A Probabilistic Method for Integrating Physics-Based and Data-Driven Storm Outage Prediction Models for Power Systems
Publication: ASCE-ASME Journal of Risk and Uncertainty in Engineering Systems, Part A: Civil Engineering
Volume 10, Issue 2
Abstract
To predict power outages for upcoming storm events and assess the resilience of power systems, accurate models of power outage probabilities are necessary. Although physics-based fragility models have been developed to forecast structural failure probabilities under strong winds, such methods may capture limited failure modes and could struggle to predict more-random outages that are not directly related to strong winds. Data-driven machine learning methods have emerged for power outage predictions considering multiple failure modes, although they may struggle to predict cases with limited data, such as extreme events. To integrate the two different approaches, a novel model is proposed to probabilistically combine physics-based and machine-learning predictions. Fragility analyses of various transmission structure types and tree species subject to wind loads were conducted for the prediction of wind-induced structural damages. An extreme gradient boosting (XGboost) machine learning model trained on infrastructure, weather, topographic, and vegetation characteristics is used for the prediction of nonstructural outage probabilities. The framework is demonstrated through a case study of the overhead transmission system in the New England region of the US over 44 storm events from 2015 to 2020. The results show an improved agreement between predicted and observed outages, as well as correlations between predicted probability and observed outage rate, highlighting the model’s effectiveness for estimations of storm impacts and grid vulnerability.
Get full access to this article
View all available purchase options and get full access to this article.
Data Availability Statement
Some data, models, or code, related to the transmission lines and power outages, used during the study were provided by third parties, ISO-New England and Eversource Energy, and are not publicly available. Direct requests for these materials may be made to the providers as indicated in the Acknowledgements. Other data requests can be made available by the corresponding author on reasonable request.
Acknowledgments
The paper reflects only the views of the authors. The project is funded in part by ISO-New England and the Graduate Assistance in Areas of National Need (GAANN) fellowship. Special thanks is given to Eversource Energy Center and Eversource Energy, including Mark Wayne and Mohsen Sahirad, for their assistance.
References
Alpay, B. A., D. Wanik, P. Watson, D. Cerrai, G. Liang, and E. Anagnostou. 2020. “Dynamic modeling of power outages caused by thunderstorms.” Forecasting 2 (May): 151–162. https://doi.org/10.3390/forecast2020008.
Bjarnadottir, S., Y. Li, and M. G. Stewart. 2013. “Hurricane risk assessment of power distribution poles considering impacts of a changing climate.” J. Infrastruct. Syst. 19 (1): 12–24. https://doi.org/10.1061/(ASCE)IS.1943-555X.0000108.
Braik, A. M., A. M. Salman, and Y. Li. 2019. “Risk-based reliability and cost analysis of utility poles subjected to tornado hazard.” J. Aerosp. Eng. 32 (4): 04019040. https://doi.org/10.1061/(ASCE)AS.1943-5525.0001029.
Braik, A. M., A. M. Salman, and Y. Li. 2020. “Reliability-based assessment and cost analysis of power distribution systems at risk of tornado hazard.” ASCE-ASME J. Risk Uncertainty Eng. Syst. Part A: Civ. Eng. 6 (2): 1–12. https://doi.org/10.1061/ajrua6.0001055.
Cai, Y., Q. Xie, S. Xue, L. Hu, and A. Kareem. 2019. “Fragility modelling framework for transmission line towers under winds.” Eng. Struct. 191 (May): 686–697. https://doi.org/10.1016/j.engstruct.2019.04.096.
Cerrai, D., M. Koukoula, P. Watson, and E. N. Anagnostou. 2020. “Outage prediction models for snow and ice storms.” Sustainable Energy Grids Networks 21 (Mar): 100294. https://doi.org/10.1016/j.segan.2019.100294.
Cerrai, D., D. W. Wanik, A. E. Bhuiyan, X. Zhang, J. Yang, M. E. B. Frediani, and E. N. Anagnostou. 2019a. “Predicting storm outages through new representations of weather and vegetation.” IEEE Access 7 (Mar): 29639–29654. https://doi.org/10.1109/ACCESS.2019.2902558.
Cerrai, D., P. Watson, and E. N. Anagnostou. 2019b. “Assessing the effects of a vegetation management standard on distribution grid outage rates.” Electr. Power Syst. Res. 175 (Oct): 105909. https://doi.org/10.1016/j.epsr.2019.105909.
