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Current Sustainable/Renewable Energy Reports

Erschienen in:

16.08.2023

Improving the Representation of Climate Risks in Long-Term Electricity Systems Planning: a Critical Review

verfasst von: James Doss-Gollin, Yash Amonkar, Katlyn Schmeltzer, Daniel Cohan

Erschienen in: Current Sustainable/Renewable Energy Reports | Ausgabe 4/2023

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Abstract

Purpose of Review

Electricity systems face substantial climate risks which are escalating due to electrification, renewable energy intermittency, population changes, and the intensifying impacts of climate change such as extreme temperatures and weather-induced infrastructure damage. This critical review investigates climate risks to the electricity sector and scrutinizes the methodologies used to represent climate risk in long-term electricity system planning studies.

Recent Findings

Climate risks to electricity systems are driven by extreme weather, average weather, technology, and other social and technological factors. All are expected to evolve in the future. Future climate risks to electricity systems depend on interactions between each, and thus assessing future climate risks to electricity systems requires exploring a wide range of possible futures.

Summary

Many studies rely on weather data and socio-economic scenarios that are inadequate to fully characterize climate risks to present and future electricity systems. We advocate for more holistic assessments that incorporate comprehensive weather data, acknowledge dynamic multi-sector interactions, and employ adaptive and robust methodologies.

Vorheriger Artikel The EU Commission’s Proposal for Improving the Electricity Market Design: Treading Water, but not Drowning

Nächster Artikel Geophysical Constraints on Decarbonized Systems—Building Spatio-Temporal Uncertainties into Future Electricity Grid Planning

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Jain Y, Jain R. India and Pakistan emerge as early victims of extreme heat conditions due to climate injustice. BMJ. 2022;377:1207. https://doi.org/10.1136/bmj.o1207. (Chap Opinion).CrossRef

Doss-Gollin J, Farnham DJ, Lall U, Modi V, How unprecedented was the February 2021 Texas cold snap? Environ Res Lett; 2021. https://doi.org/10.1088/1748-9326/ac0278.

Busby JW, Baker K, Bazilian MD, Gilbert AQ, Grubert E, Rai V, Rhodes JD, Shidore S, Smith CA, Webber ME. Cascading risks: understanding the 2021 winter blackout in Texas. Energy Res Soc Sci. 2021;77. https://doi.org/10.1016/j.erss.2021.102106.

Shahid S. Vulnerability of the power sector of Bangladesh to climate change and extreme weather events. Reg Environ Change. 2012;12(3):595–606. https://doi.org/10.1007/s10113-011-0276-z.CrossRef

Kwasinski A, Andrade F, Castro-Sitiriche MJ, O’Neill-Carrillo E. Hurricane Maria effects on Puerto Rico electric power infrastructure. IEEE Power Energy Technol Syst J. 2019;6(1):85–94. https://doi.org/10.1109/JPETS.2019.2900293.CrossRef

Do V, McBrien H, Flores NM, Northrop AJ, Schlegelmilch J, Kiang MV, Casey JA. Spatiotemporal distribution of power outages with climate events and social vulnerability in the USA. Nat Commun. 2023;14(1):2470. https://doi.org/10.1038/s41467-023-38084-6.CrossRef

Stone BJ, Gronlund CJ, Mallen E, Hondula D, O’Neill MS, Rajput M, Grijalva S, Lanza K, Harlan S, Larsen L, Augenbroe G, Krayenhoff ES, Broadbent A, Georgescu M. How blackouts during heat waves amplify mortality and morbidity risk. Environ Sci Technol. 2023. https://doi.org/10.1021/acs.est.2c09588.CrossRef

International Energy Agency. World Energy Outlook 2022. International Energy Agency: Technical report; 2022.CrossRef

Meinshausen M, Lewis J, McGlade C, Gütschow J, Nicholls Z, Burdon R, Cozzi L, Hackmann B. Realization of Paris Agreement pledges may limit warming just below 2 \(^\circ\)C. Nature. 2022;604(7905):304–9. https://doi.org/10.1038/s41586-022-04553-z.CrossRef

10.

Auffhammer M, Baylis P, Hausman CH. Climate change is projected to have severe impacts on the frequency and intensity of peak electricity demand across the United States. Proc Natl Acad Sci. 2017;114(8):1886–91. https://doi.org/10.1073/pnas.1613193114.CrossRef

11.

Romitti Y, Sue Wing I. Heterogeneous climate change impacts on electricity demand in world cities circa mid-century. Sci Rep. 2022;12(1):4280. https://doi.org/10.1038/s41598-022-07922-w.CrossRef

12.

Amonkar YV, Doss-Gollin J, Farnham DJ, Lall U, Modi V. Differential effects of climate change on average and peak demand for heating and cooling across the contiguous United States. Earth ArXiv. 2023. https://doi.org/10.31223/X5TH5X.

13.

Plaga LS, Bertsch V. Methods for assessing climate uncertainty in energy system models-a systematic literature review. Appl Energy. 2023;331. https://doi.org/10.1016/j.apenergy.2022.120384.

14.

Jung C, Schindler D. A review of recent studies on wind resource projections under climate change. Renew Sust Energ Rev. 2022;165: 112596. https://doi.org/10.1016/j.rser.2022.112596.CrossRef

15.

Koliou M, van de Lindt JW, McAllister TP, Ellingwood BR, Dillard M, Cutler H. State of the research in community resilience: progress and challenges. Sustain Resilient Infr. 2020;5(3):131–51. https://doi.org/10.1080/23789689.2017.1418547.CrossRef

16.

Yalew SG, van Vliet MTH, Gernaat DEHJ, Ludwig F, Miara A, Park C, Byers E, De Cian E, Piontek F, Iyer G, Mouratiadou I, Glynn J, Hejazi M, Dessens O, Rochedo P, Pietzcker R, Schaeffer R, Fujimori S, Dasgupta S, Mima S, da Silva SRS, Chaturvedi V, Vautard R, van Vuuren DP. Impacts of climate change on energy systems in global and regional scenarios. Nat Energy. 2020;5(10):794–802. https://doi.org/10.1038/s41560-020-0664-z.CrossRef

17.

