Intelligent Terminals Optimal Configuration Considering Flexible Resource Adjustment and Reliability

HE Xianyi; XIONG Wei; LU Zhiyang; YUAN Xufeng; ZHANG Chao

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Intelligent Terminals Optimal Configuration Considering Flexible Resource Adjustment and Reliability

HE Xianyi, XIONG Wei, LU Zhiyang, YUAN Xufeng, ZHANG Chao

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Abstract

[Objective] With the large-scale integration of flexible resources such as distributed generation (DG), energy storage systems (ESS), and soft open points (SOP) in distribution networks, the traditional “two-remote” and “three-remote” terminal configuration methods are no longer sufficient to meet the needs of automated control. There is an urgent need to introduce “four-remote” terminals for coordinated configuration. [Methods] Considering the functional characteristics of “three-remote” and “four-remote” terminals, a two-layer optimization configuration method for intelligent terminals is proposed. The upper-layer planning aims to minimize the comprehensive cost, including equipment investment and maintenance costs, wind and solar curtailment costs, and power outage losses, while ensuring the global observability of the distribution network. A terminal location optimization model is constructed. The lower-layer operation, based on the upper-layer planning results, establishes a multi-objective optimization model for N-1 fault recovery scenarios, targeting the minimization of power outage losses, wind and solar curtailment costs, and voltage deviations. The proposed model is solved using a hybrid algorithm combining the slime mould algorithm (SMA) and second-order cone programming. [Results] Validation test case shows that the proposed method reduces the comprehensive cost by 69.15% and 7.11% compared to scenarios without terminal configuration and with only “three-remote” terminal configuration, respectively. It improves power supply reliability by 0.026 1% and 0.002 2%, reduces total wind and solar curtailment by 37.79% and 4.46%, and decreases voltage deviations by 53.04% and 49.43%. [Conclusions] The proposed configuration method demonstrates significant advantages in improving investment economics, power supply reliability, renewable energy integration capability, and voltage quality. It also accommodates various flexible resource scenarios, providing a theoretical basis for the coordinated configuration of “three-remote” and “four-remote” terminals in flexible distribution networks.

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flexible resources / intelligent terminal / two-layer modelling / fault reconfiguration / reliability

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HE Xianyi, XIONG Wei, LU Zhiyang, YUAN Xufeng, ZHANG Chao. Intelligent Terminals Optimal Configuration Considering Flexible Resource Adjustment and Reliability[J]. Electric Power Construction. 0

