考虑输配电网协同的源荷储资源统筹规划

doi:10.12204/j.issn.1000-7229.2021.09.005

摘要/Abstract

摘要：

未来高比例可再生能源并网背景下,为提高集中式与分布式可再生能源的消纳,需对电力系统中多类型调节资源进行统筹规划。提出一种计及输配电网间交互过程的中长期电源规划框架,以协调输配电系统中源-荷-储调节资源的配置容量。然后,基于分布式优化理论将模型分解为输电网规划子问题和配电网规划子问题。对于分解后子规划模型中的非凸和非线性项,采用凸松弛和线性化技术将模型转化为混合整数二阶锥规划模型进行求解。最后,对由IEEE 14节点系统和IEEE 33节点系统构造的全局系统进行仿真,验证所提模型和优化方法的有效性,并分析了协同规划下系统整体经济性和可再生能源消纳情况。

关键词: 可再生能源, 源荷储统筹规划, 输配电网, 分布式优化, 二阶锥松弛

Abstract:

Under the background of high-proportion grid-connected renewable energy in the future, the planning of multi-type adjusting resources in the power system is needed to improve the consumption of centralized and distributed renewable energy. This paper proposes a generation planning framework that considers the interaction process between transmission and distribution, and coordinates the capacity of source-load-storage resources in power system. Then, according to the distributed optimization theory, the model is decomposed into two planning sub-problems for transmission and distribution network. For the non-convex and nonlinear terms in the decomposed sub-program model, convex relaxation and linearization techniques are used to transform the model into a mixed integer second-order cone program for solution. Finally, this paper simulates the global system constructed by the IEEE 14-node system and the IEEE 33-node system to verify the effectiveness of the proposed model and optimization method, and analyzes the economy of the system and renewable energy consumption under coordinate planning.

Key words: renewable energy, source-load-storage overall planning, transmission and distribution network, distributed optimization, second-order cone relaxation

中图分类号:

TM715

谢康胜, 李华强, 王俊翔, 邓靖微. 考虑输配电网协同的源荷储资源统筹规划[J]. 电力建设, 2021, 42(9): 41-52.

XIE Kangsheng, LI Huaqiang, WANG Junxiang, DENG Jingwei. Overall Planning of Source-Load-Storage Resources Considering Coordination in Transmission and Distribution Network[J]. ELECTRIC POWER CONSTRUCTION, 2021, 42(9): 41-52.

图/表 16

图1 高比例可再生能源电力系统示意图

Fig.1 Schematic diagram of power system with high proportion of renewable energy

图2 规划模型分解示意图

Fig.2 Schematic diagram of decomposing of the planning model

图3 规划模型求解流程图

Fig.3 Flow chart of planning model solving

图4 输配电测试系统

Fig.4 Transmission and distribution test system

表A1 输电网线路参数

Table A1 Branch parameters of transmission network pu

表A2 配电网线路参数

Table A2 Branch parameters of distribution network Ω

图A1 风电、光伏出力示意图

Fig.A1 Schematic diagram of photovoltaic and wind power

图A2 电价曲线

Fig.A2 Electricity price curves

表A3 机组参数

Table A3 Parameter of generators

表A4 成本参数

Table A4 Some parameters of values

表A5 需求响应参数

Table A5 The parameter of demand response

表1 规划方案

Table 1 Schemes of planning

表2 规划成本

Table 2 Costs of planning 万元

图5 机组启停次数

Fig.5 Start and shut times of generators

图6 输配边界有功无功变化趋势图

Fig.6 Change trend of active and reactive power between transmission and distribution networks

