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Identifying household cooling savings potential in the hot summer and cold winter climate zone in China: A stochastic demand frontier approach

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  • Wang, Xia
  • Ding, Chao
  • Cai, Weiguang
  • Luo, Lizi
  • Chen, Mingman

Abstract

Cooling demand increases more than ten times over the past two decades in China. Especially, cooling in the Hot Summer and Cold Winter (HSCW) climate zone increases rapidly and becomes the fastest growing part in urban residential energy consumption. It will bring huge challenges to carbon emission cap control if effective and reasonable energy-saving and emission reduction measures are not taken. This study uses a data-driven method to identify cooling savings potential at household level using survey data from 1068 households in 2018 in Chongqing, China. A stochastic frontier analysis model is applied to decompose the actual cooling electricity consumption into minimum consumption based on fixed household characteristics and estimate the over-consumption (i.e. the amount of cooling consumption that could be saved). The results show that households have an average cooling efficiency of 65 %, which indicates that each household in the HSCW area has the potential to reduce its cooling electricity consumption by 35% while still maintaining the same level of cooling services currently produced. The study shows that the cooling savings potential is strongly influenced by level of household income, the level of building energy efficiency standards, cooling behavior characteristics and households’ energy-saving consciousness. Policy implications are derived.

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  • Wang, Xia & Ding, Chao & Cai, Weiguang & Luo, Lizi & Chen, Mingman, 2021. "Identifying household cooling savings potential in the hot summer and cold winter climate zone in China: A stochastic demand frontier approach," Energy, Elsevier, vol. 237(C).
    • Handle: RePEc:eee:energy:v:237:y:2021:i:c:s0360544221018363
    DOI: 10.1016/j.energy.2021.121588
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    as
    1. Leahy, Eimear & Lyons, Sean, 2010. "Energy use and appliance ownership in Ireland," Energy Policy, Elsevier, vol. 38(8), pages 4265-4279, August.
    2. Tso, Geoffrey K.F. & Yau, Kelvin K.W., 2007. "Predicting electricity energy consumption: A comparison of regression analysis, decision tree and neural networks," Energy, Elsevier, vol. 32(9), pages 1761-1768.
    3. Blasch, Julia & Boogen, Nina & Filippini, Massimo & Kumar, Nilkanth, 2017. "Explaining electricity demand and the role of energy and investment literacy on end-use efficiency of Swiss households," Energy Economics, Elsevier, vol. 68(S1), pages 89-102.
    4. Massimo Filippini & William Greene, 2016. "Persistent and transient productive inefficiency: a maximum simulated likelihood approach," Journal of Productivity Analysis, Springer, vol. 45(2), pages 187-196, April.
    5. Filippini, Massimo & Hunt, Lester C., 2012. "US residential energy demand and energy efficiency: A stochastic demand frontier approach," Energy Economics, Elsevier, vol. 34(5), pages 1484-1491.
    6. Massimo Filippini & Lester C. Hunt, 2011. "Energy Demand and Energy Efficiency in the OECD Countries: A Stochastic Demand Frontier Approach," The Energy Journal, International Association for Energy Economics, vol. 0(Number 2), pages 59-80.
    7. Hosier, Richard H. & Dowd, Jeffrey, 1987. "Household fuel choice in Zimbabwe : An empirical test of the energy ladder hypothesis," Resources and Energy, Elsevier, vol. 9(4), pages 347-361, December.
    8. Scott Kelly, 2011. "Do homes that are more energy efficient consume less energy?: A structural equation model for England's residential sector," Working Papers EPRG 1117, Energy Policy Research Group, Cambridge Judge Business School, University of Cambridge.
    9. Wang, Xia & Feng, Wei & Cai, Weiguang & Ren, Hong & Ding, Chao & Zhou, Nan, 2019. "Do residential building energy efficiency standards reduce energy consumption in China? – A data-driven method to validate the actual performance of building energy efficiency standards," Energy Policy, Elsevier, vol. 131(C), pages 82-98.
    10. Karali, Nihan & Shah, Nihar & Park, Won Young & Khanna, Nina & Ding, Chao & Lin, Jiang & Zhou, Nan, 2020. "Improving the energy efficiency of room air conditioners in China: Costs and benefits," Applied Energy, Elsevier, vol. 258(C).
    11. Wyatt, Peter, 2013. "A dwelling-level investigation into the physical and socio-economic drivers of domestic energy consumption in England," Energy Policy, Elsevier, vol. 60(C), pages 540-549.
    12. Li, Xinyi & Yao, Runming, 2020. "A machine-learning-based approach to predict residential annual space heating and cooling loads considering occupant behaviour," Energy, Elsevier, vol. 212(C).