Schaeffer R, Szklo AS, Pereira de Lucena AF, Moreira Cesar Borba BS, Pupo Nogueira LP, Fleming FP, Troccoli A, Harrison M, Boulahya MS. Energy sector vulnerability to climate change: a review. Energy 2012;38(1)1–12. https://doi.org/10.1016/j.energy.2011.11.056.

18.

Clarke L, Wei Y-M, Navarro ADLV, Garg A, Hahmann AN, Khennas S, Azevedo IML, Löschel A, Singh AK, Steg L, Strbac G, Wada K. Energy systems. In: Shukla PR, Skea J, Slade R, Khourdajie AA, van Diemen R, McCollum D, Pathak M, Some S, Vyas P, Fradera R, Belkacemi M, Hasija A, Lisboa G, Luz S, Malley J (eds) Climate Change 2022: Mitigation of Climate Change. Contribution of Working Group III to the Sixth Assessment Report of the Intergovernmental Panel on Climate Change. Cambridge University Press, Cambridge, UK and New York, NY, USA (2022). Chap. 6. https://doi.org/10.1017/9781009157926.008.

19.

Maia-Silva D, Kumar R, Nateghi R. The critical role of humidity in modeling summer electricity demand across the United States. Nat Commun. 2020;11(1):1686. https://doi.org/10.1038/s41467-020-15393-8.CrossRef

20.

Henley A, Peirson J. Non-linearities in electricity demand and temperature: parametric versus non-parametric methods. Oxf Bull Econ Stat. 1997;59(1):149–62. https://doi.org/10.1111/1468-0084.00054.CrossRef

21.

Moral-Carcedo J, Vicéns-Otero J. Modelling the non-linear response of Spanish electricity demand to temperature variations. Energy Econ. 2005;27(3):477–94. https://doi.org/10.1016/j.eneco.2005.01.003.CrossRef

22.

Lee J, Dessler AE. The impact of neglecting climate change and variability on ERCOT’s forecasts of electricity demand in Texas. Weather Clim Soc. 2022;14(2):499–505. https://doi.org/10.1175/WCAS-D-21-0140.1. (Chap. Weather, Climate, and Society).CrossRef

23.

Shaffer, B., Quintero, D., Rhodes, J.: Changing sensitivity to cold weather in Texas power demand. iScience. 2022;25(4), 104173. https://doi.org/10.1016/j.isci.2022.104173

24.

Alipour P, Mukherjee S, Nateghi R. Assessing climate sensitivity of peak electricity load for resilient power systems planning and operation: a study applied to the Texas region. Energy. 2019;185:1143–53. https://doi.org/10.1016/j.energy.2019.07.074.CrossRef

25.

Bett PE, Thornton HE. The climatological relationships between wind and solar energy supply in Britain. Renew Energy. 2016;87:96–110. https://doi.org/10.1016/j.renene.2015.10.006.CrossRef

26.

Craig MT, Jaramillo P, Hodge B-M, Nijssen B, Brancucci C. Compounding climate change impacts during high stress periods for a high wind and solar power system in Texas. Environ Res Lett. 2020;15(2): 024002. https://doi.org/10.1088/1748-9326/ab6615.CrossRef

27.

Jerez S, Tobin I, Vautard R, Montávez JP, López-Romero JM, Thais F, Bartok B, Christensen OB, Colette A, Déqué M, Nikulin G, Kotlarski S, van Meijgaard E, Teichmann C, Wild M. The impact of climate change on photovoltaic power generation in Europe. Nat Commun. 2015;6(1):10014. https://doi.org/10.1038/ncomms10014.CrossRef

28.

Lundquist JK, DuVivier KK, Kaffine D, Tomaszewski JM. Costs and consequences of wind turbine wake effects arising from uncoordinated wind energy development. Nat Energy. 2019;4(1):26–34. https://doi.org/10.1038/s41560-018-0281-2.CrossRef

29.

van Vliet MTH, van Beek LPH, Eisner S, Flörke M, Wada Y, Bierkens MFP. Multi-model assessment of global hydropower and cooling water discharge potential under climate change. Glob Environ Change. 2016;40:156–70. https://doi.org/10.1016/j.gloenvcha.2016.07.007.CrossRef

30.

van Vliet MTH, Yearsley JR, Ludwig F, Vögele S, Lettenmaier DP, Kabat P. Vulnerability of US and European electricity supply to climate change. Nature Climate Change. 2012;2(9):676–81. https://doi.org/10.1038/nclimate1546.CrossRef

31.

Kern JD, Su Y, Hill J. A retrospective study of the 2012–2016 California drought and its impacts on the power sector. Environ Res Lett. 2020;15(9): 094008. https://doi.org/10.1088/1748-9326/ab9db1.CrossRef

32.

Su Y, Kern JD, Denaro S, Hill J, Reed P, Sun Y, Cohen J, Characklis GW. An open source model for quantifying risks in bulk electric power systems from spatially and temporally correlated hydrometeorological processes. Environ Modell Softw. 2020;126: 104667. https://doi.org/10.1016/j.envsoft.2020.104667.CrossRef

33.

Loew A, Jaramillo P, Zhai H, Ali R, Nijssen B, Cheng Y, Klima K. Fossil fuel-fired power plant operations under a changing climate. Clim Change. 2020;163(1):619–32. https://doi.org/10.1007/s10584-020-02834-y.CrossRef

34.

Coffel ED, Mankin JS. Thermal power generation is disadvantaged in a warming world. Environ Res Lett. 2020. https://doi.org/10.1088/1748-9326/abd4a8.CrossRef

35.

Liu L, Hejazi M, Li H, Forman B, Zhang X. Vulnerability of US thermoelectric power generation to climate change when incorporating state-level environmental regulations. Nat Energy. 2017;2(8):1–5. https://doi.org/10.1038/nenergy.2017.109.CrossRef

36.

