CVaR Based Risk-Averse Unit Commitment of Integrated Electricity and Natural Gas System<br />

doi:10.7652/xjtuxb202006003

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CVaR Based Risk-Averse Unit Commitment of Integrated Electricity and Natural Gas System

更新时间：2025-07-09

- CVaR Based Risk-Averse Unit Commitment of Integrated Electricity and Natural Gas System
- Vol. 54, Issue 6, Pages: 17-27(2020)
- 作者机构：
  
  1. 西安交通大学电气设备电力绝缘国家重点实验室,西安,710049
  2. 西安交通大学陕西省智能电网重点实验室,西安,710049
  3. 西安交通大学电气工程学院,西安,710049
- 作者简介：
- 基金信息：
- DOI：10.7652/xjtuxb202006003
  CLC： TM76
- Online First：10 June 2020，
  
  Published：2020
- 稿件说明：
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CVaR Based Risk-Averse Unit Commitment of Integrated Electricity and Natural Gas System
[J]. 2020, 54(6): 17-27. DOI: 10.7652/xjtuxb202006003.
DOI：

CVaR Based Risk-Averse Unit Commitment of Integrated Electricity and Natural Gas System
[J]. 2020, 54(6): 17-27. DOI: 10.7652/xjtuxb202006003. DOI：

摘要

为应对新能源不确定性带来的综合能源系统运行风险

选择合理的机组组合策略平衡综合能源系统的运行风险与运行费用

建立风险厌恶电-气综合能源系统机组组合模型。在电-气综合能源系统的机组组合中引入条件风险价值

分别描述电力系统和天然气系统的负荷损失风险

分析电力系统与天然气系统的运行风险和两系统间的相互影响。利用分段线性化技术对天然气流量方程进行线性化

通过Benders分解算法将模型分解为机组组合主问题、分场景子问题和天然气负荷损失风险校验问题

对所提模型进行高效求解。算例仿真结果表明

所提模型与传统模型相比可以有效减少小概率极端场景的电力负荷损失

算例中最严重场景负荷损失从34.62 MW减少到9.59 MW。所提模型可以协调电力负荷损失风险和天然气负荷损失风险

为电-气综合能源系统的协调调度提供参考。

Abstract

To deal with the operational risks of integrated electricity and natural gas system brought about by uncertainty of new energy sources

this approach selects a reasonable unit commitment strategy to balance the operational risks and operating costs of the integrated energy system

and constructs a risk-averse integrated energy system unit commitment model. Conditional value-at-risk(CVaR)is introduced into the unit commitment of the integrated energy system to describe the load loss risk of the power system and the natural gas system. The operational risk of the power system and the natural gas system

and mutual influence between them are analy-ed. The piecewise lineari-ation technique is used to lineari-e the natural gas flow equation

and the model is decomposed into the main unit commitment problem

sub-problems for sub-scenario and natural gas load loss risk verification problems by the Benders decomposition algorithm. Compared with the traditional model

the proposed one can effec

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references

闫海波, 李海波, 蒋韬. 电力体制改革下天然气发电产业的挑战与机遇 [J]. 燃气轮机技术, 2019, 32(3): 5-9.

YAN Haibo, LI Haibo, JIANG Tao. Challenges and opportunities of natural gas power industry under electric power system reform [J]. Gas Turbine Technology, 2019, 32(3): 5-9.

中华人民共和国国家发展和改革委员会. 电力发展“十三五”规划 [A/OL].(2017-06-05)[2019-11-21]. https:∥www.ndrc.gov.cn/fggz/fzzlgh/gjjzxgh/2017 06/W020191104624253414400.pdf.

杨自娟, 高赐威, 赵明. 电力-天然气网络耦合系统研究综述 [J]. 电力系统自动化, 2018, 42(16): 21-31, 56.

YANG Zijuan, GAO Ciwei, ZHAO Ming. Review of coupled system between power and natural gas network [J]. Automation of Electric Power Systems, 2018, 42(16): 21-31, 56.

李文沅. 电力系统风险评估: 模型、方法和应用 [M]. 北京: 科学出版社, 2006: 1.

薛禹胜, 雷兴, 薛峰, 等. 关于风电不确定性对电力系统影响的评述 [J]. 中国电机工程学报, 2014, 34(29): 5029-5040.

XUE Yusheng, LEI Xing, XUE Feng, et al. A review on impacts of wind power uncertainties on power systems [J]. Proceedings of the CSEE, 2014, 34(29): 5029-5040.

ROCKAFELLAR R T, URYASEV S. Optimization of conditional value-at-risk [J]. Journal of Risk, 2000, 3(3): 21-41.

HUANG Yuping, ZHENG Qipeng, WANG Jianhui. Two-stage stochastic unit commitment model including non-generation resources with conditional value-at-risk constraints [J]. Electric Power Systems Research, 2014, 116: 427-438.

ZHANG Yao, WANG Jianxue, DING Tao, et al. Conditional value at risk-based stochastic unit commitment considering the uncertainty of wind power generation [J]. IET Generation, Transmission Distribution, 2018, 12(2): 482-489.

胡浩, 王英瑞, 曾博, 等. 基于CVaR理论的综合能源系统经济优化调度 [J]. 电力自动化设备, 2017, 37(6): 209-219.