    13. Hori, Shiro & Kondo, Kayoko & Nogata, Daisuke & Ben, Han, 2013. "The determinants of household energy-saving behavior: Survey and comparison in five major Asian cities," Energy Policy, Elsevier, vol. 52(C), pages 354-362.
    14. Meeusen, Wim & van den Broeck, Julien, 1977. "Efficiency Estimation from Cobb-Douglas Production Functions with Composed Error," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 18(2), pages 435-444, June.
    15. Banfi, Silvia & Filippini, Massimo & Hunt, Lester C., 2005. "Fuel tourism in border regions: The case of Switzerland," Energy Economics, Elsevier, vol. 27(5), pages 689-707, September.
    16. Kelly, Scott, 2011. "Do homes that are more energy efficient consume less energy?: A structural equation model of the English residential sector," Energy, Elsevier, vol. 36(9), pages 5610-5620.
    17. Kavousian, Amir & Rajagopal, Ram & Fischer, Martin, 2013. "Determinants of residential electricity consumption: Using smart meter data to examine the effect of climate, building characteristics, appliance stock, and occupants' behavior," Energy, Elsevier, vol. 55(C), pages 184-194.
    18. Fumitoshi Mizutani & Eri Nakamura, 2015. "An Analysis of Household Electricity Saving Behavior Using the Stochastic Frontier Function," Discussion Papers 2015-10, Kobe University, Graduate School of Business Administration.
    19. Schipper, Lee & Hawk, Dianne V., 1991. "More efficient household electricity-use : An international perspective," Energy Policy, Elsevier, vol. 19(3), pages 244-265, April.
    20. Akihiro Otsuka, 2018. "Regional Determinants of Energy Efficiency: Residential Energy Demand in Japan," Energies, MDPI, vol. 11(6), pages 1-14, June.
    21. Grant D. Jacobsen & Matthew J. Kotchen, 2013. "Are Building Codes Effective at Saving Energy? Evidence from Residential Billing Data in Florida," The Review of Economics and Statistics, MIT Press, vol. 95(1), pages 34-49, March.
    22. Battese, George E. & Corra, Greg S., 1977. "Estimation Of A Production Frontier Model: With Application To The Pastoral Zone Of Eastern Australia," Australian Journal of Agricultural Economics, Australian Agricultural and Resource Economics Society, vol. 21(3), pages 1-11, December.
    23. Anin Aroonruengsawat, Maximilian Auffhammer, and Alan H. Sanstad, 2012. "The Impact of State Level Building Codes on Residential Electricity Consumption," The Energy Journal, International Association for Energy Economics, vol. 0(Number 1).
    24. Su, Yu-Wen, 2019. "Residential electricity demand in Taiwan: Consumption behavior and rebound effect," Energy Policy, Elsevier, vol. 124(C), pages 36-45.
    25. Xu, Luyi & Liu, Junjie & Pei, Jingjing & Han, Xu, 2013. "Building energy saving potential in Hot Summer and Cold Winter (HSCW) Zone, China—Influence of building energy efficiency standards and implications," Energy Policy, Elsevier, vol. 57(C), pages 253-262.
    26. Battese, G E & Coelli, T J, 1995. "A Model for Technical Inefficiency Effects in a Stochastic Frontier Production Function for Panel Data," Empirical Economics, Springer, vol. 20(2), pages 325-332.
    27. Broadstock, David C. & Li, Jiajia & Zhang, Dayong, 2016. "Efficiency snakes and energy ladders: A (meta-)frontier demand analysis of electricity consumption efficiency in Chinese households," Energy Policy, Elsevier, vol. 91(C), pages 383-396.
    28. Sardianou, Eleni, 2007. "Estimating energy conservation patterns of Greek households," Energy Policy, Elsevier, vol. 35(7), pages 3778-3791, July.
    29. Zhou, Shaojie & Teng, Fei, 2013. "Estimation of urban residential electricity demand in China using household survey data," Energy Policy, Elsevier, vol. 61(C), pages 394-402.
    30. Li, Sihui & Gong, Guangcai & Peng, Jinqing, 2019. "Dynamic coupling method between air-source heat pumps and buildings in China’s hot-summer/cold-winter zone," Applied Energy, Elsevier, vol. 254(C).
    31. Smith, Kirk R. & Apte, Michael G. & Yuqing, Ma & Wongsekiarttirat, Wathana & Kulkarni, Ashwini, 1994. "Air pollution and the energy ladder in asian cities," Energy, Elsevier, vol. 19(5), pages 587-600.
    32. Calvin Nsangou, Jean & Kenfack, Joseph & Nzotcha, Urbain & Tamo, Thomas Tatietse, 2020. "Assessment of the potential for electricity savings in households in Cameroon: A stochastic frontier approach," Energy, Elsevier, vol. 211(C).
