考虑灵活资源调节和可靠性的智能终端优化配置

何贤艺, 熊炜, 陆之洋, 袁旭峰, 张超

电力建设 ›› 0

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PDF(1342 KB)
电力建设 ›› 0

考虑灵活资源调节和可靠性的智能终端优化配置

  • 何贤艺, 熊炜, 陆之洋, 袁旭峰, 张超
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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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摘要

【目的】随着分布式电源(distributed generation, DG)、储能系统(energy storage system, ESS)等灵活资源以及智能软开关(soft open point, SOP)在配电网中大规模接入,传统的“二遥”与“三遥”终端配置方法难以满足自动化控制需求,亟需引入“四遥”终端进行协同配置。【方法】考虑“三遥”与“四遥”终端的功能特性,提出一种智能终端双层优化配置方法。上层规划以设备投资运维成本、弃风弃光成本和停电损失成本的综合成本最小化为目标,在保障配电网全局可观性的基础上,构建终端选址优化模型;下层运行基于上层规划结果,面向N-1故障恢复场景,建立以停电损失、弃风弃光成本和电压偏移量最小化为目标的多目标优化模型。针对所提模型,采用黏菌优化算法(slime mould algorithm,SMA)与二阶锥规划混合算法进行求解。【结果】算例结果表明,所提方法与未配置终端及仅配置“三遥”终端的方案相比,综合成本分别下降69.15%和7.11%,供电可靠性分别提升0.026 1%和0.002 2%,弃风弃光总电量分别下降37.79%和4.46%,电压偏移量分别降低53.04%和49.43%。【结论】所提出的配置方法在提升投资经济性、供电可靠性、新能源消纳能力以及改善电压质量方面等多方面具有显著优势,并能兼顾多种灵活性资源场景,为柔性配电网中“三遥”和“四遥”终端的协同配置提供了理论依据。

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.

关键词

灵活性资源 / 智能终端 / 双层模型 / 故障重构 / 可靠性

Key words

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

引用本文

导出引用
何贤艺, 熊炜, 陆之洋, 袁旭峰, 张超. 考虑灵活资源调节和可靠性的智能终端优化配置[J]. 电力建设. 0
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
中图分类号: TM732   

参考文献

[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.

基金

国家自然科学基金项目(52367005); 贵州省科技支撑计划([2024]049)

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