Otero N, Martius O, Allen S, Bloomfield H, Schaefli B. Characterizing renewable energy compound events across Europe using a logistic regression-based approach. Meteorol Appl. 2022; 29(5). https://doi.org/10.1002/met.2089

37.

Li B, Basu S, Watson SJ, Russchenberg HWJ. A brief climatology of dunkelflaute events over and surrounding the North and Baltic Sea areas. Energies. 2021;14(20). https://doi.org/10.3390/en14206508.

38.

Boston A, Bongers GD, Bongers N. Characterisation and mitigation of renewable droughts in the Australian National Electricity Market. Environ Res Commun. 2022;4(3): 031001. https://doi.org/10.1088/2515-7620/ac5677.CrossRef

39.

Ohba M, Kanno Y, Bando S. Effects of meteorological and climatological factors on extremely high residual load and possible future changes. Renew Sustain Energy Rev. 2023;175: 113188. https://doi.org/10.1016/j.rser.2023.113188.CrossRef

40.

Brown PT, Farnham DJ, Caldeira K. Meteorology and climatology of historical weekly wind and solar power resource droughts over western North America in ERA5. SN Appl Sci. 2021;3(10):814. https://doi.org/10.1007/s42452-021-04794-z.CrossRef

41.

Ghil M, Lucarini V. The physics of climate variability and climate change. Rev Modern Phys. 2020;92(3): 035002. https://doi.org/10.1103/revmodphys.92.035002.MathSciNetCrossRef

42.

Doss-Gollin J, Farnham DJ, Steinschneider S, Lall U. Robust adaptation to multiscale climate variability. Earths Future. 2019;7(7):734–47. https://doi.org/10.1029/2019ef001154.CrossRef

43.

Ely CR, Brayshaw DJ, Methven J, Cox J, Pearce O. Implications of the North Atlantic Oscillation for a UK-Norway Renewable power system. Energy Policy. 2013;62:1420–7. https://doi.org/10.1016/j.enpol.2013.06.037.CrossRef

44.

Jerez S, Trigo RM. Time-scale and extent at which large-scale circulation modes determine the wind and solar potential in the Iberian Peninsula. Environ Res Lett. 2013;8(4): 044035. https://doi.org/10.1088/1748-9326/8/4/044035.CrossRef

45.

Neubacher C, Witthaut D, Wohland J. Multi-decadal offshore wind power variability can be mitigated through optimized European allocation. Adv Geosci. 2021;54:205–15. https://doi.org/10.5194/adgeo-54-205-2021.CrossRef

46.

Bartos M, Chester M, Johnson N, Gorman B, Eisenberg D, Linkov I, Bates M. Impacts of rising air temperatures on electric transmission ampacity and peak electricity load in the United States. Environ Res Lett. 2016;11(11): 114008. https://doi.org/10.1088/1748-9326/11/11/114008.CrossRef

47.

Feng X, Yang J, Luo C, Sun Y, Liu M, Tang Y. A risk evaluation method for cascading failure considering transmission line icing. In: 2015 IEEE Innovative Smart Grid Technologies - Asia (ISGT ASIA). 2015; p 1–4. https://doi.org/10.1109/ISGT-Asia.2015.7387014.

48.

Yaji K, Homma H, Sakata G, Watanabe M. Evaluation on flashover voltage property of snow accreted insulators for overhead transmission lines, part I - field observations and laboratory tests to evaluate snow accretion properties. IEEE Trans Dielectr Electr Insul. 2014;21(6):2549–58. https://doi.org/10.1109/TDEI.2014.004564.CrossRef

49.

Croce P, Formichi P, Landi F, Mercogliano P, Bucchignani E, Dosio A, Dimova S. The snow load in Europe and the climate change. Clim Risk Manag. 2018;20:138–54. https://doi.org/10.1016/j.crm.2018.03.001.CrossRef

50.

Dian S, Cheng P, Ye Q, Wu J, Luo R, Wang C, Hui D, Zhou N, Zou D, Yu Q, Gong X. Integrating wildfires propagation prediction into early warning of electrical transmission line outages. IEEE Access. 2019;7:27586–603. https://doi.org/10.1109/ACCESS.2019.2894141.CrossRef

51.

Ranasinghe R, Ruane AC, Vautard R, Arnell N, Coppola E, Cruz FA, Dessai S, Islam AS, Rahimi M, Ruiz Carrascal D, Sillmann J, Sylla MB, Tebaldi C, Wang W, Zaaboul R. Climate change information for regional impact and for risk assessment. In: Masson-Delmotte V, Zhai P, Pirani A, Connors SL, Péan C, Berger S, Caud N, Chen Y, Goldfarb L, Gomis MI, Huang M, Leitzell K, Lonnoy E, Matthews JBR, Maycock TK, Waterfield T, Yelekçi O, Yu R, Zhou B (eds.) Climate Change 2021: The Physical Science Basis. Contribution of Working Group I to the Sixth Assessment Report of the Intergovernmental Panel on Climate Change. Cambridge, UK and New York, NY, USA: Cambridge University Press,(2021). Chap. 12. https://doi.org/10.1017/9781009157896.014.

52.

Committee on enhancing the resilience of the nation’s electric power transmission and distribution system, Board on Energy and Environmental Systems, Division on Engineering and Physical Sciences, National Academies of Sciences, Engineering, and Medicine: Enhancing the Resilience of the Nation’s Electricity System, p. 24836. Washington, D.C: National Academies Press, 2017.https://doi.org/10.17226/24836

53.