    33. Greene, William H., 1980. "Maximum likelihood estimation of econometric frontier functions," Journal of Econometrics, Elsevier, vol. 13(1), pages 27-56, May.
    34. van der Kroon, Bianca & Brouwer, Roy & van Beukering, Pieter J.H., 2013. "The energy ladder: Theoretical myth or empirical truth? Results from a meta-analysis," Renewable and Sustainable Energy Reviews, Elsevier, vol. 20(C), pages 504-513.
    35. Lin, Boqiang & Liu, Xia, 2013. "Electricity tariff reform and rebound effect of residential electricity consumption in China," Energy, Elsevier, vol. 59(C), pages 240-247.
    36. Hiemstra-van der Horst, Greg & Hovorka, Alice J., 2008. "Reassessing the "energy ladder": Household energy use in Maun, Botswana," Energy Policy, Elsevier, vol. 36(9), pages 3333-3344, September.
    37. Matthew J. Kotchen, 2017. "Longer-Run Evidence on Whether Building Energy Codes Reduce Residential Energy Consumption," Journal of the Association of Environmental and Resource Economists, University of Chicago Press, vol. 4(1), pages 135-153.
    38. Yun, Geun Young & Steemers, Koen, 2011. "Behavioural, physical and socio-economic factors in household cooling energy consumption," Applied Energy, Elsevier, vol. 88(6), pages 2191-2200, June.
    39. Jondrow, James & Knox Lovell, C. A. & Materov, Ivan S. & Schmidt, Peter, 1982. "On the estimation of technical inefficiency in the stochastic frontier production function model," Journal of Econometrics, Elsevier, vol. 19(2-3), pages 233-238, August.
    40. Boogen, Nina, 2017. "Estimating the potential for electricity savings in households," Energy Economics, Elsevier, vol. 63(C), pages 288-300.
    41. Twerefou, Daniel Kwabena & Abeney, Jacob Opantu, 2020. "Efficiency of household electricity consumption in Ghana," Energy Policy, Elsevier, vol. 144(C).
    42. Poortinga, Wouter & Steg, Linda & Vlek, Charles & Wiersma, Gerwin, 2003. "Household preferences for energy-saving measures: A conjoint analysis," Journal of Economic Psychology, Elsevier, vol. 24(1), pages 49-64, February.
    43. Ouyang, Jinlong & Ge, Jian & Hokao, Kazunori, 2009. "Economic analysis of energy-saving renovation measures for urban existing residential buildings in China based on thermal simulation and site investigation," Energy Policy, Elsevier, vol. 37(1), pages 140-149, January.
    44. Yu, Yihua & Guo, Jin, 2016. "Identifying electricity-saving potential in rural China: Empirical evidence from a household survey," Energy Policy, Elsevier, vol. 94(C), pages 1-9.
    45. Massimo Filippini, 1999. "Swiss residential demand for electricity," Applied Economics Letters, Taylor & Francis Journals, vol. 6(8), pages 533-538.
    46. George E. Battese & Greg S. Corra, 1977. "Estimation Of A Production Frontier Model: With Application To The Pastoral Zone Of Eastern Australia," Australian Journal of Agricultural and Resource Economics, Australian Agricultural and Resource Economics Society, vol. 21(3), pages 169-179, December.
    47. Tso, Geoffrey K.F & Yau, Kelvin K.W, 2003. "A study of domestic energy usage patterns in Hong Kong," Energy, Elsevier, vol. 28(15), pages 1671-1682.
    48. Chao Ding & Nan Zhou, 2020. "Using Residential and Office Building Archetypes for Energy Efficiency Building Solutions in an Urban Scale: A China Case Study," Energies, MDPI, vol. 13(12), pages 1-16, June.
    49. Leach, Gerald, 1992. "The energy transition," Energy Policy, Elsevier, vol. 20(2), pages 116-123, February.
    50. Suchul Kang & Elfatih A. B. Eltahir, 2018. "North China Plain threatened by deadly heatwaves due to climate change and irrigation," Nature Communications, Nature, vol. 9(1), pages 1-9, December.
    51. Naji, Sareh & Keivani, Afram & Shamshirband, Shahaboddin & Alengaram, U. Johnson & Jumaat, Mohd Zamin & Mansor, Zulkefli & Lee, Malrey, 2016. "Estimating building energy consumption using extreme learning machine method," Energy, Elsevier, vol. 97(C), pages 506-516.
    52. Aigner, Dennis & Lovell, C. A. Knox & Schmidt, Peter, 1977. "Formulation and estimation of stochastic frontier production function models," Journal of Econometrics, Elsevier, vol. 6(1), pages 21-37, July.
    53. Berkhout, Peter H. G. & Muskens, Jos C. & W. Velthuijsen, Jan, 2000. "Defining the rebound effect," Energy Policy, Elsevier, vol. 28(6-7), pages 425-432, June.
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