Chen, J., Q. Xian, and P. Zhang. 2019. “Buckling analysis of transmission tower considering ice load.” IOP Conf. Ser.: Mater. Sci. Eng. 473 (1): 012036. https://doi.org/10.1088/1757-899X/473/1/012036.
Darestani, Y., J. Padgett, and A. Shafieezadeh. 2022. “Parametrized wind–surge–wave fragility functions for wood utility poles.” J. Struct. Eng. 148 (6): 04022057. https://doi.org/10.1061/(ASCE)ST.1943-541X.0003319.
Darestani, Y. M., and A. Shafieezadeh. 2019. “Multi-dimensional wind fragility functions for wood utility poles.” Eng. Struct. 183 (Mar): 937–948. https://doi.org/10.1016/j.engstruct.2019.01.048.
Fu, X., and H. N. Li. 2018. “Uncertainty analysis of the strength capacity and failure path for a transmission tower under a wind load.” J. Wind Eng. Ind. Aerodyn. 173 (Mar): 147–155. https://doi.org/10.1016/j.jweia.2017.12.009.
Fu, X., H. N. Li, and G. Li. 2016. “Fragility analysis and estimation of collapse status for transmission tower subjected to wind and rain loads.” Struct. Saf. 58 (May): 1–10. https://doi.org/10.1016/j.strusafe.2015.08.002.
Fu, X., H. N. Li, G. Li, Z. Q. Dong, and M. Zhao. 2021. “Failure analysis of a transmission line considering the joint probability distribution of wind speed and rain intensity.” Eng. Struct. 233 (Apr): 111913. https://doi.org/10.1016/j.engstruct.2021.111913.
Goforth, E., A. Yosri, W. El-Dakhakhni, and L. Wiebe. 2022. “Rapidity prediction of power infrastructure forced outages: Data-driven approach for resilience planning.” J. Energy Eng. 148 (3): 1–13. https://doi.org/10.1061/(ASCE)EY.1943-7897.0000836.
Gu, X., L. Wang, Q. Ou, and W. Zhang. 2023. “Efficient stochastic analysis of unsaturated slopes subjected to various rainfall intensities and patterns.” Geosci. Front. 14 (1): 101490. https://doi.org/10.1016/j.gsf.2022.101490.
Han, S., S. D. Guikema, and S. M. Quiring. 2009. “Improving the predictive accuracy of hurricane power outage forecasts using generalized additive models.” Risk Anal. 29 (10): 1443–1453. https://doi.org/10.1111/j.1539-6924.2009.01280.x.
Hong, M., X. Luo, S. Maslennikov, and L. E. Litvinov. 2021. “Enhancement of operational resilience with the online weather look-ahead study.” In Proc., IEEE Power and Energy Society General Meeting. New York: IEEE.
Hou, G., and S. Chen. 2020. “Probabilistic modeling of disrupted infrastructures due to fallen trees subjected to extreme winds in urban community.” Nat. Hazards 102 (3): 1323–1350. https://doi.org/10.1007/s11069-020-03969-y.
Hou, G., and K. K. Muraleetharan. 2023. “Modeling the resilience of power distribution systems subjected to extreme winds considering tree failures: An integrated framework.” Int. J. Disaster Risk Sci. 14 (2): 194–208. https://doi.org/10.1007/s13753-023-00478-x.
Hou, H., Z. Zhang, J. Yu, R. Wei, Y. Huang, and X. Li. 2022. “Damage prediction of 10kV power towers in distribution network under typhoon disaster based on data-driven model.” Int. J. Electr. Power Energy Syst. 142 (Mar): 108307. https://doi.org/10.1016/j.ijepes.2022.108307.
Hughes, W., Q. Lu, Z. Ding, and W. Zhang. 2023. “Modeling tree damages and infrastructure disruptions under strong winds for community resilience assessment.” ASCE-ASME J. Risk Uncertainty Eng. Syst. Part A: Civ. Eng. 9 (1): 04022057. https://doi.org/10.1061/ajrua6.rueng-956.
Hughes, W., W. Zhang, D. Cerrai, A. Bagtzoglou, D. Wanik, and E. Anagnostou. 2022a. “A hybrid physics-based and data-driven model for power distribution system infrastructure hardening and outage simulation.” Reliab. Eng. Syst. Saf. 225 (2022): 108628. https://doi.org/10.1016/j.ress.2022.108628.
