NGO在光储微网系统功率分配中的应用  

Application of NGOs in Power Distribution of Photovoltaic Storage Microgrid Systems

作　　者：马丙泰 徐庆锋 彭逸 王江伟 张宝芳[1] 郭华杰 MA Bingtai;XU Qingfeng;PENG Yi;WANG Jiangwei;ZHANG Baofang;GUO Huajie(Guangxi Vocational College of Water Resources and Electric Power,Guangxi Nanning 530023,China)

机构地区：[1]广西水利电力职业技术学院,广西南宁530023

出　　处：《广西电力》2024年第2期67-73,86,共8页Guangxi Electric Power

基　　金：2024年度广西高校中青年科研基础能力提升项目(2024KY1142)。

摘　　要：光伏发电混合储能系统中,为降低常见智能算法参数优化VMD中分解模态数(K)、二次惩罚因子(α)取值不合理对系统重构功率准确性的影响。提出采用一种新的智能算法即北方苍鹰(NGO)算法进行优化分析;利用NGO参数优化VMD以更加稳定的获得[K,a]最优组合,并将寻优结果应用于微网系统剩余功率分解中,从而提升重构功率与原始剩余功率信号重合程度,将剩余功率合理的分配给混合储能系统,优化储能系统初次功率分配及容量配置等问题。算例分析中,通过与粒子群及乌燕鸥算法参数优化VMD结果进行对比,并结合对称平均绝对百分误差(SMAPE)分析功率重构误差,验证了所述方法的有效性与优越性。In order to reduce the unreasonable values of common intelligent algorithm optimize the decomposition mode number(K)and quadratic penalty factor(a)parameters in VMD,which can impact the system reconstruction power accuracy in the hybrid energy storage system of photovoltaic power generation,a new intelligent algorithm,the Northern Goshawk Optimization(NGO)algorithm,is proposed for optimization analysis.The NGO parameters are used to optimize the VMD to obtain the optimal combination of[K,a]more stably,and the optimization results are applied to the residual power decomposition of the microgrid system,so as to improve the degree of overlap between the reconstructed power and the original residual power signal,reasonably allocate the residual power to the hybrid energy storage system,and optimize the primary power allocation and capacity configuration of the energy storage system.In the case analysis,the effectiveness and superiority of the proposed method are verified by comparing the VMD results with the parameter optimization of particle swarm and black tern algorithms,and analyzing the power reconstruction error by combining the Symmetric Mean Absolute Percentage Error(SMAPE).

关 键 词：剩余功率 参数优化 重构功率 北方苍鹰算法 对称平均绝对百分误差 

分 类 号：TM73[电气工程—电力系统及自动化]