基于ICOA算法的配电网分布式电源选址定容方法

庞广明; 王鹏飞; 田超; 杨博

doi:10.19912/j.0254-0096.tynxb.2023-0952

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太阳能学报 ›› 2024, Vol. 45 ›› Issue (10) : 211-219. DOI: 10.19912/j.0254-0096.tynxb.2023-0952

基于ICOA算法的配电网分布式电源选址定容方法

庞广明, 王鹏飞, 田超, 杨博

作者信息 +

LOCATION AND CAPACITY DETERMINATION METHOD OF DISTRIBUTED GENERATION IN DISTRIBUTION NETWORK BASED ON ICOA ALGORITHM

Pang Guangming, Wang Pengfei, Tian Chao, Yang Bo

Author information +

文章历史 +

摘要

针对分布式电源（DG）在配电网中的优化配置问题,考虑DG接入数量和不同功率因数对配电网有功损耗和母线电压分布的影响,提出一种基于改进黑猩猩优化（ICOA）算法的DG选址定容策略。首先,以系统运行有功损耗最小、电压稳定性指数最高、平均损耗最小为目标建立DG选址定容优化模型;然后,考虑DG接入数量对配电网优化运行指标的影响,利用CPLEX求解器确定DG最优接入数量;在此基础上,计及DG以整功率因数接入和变功率因数接入两种应用场景,利用ICOA对DG选址定容模型进行求解;最后,利用IEEE-33节点配电系统进行仿真验证分析。结果表明,相比于接入整功率因数的DG,接入变功率因数的DG可进一步降低系统运行有功损耗、改善母线电压分布;与传统算法相比,改进算法具有更高的收敛精度,可有效求解DG选址定容多目标优化问题。

Abstract

In response to the optimization configuration problem of distributed generation （DG） in the distribution network, this article considers the impact of the number of DG connections and different power factors on the active power loss and bus voltage distribution in the distribution network, and proposes a DG location and capacity determination strategy based on the improved chimpanzee optimization algorithm （ICOA）. Firstly, a DG location and capacity optimization model is established with the goal of minimizing active power loss, maximizing voltage stability index, and minimizing average loss during system operation; Then, considering the impact of the number of DG connections on the optimization operation indicators of the distribution network, the CPLEX solver is used to determine the optimal number of DG connections; On this basis, taking into account the two application scenarios of integrated power factor access and variable power factor access for DG, ICOA is used to solve the DG location and capacity model; Finally, simulation verification analysis is conducted using the IEEE-33 node distribution system. The results show that compared to DG with integrated power factor, DG with variable power factor can further reduce active power loss and improve bus voltage distribution during system operation; Compared with traditional algorithms, the improved algorithm has higher convergence accuracy and can effectively solve the multi-objective optimization problem of DG location and capacity.

导出引用

庞广明, 王鹏飞, 田超, 杨博. 基于ICOA算法的配电网分布式电源选址定容方法[J]. 太阳能学报. 2024, 45(10): 211-219 https://doi.org/10.19912/j.0254-0096.tynxb.2023-0952

Pang Guangming, Wang Pengfei, Tian Chao, Yang Bo. LOCATION AND CAPACITY DETERMINATION METHOD OF DISTRIBUTED GENERATION IN DISTRIBUTION NETWORK BASED ON ICOA ALGORITHM[J]. Acta Energiae Solaris Sinica. 2024, 45(10): 211-219 https://doi.org/10.19912/j.0254-0096.tynxb.2023-0952

中图分类号： TM721

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