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[1] 高志远, 张晶, 庄卫金, 等. 关于新型电力系统部分特点的思考[J]. 电力自动化设备, 2023, 43(6): 137-143, 151.
GAO Zhiyuan, ZHANG Jing, ZHUANG Weijin, et al.Thoughts on some characteristics of new style power system[J]. Electric Power Automation Equipment, 2023, 43(6): 137-143, 151.
[2] 华昊辰, 张洲赫, 邹奕群, 等. 新型电力系统需求侧灵活性资源低碳协同优化研究综述[J]. 电力建设, 2025, 46(6): 60-75.
HUA Haochen, ZHANG Zhouhe, ZOU Yiqun, et al.Review of low-carbon co-optimization research on demand-side flexibility resources for new power systems[J]. Electric Power Construction, 2025, 46(6): 60-75.
[3] 刘思言, 姜东翔, 唐壮. 基于图强化学习的配电网源网荷储协同优化调度[J]. 供用电, 2025, 42(11): 37-46.
LIU Siyan, JIANG Dongxiang, TANG Zhuang.Coordinated optimal dispatching of source-grid-load-storage in distribution network based on graph reinforcement learning[J]. Distribution & Utilization, 2025, 42(11): 37-46.
[4] 杨波, 王辰, 杨慎全, 等. 配电网分布式光伏集群的分散自适应发电控制策略[J]. 供用电, 2025, 42(11): 95-103.
YANG Bo, WANG Chen, YANG Shenquan, et al.Decentralized adaptive generation control strategy for distributed photovoltaic clusters in distribution networks[J]. Distribution & Utilization, 2025, 42(11): 95-103.
[5] 鲍红焉, 刘吉成, 刘子毅, 等. 考虑电氢混合储能容量配置的主动配电网双层优化模型[J]. 中国电力, 2025, 58(10): 27-38.
BAO Hongyan, LIU Jicheng, LIU Ziyi, et al.A two-layer optimization model for active distribution networks considering electric-hydrogen hybrid energy storage capacity allocation[J]. Electric Power, 2025, 58(10): 27-38.
[6] 吉兴全, 刘健, 叶平峰, 等. 计及灵活性与可靠性的综合能源系统优化调度[J]. 电力系统自动化, 2023, 47(8): 132-144.
JI Xingquan, LIU Jian, YE Pingfeng, et al.Optimal scheduling of integrated energy system considering flexibility and reliability[J]. Automation of Electric Power Systems, 2023, 47(8): 132-144.
[7] 史训涛, 柯清派, 袁智勇, 等. 考虑光伏和负荷随机性的含柔性开关配电网故障重构[J]. 南方电网技术, 2020, 14(7): 56-61.
SHI Xuntao, KE Qingpa, YUAN Zhiyong, et al.Fault reconfiguration of distribution networks with soft open points considering the uncertainties of photovoltaics and loads[J]. Southern Power System Technology, 2020, 14(7): 56-61.
[8] 金凡凡, 郭瑞鹏, 林振智, 等. 考虑配电网供电可靠性与经济性的FTU优化配置[J]. 电力自动化设备, 2024, 44(12): 132-139.
JIN Fanfan, GUO Ruipeng, LIN Zhenzhi, et al.Optimal placement of FTUs considering power supply reliability and economy of distribution network[J]. Electric Power Automation Equipment, 2024, 44(12): 132-139.
[9] 陈东新, 武志刚. 配电自动化终端布点优化的动态规划研究[J]. 电力系统保护与控制, 2017, 45(12): 1-8.
CHEN Dongxin, WU Zhigang.Dynamic planning of distribution automation terminal units placement optimization[J]. Power System Protection and Control, 2017, 45(12): 1-8.
[10] 王旭东, 梁栋, 曹宝夷, 等. 三遥配电自动化终端的优化配置[J]. 电力系统及其自动化学报, 2016, 28(2): 36-42.
WANG Xudong, LIANG Dong, CAO Baoyi, et al.Optimal placement of three remote distribution automation terminal units[J]. Proceedings of the CSU-EPSA, 2016, 28(2): 36-42.
[11] 刘健, 程红丽, 张志华. 配电自动化系统中配电终端配置数量规划[J]. 电力系统自动化, 2013, 37(12): 44-50.
LIU Jian, CHENG Hongli, ZHANG Zhihua.Planning of terminal unit amount in distribution automation systems[J]. Automation of Electric Power Systems, 2013, 37(12): 44-50.
[12] 项添春, 戚艳, 董逸超, 等. 提高配电网供电可靠性和状态可观性的终端优化配置方法[J]. 电力系统及其自动化学报, 2017, 29(6): 107-112.
