AI Chat Paper
Note: Please note that the following content is generated by AMiner AI. SciOpen does not take any responsibility related to this content.
{{lang === 'zh_CN' ? '文章概述' : 'Summary'}}
{{lang === 'en_US' ? '中' : 'Eng'}}
Chat more with AI
Powered by AMiner. Clicking this button will take you away from SciOpen.
Home CSEE Journal of Power and Energy Systems Article
PDF (2 MB)
Cite
EndNote(RIS) BibTeX
Collect
Submit Manuscript AI Chat Paper
Show Outline
Outline
Show full outline
Hide outline
Outline
Show full outline
Hide outline
Regular Paper | Open Access

Integrated Model for Resilience Evaluation of Power-gas Systems Under Windstorms

Yucui Wang1, Yongbiao Yang2,3( ), Qingshan Xu2,3
School of Cyber Science and Engineering, Southeast University, Nanjing 210096, China
School of Electrical Engineering, Southeast University, Nanjing 210096, China
Nanjing Center for Applied Mathematics, Nanjing 210096, China
Show Author Information

Abstract

Integrated power-gas systems (IPGS) have developed critical infrastructure in integrated energy systems. Moreover, various extreme weather events with low probability and high risk have seriously affected the stable operation of IPGSs. Due to close interconnectedness through coupling elements between the power system (PS) and natural gas system (NGS) when a disturbance happens in one system, a series of complicated sequences of dependent events may follow in another system. Especially under extreme conditions, this coupling can lead to a dramatic degradation of system performance, resulting in catastrophic failures. Therefore, there is an urgent need to model and evaluate resilience of IPGSs under extreme weather. Following this development trend, an integrated model for resilience evaluation of IPGS is proposed under extreme weather events focusing on windstorms. First, a framework of IPGS is proposed to describe states of the system at different stages under disaster conditions. Furthermore, an evaluation model considering cascading effects is used to quantify the impact of windstorms on NGS and PS. Meanwhile, a Monte Carlo simulation (MCS) technique is utilized to characterize chaotic fault of components. Moreover, time-dependent nodal and system resilience indices for IPGS are proposed to display impacts of windstorms. Numerical results on the IPGS test system demonstrate the proposed methods.

Keywords

Cascading effectsintegrated power-gas systemsnodal resilience indicesoptimal power flow modelresilience assessmentsystem resilience indiceswindstorms

References

[1]
Q. Peng et al., “Hybrid energy sharing mechanism for integrated energy systems based on the Stackelberg game, ” in CSEE Journal of Power and Energy Systems, vol. 7, no. 5, pp. 911–921, Sep. 2021, doi: 10.17775/CSEEJPES.2020.06500.
Crossref
[2]

Y. Wang, Y. Yang and Q. Xu, “Reliability Assessment for Integrated Power-gas Systems Considering Renewable Energy Uncertainty and Cascading Effects, ” CSEE Journal of Power and Energy Systems, vol. 9, no. 3, pp. 1214–1226, May 2023, doi: 10.17775/CSEEJPES.2022.00740.
Crossref Google Scholar
[3]

B. Zhang, L. Zhang, W. Tang, Z. Wang and C. Wang, “A coordinated restoration method of electric buses and network reconfiguration in distribution systems under extreme events, ” CSEE Journal of Power and Energy Systems, doi: 10.17775/CSEEJPES.2020.04320.
Crossref Google Scholar
[4]
M. Kezunovic, I. Dobson, and Y. M. Dong, “Impact of extreme weather on power system blackouts and forced outages: new challenges, ” 2008.
[5]
X. E. Jiang and Y. S. Wang. (2021, Jul. 21). In addition to the Zhengzhou rainstorm, the world has experienced at least 189 extreme weather events in 2021.[Online]. Available: https://www.thepaper.cn/newsDetail_forward_13675353.
[6]
IPCC. (2022). Climate change 2022: mitigation of climate change.[Online]. https://www.ipcc.ch/report/ar6/wg3/downloads/report/IPCC_AR6_WGⅢ_FullReport.pdf.
[7]