HU Hao, WANG Yingrui, ZENG Bo, et al. CVaR-based economic optimal dispatch of integrated energy system [J]. Electric Power Automation Equipment, 2017, 37(6): 209-219.

晋宏杨, 孙宏斌, 牛涛, 等. 考虑风险约束的高载能负荷——风电协调调度方法 [J]. 电力系统自动化, 2019, 43(16): 9-18.

JIN Hongyang, SUN Hongbin, NIU Tao, et al. Coordinated dispatch method of energy-extensive load and wind power risk constraints [J]. Automation of Electric Power Systems, 2019, 43(16): 9-18.

SHAHIDEHPOUR M, FU Y, WIEDMAN T. Impact of natural gas infrastructure on electric power systems [J]. Proceedings of the IEEE, 2005, 93(5): 1042-1056.

LIU Cong, SHAHIDEHPOUR M, FU Yong, et al. Security-constrained unit commitment with natural gas transmission constraints [J]. IEEE Transactions on Power Systems, 2009, 24(3): 1523-1536.

CORREA-POSADA C M, SáNCHEZ-MARTíN P. Integrated power and natural gas model for energy adequacy in short-term operation [J]. IEEE Transactions on Power Systems, 2015, 30(6): 3347-3355.

ZHANG X, SHAHIDEHPOUR M, ALABDULWAHAB A, et al. Hourly electricity demand response in the stochastic day-ahead scheduling of coordinated electricity and natural gas networks [J]. IEEE Transactions on Power Systems, 2016, 31(1): 592-601.

QIU Jing, DONG Zhaoyang, ZHAO Junhua, et al. Low carbon oriented expansion planning of integrated gas and power systems [J]. IEEE Transactions on Power Systems, 2015, 30(2): 1035-1046.

余娟, 马梦楠, 郭林, 等. 含电转气的电-气互联系统可靠性评估 [J]. 中国电机工程学报, 2018, 38(3): 708-715.

YU Juan, MA Mengnan, GUO Lin, et al. Reliability evaluation of integrated electrical and natural-gas system with power-to-gas [J]. Proceedings of the CSEE, 2018, 38(3): 708-715.

ZHANG X, CHE L, SHAHIDEHPOUR M, et al. Electricity-natural gas operation planning with hourly demand response for deployment of flexible ramp [J]. IEEE Transactions on Sustainable Energy, 2016, 7(3): 996-1004.

卫志农, 张思德, 孙国强, 等. 计及电转气的电-气互联综合能源系统削峰填谷研究 [J]. 中国电机工程学报, 2017, 37(16): 4601-4609, 885.

WEI Zhinong, ZHANG Side, SUN Guoqiang, et al. Power-to-gas considered peak load shifting research for integrated electricity and natural-gas energy systems [J]. Proceedings of the CSEE, 2017, 37(16): 4601-4609, 885.

张思德, 胡伟, 卫志农, 等. 基于机会约束规划的电-气互联综合能源系统随机最优潮流 [J]. 电力自动化设备, 2018, 38(9): 121-128.

ZHANG Side, HU Wei, WEI Zhinong, et al. Stochastic optimal power flow of integrated power and natural gas energy system based on chance-constrainted programming [J]. Electric Power Automation Equipment, 2018, 38(9): 121-128.

BAI Linquan, LI Fangxing, JIANG Tao, et al. Robust scheduling for wind integrated energy systems considering gas pipeline and power transmission N-1 contingencies [J]. IEEE Transactions on Power Systems, 2016, 32(2): 1582-1584.

严超, 别朝红, 王灿, 等. 面向新一代能源系统的风险评估研究现状及展望 [J]. 电网技术, 2019, 43(1): 12-22.

YAN Chao, BIE Zhaohong, WANG Can, et al. Risk assessment studies for next-generation energy system [J]. Power System Technology, 2019, 43(1): 12-22.

ZHAO B, CONEJO A J, SIOSHANSIS R. Unit commitment under gas-supply uncertainty and gas-price variability [J]. IEEE Transactions on Power Systems, 2017, 32(3): 2394-2405.

LIU C, SHAHIDEHPOUR M, WANG J. Coordinated scheduling of electricity and natural gas infrastructures with a transient model for natural gas flow [J]. Chaos: An Interdisciplinary Journal of Nonlinear Science, 2011, 21(2): 025102.

SHARIFZADEH H, AMJADY N, ZAREIPOUR H. Multi-period stochastic security-constrained OPF considering the uncertainty sources of wind power, load demand and equipment unavailability [J]. Electric Power Systems Research, 2017, 146: 33-42.

BERALDI P, BRUNI M. A clustering approach for scenario tree reduction: an application to a stochastic programming portfolio optimization problem [J]. TOP, 2014, 22(3): 934-949.

HONG T, PINSON P, FAN S, et al. Probabilistic energy forecasting: global energy forecasting competition 2014 and beyond [J]. International Journal of Forecasting, 2016, 32(3): 896-913.

CHEN Zexing, ZHANG Yongjun, JI Tianyao, et al. Coordinated optimal dispatch and market equilibrium of integrated electric power and natural gas networks with P2G embedded [J]. Journal of Modern Power Systems and Clean Energy, 2018, 6(3): 495-508.

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