Hughes, W., W. Zhang, Q. Lu, and Z. Ding. 2022b. “Fragility assessment of diverse power transmission structures under strong winds.” In Proc., 14th Americas Conf. on Wind Engineering. Fort Collins, CO: American Association for Wind Engineering.
Jin, S., C. Homer, L. Yang, P. Danielson, J. Dewitz, C. Li, Z. Zhu, G. Xian, and D. Howard. 2019. “Overall methodology design for the United States national land cover database 2016 products.” Remote Sens. 11 (24): 2971. https://doi.org/10.3390/rs11242971.
Krist, F. J., F. J. Sapio, and B. M. Tkacz. 2007. A multicriteria framework for producing local, regional, and national insect and disease risk maps, Washington, DC: US Forest Service.
Lai, Z., C. Mylonas, S. Nagarajaiah, and E. Chatzi. 2021. “Structural identification with physics-informed neural ordinary differential equations.” J. Sound Vib. 508 (Apr): 116196. https://doi.org/10.1016/j.jsv.2021.116196.
Liu, H., R. A. Davidson, and T. V. Apanasovich. 2008. “Spatial generalized linear mixed models of electric power outages due to hurricanes and ice storms.” Reliab. Eng. Syst. Saf. 93 (Mar): 875–890. https://doi.org/10.1016/j.ress.2007.03.038.
Lu, Q., and W. Zhang. 2022. “An integrated damage modeling and assessment framework for overhead power distribution systems considering tree-failure risks.” Struct. Infrastruct. Eng. 19 (12): 1745–1760. https://doi.org/10.1080/15732479.2022.2053552.
Lu, Q., W. Zhang, and A. Bagtzoglou. 2022. “Physics-based reliability assessment of community-based power distribution system using synthetic hurricanes.” ASCE-ASME J. Risk Uncertainty Eng. Syst. Part A: Civ. Eng. 8 (1): 04021088. https://doi.org/10.1061/AJRUA6.0001205.
Ma, L., P. Bocchini, and V. Christou. 2020a. “Fragility models of electrical conductors in power transmission networks subjected to hurricanes.” Struct. Saf. 82 (Feb): 101890. https://doi.org/10.1016/j.strusafe.2019.101890.
Ma, L., V. Christou, and P. Bocchini. 2021. “Framework for probabilistic simulation of power transmission network performance under hurricanes.” Reliab. Eng. Syst. Saf. 217 (Mar): 108072. https://doi.org/10.1016/j.ress.2021.108072.
Ma, Y., Q. Dai, and W. Pang. 2020b. “Reliability assessment of electrical grids subjected to wind hazards and ice accretion with concurrent wind.” J. Struct. Eng. 146 (7): 04020134. https://doi.org/10.1061/(ASCE)ST.1943-541X.0002684.
McPherson, E. G., N. S. van Doorn, and P. J. Peper. 2016. Urban tree database and allometric equations. Fresno, CA: Pacific Southewest Research Station.
Montoya-Rincon, J. P., J. E. Gonzalez-Cruz, and M. P. Jensen. 2023. “Evaluation of transmission line hardening scenarios using a machine learning approach.” ASCE-ASME J. Risk Uncertainty Eng. Syst. Part B: Mech. Eng. 9 (Mar): 1–7. https://doi.org/10.1115/1.4063012.
NASA/METI/AIST/Japan Spacesystems and US/Japan ASTER Science Team. 2019. “ASTER global digital elevation model V003.” Accessed November 30, 2013. https://doi.org/10.5067/ASTER/ASTGTM.003.
Nateghi, R., S. Guikema, and S. M. Quiring. 2014. “Power outage estimation for tropical cyclones: Improved accuracy with simpler models.” Risk Anal. 34 (6): 1069–1078. https://doi.org/10.1111/risa.12131.
Panteli, M., D. N. Trakas, P. Mancarella, and N. D. Hatziargyriou. 2016. “Boosting the power grid resilience to extreme weather events using defensive islanding.” IEEE Trans. Smart Grid 7 (6): 2913–2922. https://doi.org/10.1109/TSG.2016.2535228.
Potapov, P., et al. 2021. “Mapping global forest canopy height through integration of GEDI and Landsat data.” Remote Sens. Environ. 253 (2021): 112165. https://doi.org/10.1016/j.rse.2020.112165.
Pretzsch, H., and P. Biber. 2005. “A re-evaluation of Reineke’s rule and stand density index.” For. Sci. 51 (4): 304–320.
