443000,China;Fuzhou Power Supply Company,State Grid Fujian Electric Power Co.,Ltd.,Fuzhou Fujian 350000,China;Jingmen Power Supply Company,State Grid Hubei Electric Power Co.,Ltd.,Jingmen Hubei 448000,China)
出处 《电气自动化》 2024年第1期1-4,共4页 Electrical Automation
基金 国家自然科学基金资助项目“基于惯量削弱量责任分担的风电场虚拟惯性补偿控制方法”(51907104)。
关键词 微电网 优化调度 帝国竞争算法 高斯变异 柯西变 microgrid optimized dispatching imperialist competitive algorithm gaussian variation cauchy variation
  • 相关文献

参考文献11

二级参考文献134

共引文献167

同被引文献10

引证文献1

相关作者

内容加载中请稍等...

相关机构

内容加载中请稍等...

相关主题

内容加载中请稍等...

浏览历史

内容加载中请稍等...
;
使用帮助 返回顶部