W. P. Wang, S. N. Yang, F. Y. Hu, H. E. Stanley, S. He, and M. M. Shi, “An approach for cascading effects within critical infrastructure systems, ” Physica A: Statistical Mechanics and its Applications, vol. 510, pp. 164–177, Nov. 2018, doi: 10.1016/j.physa.2018.06.129.
Crossref Google Scholar
[8]

S. Hosseini, K. Barker, and J. E. Ramirez-Marquez, “A review of definitions and measures of system resilience, ” Reliability Engineering & System Safety, vol. 145, pp. 47–61, Jan. 2016, doi: 10.1016/j.ress.2015.08.006.
Crossref Google Scholar
[9]

J. Z. Lu, J. Guo, Z. Jian, Y. H. Yang, and W. H. Tang, “Resilience assessment and its enhancement in tackling adverse impact of ice disasters for power transmission systems, ” Energies, vol. 11, no. 9, pp. 2272, Aug. 2018, doi: 10.3390/en11092272.
Crossref Google Scholar
[10]

H. B. Liu, R. A. Davidson, and T. V. Apanasovich, “Statistical forecasting of electric power restoration times in hurricanes and ice storms, ” IEEE Transactions on Power Systems, vol. 22, no. 4, pp. 2270–2279, Nov. 2007, doi: 10.1109/TPWRS.2007.907587.
Crossref Google Scholar
[11]

M. Ouyang, L. Dueñas-Osorio, and X. Min, “A three-stage resilience analysis framework for urban infrastructure systems, ” Structural Safety, vol. 36–37, pp. 23–31, May/Jul. 2012, doi: 10.1016/j.strusafe.2011.12.004.
Crossref Google Scholar
[12]

M. Panteli, C. Pickering, S. Wilkinson, R. Dawson, and P. Mancarella, “Power system resilience to extreme weather: fragility modeling, probabilistic impact assessment, and adaptation measures, ” IEEE Transactions on Power Systems, vol. 32, no. 5, pp. 3747–3757, Sep. 2017, doi: 10.1109/TPWRS.2016.2641463.
Crossref Google Scholar
[13]

F. Cadini, G. L. Agliardi, and E. Zio, “A modeling and simulation framework for the reliability/availability assessment of a power transmission grid subject to cascading failures under extreme weather conditions, ” Applied Energy, vol. 185, pp. 267–279, Jan. 2017, doi: 10.1016/j.apenergy.2016.10.086.
Crossref Google Scholar
[14]

M. Ouyang and L. Dueñas-Osorio, “Multi-dimensional hurricane resilience assessment of electric power systems, ” Structural Safety, vol. 48, pp. 15–24, May 2014, doi: 10.1016/j.strusafe.2014.01.001.
Crossref Google Scholar
[15]

G. P. Cimellaro, O. Villa, and M. Bruneau, “Resilience-based design of natural gas distribution networks, ” Journal of Infrastructure Systems, vol. 21, no. 1, pp. 05014005, Mar. 2015, doi: 10.1061/(ASCE)IS.1943-555X.0000204.
Crossref Google Scholar
[16]

Y. T. Ding, S. Chen, Y. L. Zheng, S. L. Chai, and R. Nie, “Resilience assessment of China's natural gas system under supply shortages: a system dynamics approach, ” Energy, vol. 247, pp. 123518, May 2022, doi: 10.1016/j.energy.2022.123518.
Crossref Google Scholar
[17]
P. Hauser, H. Hobbie, and D. Möst, “Resilience in the German natural gas network: modelling approach for a high-resolution natural gas system, ” in 2017 14th International Conference on the European Energy Market (EEM), Dresden, Germany, 2017, pp. 1–6, doi: 10.1109/EEM.2017.7981942.
Crossref
[18]