Seneviratne SI, Zhang X, Adnan M, Badi W, Dereczynski C, Di Luca A, Ghosh S, Iskandar I, Kossin J, Lewis S, Otto F, Pinto I, Satoh M, Vicente-Serrano SM, Wehner M, Zhou B. Weather and climate extreme events in a changing climate. In: Masson-Delmotte V, Zhai P, Pirani A, Connors SL, Péan C, Berger S, Caud N, Chen Y, Goldfarb L, Gomis MI, Huang M, Leitzell K, Lonnoy E, Matthews JBR, Maycock TK, Waterfield T, Yelekçi O, Yu R, Zhou B (eds) Climate Change 2021: The Physical Science Basis. Contribution of Working Group I to the Sixth Assessment Report of the Intergovernmental Panel on Climate Change. Cambridge, UK and New York, NY, USA: Cambridge University Press, 2021. Chap. 11. https://doi.org/10.1017/9781009157896.013.

54.

Knutson T, Camargo SJ, Chan JCL, Emanuel K, Ho C-H, Kossin J, Mohapatra M, Satoh M, Sugi M, Walsh K, Wu L. Tropical cyclones and climate change assessment: part II: projected response to anthropogenic warming. Bull Am Meteorol Soc. 2020;101(3):303–22. https://doi.org/10.1175/BAMS-D-18-0194.1. (Chap. Bulletin of the American Meteorological Society).CrossRef

55.

Sobel AH, Wing AA, Camargo SJ, Patricola CM, Vecchi GA, Lee C-Y, Tippett MK. Tropical cyclone frequency. Earths. Future. 2021;9(12):2021–002275. https://doi.org/10.1029/2021EF002275.CrossRef

56.

Kopp RE, DeConto RM, Bader DA, Hay CC, Horton RM, Kulp S, Oppenheimer M, Pollard D, Strauss BH. Evolving understanding of Antarctic ice-sheet physics and ambiguity in probabilistic sea-level projections. Earths Fut. 2017;5(12):1217–33. https://doi.org/10.1002/2017ef000663.CrossRef

57.

Gori A, Lin N, Xi D, Emanuel K. Tropical cyclone climatology change greatly exacerbates US extreme rainfall-surge hazard. Nat Clim Change. 2022;12(2):171–8. https://doi.org/10.1038/s41558-021-01272-7.CrossRef

58.

Flannigan M, Cantin AS, de Groot WJ, Wotton M, Newbery A, Gowman LM. Global wildland fire season severity in the 21st century. For Ecol Manag. 2013;294:54–61. https://doi.org/10.1016/j.foreco.2012.10.022.CrossRef

59.

Lee J-Y, Marotzke J, Bala G, Cao L, Corti S, Dunne JP, Engelbrecht F, Fischer E, Fyfe JC, Jones C, Maycock A, Mutemi J, Ndiaye O, Panickal S, Zhou T. Future global climate: scenario-based projections and near-term information. In: Masson-Delmotte V, Zhai P, Pirani A, Connors SL, Péan C, Berger S, Caud N, Chen Y, Goldfarb L, Gomis MI, Huang M, Leitzell K, Lonnoy E, Matthews JBR, Maycock TK, Waterfield T, Yelekçi O, Yu R, Zhou B (eds) Climate Change 2021: The Physical Science Basis. Contribution of Working Group I to the Sixth Assessment Report of the Intergovernmental Panel on Climate Change. Cambridge, UK and New York, NY, USA: Cambridge University Press; 2021. Chap. 4. https://doi.org/10.1017/9781009157896.006.

60.

Santer BD, Po-Chedley S, Zelinka MD, Cvijanovic I, Bonfils C, Durack PJ, Fu Q, Kiehl J, Mears C, Painter J, Pallotta G, Solomon S, Wentz FJ, Zou C-Z. Human influence on the seasonal cycle of tropospheric temperature. Science. 2018;361(6399). https://doi.org/10.1126/science.aas8806.

61.

Donohoe A, Battisti DS. The seasonal cycle of atmospheric heating and temperature. J Clim. 2013;26(14):4962–80. https://doi.org/10.1175/JCLI-D-12-00713.1. (Chap. Journal of Climate).CrossRef

62.

Shaw TA, Baldwin M, Barnes EA, Caballero R, Garfinkel CI, Hwang YT, Li C, O’Gorman PA, Rivière G, Simpson IR, Voigt A. Storm track processes and the opposing influences of climate change. Nat Geosci. 2016;9(9):656–64. https://doi.org/10.1038/ngeo2783.CrossRef

63.

Nabizadeh E, Hassanzadeh P, Yang D, Barnes EA. Size of the atmospheric blocking events: scaling law and response to climate change. Geophys Res Lett. 2019;46(22):13488–99. https://doi.org/10.1029/2019gl084863.CrossRef

64.

Gulev SK, Thorne PW, Ahn J, Dentener FJ, Domingues CM, Gerland S, Gong D, Kaufman DS, Nnamchi HC, Quaas J, Rivera JA, Sathyendranath S, Smith SL, Trewin B, von Schuckmann K, Vose RS. Changing state of the climate system. In: Masson-Delmotte V, Zhai P, Pirani A, Connors S.L, Péan C, Berger S, Caud N, Chen Y, Goldfarb L, Gomis MI, Huang M, Leitzell K, Lonnoy E, Matthews JBR, Maycock TK, Waterfield T, Yelekçi, O, Yu R, Zhou B (eds) Climate Change 2021: The Physical Science Basis. Contribution of Working Group I to the Sixth Assessment Report of the Intergovernmental Panel on Climate Change. Cambridge, UK and New York, NY, USA: Cambridge University Press, 2021;Chap. 2. https://doi.org/10.1017/9781009157896.004.

65.

Petoukhov V, Petri S, Rahmstorf S, Coumou D, Kornhuber K, Schellnhuber HJ. Role of quasiresonant planetary wave dynamics in recent boreal spring-to-autumn extreme events. Proc Nat Acad Sci Unit Am. 2016;113(25):6862–7. https://doi.org/10.1073/pnas.1606300113.CrossRef

66.