Quiring, S. M., L. Zhu, and S. D. Guikema. 2011. “Importance of soil and elevation characteristics for modeling hurricane-induced power outages.” Nat. Hazards 58 (Mar): 365–390. https://doi.org/10.1007/s11069-010-9672-9.
Rao, C., H. Sun, and Y. Liu. 2021. “Physics-informed deep learning for computational elastodynamics without labeled data.” J. Eng. Mech. 147 (8): 04021043. https://doi.org/10.1061/(ASCE)EM.1943-7889.0001947.
Robison, E. G., and R. L. Beschta. 1990. “Identifying trees in riparian areas that can provide coarse woody debris to streams.” For. Sci. 36 (3): 790–801. https://doi.org/10.1093/FORESTSCIENCE/36.3.790.
Romanoff, M. 1957. “Underground corrosion.” In Bureau of Standards circular 579. Washington, DC: US Government Printing Office.
Salman, A. M., and Y. Li. 2016. “Age-dependent fragility and life-cycle cost analysis of wood and steel power distribution poles subjected to hurricanes.” Struct. Infrastruct. Eng. 12 (8): 890–903. https://doi.org/10.1080/15732479.2015.1053949.
Shafieezadeh, A., U. P. Onyewuchi, M. M. Begovic, and R. Desroches. 2014. “Age-dependent fragility models of utility wood poles in power distribution networks against extreme wind hazards.” IEEE Trans. Power Deliv. 29 (1): 131–139. https://doi.org/10.1109/TPWRD.2013.2281265.
Shaw, J. D. 2006. “Reineke’s stand density index: Where are we and where do we go from here?” Society of American Foresters 2005 National Convention. Accessed October 19, 2005. https://www.fs.usda.gov/research/treesearch/25003.
Sheil, B. B. 2021. “Hybrid framework for forecasting circular excavation collapse: combining physics-based and data-driven modeling.” J. Geotech. Geoenviron. Eng. 147 (12): 04021140. https://doi.org/10.1061/(ASCE)GT.1943-5606.0002683.
Skamarock, W. C., J. B. Klemp, J. Dudhi, D. O. Gill, D. M. Barker, M. G. Duda, X.-Y. Huang, W. Wang, and J. G. Powers. 2008. “A description of the advanced research WRF version 3” NCAR Techn. Note 475 (Jun): 113. https://doi.org/10.5065/D68S4MVH.
Taylor, W. O., S. Nyame, W. Hughes, M. Koukoula, D. Cerrai, and E. N. Anagnostou. 2023. “Machine learning evaluation of storm-related transmission outage factors and risk.” Sustainable Energy Grids Networks 34 (Jun): 101016. https://doi.org/10.1016/j.segan.2023.101016.
Taylor, W. O., P. L. Watson, D. Cerrai, and E. N. Anagnostou. 2022. “Dynamic modeling of the effects of vegetation management on weather-related power outages.” Electr. Power Syst. Res. 207 (Mar): 107840. https://doi.org/10.1016/j.epsr.2022.107840.
Tervo, R., I. Láng, A. Jung, and A. Mäkelä. 2021. “Predicting power outages caused by extratropical storms.” Nat. Hazards Earth Syst. Sci. 21 (2): 607–627. https://doi.org/10.5194/nhess-21-607-2021.
Tian, H., and Y. Wang. 2023. “Data-driven and physics-informed Bayesian learning of spatiotemporally varying consolidation settlement from sparse site investigation and settlement monitoring data.” Comput. Geotech. 157 (Feb): 105328. https://doi.org/10.1016/j.compgeo.2023.105328.
Tian, L., H. Pan, R. Ma, L. Zhang, and Z. Liu. 2020. “Full-scale test and numerical failure analysis of a latticed steel tubular transmission tower.” Eng. Struct. 208 (Apr): 109919. https://doi.org/10.1016/j.engstruct.2019.109919.
Udeh, K., D. W. Wanik, D. Cerrai, and D. Aguiar. 2022. “Autoregressive modeling of utility customer outages with deep neural networks.” In Proc., 2022 IEEE 12th Annual Computing and Communication Workshop and Conf. (CCWC), 406–414. New York: IEEE.
Wang, R., K. Kashinath, M. Mustafa, A. Albert, and R. Yu. 2020. “Towards physics-informed deep learning for turbulent flow prediction.” In Proc., ACM SIGKDD Int. Conf. on Knowledge Discovery and Data Mining, 1457–1466. New York: Association for Computing Machinery.
