摘要
针对温差发电系统非均匀温度场条件下,功率电压曲线呈现多峰特性,传统粒子群算法易陷入到局部最优,布谷鸟算法收敛时间慢等问题,提出了改进布谷鸟算法与粒子群算法相混合的最大功率点跟踪控制算法。引入自适应发现概率,扩大种群搜索范围,以最小收敛时间为约束函数,通过参数寻优确定最佳功率区间划分临界点参数,将寻优过程划分为粒子群快速粗寻优与改进布谷鸟稳态精寻优两个阶段,以提升算法的收敛速度和发电效率。仿真结果表明,本算法在均匀温度场条件下,收敛时间0.24 s,发电效率99.89%,在非均匀温度场条件下,收敛时间0.13 s,发电效率99.92%,均优于其他算法,该算法收敛迅速,跟踪精度高,并通过了基准测试函数测试,验证了该算法的有效性和通用性。
Under the condition of non-uniform temperature field in thermoelectric power generation system,the power voltage curve has multi-peak characteristics,the traditional particle swarm optimization algorithm is easy to fall into the local optimum,and the convergence time of cuckoo search algorithm is slow,so a maximum power point tracking control algorithm based on improved cuckoo search algorithm and particle swarm optimization algorithm is proposed.With the minimum convergence time as the constraint function,the optimal power interval is determined by parameter optimization and the critical point parameters is divided.The optimization process is divided into two stages:particle swarm fast coarse optimization and improved cuckoo search steady precision optimization,so as to improve the convergence speed and power generation efficiency of the algorithm.The simulation results show that the proposed algorithm is superior to other algorithms when the convergence time is 0.24 s and the power generation efficiency is 99.89%under the condition of uniform temperature field,and when the convergence time is 0.13 s and the power generation efficiency is 99.92%under the condition of non-uniform temperature field.The algorithm converges quickly and has high tracking accuracy,and has passed the benchmark test function test.The effectiveness and universality of the algorithm are verified.
作者
李成颖
张江
莫思特
李碧雄
龙西亭
Li Chengying;Zhang Jiang;Mo Site;Li Bixiong;Long Xiting(College of Electrical Engineering,Sichuan University,Chengdu 610065,China;College of Architecture and Environment,Sichuan University,Chengdu 610065,China;Institute of Deep Earth Sciences and Green Energy,Shenzhen University,Shenzhen 518060,China)
出处
《电子测量技术》
北大核心
2023年第18期76-84,共9页
Electronic Measurement Technology
基金
国家重点研发计划(2021YFB1507400)项目资助
关键词
温差发电系统
最大功率点跟踪
布谷鸟算法
粒子群算法
非均匀温度场
thermoelectric power generation
maximum power point tracking
cuckoo search algorithm
particle swarm optimization algorithm
non-uniform temperature distribution