考虑跨区能流交互计划的多区域电-气综合能源系统分散调度方法

doi:10.12204/j.issn.1000-7229.2020.12.007

摘要/Abstract

摘要：

针对多区域电-气互联系统优化调度问题,提出考虑联络线、联络管道能流交互计划的分散式调度方法。首先,利用二阶锥松弛方法将气网潮流方程线性化;在区域间,通过优化联络线与联络管道能流交互计划,对机组出力进行优化配置以促进互联区域的风电消纳,并以单个区域为决策主体建立满足联络线与联络管道约束的集中式优化模型。然后,分析了多区域电-气互联系统能量流解耦机制,并基于标准交替方向乘子法,得到分散式优化算法,即同步交替方向乘子法(synchronous-alternating direction method of multipliers,S-ADMM),再利用上述算法对集中式模型进行重构,建立一种完全分散式的调度模型。最后,在不同规模的多区域电-气互联系统中开展算例分析,其结果表明:所提算法有较优的收敛性;通过联络线与联络管道的互联方式使系统运行最优;多区域电-气互联系统可改变联络线峰谷差率,使各区域发电资源达到配置最优,并减少了区域弃风量,降低了运行成本,可为多区域能源系统优化运行提供参考。

关键词: 多区域电-气互联系统, 分散式协同优化, 二阶锥松弛, 能流交互

Abstract:

According to the problem of collaborative optimization with multi-region electricity-gas interconnection system, a distributed optimization method considering interaction plan of energy flow with tie lines and tie pipes is proposed in this paper. Firstly, the second-order cone relaxation is adopted to linearize the gas flow equation of the gas network; between regions, by optimizing the energy flow interaction plan of the connection line and pipeline, the output of the generation unit is optimized to promote the wind power consumption in the interconnected region, a centralized optimization model that satisfies the constraints of the tie line and the tie pipe is established with a single region as the decision-making subject. Then, the paper analyzes the energy flow decoupling mechanism of multi-region electricity-gas interconnection system, and on the basis of a standard alternating direction multiplier method, a decentralized optimization algorithm, synchronous-ADMM method (S-ADMM), is obtained, in which the authors performs a reconstruction solution and establishes a completely decentralized scheduling model. Finally,the analysis of calculation examples is carried out in multi-regional electrical interconnection systems of different scales, and it is obtained that the proposed algorithm has better convergence; the system operation is optimized by the interconnected way of tie lines and pipes; the multi-region interconnection system can be changed by the peak-to-valley ratio of tie line optimizes the allocation of power generation resources in each region, reduces the amount of regional wind abandonment, and reduces operating costs, which can provide a reference for optimization of multi-regional energy systems.

Key words: multi-region electricity-gas interconnection system, distributed collaborative optimization, second-order cone relaxation, energy flow interaction

中图分类号:

TM73

魏震波, 魏平桉, 郭毅, 黄宇涵, 卢炳文. 考虑跨区能流交互计划的多区域电-气综合能源系统分散调度方法[J]. 电力建设, 2020, 41(12): 68-81.

WEI Zhenbo, WEI Pingan, GUO Yi, HUANG Yuhan, LU Bingwen. Distributed Dispatch Method for Multi-region Electricity-Gas Integrated Energy Systems Considering Cross-region Energy Flow Interaction Plan[J]. ELECTRIC POWER CONSTRUCTION, 2020, 41(12): 68-81.

图/表 28

图1 多区域电-气互联系统分散调度结构

Fig.1 Distributed dispatch structure of multi-region electricity-gas integrated system

图2 多区域电-气互联系统解耦机制

Fig.2 Decomposition mechanism of multi-region electricity-gas integrated system

图3 S-ADMM算法的计算流程

Fig.3 Calculating process of S-ADMM algorithm

图4 两区域12节点电-气互联系统

Fig.4 Two-region electricity-gas integrated system with 12 nodes

表1 两区域12节点电-气互联系统优化结果

Table 1 Optimization result of a two-region electricity-gas integrated system with 12 nodes

图5 算法迭代收敛过程

Fig.5 Convergence process of the algorithm

表2 两区域12节点电-气互联系统不同运行策略比较

Table 2 Comparison of different operation strategies with two-region electricity-gas integrated system with 12 nodes

图6 联络线与联络管道能流交互计划

Fig.6 Energy flow interaction plan of the tie-line and the tie-pipe

表3 三区域电-气互联系统优化结果

Table 3 Optimization result of a three-region electricity-gas integrated system

表4 三区域电-气耦合系统互联方式比较

Table 4 Comparison of interconnecting method with three-region electricity-gas integrated system