图7 输配支路误差图

Fig.7 Error of branch of transmission and distribution networks

参考文献 22

[1]	鲁宗相, 李海波, 乔颖. 含高比例可再生能源电力系统灵活性规划及挑战[J]. 电力系统自动化, 2016, 40(13):147-158.
	LU Zongxiang, LI Haibo, QIAO Ying. Power system flexibility planning and challenges considering high proportion of renewable energy[J]. Automation of Electric Power Systems, 2016, 40(13):147-158.
[2]	康重庆, 姚良忠. 高比例可再生能源电力系统的关键科学问题与理论研究框架[J]. 电力系统自动化, 2017, 41(9):2-11.
	KANG Chongqing, YAO Liangzhong. Key scientific issues and theoretical research framework for power systems with high proportion of renewable energy[J]. Automation of Electric Power Systems, 2017, 41(9):2-11.
[3]	李星梅, 钟志鸣, 阎洁. 大规模风电接入下的火电机组灵活性改造规划[J]. 电力系统自动化, 2019, 43(3):51-57.
	LI Xingmei, ZHONG Zhiming, YAN Jie. Flexibility reformation planning of thermal power units with large-scale integration of wind power[J]. Automation of Electric Power Systems, 2019, 43(3):51-57.
[4]	温丰瑞, 李华强, 温翔宇, 等. 主动配电网中计及灵活性不足风险的储能优化配置[J]. 电网技术, 2019, 43(11):3952-3962.
	WEN Fengrui, LI Huaqiang, WEN Xiangyu, et al. Optimal allocation of energy storage systems considering flexibility deficiency risk in active distribution network[J]. Power System Technology, 2019, 43(11):3952-3962.
[5]	易文飞, 张艺伟, 曾博, 等. 多形态激励型需求侧响应协同平衡可再生能源波动的鲁棒优化配置[J]. 电工技术学报, 2018, 33(23):5541-5554.
	YI Wenfei, ZHANG Yiwei, ZENG Bo, et al. Robust optimization allocation for multi-type incentive-based demand response collaboration to balance renewable energy fluctuations[J]. Transactions of China Electrotechnical Society, 2018, 33(23):5541-5554.
[6]	张宁, 代红才, 胡兆光, 等. 考虑系统灵活性约束与需求响应的源网荷协调规划模型[J]. 中国电力, 2019, 52(2):61-69.
	ZHANG Ning, DAI Hongcai, HU Zhaoguang, et al. A source-grid-load coordinated planning model considering system flexibility constraints and demand response[J]. Electric Power, 2019, 52(2):61-69.
[7]	徐唐海, 鲁宗相, 乔颖, 等. 源荷储多类型灵活性资源协调的高比例可再生能源电源规划[J]. 全球能源互联网, 2019, 2(1):27-34.
	XU Tanghai, LU Zongxiang, QIAO Ying, et al. High penetration of renewable energy power planning considering coordination of source-load-storage multi-type flexible resources[J]. Journal of Global Energy Interconnection, 2019, 2(1):27-34.
[8]	郑宗强, 韩冰, 闪鑫, 等. 输配电网高级应用协同运行关键技术分析[J]. 电力系统自动化, 2017, 41(6):122-128.
	ZHENG Zongqiang, HAN Bing, SHAN Xin, et al. Analysis on key technologies for coordinated operation of advanced application software in transmission and distribution network[J]. Automation of Electric Power Systems, 2017, 41(6):122-128.
[9]	张福民, 裴雪辰, 王博. 主动配电网与输电网协调调度与阻塞管理[J]. 电测与仪表, 2020, 57(3):46-53,65.
	ZHANG Fumin, PEI Xuechen, WANG Bo. Coordinated dispatch and congestion management of active distribution network and transmission network[J]. Electrical Measurement & Instrumentation, 2020, 57(3):46-53,65.
[10]	MIGLIAVACCA G, ROSSI M, SIX D, et al. SmartNet: H2020 project analysing TSO-DSO interaction to enable ancillary services provision from distribution networks[J]. CIRED-Open Access Proceedings Journal, 2017, 2017(1):1998-2002. doi: 10.1049/oap-cired.2017.0104 URL
[11]	齐琛, 汪可友, 李国杰, 等. 交直流混合主动配电网的分层分布式优化调度[J]. 中国电机工程学报, 2017, 37(7):1909-1918.