Kornhuber K, Osprey S, Coumou D, Petri S, Petoukhov V, Rahmstorf S, Gray L. Extreme weather events in early summer 2018 connected by a recurrent hemispheric wave-7 pattern. Environ Res Lett. 2019;14(5): 054002. https://doi.org/10.1088/1748-9326/ab13bf.CrossRef

67.

Trenberth KE, Fasullo JT. Climate extremes and climate change: the Russian heat wave and other climate extremes of 2010. J Geophys Res Atmos. 2012;117:D17. https://doi.org/10.1029/2012jd018020.CrossRef

68.

Pfleiderer P, Schleussner C-F, Kornhuber K, Coumou D. Summer weather becomes more persistent in a 2 \(^\circ\)C world. Nat Clim Change. 2019;1–6. https://doi.org/10.1038/s41558-019-0555-0.

69.

Miller NL, Hayhoe K, Jin J, Auffhammer M. Climate, extreme heat, and electricity demand in California. J Appl Meteorol Climatol. 2008;47(6):1834–44. https://doi.org/10.1175/2007JAMC1480.1. (Chap. Journal of Applied Meteorology and Climatology).CrossRef

70.

Cohen J, Zhang X, Francis J, Jung T, Kwok R, Overland J, Ballinger TJ, Bhatt US, Chen HW, Coumou D, Feldstein S, Gu H, Handorf D, Henderson G, Ionita M, Kretschmer M, Laliberte F, Lee S, Linderholm HW, Maslowski W, Peings Y, Pfeiffer K, Rigor I, Semmler T, Stroeve J, Taylor PC, Vavrus S, Vihma T, Wang S, Wendisch M, Wu Y, Yoon J. Divergent consensuses on Arctic amplification influence on midlatitude severe winter weather. Nat Clim Change. 2020;10(1):20–9. https://doi.org/10.1038/s41558-019-0662-y.CrossRef

71.

Tobin I, Greuell W, Jerez S, Ludwig F, Vautard R, van Vliet MTH, Bréon F-M. Vulnerabilities and resilience of European power generation to 1.5 \(^\circ\)C, 2 \(^\circ\)C and 3 \(^\circ\)C warming. Environ Res Lett. 2018;13(4),044024. https://doi.org/10.1088/1748-9326/aab211.

72.

Bonanno R, Viterbo F, Maurizio RG. Climate change impacts on wind power generation for the Italian peninsula. Reg Environ Change. 2023;23(1). https://doi.org/10.1007/s10113-022-02007-w.

73.

Hahmann AN, García-Santiago O, Peña A. Current and future wind energy resources in the North Sea according to CMIP6. Wind Energy Sci. 2022;7(6):2373–91. https://doi.org/10.5194/wes-7-2373-2022.CrossRef

74.

Wohland J. Process-based climate change assessment for European winds using EURO-CORDEX and global models. Environ Res Lett. 2022;17(12). https://doi.org/10.1088/1748-9326/aca77f.

75.

Gonzalez PLM, Brayshaw DJ, Zappa G. The contribution of North Atlantic atmospheric circulation shifts to future wind speed projections for wind power over Europe. Clim Dyn. 2019;53(7–8):4095–113. https://doi.org/10.1007/s00382-019-04776-3.CrossRef

76.

Wasti A, Ray P, Wi S, Folch C, Ubierna M, Karki P. Climate change and the hydropower sector: a global review. WIREs Clim Change. 2022;13(2):757. https://doi.org/10.1002/wcc.757.CrossRef

77.

Dodman D, Hayward B, Pelling M, Castan Broto V, Chow W, Chu E, Dawson R, Khirfan L, McPhearson T, Prakash A, Zheng Y, Ziervogel G. Cities, settlements and key infrastructure. In: Pörtner HO, Roberts DC, Tignor M, Poloczanska ES, Mintenbeck K, Alegría A, Craig M, Langsdorf S, Löschke S, Möller V, Okem A, Rama B (eds) Climate change 2022: impacts, adaptation and vulnerability. Contribution ofWorking Group II to the Sixth Assessment Report of the Intergovernmental Panel on Climate Change. Cambridge, UK and New York, NY, USA: Cambridge University Press, 2022;Chap. 6. https://doi.org/10.1017/9781009325844.008.

78.

Carvajal PE, Li FGN, Soria R, Cronin J, Anandarajah G, Mulugetta Y. Large hydropower, decarbonisation and climate change uncertainty: modelling power sector pathways for Ecuador. Energy Strat Rev. 2019;23:86–99. https://doi.org/10.1016/j.esr.2018.12.008.CrossRef

79.

Dittes B, Špačková O, Schoppa L, Straub D. Managing uncertainty in flood protection planning with climate projections. Hydrol Earth Syst Sci. 2018;22(4):2511–26. https://doi.org/10.5194/hess-22-2511-2018.CrossRef

80.

Lafferty DC, Sriver RL. Downscaling and bias-correction contribute considerable uncertainty to local climate projections in CMIP6. Preprints. 2023. https://doi.org/10.22541/essoar.168286894.44910061/v1.

81.

Perera ATD, Nik VM, Chen D, Scartezzini J-L, Hong T. Quantifying the impacts of climate change and extreme climate events on energy systems. Nat Energy. 2020;5(2):150–9. https://doi.org/10.1038/s41560-020-0558-0.CrossRef

82.

DeAngelo J, Azevedo I, Bistline J, Clarke L, Luderer G, Byers E, Davis SJ. Energy systems in scenarios at net-zero CO2 emissions. Nat Commun. 2021;12(1):6096. https://doi.org/10.1038/s41467-021-26356-y.CrossRef

83.

Kondi-Akara G, Hingray B, Francois B, Diedhiou A. Recent trends in urban electricity consumption for cooling in West and Central African countries. Energy. 2023;276: 127597. https://doi.org/10.1016/j.energy.2023.127597.CrossRef

84.

Waite M, Modi V. Electricity load implications of space heating decarbonization pathways. Joule. 2020;4(2):376–94. https://doi.org/10.1016/j.joule.2019.11.011.CrossRef

85.