图7 弃风量和运行成本与联络线峰谷差率的关系

Fig.7 The relationship between wind curtailment power,operation cost and peak-valley difference of the tie-line

图8 区域一弃风功率与联络线功率分时展示图

Fig.8 Plots of wind curtailment power and tie-line power in region 1

表 B1 算例一机组参数

Table B1 Parameters of thermal units in calculation example one

表 B2 算例一联络线参数

Table B2 Parameters of tie-lines in calculation example one

表 B3 算例一气源参数

Table B3 Parameters of gas source in calculation example one

表 B4 算例一区域内能源转换元件参数

Table B4 Parameters of intra-regional energy convertors in calculation example one

表 B5 算例一气管道参数

Table B5 Parameters of pipelines in calculation example one

表 B6 算例一、二算法初值及参数设定

Table B6 algorithm Initial values and parameters in calculation example one and two

图 B1 各区域电负荷、风电预测

Fig.B1 Prediction of electric load and wind power in each region

图 B2 各区域气负荷预测

Fig.B2 Prediction of gas load in each region

图 B3 各种模式下机组出力情况

Fig.B3 Profile of units output under various modes

图 C1 各区域电负荷和风电出力预测

Fig.C1 Prediction of electric load and wind power of each region

图 C2 各区域气负荷预测

Fig.C2 Prediction of natural gas load and of each region

图 C3 算法迭代收敛过程

Fig.C3 Convergence process of algorithm

表 C1 算例二气源参数

Table C1 Parameters of gas source in calculation example two

表 C2 算例二联络线参数

Table C2 Parameters of tie-lines in calculation example two

表 C3 算例二耦合元件相关参数

Table C3 Coupling element related parameters in calculation example two

表 C4 算例二气管道参数

Table C4 Parameters of pipelines in calculation example two

参考文献 19

[1]	吴嘉豪, 曾成碧, 苗虹. 计及子区域间能量交换的多区域综合能源系统协调经济调度[J]. 电力建设, 2019,40(11):39-47.
	WU Jiahao, ZENG Chengbi, MIAO Hong. Coordinated economic scheduling for multi-regional integrated energy system considering energy exchange between sub-regions[J]. Electric Power Construction, 2019,40(11):39-47.
[2]	文云峰, 瞿小斌, 肖友强, 等. 耦合能量枢纽多区域电-气互联能源系统分布式协同优化调度[J]. 电力系统自动化, 2019,43(9):22-34.
	WEN Yunfeng, QU Xiaobin, XIAO Youqiang, et al. Distributed coordinated optimal dispatch of multi-regional electricity-gas integrated energy systems with energy hubs[J]. Automation of Electric Power Systems, 2019,43(9):22-34.
[3]	许丹, 丁强, 黄国栋, 等. 考虑安全约束的联络线供需协调计划模型[J]. 电网技术, 2015,39(9):2591-2596. doi: 10.13335/j.1000-3673.pst.2015.09.033 URL
	XU Dan, DING Qiang, HUANG Guodong, et al. Modeling for tie-line scheduling plan based on security constraints and supply-demand coordination[J]. Power System Technology, 2015,39(9):2591-2596. doi: 10.13335/j.1000-3673.pst.2015.09.033 URL
[4]	许丹, 李晓磊, 丁强, 等. 基于全网统筹的联络线分层优化调度[J]. 电力系统自动化, 2014,38(2):122-126. doi: 10.7500/AEPS20130516004 URL
	XU Dan, LI Xiaolei, DING Qiang, et al. Optimization of tie-line hierarchical schedule based on network-wide coordination[J]. Automation of Electric Power Systems, 2014,38(2):122-126. doi: 10.7500/AEPS20130516004 URL
[5]	WU G, XIANG Y, LIU J Y, et al. Decentralized day-ahead scheduling of multi-area integrated electricity and natural gas systems considering reserve optimization[J]. Energy, 2020,198:117271. doi: 10.1016/j.energy.2020.117271 URL
[6]	曾方迪, 李更丰, 别朝红, 等. 考虑跨区联络线交易计划的多区域互联系统分散调度方法[J]. 电力系统自动化, 2018,42(16):32-40.
	ZENG Fangdi, LI Gengfeng, BIE Zhaohong, et al. Decentralized dispatch method for multi-area interconnected power systems considering cross-area tie-line transaction strategy[J]. Automation of Electric Power Systems, 2018,42(16):32-40.
[7]	李晓露, 单福州, 宋燕敏, 等. 考虑热网约束和碳交易的多区域综合能源系统优化调度[J]. 电力系统自动化, 2019,43(19):52-61, 131.