XIANG Tianchun, QI Yan, DONG Yichao, et al.Optimal configuration method for terminals considering the reliability and observability of distribution network[J]. Proceedings of the CSU-EPSA, 2017, 29(6): 107-112.
[13] 刘艳茹, 刘洪, 谷毅, 等. 考虑多种终端配置的中低压配电网供电可靠性协同评估[J]. 电力建设, 2022, 43(2): 54-62.
LIU Yanru, LIU Hong, GU Yi, et al.Cooperative evaluation of power supply reliability of medium and low voltage distribution network considering multiple terminal configurations[J]. Electric Power Construction, 2022, 43(2): 54-62.
[14] 吕小东, 高红均, 叶圣永, 等. 考虑事故-经济重构共同影响的配电网智能终端规划[J]. 中国电机工程学报, 2022, 42(2): 589-603.
LYU Xiaodong, GAO Hongjun, YE Shengyong, et al.Intelligent terminal planning strategy considering reliability and economy reconfiguration for distribution network[J]. Proceedings of the CSEE, 2022, 42(2): 589-603.
[15] 胥德玉, 黄媛, 唐志远, 等. 面向配电网分布式光伏消纳和可靠性提高的构网型储能优化配置[J/OL]. 电力建设, 2025: 1-16. (2025-06-06). https://kns.cnki.net/kcms/detail/11.2583.tm.20250605.1446.002.html.
XU Deyu, HUANG Yuan, TANG Zhiyuan, et al. Optimal configuration of networked energy storage for distributed photovoltaic consumption and reliability improvement of distribution network[J/OL]. Electric Power Construction, 2025: 1-16. (2025-06-06). https://kns.cnki.net/kcms/detail/11.2583.tm.20250605.1446.002.html.
[16] 俞拙非, 刘菲, 刘瑞环, 等. 面向配电网弹性提升的源网荷灵活资源优化研究综述及展望[J]. 中国电力, 2022, 55(4): 132-144.
YU Zhuofei, LIU Fei, LIU Ruihuan, et al.Resilience-oriented optimization of source-grid-load flexible resources in distribution systems: review and prospect[J]. Electric Power, 2022, 55(4): 132-144.
[17] 樊文婷, 白牧可, 刘敬敬, 等. 基于可达性与改进和声算法的高比例DG交直流配电网可靠性评估[J]. 供用电, 2025, 42(1): 86-95.
FAN Wenting, BAI Muke, LIU Jingjing, et al.Reliability evaluation of AC/DC distribution network with high proportion of DG based on reachability and improved harmony algorithm[J]. Distribution & Utilization, 2025, 42(1): 86-95.
[18] 陈钢, 黄国政, 邓瑞麒, 等. 结合网络重构的主动配电网日前无功电压双层优化[J]. 供用电, 2022, 39(5): 13-24.
CHEN Gang, HUANG Guozheng, DENG Ruiqi, et al.Bi-level optimization of day-ahead reactive-voltage in active distribution network with network reconfiguration[J]. Distribution & Utilization, 2022, 39(5): 13-24.
[19] 齐桓若, 陈晨, 郭放, 等. 考虑精细化充放电与碳效益的配电网储能多目标双层规划模型[J]. 中国电力, 2025, 58(10): 121-135.
QI Huanruo, CHEN Chen, GUO Fang, et al.Multi-objective bi-level planning model for distribution network energy storage considering refined charging/discharging and carbon benefits[J]. Electric Power, 2025, 58(10): 121-135.
[20] 闫丽梅, 解山岳, 汤奕. 基于目标自驱动下的有源配电网协同优化调度策略[J]. 广东电力, 2025, 38(3): 91-103.
YAN Limei, XIE Shanyue, TANG Yi.Coordinated optimization and scheduling strategy for active distribution networks based on self-target-driven control[J]. Guangdong Electric Power, 2025, 38(3): 91-103.
[21] 何剑军, 吴龙腾, 吴杰康, 等. 极端灾害下配电网用户侧柔性资源协同调控模型[J]. 广东电力, 2025, 38(4): 58-69.
HE Jianjun, WU Longteng, WU Jiekang, et al.Collaborative regulation and control model for user side flexible resources in distribution networks under extreme disasters[J]. Guangdong Electric Power, 2025, 38(4): 58-69.
[22] 王阳, 查正发, 于玮, 等. 基于逆变器调相控制的无功遥调技术在大中型并网光伏发电站中的应用[J]. 中国电力, 2014, 47(11): 101-107.
WANG Yang, ZHA Zhengfa, YU Wei, et al.Remote control and operation of reactive power for medium and large grid-connected photovoltaic power plants based on phase modulation inverter control[J]. Electric Power, 2014, 47(11): 101-107.
