An Optimal Energy Flow Calculation Method for Integrated Electricity-Gas System Applying Parametric Linear Programming

doi:10.12204/j.issn.1000-7229.2022.01.004

Abstract

Abstract:

The calculation of the optimal energy flow (OEF) of the integrated electricity-gas system (IEGS) is the basis of the optimal planning and operation analysis of IEGS. There are some problems in the existing methods for solving the OEF of the IEGS, such as frequent data interaction, poor convergence and difficulty in ensuring privacy. Therefore, a method for calculating the OEF applying parameter linear programming is proposed in this paper. Firstly, the optimal power flow (OPF) models for the power network and natural gas network are constructed, respectively. The OPF model of the power network adopts the optimal DC power flow model considering the active power loss. The OPF model of the natural gas network is established on the basis of the second-order cone relaxation. Secondly, the correlation function between the electricity-gas coupling power and the optimal solution of the power flow is constructed based on the parameter linear programming theory. Then, the correlation function is transferred to the natural gas system for joint optimization, and returns the electricity-gas coupling power information to the power system for solution. Thus, the natural gas flow and power flow results of the OEF are obtained. Through the simulation analysis, the method proposed in this paper can accurately solve the OEF through one-time information exchange. At the same time, the amount of interactive information is small and able to protect private information. It is suitable for the decomposition calculation of the OEF.

Key words: integrated electricity-gas system (IEGS), optimal energy flow (OEF), stochastic robust optimization, decomposition, privacy

CLC Number:

TM73

CAI Jie, ZHAO Haipeng, GUAN Qinyue, GUO Ting, ZHANG Di, MIAO Shihong. An Optimal Energy Flow Calculation Method for Integrated Electricity-Gas System Applying Parametric Linear Programming[J]. ELECTRIC POWER CONSTRUCTION, 2022, 43(1): 29-37.

Figures/Tables 10

Fig.1 Relationship between electricity-gas coupling power and optimal solution

Fig.2 Process of IEGS distributed OEF calculation method based on parametric linear programming

Fig.3 Example system topology

Table 1 The example parameter

Table 2 Error index of active-power loss calculation based on the first-order Taylor expansion approximation

Fig.4 Relationship between optimal power flow solution and coupling power in IEEE 33-node distribution network

Fig.5 Relationship between optimal power flow solution and coupling power in IEEE 14-node distribution network

Table 3 Optimization results in different scenarios

Fig.6 Outputs of electric power source, gas source and coupling device by different solutions in scenario 3

Table 4 Comparison of information interaction times of different solution methods