	LI Xiaolu, SHAN Fuzhou, SONG Yanmin, et al. Optimal dispatch of multi-region integrated energy systems considering heating network constraints and carbon trading[J]. Automation of Electric Power Systems, 2019,43(19):52-61, 131.
[8]	郭丹阳, 班明飞, 于继来. 提升重污染天气时环境互济效益的多区域电网协调策略[J]. 中国电机工程学报, 2019,39(19):5750-5762, 5903.
	GUO Danyang, BAN Mingfei, YU Jilai. Multi-regional power grid coordination strategy for promoting mutual environmental benefit during heavy pollution weather[J]. Proceedings of the CSEE, 2019,39(19):5750-5762, 5903.
[9]	张文韬, 王秀丽, 李言, 等. 大规模风电并网下多区域互联系统热电综合调度模型[J]. 电网技术, 2018,42(1):154-161.
	ZHANG Wentao, WANG Xiuli, LI Yan, et al. An analysis model of multi-area interconnected power systems with large-scale wind power involved in comprehensive heating and power system scheduling[J]. Power System Technology, 2018,42(1):154-161.
[10]	瞿凯平, 黄琳妮, 余涛, 等. 碳交易机制下多区域综合能源系统的分散调度[J]. 中国电机工程学报, 2018,38(3):697-707.
	QU Kaiping, HUANG Linni, YU Tao, et al. Decentralized dispatch of multi-area integrated energy systems with carbon trading[J]. Proceedings of the CSEE, 2018,38(3):697-707.
[11]	张睿, 黄国日, 文福拴, 等. 电力-天然气集成能源系统的统一规划模型与Benders解耦方法[J]. 电力建设, 2017,38(7):67-76.
	ZHANG Rui, HUANG Guori, WEN Fushuan, et al. Unified planning model of integrated electric power and natural gas energy systems based on benders decomposition[J]. Electric Power Construction, 2017,38(7):67-76.
[12]	LI Z G, WU W C, ZENG B, et al. Decentralized contingency-constrained tie-line scheduling for multi-area power grids[J]. IEEE Transactions on Power Systems, 2017,32(1):354-367. doi: 10.1109/TPWRS.2016.2539278 URL
[13]	ZHOU M, ZHAI J Y, LI G Y, et al. Distributed dispatch approach for bulk AC/DC hybrid systems with high wind power penetration[J]. IEEE Transactions on Power Systems, 2018,33(3):3325-3336. doi: 10.1109/TPWRS.2017.2762358 URL
[14]	税月, 刘俊勇, 高红均, 等. 考虑风电不确定性的电气能源系统两阶段分布鲁棒协同调度[J]. 电力系统自动化, 2018,42(13):43-50, 75.
	SHUI Yue, LIU Junyong, GAO Hongjun, et al. Two-stage distributed robust cooperative dispatch for integrated electricity and natural gas energy systems considering uncertainty of wind power[J]. Automation of Electric Power Systems, 2018,42(13):43-50, 75.
[15]	ZHANG Y, HU Y, MA J, et al. A mixed-integer linear programming approach to security-constrained co-optimization expansion planning of natural gas and electricity transmission systems[J]. IEEE Transactions on Power Systems, 2018,33(6):6368-6378. doi: 10.1109/TPWRS.2018.2832192 URL
[16]	BENT R, BLUMSACK S, VAN HENTENRYCK P, et al. Joint electricity and natural gas transmission planning with endogenous market feedbacks[J]. IEEE Transactions on Power Systems, 2018,33(6):6397-6409. doi: 10.1109/TPWRS.59 URL
[17]	张博文, 孙永辉, 张世达. 基于SOCP的综合能源系统日前调度概率最优能量流[J]. 电力系统自动化, 2019,43(6):25-36.
	ZHANG Bowen, SUN Yonghui, ZHANG Shida. Second-order cone programming based probabilistic optimal energy flow of day-ahead dispatch for integrated energy system[J]. Automation of Electric Power Systems, 2019,43(6):25-36.
[18]	ERSEGHE T. Distributed optimal power flow using ADMM[J]. IEEE Transactions on Power Systems, 2014,29(5):2370-2380. doi: 10.1109/TPWRS.2014.2306495 URL
[19]	王旭, 别朝红. 基于交替方向乘子法的电-气互联系统分布式协同规划[J]. 电力系统自动化, 2018,42(22):107-120.
	WANG Xu, BIE Zhaohong. Distributed co-planning of electricity and natural gas systems based on alternating direction method of multipliers[J]. Automation of Electric Power Systems, 2018,42(22):107-120.