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基于改进黏菌算法的分布式光伏发电并网规划

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针对分布式光伏不合理布局可能给配电网带来的重大冲击提出了一种考虑负荷与光伏系统出力时序性的双层优化分布式光伏选址定容模型.上层优化旨在筛选一组包含光伏接入节点和装机容量的组合数据,下层优化以网损、电压偏移量和投资成本最小为目标函数,在解决高维度、非线性的功率因数优化问题同时将最优规划结果反馈给上层优化层,从而确定分布式光伏的最佳接入节点和装机容量.此外,引入改进交叉算子的自适应人工蜂群黏菌算法求解该模型,其具有优秀的全局搜索能力、局部开发能力和个体更新机制,针对此类模型能够获得更加理想的高质量解.仿真结果表明,改进黏菌算法在兼顾经济性的同时对配电网的有功损耗、电能质量的改善效果显著优于其他算法.
Integration Planning of Distributed Photovoltaic Generation Based on Improved Slime Mould Algorithm
In view of the unreasonable layout of distributed photovoltaics will bring major impact to the distribution network,a double-layer optimized locating and sizing model of distributed photovoltaic considering the load and PV system output timing is proposed.The upper-layer optimization aims to screen a set of combined data of PV access nodes and installed capacity.The lower-layer optimization takes the network loss,voltage offset and minimum investment cost as the objective function,and feeds back the optimal planning results to the upper optimization layer while solving the high-dimensional and nonlinear power factor optimization problem,so as to determine the optimal access node and installed capacity of distributed photovoltaics.In addition,the adaptive artificial bee colony slime mold algorithm with improved crossover operator is introduced to solve the model,which has excellent global search ability,local development ability and renewal mechanism of the individual,which can obtain more ideal high-quality solutions for such models.The simulation results show that the improved slime mould algorithm not only considers the economy,but also significantly improves the active power loss and power quality of the distribution network compared to other algorithms..

distributed photovoltaiclocating and sizingimproved slime mould algorithmdistribution networkpower factor

杨海柱、刘森、张鹏、白亚楠

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河南理工大学电气工程与自动化学院,河南 焦作 454000

天津大学电气自动化与信息工程学院,天津 300072

分布式光伏 选址定容 改进黏菌算法 配电网 功率因数

2024

南方电网技术
南方电网科学研究所有限责任公司

南方电网技术

CSTPCD北大核心
影响因子:1.42
ISSN:1674-0629
年,卷(期):2024.18(11)