Hausfather Z, Peters GP. Emissions-the ‘business as usual’ story is misleading. Nature. 2020;577(7792):618–20. https://doi.org/10.1038/d41586-020-00177-3.CrossRef

86.

Walker WE, Lempert RJ, Kwakkel JH. Deep uncertainty. In: Gass SI, Fu MC (eds) Encyclopedia of operations research and management science. p 395–402. Boston, MA: Springer US, 2013. https://doi.org/10.1007/978-1-4419-1153-7_1140.

87.

Mathy S, Criqui P, Knoop K, Fischedick M, Samadi S. Uncertainty management and the dynamic adjustment of deep decarbonization pathways. Clim Policy. 2016;16(sup1):47–62. https://doi.org/10.1080/14693062.2016.1179618.CrossRef

88.

Sepulveda NA, Jenkins JD, Edington A, Mallapragada DS, Lester RK. The design space for long-duration energy storage in decarbonized power systems. Nat Energy. 2021;6(5):506–16. https://doi.org/10.1038/s41560-021-00796-8.CrossRef

89.

Larson E, Greig C, Jenkins J, Mayfield E, Pascale A, Zhang C, Drossman J, Williams R, Pacala S, Socolow R, Baik E, Birdsey R, Duke R, Jones R, Haley B, Leslie E, Paustian K, Swan A. Net-zero America: potential pathways, infrastructure, and impacts. Technical report. Princeton: Princeton University; 2021.

90.

Denholm P, Brown P, Cole W, Mai T, Sergi B. Examining supply-side options to achieve 100% clean electricity by 2035. Technical Report NREL/TP-6A40-81644. Golden: National Renewable Energy Laboratory, 2022. https://doi.org/10.2172/1885591

91.

Walter L, Jantarasami L, Schneider C. Pathways to net-zero emissions. Decarb America: Technical report; 2021.

92.

Shaner MR, Davis SJ, Lewis NS, Caldeira K. Geophysical constraints on the reliability of solar and wind power in the United States. Energy Environ Sci. 2018;11(4):914–25. https://doi.org/10.1039/C7EE03029K.CrossRef

93.

Tong D, Farnham DJ, Duan L, Zhang Q, Lewis NS, Caldeira K, Davis SJ. Geophysical constraints on the reliability of solar and wind power worldwide. Nat Communications. 2021;12(1):6146. https://doi.org/10.1038/s41467-021-26355-z.CrossRef

94.

The Nature Conservancy. Power of place: national. The Nature Conservancy: Technical report; 2023.

95.

Pianosi F, Beven K, Freer J, Hall JW, Rougier J, Stephenson DB, Wagener T. Sensitivity analysis of environmental models: a systematic review with practical workflow. Environ Modell Softw. 2016;79:214–32. https://doi.org/10/f8n6zw

96.

Srikrishnan V, Lafferty DC, Wong TE, Lamontagne JR, Quinn JD, Sharma S, Molla NJ, Herman JD, Sriver RL, Morris JF, Lee BS. Uncertainty analysis in multi-sector systems: considerations for risk analysis, projection, and planning for complex systems. Earths Fut. 2022;10(8):2021–002644. https://doi.org/10.1029/2021EF002644.CrossRef

97.

Saltelli A, Ratto M, Andres T, Campolongo F, Cariboni J, Gatelli D, Saisana M, Tarantola S. Global sensitivity analysis: the primer. John Wiley & Sons, Ltd, 2008.

98.

Stephens GL, L’Ecuyer T, Forbes R, Gettlemen A, Golaz J-C, Bodas-Salcedo A, Suzuki K, Gabriel P, Haynes J. Dreary state of precipitation in global models. J Geophys Res Atmosp. 2010;115(D24):24211. https://doi.org/10.1029/2010jd014532.CrossRef

99.

Muller CJ, O’Gorman PA, Back LE. Intensification of precipitation extremes with warming in a cloud-resolving model. J Clim. 2011;24(11):2784–800. https://doi.org/10.1175/2011jcli3876.1.CrossRef

100.

Espinoza V, Waliser DE, Guan B, Lavers DA, Ralph FM. Global analysis of climate change projection effects on atmospheric rivers. Geophys Res Lett. 2018;47(3):514. https://doi.org/10.1029/2017gl076968.CrossRef

101.

Smith DM, Scaife AA, Eade R, Athanasiadis P, Bellucci A, Bethke I, Bilbao R, Borchert LF, Caron L-P, Counillon F, Danabasoglu G, Delworth T, Doblas-Reyes FJ, Dunstone NJ, Estella-Perez V, Flavoni S, Hermanson L, Keenlyside N, Kharin V, Kimoto M, Merryfield WJ, Mignot J, Mochizuki T, Modali K, Monerie P-A, Müller WA, Nicolí D, Ortega P, Pankatz K, Pohlmann H, Robson J, Ruggieri P, Sospedra-Alfonso R, Swingedouw D, Wang Y, Wild S, Yeager S, Yang X, Zhang L. North Atlantic climate far more predictable than models imply. Nature. 2020;583(7818):796–800. https://doi.org/10.1038/s41586-020-2525-0.CrossRef

102.

Kravtsov S. Pronounced differences between observed and CMIP5-simulated multidecadal climate variability in the twentieth century. Geophys Res Lett. 2017;44(11):5749–57. https://doi.org/10.1002/2017GL074016.CrossRef

103.

Greene AM, Robertson AW. Interannual and low-frequency variability of Upper Indus Basin winter/spring precipitation in observations and CMIP5 models. Clim Dynam. 2017;49(11–12):4171–88. https://doi.org/10.1007/s00382-017-3571-7.CrossRef

104.

Feng J, Lian T, Ying J, Li J, Li G. Do CMIP5 models show El Niño diversity? J Clim. 2019. https://doi.org/10.1175/jcli-d-18-0854.1.CrossRef

105.

