IDEAS home Printed from https://ideas.repec.org/a/eee/appene/v262y2020ics0306261919321063.html
   My bibliography  Save this article

Evaluating the climate sensitivity of coupled electricity-natural gas demand using a multivariate framework

Author

Listed:
  • Obringer, Renee
  • Mukherjee, Sayanti
  • Nateghi, Roshanak

Abstract

Projected climate change will significantly influence the shape of the end-use energy demand profiles for space conditioning—leading to a likely increase in cooling needs and a subsequent decrease in heating needs. This shift will put pressure on existing infrastructure and utility companies to meet a demand that was not accounted for in the initial design of the systems. Furthermore, the traditional linear models typically used to predict energy demand focus on isolating either the electricity or natural gas demand, even though the two demands are highly interconnected. This practice often leads to less accurate predictions for both demand profiles. Here, we propose a multivariate, multi-sector (i.e., residential, commercial, industrial) framework to model the climate sensitivity of the coupled electricity and natural gas demand simultaneously, leveraging advanced statistical learning algorithms. Our results indicate that the season-to-date heating and cooling degree-days, as well as the dew point temperature are the key predictors for both the electricity and natural gas demand. We also found that the energy sector is most sensitive to climate during the autumn and spring (intermediate) seasons, followed by the summer and winter seasons. Moreover, the proposed model outperforms a similar univariate model in terms of predictive accuracy, indicating the importance of accounting for the interdependence within the energy sectors. By providing accurate predictions of the electricity and natural gas demand, the proposed framework can help infrastructure planners and operators make informed decisions towards ensuring balanced energy delivery and minimizing supply inadequacy risks under future climate variability and change.