M. L. Bao, Y. Ding, C. Z. Shao, Y. Yang, and P. Wang, “Nodal reliability evaluation of interdependent gas and power systems considering cascading effects, ” IEEE Transactions on Smart Grid, vol. 11, no. 5, pp. 4090–4104, Sep. 2020, doi: 10.1109/TSG.2020.2982562.
Crossref Google Scholar
[19]

R. Hemmati, H. Mehrjerdi, and S. M. Nosratabadi, “Resilience-oriented adaptable microgrid formation in integrated electricity-gas system with deployment of multiple energy hubs, ” Sustainable Cities and Society, vol. 71, pp. 102946, Aug. 2021, doi: 10.1016/j.scs.2021.102946.
Crossref Google Scholar
[20]

Y. T. Xu, S. S. Chen, S. M. Tian, and F. X. Gong, “Demand management for resilience enhancement of integrated energy distribution system against natural disasters, ” Sustainability, vol. 14, no. 1, pp. 5, Dec. 2021, doi: 10.3390/su14010005.
Crossref Google Scholar
[21]
H. J. Zhang, T. Y. Zhao, P. Wang, and S. H. Yao, “Power system resilience assessment considering of integrated natural gas system, ” in IET International Conference on Resilience of Transmission and Distribution Networks (RTDN 2017), Birmingham, UK, 2017, pp. 1–7, doi: 10.1049/cp.2017.0334.
Crossref
[22]

H. J. Zhang, P. Wang, S. H. Yao, X. C. Liu, and T. Y. Zhao, “Resilience assessment of interdependent energy systems under hurricanes, ” IEEE Transactions on Power Systems, vol. 35, no. 5, pp. 3682–3694, Sep. 2020, doi: 10.1109/TPWRS.2020.2973699.
Crossref Google Scholar
[23]

E. B. Watson and A. H. Etemadi, “Modeling electrical grid resilience under hurricane wind conditions with increased solar and wind power generation, ” IEEE Transactions on Power Systems, vol. 35, no. 2, pp. 929–937, Mar. 2020, doi: 10.1109/TPWRS.2019.2942279.
Crossref Google Scholar
[24]

M. L. Bao, Y. Ding, M. S. Sang, D. Q. Li, C. Z. Shao, and J. Y. Yan, “Modeling and evaluating nodal resilience of multi-energy systems under windstorms, ” Applied Energy, vol. 270, pp. 115136, Jul. 2020, doi: 10.1016/j.apenergy.2020.115136.
Crossref Google Scholar
[25]
A. F. Mensah, “Resilience assessment of electric grids and distributed wind generation under hurricane hazards, ” Ph.D. dissertation, department, Rice University, Houston, TX, 2015.
[26]
Code for Design of 20kV and Below Substations, GB 50053–2013, 2014.
[27]
Code for Design of Small Fossil Fired Power Plant, GB 50049–2011, 2011.
[28]

S. Rose, P. Jaramillo, M. J. Small, and J. Apt, “Quantifying the hurricane catastrophe risk to offshore wind power, ” Risk Analysis, vol. 33, no. 12, pp. 2126–2141, Dec. 2013, doi: 10.1111/risa.12085.
Crossref Google Scholar
[29]

W. H. Tang, Y. H. Yang, Y. J. Li, J. Z. Lu, and Q. H. Wu, “Investigation on resilience assessment and enhancement for power transmission systems under extreme meteorological disasters, ” Proceedings of the CSEE, vol. 40, no. 7, pp. 2244–2254, Apr. 2020, doi: 10.13334/j.0258-8013.pcsee.182191.
Crossref Google Scholar
[30]

B. J. Li, H. W. Qi, J. Y. Fu, Z. H. Gao, and L. Guo, “Analysis on the impact of extreme weather on new energy operation, ” Jilin Electric Power, vol. 50, no. 1, pp. 10–13, Feb. 2022, doi: 10.16109/j.cnki.jldl.2022.01.002.
Crossref Google Scholar
[31]

