基于海洋捕食者算法的电力系统动态经济调度  

Dynamic Economic Dispatchof Power System Based on Marine Predator Algorithm

作　　者：陶琼 周孟然[1] TAO Qiong;ZHOU Meng-ran(School of Electrical and Information Engineering,Anhui University of Science and Technology,Huainan 232001,Anhui,China)

机构地区：[1]安徽理工大学电气与信息工程学院,安徽淮南232001

出　　处：《兰州文理学院学报（自然科学版）》2023年第6期60-66,共7页Journal of Lanzhou University of Arts and Science(Natural Sciences)

基　　金：煤炭安全精准开采国家地方联合工程研究中心开放基金(EC2021006)。

摘　　要：电力系统动态经济调度(Dynamic Economic Dispatch,DED)是电力部门最重要的优化任务之一,其目标函数非线性、不连续、高维度、强约束,非常具有挑战性.针对传统的海洋捕食者算法存在容易滞于局部解、收敛速度慢等缺点,提出了一种改进的海洋捕食者算法(IMPA).首先采用Logistic-Tent级联的混沌映射进行初始化种群,提高了初始解的均匀性;其次,对优化节点进行调整,优化自适应步长参数CF,增强了算法全局搜索性能;最后,采用了非对称性信息交流机制强化搜索代理跳出局部最优的能力.仿真分析了基准测试函数和5机组电力系统算例,并与其他几种算法对比.实验结果表明IMPA比改进前最优成本提高了23.29美元,各项评价指标均有改善,能够为电力部门提供成本更少的调度方案.Dynamic economic dispatch(DED)of power system is one of the most important optimization tasks in power sector.Its objective function is nonlinear,discontinuous,high dimension and strong constraint,which is very challenging.An improved Marine Predator Algorithm(IMPA)is proposed to solve the shortcomings of the traditional Marine predator algorithm,which tends to lag in the local solution and converge slowly.Firstly,a Logistic-Tent cascaded chaotic map is used to initialize the population,which improves the uniformity of the initial solution.Secondly,the cut-off point of the optimization stage is adjusted,and the adaptive step size parameter CF is optimized to enhance the global search intensity of the algorithm.Finally,asymmetric information exchange mechanism is used to strengthen the ability of search agent to escape from local optimal.The benchmark test function and the power system of 5 units are simulated.Compared with other algorithms,the experimental results show that IMPA increases the optimal cost by$23.29,which verifies the effectiveness of this method and can provide a dispatch scheme with less cost for the power department.

关 键 词：动态经济调度 IMPA Logistic-Tent级联混沌映射 自适应步长参数调整 非对称信息交流机制 

分 类 号：TM734[电气工程—电力系统及自动化]