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A multi-paradigm framework to assess the impacts of climate change on end-use energy demand

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  • Roshanak Nateghi
  • Sayanti Mukherjee

Abstract

Projecting the long-term trends in energy demand is an increasingly complex endeavor due to the uncertain emerging changes in factors such as climate and policy. The existing energy-economy paradigms used to characterize the long-term trends in the energy sector do not adequately account for climate variability and change. In this paper, we propose a multi-paradigm framework for estimating the climate sensitivity of end-use energy demand that can easily be integrated with the existing energy-economy models. To illustrate the applicability of our proposed framework, we used the energy demand and climate data in the state of Indiana to train a Bayesian predictive model. We then leveraged the end-use demand trends as well as downscaled future climate scenarios to generate probabilistic estimates of the future end-use demand for space cooling, space heating and water heating, at the individual household and building level, in the residential and commercial sectors. Our results indicated that the residential load is much more sensitive to climate variability and change than the commercial load. Moreover, since the largest fraction of the residential energy demand in Indiana is attributed to heating, future warming scenarios could lead to reduced end-use demand due to lower space heating and water heating needs. In the commercial sector, the overall energy demand is expected to increase under the future warming scenarios. This is because the increased cooling load during hotter summer months will likely outpace the reduced heating load during the more temperate winter months.

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  • Roshanak Nateghi & Sayanti Mukherjee, 2017. "A multi-paradigm framework to assess the impacts of climate change on end-use energy demand," PLOS ONE, Public Library of Science, vol. 12(11), pages 1-23, November.
    • Handle: RePEc:plo:pone00:0188033
    DOI: 10.1371/journal.pone.0188033
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    References listed on IDEAS

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    1. Hahn, Heiko & Meyer-Nieberg, Silja & Pickl, Stefan, 2009. "Electric load forecasting methods: Tools for decision making," European Journal of Operational Research, Elsevier, vol. 199(3), pages 902-907, December.
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    1. Sayanti Mukherjee & Roshanak Nateghi, 2019. "A Data‐Driven Approach to Assessing Supply Inadequacy Risks Due to Climate‐Induced Shifts in Electricity Demand," Risk Analysis, John Wiley & Sons, vol. 39(3), pages 673-694, March.
    2. Mukherjee, Sayanti & Nateghi, Roshanak & Hastak, Makarand, 2018. "A multi-hazard approach to assess severe weather-induced major power outage risks in the U.S," Reliability Engineering and System Safety, Elsevier, vol. 175(C), pages 283-305.
    3. Renee Obringer & Rohini Kumar & Roshanak Nateghi, 2020. "Managing the water–electricity demand nexus in a warming climate," Climatic Change, Springer, vol. 159(2), pages 233-252, March.
    4. Alipour, Panteha & Mukherjee, Sayanti & Nateghi, Roshanak, 2019. "Assessing climate sensitivity of peak electricity load for resilient power systems planning and operation: A study applied to the Texas region," Energy, Elsevier, vol. 185(C), pages 1143-1153.
    5. Burleyson, Casey D. & Iyer, Gokul & Hejazi, Mohamad & Kim, Sonny & Kyle, Page & Rice, Jennie S. & Smith, Amanda D. & Taylor, Z. Todd & Voisin, Nathalie & Xie, Yulong, 2020. "Future western U.S. building electricity consumption in response to climate and population drivers: A comparative study of the impact of model structure," Energy, Elsevier, vol. 208(C).
    6. Obringer, Renee & Mukherjee, Sayanti & Nateghi, Roshanak, 2020. "Evaluating the climate sensitivity of coupled electricity-natural gas demand using a multivariate framework," Applied Energy, Elsevier, vol. 262(C).
    7. Mukherjee, Sayanti & Vineeth, C.R. & Nateghi, Roshanak, 2019. "Evaluating regional climate-electricity demand nexus: A composite Bayesian predictive framework," Applied Energy, Elsevier, vol. 235(C), pages 1561-1582.
    8. Ganguly, Prasangsha & Mukherjee, Sayanti, 2021. "A multifaceted risk assessment approach using statistical learning to evaluate socio-environmental factors associated with regional felony and misdemeanor rates," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 574(C).
    9. Jones, Andrew & Nock, Destenie & Samaras, Constantine & Qiu, Yueming (Lucy) & Xing, Bo, 2023. "Climate change impacts on future residential electricity consumption and energy burden: A case study in Phoenix, Arizona," Energy Policy, Elsevier, vol. 183(C).
    10. Pezalla, Simon & Obringer, Renee, 2023. "Evaluating the household-level climate-electricity nexus across three cities through statistical learning techniques," Socio-Economic Planning Sciences, Elsevier, vol. 89(C).
    11. Xiaowen Ding & Lin Liu & Guohe Huang & Ye Xu & Junhong Guo, 2019. "A Multi-Objective Optimization Model for a Non-Traditional Energy System in Beijing under Climate Change Conditions," Energies, MDPI, vol. 12(9), pages 1-21, May.
    12. Plaga, Leonie Sara & Bertsch, Valentin, 2023. "Methods for assessing climate uncertainty in energy system models — A systematic literature review," Applied Energy, Elsevier, vol. 331(C).
    13. Yongping Sun & Xin Zou & Xunpeng Shi & Ping Zhang, 2019. "The economic impact of climate risks in China: evidence from 47-sector panel data, 2000–2014," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 95(1), pages 289-308, January.
    14. Madadkhani, Shiva & Ikonnikova, Svetlana, 2024. "Toward high-resolution projection of electricity prices: A machine learning approach to quantifying the effects of high fuel and CO2 prices," Energy Economics, Elsevier, vol. 129(C).
    15. Liz Wachs & Shweta Singh, 2020. "Projecting the urban energy demand for Indiana, USA, in 2050 and 2080," Climatic Change, Springer, vol. 163(4), pages 1949-1966, December.
    16. Nnaemeka Vincent Emodi & Taha Chaiechi & ABM Rabiul Alam Beg, 2018. "The impact of climate change on electricity demand in Australia," Energy & Environment, , vol. 29(7), pages 1263-1297, November.
    17. Shu Chen & Zhengen Ren & Zhi Tang & Xianrong Zhuo, 2021. "Long-Term Prediction of Weather for Analysis of Residential Building Energy Consumption in Australia," Energies, MDPI, vol. 14(16), pages 1-20, August.
    18. Leigh Raymond & Douglas Gotham & William McClain & Sayanti Mukherjee & Roshanak Nateghi & Paul V. Preckel & Peter Schubert & Shweta Singh & Elizabeth Wachs, 2020. "Projected climate change impacts on Indiana’s Energy demand and supply," Climatic Change, Springer, vol. 163(4), pages 1933-1947, December.

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