H. Y. Yuan, F. X. Li, Y. L. Wei, and J. X. Zhu, “Novel linearized power flow and linearized OPF models for active distribution networks with application in distribution LMP, ” IEEE Transactions on Smart Grid, vol. 9, no. 1, pp. 438–448, Jan. 2018, doi: 10.1109/TSG.2016.2594814.
Crossref Google Scholar
[32]

A. Mehrtash, P. Wang, and L. Goel, “Reliability evaluation of power systems considering restructuring and renewable generators, ” IEEE Transactions on Power Systems, vol. 27, no. 1, pp. 243–250, Feb. 2012, doi: 10.1109/TPWRS.2011.2161350.
Crossref Google Scholar
[33]

M. Panteli, P. Mancarella, D. N. Trakas, E. Kyriakides, and N. D. Hatziargyriou, “Metrics and quantification of operational and infrastructure resilience in power systems, ” IEEE Transactions on Power Systems, vol. 32, no. 6, pp. 4732–4742, Nov. 2017, doi: 10.1109/TPWRS.2017.2664141.
Crossref Google Scholar
[34]

C. Wang and M. H. Nehrir, “Analytical approaches for optimal placement of distributed generation sources in power systems, ” IEEE Transactions on Power Systems, vol. 19, no. 4, pp. 2068–2076, Nov. 2004, doi: 10.1109/TPWRS.2004.836189.
Crossref Google Scholar
[35]

D. De Wolf and Y. Smeers, “The gas transmission problem solved by an extension of the simplex algorithm, ” Management Science, vol. 46, no. 11, pp. 1454–1465, Nov. 2000, doi: 10.1287/mnsc.46.11.1454.12087.
Crossref Google Scholar
[36]
S. An, Q. Li, and T. W. Gedra, “Natural gas and electricity optimal power flow, ” in 2003 IEEE PES Transmission and Distribution Conference and Exposition, Dallas, TX, USA, 2003, pp. 138–143, doi: 10.1109/TDC.2003.1335171.
Crossref
[37]

K. A. Pambour, B. C. Erdener, R. Bolado-Lavin, and G. P. J. Dijkema, “Development of a simulation framework for analyzing security of supply in integrated gas and electric power systems, ” Applied Sciences, vol. 7, no. 1, pp. 47, Jan. 2017.
Crossref Google Scholar
[38]

D. A. Alves, L. C. P. da Silva, C. A. Castro, and V. F. da Costa, “Continuation fast decoupled power flow with secant predictor, ” IEEE Transactions on Power Systems, vol. 18, no. 3, pp. 1078–1085, Aug. 2003, doi: 10.1109/TPWRS.2003.814892.
Crossref Google Scholar
[39]

Q. D. Meng, S. Zhang, B. X. Li, X. Li, and G. Q. Li, “Fast decoupling based parallel computing method for continuation power flow in power system, ” Proceedings of the CSU-EPSA, vol. 33, no. 7, pp. 41–48, Jul. 2021, doi: 10.19635/j.cnki.csu-epsa.000742.
Crossref Google Scholar
[40]
“Wind grade table”, Qinghai Agro-Technology Extension, vol. 2022, no. 3, pp. 55.
CSEE Journal of Power and Energy Systems
Volume 10 Issue 4,
July 2024
Pages 1427-1440
DOI: 10.17775/CSEEJPES.2022.05420
Cite this article:
Wang Y, Yang Y, Xu Q. Integrated Model for Resilience Evaluation of Power-gas Systems Under Windstorms. CSEE Journal of Power and Energy Systems, 2024, 10(4): 1427-1440. https://doi.org/10.17775/CSEEJPES.2022.05420

142

Views

4

Downloads

0

Crossref

0

Web of Science

0

Scopus

0

CSCD

Altmetrics
Received: 07 August 2022
Revised: 06 November 2022
Accepted: 11 November 2022
Published: 08 September 2023
© 2022 CSEE.

This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
Return