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基于增强卷尾猴搜索算法的分布式电源定容选址方法

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  • 国家科技期刊平台
  • NETL
  • NSTL
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在新能源特征和分布情况的影响下,大规模的分布式电源(Distributed Generator,DG)与电动汽车(Electric Ve-hicle,EV)接入电网,使得电网的结构和运行方式发生了根本性变化.为了提高DG的利用率,降低电网波动,以配电网的年综合成本最小为目标函数,在节点电压、支路功率等安全约束的条件下,建立包含EV充电的配电网DG定容选址的规划模型,并提出一种增强卷尾猴搜索算法对模型进行求解.该算法将野马优化算法中领导者选择的社会行为对传统卷尾猴搜索算法进行改进,以避免出现陷入局部最优的情况.最后对IEEE-33节点典型配电网系统进行仿真计算,并与其他算法结果进行比较,验证本文提出的算法的优越性.
Method of Location and Capacity Determination for Distributed Generator Based on Enhanced Capuchin Search Algorithm
Under the influence of the characteristics and distribution of new energy,large-scale distributed generator(DG)and electric vehicles(EV)are connected to the distributed network,which makes a fundamental change in the structure and opera-tion mode of the power grid.In order to improve the utilization rate of DG and reduce the fluctuation of the distributed network,the minimum annual comprehensive cost of the distribution generation is taken as the objective function.Under the constraint conditions of node voltage and branch power,a planning model of constant volume location of distributed network DG is estab-lished including EV charging,and an enhanced capuchin search algorithm is proposed to solve the model.This algorithm im-proves the social behaviors selected by the leader in the wild horse optimizer on the traditional capuchin search algorithm to avoid falling into the local optimal situation.Finally,the typical distribution system of IEEE-33 bus is simulated and compared with other algorithms to verify the superiority of the proposed algorithm.

distributed generator(DG)location and capacity determinationelectric vehicle(EV)distribution networken-hanced capuchin search algorithm(ECapSA)

李佳多、闫秀英

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西安建筑科技大学建筑设备科学与工程学院,陕西 西安 710055

分布式电源 定容选址 电动汽车 配电网 增强卷尾猴搜索算法

国家自然科学基金面上项目陕西省低能耗建筑节能创新示范工程研究项目

522781252017DXM-GY-025

2024

10.3969/j.issn.1006-2475.2024.04.005

计算机与现代化
江西省计算机学会 江西省计算技术研究所

计算机与现代化

CSTPCD
影响因子：0.472
ISSN：1006-2475
年,卷(期)：2024.(4)
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