Srikrishnan V, Guan Y, Tol RSJ, Keller K. Probabilistic projections of baseline twenty-first century CO2 emissions using a simple calibrated integrated assessment model. Climatic Change. 2022;170(3):37. https://doi.org/10.1007/s10584-021-03279-7.CrossRef

106.

Milly PCD, Betancourt J, Falkenmark M, Hirsch RM, Kundzewicz ZW, Lettenmaier DP, Stouffer RJ. Stationarity is dead: whither water management? Science. 2008;319(5863):573–4. https://doi.org/10.1126/science.1151915.CrossRef

107.

Doss-Gollin J, Keller K. A subjective Bayesian framework for synthesizing deep uncertainties in climate risk management. Earths Fut. 2023; 11(1). https://doi.org/10.1029/2022EF003044.

108.

Jain S, Lall U. Floods in a changing climate: does the past represent the future? Water Resour Res. 2001;37(12):3193–205. https://doi.org/10.1029/2001wr000495.CrossRef

109.

Dowling JA, Rinaldi KZ, Ruggles TH, Davis SJ, Yuan M, Tong F, Lewis NS, Caldeira K. Role of long-duration energy storage in variable renewable electricity systems. Joule. 2020;4(9):1907–28. https://doi.org/10.1016/j.joule.2020.07.007.CrossRef

110.

Collins S, Deane P, Ó Gallachóir B, Pfenninger S, Staffell I. Impacts of inter-annual wind and solar variations on the European power system. Joule. 2018; 2(10), 2076–2090. https://doi.org/10.1016/j.joule.2018.06.020.

111.

Lanzante JR, Dixon KW, Nath MJ, Whitlock CE, Adams-Smith D. Some pitfalls in statistical downscaling of future climate. Bull Am Meteorol Soc. 2018;99(4):791–803. https://doi.org/10.1175/bams-d-17-0046.1.CrossRef

112.

Ehret U, Zehe E, Wulfmeyer V, Warrach-Sagi K, Liebert J. Should we apply bias correction to global and regional climate model data? Hydrol Earth Syst Sci. 2012;16(9):3391–404. https://doi.org/10.5194/hess-16-3391-2012.CrossRef

113.

Harder P, Yang Q, Ramesh V, Hernandez-Garcia A, Watson CD, Szwarcman D, Rolnick D. Generating physically-consistent high-resolution climate data with hard-constrained neural networks. In: AAAI 2022 Fall Symposium: The Role of AI in Responding To Climate Challenges. 2022, p 7.

114.

Price I, Rasp S. Increasing the accuracy and resolution of precipitation forecasts using deep generative models. arXiv. 2022. https://doi.org/10.48550/arXiv.2203.12297.

115.

Lall U, Sharma A. A nearest neighbor bootstrap for resampling hydrologic time series. Water Resources Research. 1996;32(3):679–93. https://doi.org/10.1029/95WR02966.CrossRef

116.

Rajagopalan B, Lall U. A k-nearest-neighbor simulator for daily precipitation and other weather variables. Water Resour Res. 1999;35(10):3089–101. https://doi.org/10.1029/1999WR900028.CrossRef

117.

Amonkar Y, Farnham DJ, Lall U. A k-nearest neighbor space-time simulator with applications to large-scale wind and solar power modeling. Patterns. 2022;3(3): 100454. https://doi.org/10.1016/j.patter.2022.100454.CrossRef

118.

Papalexiou SM, Serinaldi F, Clark MP. Large-domain multisite precipitation generation: operational blueprint and demonstration for 1,000 sites. Water Resour Res. 2023;59(3):2022–034094. https://doi.org/10.1029/2022WR034094.CrossRef

119.

Steinschneider S, Brown C. A semiparametric multivariate, multisite weather generator with low-frequency variability for use in climate risk assessments. Water Resour Res. 2013;49(11):7205–20. https://doi.org/10.1002/wrcr.20528.CrossRef

120.

Gupta RS, Steinschneider S, Reed PM. Understanding contributions of Paleo-informed natural variability and climate changes on hydroclimate extremes in the Central Valley region of California. Preprint, Preprints, 2023. https://doi.org/10.22541/essoar.167870424.46495295/v1.

121.

Bracken C, Rajagopalan B, Zagona E. A hidden Markov model combined with climate indices for multidecadal streamflow simulation. Water Resour Res. 2014;50(10):7836–46. https://doi.org/10.1002/2014WR015567.CrossRef

122.

...Merz B, Aerts JCJH, Arnbjerg-Nielsen K, Baldi M, Becker A, Bichet A, Blöschl G, Bouwer LM, Brauer A, Cioffi F, Delgado JM, Gocht M, Guzzetti F, Harrigan S, Hirschboeck K, Kilsby C, Kron W, Kwon HH, Lall U, Merz R, Nissen K, Salvatti P, Swierczynski T, Ulbrich U, Viglione A, Ward PJ, Weiler M, Wilhelm B, Nied M. Floods and climate: emerging perspectives for flood risk assessment and management. Nat Hazards Earth Syst Sci. 2014;14(7):1921–42. https://doi.org/10/gb9nzm

123.

Lamontagne JR, Reed PM, Link R, Calvin KV, Clarke LE, Edmonds JA. Large ensemble analytic framework for consequence-driven discovery of climate change scenarios. Earths Fut. 2018;6(3):488–504. https://doi.org/10.1002/2017ef000701.CrossRef

124.

Dolan F, Lamontagne J, Link R, Hejazi M, Reed P, Edmonds J. Evaluating the economic impact of water scarcity in a changing world. Nat Commun. 2021;12(1):1915.CrossRef

125.

Zarekarizi M, Srikrishnan V, Keller K. Neglecting uncertainties biases house-elevation decisions to manage riverine flood risks. Nat Commun. 2020;11(1):5361. https://doi.org/10.1038/s41467-020-19188-9.CrossRef

126.

