基于区域间场景等值的配电网随机潮流加速算法

doi:10.19595/j.cnki.1000-6753.tces.230156

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摘要针对配电网随机潮流算法中需要对节点功率注入进行大量模拟所引起的计算效率低的问题,提出一种基于区域间场景等值的配电网随机潮流加速算法。首先,从配电网的拓扑连接规律出发,将各区域内节点功率注入对其他区域潮流的影响转换为对边界量的影响,并由此建立了基于边界量的多区域潮流模型;其次,提出一种区域间场景等值方法,快速等值引起其他区域相同潮流变化的功率注入场景;再次,设计了一种随机潮流的分布式求解算法,在求解过程中各区域通过交换边界等值场景集并结合局部功率注入信息重新构造潮流方程,分布式地求解各区域内的随机潮流;最后,通过IEEE 118节点测试系统进行算例分析,验证了所提方法的准确性,且该方法能够显著提高计算效率。

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关键词 ：配电网, 场景等值, 分布式光伏, 随机潮流

Abstract：In the stochastic power flow algorithm of distribution network, the power injection needs a lot of simulation, which will lead to the problem of low computational efficiency. In recent years, scholars have made some achievements in the research of scene reduction, but the designed methods may still face the problem of low computational efficiency after being implemented in systems with too many nodes. Therefore, this paper proposes a stochastic power flow acceleration algorithm for distribution networks based on inter-regional scenario equivalence. Based on the existing mainstream scenario reduction method, the stochastic power flow calculation is further accelerated by adding scenarios that lead to the injection of the same boundary quantity in other regions.
Firstly, based on the topology connection law of distribution network, the influence of power injection scenarios in each region on power flow in other regions is transformed into the influence on its boundary quantities, and the multi-regional power flow model that affects each other through boundary quantities is established. Secondly, an inter-regional scenario equivalence method is proposed, which can quickly equalize scenarios that cause the same power flow change in other regions. Then, a distributed solution algorithm for stochastic power flow is designed. Each region completes the distributed solution of stochastic power flow by exchanging boundary equivalent scenarios and combining local power injection information.
According to this method, the IEEE 118 node test system is solved with partition and stochastic power flow. Simulation results show that the proposed distributed algorithm converges in all regions. In terms of calculation accuracy, the maximum errors of voltage and active power between the scene equivalent imitation method proposed in the main region and the Monte Carlo simulation method are 0.069% and 0.98% respectively, while the maximum errors of voltage and active power between the scene equivalent imitation method proposed in the sub-region and the Monte Carlo simulation method are 0.058% and 0.003% respectively. It can be considered that the calculation results are consistent. In terms of computational efficiency, the number of scenarios required by Monte Carlo simulation and distributed solution algorithms is 531 441 and 43 497, respectively. Compared with Monte Carlo simulation, the acceleration ratio of distributed solution method is 11.32, which effectively reduces the simulation scenarios required by stochastic power flow.
Through the example analysis, the following conclusions can be drawn: (1) By merging the power injection scenarios that cause the same boundary quantity in other regions, the redundant information in the transmission process can be effectively reduced. (2) The proposed stochastic power flow distributed algorithm does not require centralized processing and unified calculation of the stochastic power flow injection samples of each node, but only needs to solve the stochastic power flow results through the power flow samples of each region and exchange the equivalent scenario information. (3) Compared with the existing centralized stochastic power flow algorithm, the distributed stochastic power flow algorithm can calculate more samples under the same time constraint. In the next step, the point estimation method can be combined with the proposed inter-zone scenario equivalence method to improve its calculation accuracy and enrich the distribution network region division method.

Key words： Distribution network scene equivalent distributed photovoltaic distributed stochastic power flow

收稿日期: 2023-02-14

PACS:

TM711

基金资助:内蒙古自治区科学技术厅揭榜挂帅项目（2022JBGS0044）和东北电力大学博士科研启动基金（BSJXM-2021102）资助

通讯作者: 朱星旭男,1989年生,讲师,硕士生导师,研究方向为电力系统运行与控制。E-mail：neduzxx@163.com

作者简介: 李军徽男,1976年生,教授,博士生导师,博士,研究方向为新能源发电运行与控制,储能技术在电力系统中的应用。E-mail：lijunhui@neepu.edu.cn

引用本文:

李军徽, 赵寒杰, 朱星旭, 郭琦, 李翠萍. 基于区域间场景等值的配电网随机潮流加速算法[J]. 电工技术学报, 2024, 39(7): 1957-1970. Li Junhui, Zhao Hanjie, Zhu Xingxu, Guo Qi, Li Cuiping. Stochastic Power Flow Acceleration Algorithm of Distribution Network Based on Scene Equivalence between Regions. Transactions of China Electrotechnical Society, 2024, 39(7): 1957-1970.

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