	QI Chen, WANG Keyou, LI Guojie, et al. Hierarchical and distributed optimal scheduling of AC/DC hybrid active distribution network[J]. Proceedings of the CSEE, 2017, 37(7):1909-1918.
[12]	LI Z S, GUO Q L, SUN H B, et al. Coordinated economic dispatch of coupled transmission and distribution systems using heterogeneous decomposition[J]. IEEE Transactions on Power Systems, 2016, 31(6):4817-4830. doi: 10.1109/TPWRS.2016.2515578 URL
[13]	LIN C H, WU W C, ZHANG B M, et al. Decentralized reactive power optimization method for transmission and distribution networks accommodating large-scale DG integration[J]. IEEE Transactions on Sustainable Energy, 2017, 8(1):363-373. doi: 10.1109/TSTE.2016.2599848 URL
[14]	AHMADI-KHATIR A, CONEJO A J, CHERKAOUI R. Multi-area energy and reserve dispatch under wind uncertainty and equipment failures[J]. IEEE Transactions on Power Systems, 2013, 28(4):4373-4383. doi: 10.1109/TPWRS.59 URL
[15]	TOSSERAMS S, ETMAN L F P, PAPALAMBROS P Y, et al. An augmented Lagrangian relaxation for analytical target cascading using the alternating direction method of multipliers[J]. Structural and Multidisciplinary Optimization, 2006, 31(3):176-189. doi: 10.1007/s00158-005-0579-0 URL
[16]	ORTEGA-VAZQUEZ M A. Optimal scheduling of electric vehicle charging and vehicle-to-grid services at household level including battery degradation and price uncertainty[J]. IET Generation, Transmission & Distribution, 2014, 8(6):1007-1016. doi: 10.1049/gtd2.v8.6 URL
[17]	高红均, 刘俊勇. 考虑不同类型DG和负荷建模的主动配电网协同规划[J]. 中国电机工程学报, 2016, 36(18):4911-4922,5115.
	GAO Hongjun, LIU Junyong. Coordinated planning considering different types of DG and load in active distribution network[J]. Proceedings of the CSEE, 2016, 36(18):4911-4922,5115.
[18]	林哲, 胡泽春, 宋永华. 最优潮流问题的凸松弛技术综述[J]. 中国电机工程学报, 2019, 39(13):3717-3728.
	LIN Zhe, HU Zechun, SONG Yonghua. Convex relaxation for optimal power flow problem: A recent review[J]. Proceedings of the CSEE, 2019, 39(13):3717-3728.
[19]	高红均, 刘俊勇, 沈晓东, 等. 主动配电网最优潮流研究及其应用实例[J]. 中国电机工程学报, 2017, 37(6):1634-1645.
	GAO Hongjun, LIU Junyong, SHEN Xiaodong, et al. Optimal power flow research in active distribution network and its application examples[J]. Proceedings of the CSEE, 2017, 37(6):1634-1645.
[20]	HASSAN A, DVORKIN Y. Energy storage siting and sizing in coordinated distribution and transmission systems[J]. IEEE Transactions on Sustainable Energy, 2018, 9(4):1692-1701. doi: 10.1109/TSTE.2018.2809580 URL
[21]	LIU J, CHENG H Z, ZENG P L, et al. Decentralized stochastic optimization based planning of integrated transmission and distribution networks with distributed generation penetration[J]. Applied Energy, 2018, 220:800-813. doi: 10.1016/j.apenergy.2018.03.016 URL
[22]	马鑫, 郭瑞鹏, 王蕾, 等. 基于二阶锥规划的交直流主动配电网日前调度模型[J]. 电力系统自动化, 2018, 42(22):144-150.
	MA Xin, GUO Ruipeng, WANG Lei, et al. Day-ahead scheduling model for AC/DC active distribution network based on second-order cone programming[J]. Automation of Electric Power Systems, 2018, 42(22):144-150.