Zeighami A, Kern J, Yates AJ, Weber P, Bruno AAUS. West Coast droughts and heat waves exacerbate pollution inequality and can evade emission control policies. Nat Commun. 2023;14:1415. https://doi.org/10.1038/s41467-023-37080-0.CrossRef

127.

Chowdhury AFMK, Dang TD, Nguyen HTT, Koh R, Galelli S. The Greater Mekong’s Climate-Water-Energy Nexus: How ENSO-Triggered Regional Droughts Affect Power Supply and CO2 Emissions. Earths Fut. 2021;9(3):2020–001814. https://doi.org/10.1029/2020EF001814.CrossRef

128.

Gómez C, Sanchez-Silva M, Dueñas-Osorio L, Rosowsky D. Hierarchical infrastructure network representation methods for risk-based decision-making. Structure and Infrastructure Engineering. 2013;9(3):260–74. https://doi.org/10.1080/15732479.2010.546415.CrossRef

129.

Zhou X, Duenas-Osorio L, Doss-Gollin J, Liu L, Stadler L, Li Q. Mesoscale modeling of distributed water systems enables policy search. Water Resour Res. 2023;59(5). https://doi.org/10.1029/2022WR033758.

130.

Kazadi AN, Doss-Gollin J, Sebastian A, Silva A. Flood prediction with graph neural networks. In: Climate Change AI. Climate Change AI, 2022.

131.

da Silva AL, Kocayusufoglu F, Jafarpour S, Bullo F, Swami A, Singh A. Combining physics and machine learning for network flow estimation. In: International Conference on Learning Representations, 2020.

132.

Wong TE, Bakker AMR, Ruckert K, Applegate P, Slangen ABA, Keller K. BRICK v0.2, a simple, accessible, and transparent model framework for climate and regional sea-level projections. Geosci Model Dev. 2017;10(7),2741–2760. https://doi.org/10.5194/gmd-10-2741-2017.

133.

Keller K, Helgeson C, Srikrishnan V. Climate risk management. Ann Rev Earth Planetary Sci. 2021;49(1):95–116. https://doi.org/10.1146/annurev-earth-080320-055847.CrossRef

134.

Bankes S. Exploratory modeling for policy analysis. Oper Res. 1993;41(3):435–49. https://doi.org/10/c7rgcr.

135.

Brown CM, Ghile Y, Laverty M, Li K. Decision scaling: linking bottom-up vulnerability analysis with climate projections in the water sector. Water Resour Res. 2012;48(9). https://doi.org/10/gc3d7d.

136.

Steinschneider S, McCrary R, Wi S, Mulligan K, Mearns LO, Brown CM. Expanded decision-scaling framework to select robust long-term water-system plans under hydroclimatic uncertainties. J Water Resour Plann Manag. 2015;141(11). https://doi.org/10.1061/(asce)wr.1943-5452.0000536.

137.

Taner MÜ, Ray P, Brown C. Incorporating multidimensional probabilistic information into robustness-based water systems planning. Water Resour Res. 2019;55(5):3659–79. https://doi.org/10.1029/2018WR022909.CrossRef

138.

Lempert RJ. Robust Decision Making (RDM). In: Marchau VAWJ, Walker WE, Bloemen PJTM, Popper SW (eds) Decision making under deep uncertainty: from theory to practice. Cham: Springer International Publishing, (2019), p 23–51. https://doi.org/10.1007/978-3-030-05252-2_2.

139.

Kasprzyk JR, Nataraj S, Reed PM, Lempert RJ. Many objective robust decision making for complex environmental systems undergoing change. Environ Model Softw. 2013;42:55–71. https://doi.org/10.1016/j.envsoft.2012.12.007.CrossRef

140.

Gupta SK, Rosenhead J. Robustness in sequential investment decisions. Manag Sci. 1968;15(2):18–229. https://doi.org/10.1287/mnsc.15.2.b18. arXiv:abs/2628850

141.

de Neufville R, Smet K. Engineering Options Analysis (EOA). In: Marchau VAWJ, Walker WE, Bloemen PJTM, Popper SW, editors. Decision making under deep uncertainty: from theory to practice. Cham: Springer International Publishing; 2019. p. 117–32. https://doi.org/10.1007/978-3-030-05252-2_6.

142.

Erfani T, Pachos K, Harou JJ. Real-options water supply planning: multistage scenario trees for adaptive and flexible capacity expansion under probabilistic climate change uncertainty. Water Resour Res. 2018;54(7):5069–87. https://doi.org/10.1029/2017wr021803.CrossRef

143.

Hino M, Hall JW. Real options analysis of adaptation to changing flood risk: structural and nonstructural measures. ASCE-ASME J Risk Uncertain Eng Sys A Civil Eng. 2017;3(3):04017005. https://doi.org/10.1061/ajrua6.0000905.CrossRef

144.

Quinn JD, Reed PM, Keller K. Direct policy search for robust multi-objective management of deeply uncertain socio-ecological tipping points. Environ Model Softw. 2017;92:125–41. https://doi.org/10.1016/j.envsoft.2017.02.017.CrossRef

145.

Schmidhuber J. Sequential Decision Making Based on Direct Search. In: Sun R, Giles CL (eds) Sequence learning: paradigms, algorithms, and applications. Lecture Notes in Computer Science. Berlin, Heidelberg: Springer, 2001, p 212–240. https://doi.org/10.1007/3-540-44565-X_10.

146.

Sutton RS, Barto AG. Reinforcement learning: an introduction, Second. edition. Cambridge, Massachusetts and London, England: MIT Press; 2018.

Titel: Improving the Representation of Climate Risks in Long-Term Electricity Systems Planning: a Critical Review
verfasst von: James Doss-Gollin
Yash Amonkar
Katlyn Schmeltzer
Daniel Cohan
Publikationsdatum: 16.08.2023
Verlag: Springer International Publishing
Erschienen in: Current Sustainable/Renewable Energy Reports / Ausgabe 4/2023
Elektronische ISSN: 2196-3010
DOI: https://doi.org/10.1007/s40518-023-00224-3

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