References 21

[1]	杨海柱, 李梦龙, 江昭阳, 等. 考虑需求侧电热气负荷响应的区域综合能源系统优化运行[J]. 电力系统保护与控制, 2020, 48(10):30-37.
	YANG Haizhu, LI Menglong, JIANG Zhaoyang, et al. Optimal operation of regional integrated energy system considering demand side electricity heat and natural-gas loads response[J]. Power System Protection and Control, 2020, 48(10):30-37.
[2]	孙宏斌, 潘昭光, 郭庆来. 多能流能量管理研究: 挑战与展望[J]. 电力系统自动化, 2016, 40(15): 1-8,16.
	SUN Hongbin, PAN Zhaoguang, GUO Qinglai. Energy management for multi-energy flow: Challenges and prospects[J]. Automation of Electric Power Systems, 2016, 40(15): 1-8,16.
[3]	林涛, 毕如玉, 杜蕙, 等. 电-气互联系统潮流优化与安全性研究综述[J]. 全球能源互联网, 2019, 2(5): 441-448.
	LIN Tao, BI Ruyu, DU Hui, et al. Summary of research on power flow optimization and safety of integrated electricity and gas systems[J]. Journal of Global Energy Interconnection, 2019, 2(5): 441-448.
[4]	CHEN S, WEI Z N, SUN G Q, et al. Identifying optimal energy flow solvability in electricity-gas integrated energy systems[J]. IEEE Transactions on Sustainable Energy, 2017, 8(2): 846-854. doi: 10.1109/TSTE.2016.2623631 URL
[5]	陈思宇, 柴庆宣, 李延松, 等. 综合能源系统潮流及最优潮流计算模型与方法综述[J]. 热力发电, 2020, 49(7): 1-12,20.
	CHEN Siyu, CHAI Qingxuan, LI Yansong, et al. Models and methods of power flow and optimal power flow calculation for integrated energy system: A review[J]. Thermal Power Generation, 2020, 49(7): 1-12,20.
[6]	陈彬彬, 孙宏斌, 陈瑜玮, 等. 综合能源系统分析的统一能路理论(一): 气路[J]. 中国电机工程学报, 2020, 40(2): 436-444.
	CHEN Binbin, SUN Hongbin, CHEN Yuwei, et al. Energy circuit theory of integrated energy system analysis (I): Gaseous circuit[J]. Proceedings of the CSEE, 2020, 40(2): 436-444.
[7]	王泽森, 唐艳梅, 乔宝榆, 等. 气-电综合能源系统最优潮流及其环境增效研究[J]. 中国电机工程学报, 2018, 38(S1): 111-120.
	WANG Zesen, TANG Yanmei, QIAO Baoyu, et al. Research on integrated natural gas and electric power system optimal power flow and its environmental synergy[J]. Proceedings of the CSEE, 2018, 38(S1): 111-120.
[8]	韩佶, 苗世洪, 李超, 等. 计及相关性的电-气-热综合能源系统概率最优能量流[J]. 电工技术学报, 2019, 34(5): 1055-1067.
	HAN Ji, MIAO Shihong, LI Chao, et al. Probabilistic optimal energy flow of electricity-gas-heat integrated energy system considering correlation[J]. Transactions of China Electrotechnical Society, 2019, 34(5): 1055-1067.
[9]	陈胜, 卫志农, 孙国强, 等. 电-气混联综合能源系统概率能量流分析[J]. 中国电机工程学报, 2015, 35(24): 6331-6340.
	CHEN Sheng, WEI Zhinong, SUN Guoqiang, et al. Probabilistic energy flow analysis in integrated electricity and natural-gas energy systems[J]. Proceedings of the CSEE, 2015, 35(24): 6331-6340.
[10]	杨经纬, 张宁, 康重庆. 多能源网络的广义电路分析理论: (二)网络模型[J]. 电力系统自动化, 2020, 44(10): 10-21.
	YANG Jingwei, ZHANG Ning, KANG Chongqing. Analysis theory of generalized electric circuit for multi-energy networks—part two network model[J]. Automation of Electric Power Systems, 2020, 44(10): 10-21.
[11]	WEN Y F, QU X B, LI W Y, et al. Synergistic operation of electricity and natural gas networks via ADMM[J]. IEEE Transactions on Smart Grid, 2018, 9(5): 4555-4565. doi: 10.1109/TSG.2017.2663380 URL
[12]	史佳琪, 胡浩, 张建华. 计及多个独立运营商的综合能源系统分布式低碳经济调度[J]. 电网技术, 2019, 43(1): 127-136.
	SHI Jiaqi, HU Hao, ZHANG Jianhua. Distributed low-carbon economy scheduling for integrated energy system with multiple individual energy-hubs[J]. Power System Technology, 2019, 43(1): 127-136.
[13]	史守圆, 瞿凯平, 余涛, 等. 计及大气污染物时空扩散的电-气能流分散协同优化[J]. 电工技术学报, 2019, 34(23): 4957-4971.
	SHI Shouyuan, QU Kaiping, YU Tao, et al. A distributed algorithm for optimal power-gas flow considering space-time diffusion of atmospheric pollutants[J]. Transactions of China Electrotechnical Society, 2019, 34(23): 4957-4971.
[14]	LIU C, SHAHIDEHPOUR M, WANG J. Application of augmented Lagrangian relaxation to coordinated scheduling of interdependent hydrothermal power and natural gas systems[J]. IET Generation, Transmission & Distribution, 2010, 4(12): 1314.
[15]	LIN C H, WU W C, SHAHIDEHPOUR M, et al. A non-iterative decoupled solution of the coordinated robust OPF in transmission and distribution networks with variable generating units[J]. IEEE Transactions on Sustainable Energy, 2020, 11(3): 1579-1588. doi: 10.1109/TSTE.2019.2931908 URL
[16]	刘天琪, 张琪, 何川. 考虑气电联合需求响应的气电综合能源配网系统协调优化运行[J]. 中国电机工程学报, 2021, 41(5): 1664-1677.
	LIU Tianqi, ZHANG Qi, HE Chuan. Coordinated optimal operation of electricity and natural gas distribution system considering integrated electricity-gas demand response[J]. Proceedings of the CSEE, 2021, 41(5): 1664-1677.
[17]	SINGH M K, KEKATOS V. Natural gas flow solvers using convex relaxation[J]. IEEE Transactions on Control of Network Systems, 2020, 7(3): 1283-1295. doi: 10.1109/TCNS.2020.2972593 URL
[18]	陈宝林. 最优化理论与算法[M]. 2版. 北京: 清华大学出版社, 2005: 157-163.
[19]	GAL T. Linear parametric programming: A brief survey[J]. Mathematical Programming Studies, 1984(21): 43-68.
[20]	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. doi: 10.1109/61.25627 URL
[21]	舒隽, 关睿, 韩冰, 等. 考虑电热耦合效应的配电网潮流计算[J]. 电力系统自动化, 2015, 39(19): 48-53.
	SHU Jun, GUAN Rui, HAN Bing, et al. Calculation of distribution network power flow considering electrothermal coupling effect[J]. Automation of Electric Power Systems, 2015, 39(19): 48-53.