Wanik, D. W., E. N. Anagnostou, B. M. Hartman, M. E. B. Frediani, and M. Astitha. 2015. “Storm outage modeling for an electric distribution network in Northeastern USA.” Nat. Hazards 79 (2): 1359–1384. https://doi.org/10.1007/s11069-015-1908-2.
Watson, P., M. Koukoula, and E. Anagnostou. 2021. “Influence of the characteristics of weather information in a thunderstorm-related power outage prediction system.” Forecasting 3 (May): 541–560. https://doi.org/10.3390/forecast3030034.
Wilson, B. T., A. J. Lister, R. I. Riemann, and D. M. Griffith. 2013. Live tree species basal area of the contiguous United States (2000–2009). Newtown Square, PA: USDA Forest Service, Rocky Mountain Research Station.
Winkler, J., L. Dueñas-Osorio, R. Stein, and D. Subramanian. 2010. “Performance assessment of topologically diverse power systems subjected to hurricane events.” Reliab. Eng. Syst. Saf. 95 (4): 323–336. https://doi.org/10.1016/j.ress.2009.11.002.
Xue, J., F. Mohammadi, X. Li, M. Sahraei-Ardakani, G. Ou, and Z. Pu. 2020. “Impact of transmission tower-line interaction to the bulk power system during hurricane.” Reliab. Eng. Syst. Saf. 203 (Nov): 107079. https://doi.org/10.1016/j.ress.2020.107079.
Xue, J., Z. Xiang, and G. Ou. 2021. “Predicting single freestanding transmission tower time history response during complex wind input through a convolutional neural network based surrogate model.” Eng. Struct. 233 (2021): 11859. https://doi.org/10.1016/j.engstruct.2021.111859.
Yang, H., C. Y. Chung, J. Zhao, and Z. Dong. 2013. “A probability model of ice storm damages to transmission facilities.” IEEE Trans. Power Deliv. 28 (2): 557–565. https://doi.org/10.1109/TPWRD.2012.2212216.
Younesi, A., Z. Wang, and L. Wang. 2022. “Investigating the impacts of climate change and natural disasters on the feasibility of power system resilience.” In Proc., IEEE Power and Energy Society General Meeting. New York: IEEE.
Yuan, H., W. Zhang, J. Zhu, and A. C. Bagtzoglou. 2018. “Resilience assessment of overhead power distribution system under strong winds for hardening prioritization.” ASCE-ASME J. Risk Uncertainty Eng. Syst. Part A: Civ. Eng. 4 (4): 04018037. https://doi.org/10.1061/AJRUA6.0000988.
Zhang, H., H. Wang, Z. Xu, Z. Liu, and B. C. Khoo. 2023. “A physics-informed neural network-based approach to reconstruct the tornado vortices from limited observed data.” J. Wind Eng. Ind. Aerodyn. 241 (Oct): 105534. https://doi.org/10.1016/j.jweia.2023.105534.
Zhang, J., W. Zhang, Q. Lu, J. Zhu, and A. C. Bagtzoglou. 2022. “A fragility-weighted topological network for resilient assessment of overhead power distribution system subjected to hurricane winds.” ASCE-ASME J. Risk Uncertainty Eng. Syst. Part A: Civ. Eng. 8 (2): 1–11. https://doi.org/10.1061/AJRUA6.0001232.
Zhu, C., Q. Yang, D. Wang, G. Huang, and S. Liang. 2023. “Fragility analysis of transmission towers subjected to downburst winds.” Appl. Sci. 13 (16): 9167. https://doi.org/10.3390/app13169167.
Zhu, X., G. Ou, F. Jafarishiadeh, and M. Sahraei-ardakani. 2022. “A data generation engine and workflow for power network damage and loss estimation under hurricane.” In Proc., 2022 North American Power Symp. 2022. New York: IEEE.
Information & Authors
Information
Published In
ASCE-ASME Journal of Risk and Uncertainty in Engineering Systems, Part A: Civil Engineering
Volume 10 • Issue 2 • June 2024
Copyright
© 2024 American Society of Civil Engineers.
History
Received: Jul 4, 2023
Accepted: Dec 10, 2023
Published online: Mar 14, 2024
Published in print: Jun 1, 2024
Discussion open until: Aug 14, 2024
Authors
Metrics & Citations
Metrics
Citations
Download citation
If you have the appropriate software installed, you can download article citation data to the citation manager of your choice. Simply select your manager software from the list below and click Download.