摘要
针对麻雀搜索算法(Sparrow Search Algorithm,SSA)在解决高维、非线性的分布式电源(Distributed Generation,DG)优化配置问题中求解精度与稳定性不足的问题,提出一种改进麻雀搜索算法进行求解。通过引入Tent混沌提高初始解的质量,利用Levy飞行策略和柯西高斯变异,增强算法搜索方向的多元性以及跳出局部最优的能力,针对算法在工程应用中产生大量无效麻雀的问题,优化了麻雀位置更新公式,以提高SSA的工程实用性。分别用标准SSA、ISSA、蝴蝶优化算法(Butterfly Optimization Algorithm,BOA)、鲸鱼优化算法(Whale Optimization Algorithm,WOA)测试基准函数,对比验证ISSA的有效性,并将ISSA应用于IEEE33节点系统的DG化配置模型求解,所求的DG配置方案能更大程度地降低配电网有功损耗与电压偏差。
Inorder to solve the problem of insufficient precision and stability of Sparrow Search Algorithm(SSA)in solving the high-dimensional and nonlinear Distributed Generation(DG)optimal configuration problem,an improved SSA is proposed.The quality of initial solution is improved by introducing Tent chaos,and the diversity of search directions and the ability to jump out of local optimum are enhanced by using Levy flight strategy and Cauchy Gaussian mutation.Finally,aiming at the problem that the algorithm produces a large number of invalid sparrows in engineering application,the sparrow position updating formula is optimized to improve the engineering practicability of SSA.The benchmark functions are tested by standard SSA,ISSA,Butterfly Optimization Algorithm(BOA)and Whale Optimization Algorithm(WOA)respectively,and the validity of ISSA is verified by comparison.ISSA is applied to solve the DG configuration model of IEEE33-bus system,and the DG configuration scheme obtained can reduce the power loss and voltage deviation of distribution network to a greater extent.
作者
王海瑞
鲜于建川
WANG Hairui;XIANYU Jianchuan(School of Business,Shanghai Dianji University,Shanghai 201306,China)
出处
《计算机工程与应用》
CSCD
北大核心
2021年第20期245-252,共8页
Computer Engineering and Applications
基金
国家自然科学基金(52002243)。
