摘要
针对微电网可再生能源不稳定性对电网造成的冲击,合理优化配置分布式能源以实现更为经济和环保的目标。提出了改进的鲸鱼算法,通过tent映射提高了初始种群的均匀程度,建立改进的精英反向学习方法提高算法跳出局部最优解的能力,通过自适应参数优化调节鲸鱼算法搜索策略的选取,并且选取阿基米德螺线替换原有的螺旋收缩方式,加强局部搜索能力,采用多种基准函数验证了算法性能上的提高,并以污染治理费用和运行费用作为目标函数,针对多种电源类型的微电网进行优化,通过仿真试验对比其他算法验证改进鲸鱼算法的有效性和实用性。
Aimed at the impact of the instability of renewable energy on the power grid,the distributed energy was rationally optimized to achieve the goal of more economy and environmentally friendly.An improved whale algorithm was proposed,which improves the evenness of the initial population through tent mapping,an improved elite reverse learning method was established to improve the ability of the algorithm to jump out of the local optimal solution,the selection of the search strategy of the whale algorithm was adjusted through adaptive parameter optimization,and Archimedes spiral was selected to replace the original spiral contraction mode to enhance the local search ability.A variety of benchmark functions were used to verify the improvement of the algorithm performance,and the pollution control cost and operating cost were used as objective functions to optimize microgrids of various power types.The effectiveness and practicality of the improved whale algorithm were verified through simulation experiments and comparison with other algorithms.
作者
王骏玮
岳云涛
李炳华
WANG Jun-wei;YUE Yun-tao;LI Bing-hua(School of Electrical and Information Engineering,Beijing University of Civil Engineering and Architecture,Beijing 100044,China;CCDI Group(Beijing),Beijing 100013,China)
出处
《科学技术与工程》
北大核心
2023年第29期12577-12584,共8页
Science Technology and Engineering
基金
北京市自然科学基金(4204093)。
关键词
微电网
鲸鱼优化算法
混沌映射
改进精英反向学习
分布式电源
阿基米德螺线
microgrid
whale optimization algorithm
chaotic map
improved elite reverse learning
distributed power
Archimedes spiral