Suggested Citation

  • 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).
    • Handle: RePEc:eee:appene:v:262:y:2020:i:c:s0306261919321063
    DOI: 10.1016/j.apenergy.2019.114419
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0306261919321063
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.apenergy.2019.114419?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. 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.
    2. Sailor, David J, 2001. "Relating residential and commercial sector electricity loads to climate—evaluating state level sensitivities and vulnerabilities," Energy, Elsevier, vol. 26(7), pages 645-657.
    3. Mukhopadhyay, Sayanti & Nateghi, Roshanak, 2017. "Climate sensitivity of end-use electricity consumption in the built environment: An application to the state of Florida, United States," Energy, Elsevier, vol. 128(C), pages 688-700.
    4. Sailor, David J. & Muñoz, J.Ricardo, 1997. "Sensitivity of electricity and natural gas consumption to climate in the U.S.A.—Methodology and results for eight states," Energy, Elsevier, vol. 22(10), pages 987-998.
    5. 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.
    6. Roshanak Nateghi & Seth D. Guikema & Steven M. Quiring, 2011. "Comparison and Validation of Statistical Methods for Predicting Power Outage Durations in the Event of Hurricanes," Risk Analysis, John Wiley & Sons, vol. 31(12), pages 1897-1906, December.
    7. 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.
    8. Ruth, Matthias & Lin, Ai-Chen, 2006. "Regional energy demand and adaptations to climate change: Methodology and application to the state of Maryland, USA," Energy Policy, Elsevier, vol. 34(17), pages 2820-2833, November.
    9. Obringer, R. & Kumar, R. & Nateghi, R., 2019. "Analyzing the climate sensitivity of the coupled water-electricity demand nexus in the Midwestern United States," Applied Energy, Elsevier, vol. 252(C), pages 1-1.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Yihsuan Wu & Jian Hua, 2022. "Investigating a Retrofit Thermal Power Plant from a Sustainable Environment Perspective—A Fuel Lifecycle Assessment Case Study," Sustainability, MDPI, vol. 14(8), pages 1-26, April.
    2. Yetuo Tan & Yongming Zhi & Zhengbin Luo & Honggang Fan & Jun Wan & Tao Zhang, 2023. "Optimal Scheduling of Virtual Power Plant with Flexibility Margin Considering Demand Response and Uncertainties," Energies, MDPI, vol. 16(15), pages 1-14, August.
    3. 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).
    4. Xu, Xiao & Hu, Weihao & Cao, Di & Liu, Wen & Huang, Qi & Hu, Yanting & Chen, Zhe, 2021. "Enhanced design of an offgrid PV-battery-methanation hybrid energy system for power/gas supply," Renewable Energy, Elsevier, vol. 167(C), pages 440-456.
    5. Chen, Ying & Koch, Thorsten & Zakiyeva, Nazgul & Zhu, Bangzhu, 2020. "Modeling and forecasting the dynamics of the natural gas transmission network in Germany with the demand and supply balance constraint," Applied Energy, Elsevier, vol. 278(C).
    6. 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).
    7. Huang, Shanshan & Suo, Cai & Guo, Junhong & Lv, Jing & Jing, Rui & Yu, Lei & Fan, Yurui & Ding, Yanming, 2023. "Balancing the water-energy dilemma in nexus system planning with bi-level and multi-uncertainty," Energy, Elsevier, vol. 278(C).
    8. Ahmad, Shakeel & Jia, Haifeng & Chen, Zhengxia & Li, Qian & Xu, Changqing, 2020. "Water-energy nexus and energy efficiency: A systematic analysis of urban water systems," Renewable and Sustainable Energy Reviews, Elsevier, vol. 134(C).
    9. Renee Obringer & Dave D. White, 2023. "Leveraging Unsupervised Learning to Develop a Typology of Residential Water Users’ Attitudes Towards Conservation," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 37(1), pages 37-53, January.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. 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.
    2. 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.
    3. 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.
    4. 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).
    5. 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.
    6. Eshraghi, Hadi & Rodrigo de Queiroz, Anderson & Sankarasubramanian, A. & DeCarolis, Joseph F., 2021. "Quantification of climate-induced interannual variability in residential U.S. electricity demand," Energy, Elsevier, vol. 236(C).
    7. 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).
    8. 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.
    9. Yau, Y.H. & Pean, H.L., 2011. "The climate change impact on air conditioner system and reliability in Malaysia—A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 15(9), pages 4939-4949.
    10. Psiloglou, B.E. & Giannakopoulos, C. & Majithia, S. & Petrakis, M., 2009. "Factors affecting electricity demand in Athens, Greece and London, UK: A comparative assessment," Energy, Elsevier, vol. 34(11), pages 1855-1863.
    11. Son, Hyojoo & Kim, Changwan, 2017. "Short-term forecasting of electricity demand for the residential sector using weather and social variables," Resources, Conservation & Recycling, Elsevier, vol. 123(C), pages 200-207.
    12. Mukhopadhyay, Sayanti & Nateghi, Roshanak, 2017. "Climate sensitivity of end-use electricity consumption in the built environment: An application to the state of Florida, United States," Energy, Elsevier, vol. 128(C), pages 688-700.
    13. Pilli-Sihvola, Karoliina & Aatola, Piia & Ollikainen, Markku & Tuomenvirta, Heikki, 2010. "Climate change and electricity consumption--Witnessing increasing or decreasing use and costs?," Energy Policy, Elsevier, vol. 38(5), pages 2409-2419, May.
    14. Ahmed, T. & Muttaqi, K.M. & Agalgaonkar, A.P., 2012. "Climate change impacts on electricity demand in the State of New South Wales, Australia," Applied Energy, Elsevier, vol. 98(C), pages 376-383.
    15. Li, Xian-Xiang, 2018. "Linking residential electricity consumption and outdoor climate in a tropical city," Energy, Elsevier, vol. 157(C), pages 734-743.
    16. Vu, D.H. & Muttaqi, K.M. & Agalgaonkar, A.P., 2015. "A variance inflation factor and backward elimination based robust regression model for forecasting monthly electricity demand using climatic variables," Applied Energy, Elsevier, vol. 140(C), pages 385-394.
    17. Hekkenberg, M. & Benders, R.M.J. & Moll, H.C. & Schoot Uiterkamp, A.J.M., 2009. "Indications for a changing electricity demand pattern: The temperature dependence of electricity demand in the Netherlands," Energy Policy, Elsevier, vol. 37(4), pages 1542-1551, April.
    18. Jianhua Huang & Kevin Robert Gurney, 2016. "Impact of climate change on U.S. building energy demand: sensitivity to spatiotemporal scales, balance point temperature, and population distribution," Climatic Change, Springer, vol. 137(1), pages 171-185, July.
    19. Zheng, Shuguang & Huang, Guohe & Zhou, Xiong & Zhu, Xiaohang, 2020. "Climate-change impacts on electricity demands at a metropolitan scale: A case study of Guangzhou, China," Applied Energy, Elsevier, vol. 261(C).
    20. Huang, Jianhua & Gurney, Kevin Robert, 2016. "The variation of climate change impact on building energy consumption to building type and spatiotemporal scale," Energy, Elsevier, vol. 111(C), pages 137-153.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:appene:v:262:y:2020:i:c:s0306261919321063. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/wps/find/journaldescription.cws_home/405891/description#description .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.