[23] 刘洪, 滑雪娇, 韩柳, 等. 配电网网架规划与多模块智能终端配置联合优化方法[J]. 电力自动化设备, 2023, 43(1): 41-47.
LIU Hong, HUA Xuejiao, HAN Liu, et al.Joint optimization method of distribution network grid planning and multi-module intelligent terminal configuration[J]. Electric Power Automation Equipment, 2023, 43(1): 41-47.
[24] 娄铖伟, 张筱慧, 丛鹏伟, 等. 含柔性软开关的有源配电网故障恢复策略[J]. 电力系统自动化, 2018, 42(1): 23-31.
LOU Chengwei, ZHANG Xiaohui, CONG Pengwei, et al.Service restoration strategy of active distribution network with soft open points[J]. Automation of Electric Power Systems, 2018, 42(1): 23-31.
[25] FARIVAR M, LOW S H.Branch flow model: relaxations and convexification: part I[J]. IEEE Transactions on Power Systems, 2013, 28(3): 2554-2564.
[26] DING T, LIN Y L, LI G F, et al.A new model for resilient distribution systems by microgrids formation[J]. IEEE Transactions on Power Systems, 2017, 32(5): 4145-4147.
[27] CAO W Y, WU J Z, JENKINS N, et al.Operating principle of Soft Open Points for electrical distribution network operation[J]. Applied Energy, 2016, 164: 245-257.
[28] 叶云, 周飞, 张博, 等. 协调故障重构和智能软开关的柔性配电系统故障恢复策略[J]. 电力系统及其自动化学报, 2025, 37(1): 74-83.
YE Yun, ZHOU Fei, ZHANG Bo, et al.Service restoration strategy for resilient distribution system by coordinating fault reconfiguration and soft open points[J]. Proceedings of the CSU-EPSA, 2025, 37(1): 74-83.
[29] 张海波, 胡玉康, 李正荣, 等. 负荷高密度地区中计及灵活性不足风险的储能优化配置[J]. 电网技术, 2023, 47(12): 4926-4940.
ZHANG Haibo, HU Yukang, LI Zhengrong, et al.Optimal configuration of energy storage considering the risk of insufficient flexibility in high load density areas[J]. Power System Technology, 2023, 47(12): 4926-4940.
[30] LI S M, CHEN H L, WANG M J, et al.Slime mould algorithm: a new method for stochastic optimization[J]. Future Generation Computer Systems, 2020, 111: 300-323.
[31] BARAN M E, WU F F.Network reconfiguration in distribution systems for loss reduction and load balancing[J]. IEEE Transactions on Power Delivery, 1989, 4(2): 1401-1407.
[32] LIN D, LIU Q J, LI F S, et al.Optimal placement of multiple feeder terminal units using intelligent algorithms[J]. Applied Sciences, 2020, 10(1): 299.
[33] ENTSO-E Transparency Platform. Generation forecast for wind and solar [EB/OL]. (2022-02-15)[2025-05-15]. https://transparency.entsoe.eu/
[34] 李东东, 王啸林, 沈运帷, 等. 考虑多重不确定性的含需求响应及电碳交易的虚拟电厂优化调度策略[J]. 电力自动化设备, 2023, 43(5): 210-217, 251.
LI Dongdong, WANG Xiaolin, SHEN Yunwei, et al.Optimal scheduling strategy of virtual power plant with demand response and electricity-carbon trading considering multiple uncertainties[J]. Electric Power Automation Equipment, 2023, 43(5): 210-217, 251.
[35] 马溪原, 郭晓斌, 雷金勇. 面向多能互补的分布式光伏与气电混合容量规划方法[J]. 电力系统自动化, 2018, 42(4): 55-63.
MA Xiyuan, GUO Xiaobin, LEI Jinyong.Capacity planning method of distributed PV and P2G in multi-energy coupled system[J]. Automation of Electric Power Systems, 2018, 42(4): 55-63.
[36] WANG D S, TAN D P, LIU L.Particle swarm optimization algorithm: an overview[J]. Soft Computing, 2018, 22(2): 387-408.
[37] Li C Y,Zhao N L,Zhou J S .Review of Genetic Algorithm[J]. Advanced Materials Research, 2011, 1105(179-180): 365-367.