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Long-term equilibrium relationship analysis and energy-saving measures of metro energy consumption and its influencing factors based on cointegration theory and an ARDL model

Author

Listed:
  • Feng, Zongbao
  • Chen, Weiya
  • Liu, Yang
  • Chen, Hongyu
  • Skibniewski, Mirosław J.

Abstract

The energy consumption of metros has widely been concerned with respect to their economy and environmental protection. To analyze the complex dynamic relationship between metro energy consumption and its influencing factors and provide a reference for metro energy conservation control, this paper uses the monthly energy consumption, passenger flow and operating distance statistical data for Wuhan Metro Line 2 from 2018 to 2019. First, metro energy consumption and its influencing factors are qualitatively analyzed and identified. Then, based on cointegration theory and an autoregressive distributed lag (ARDL) model, a correlation hypothesis between metro energy consumption and its influencing factors is constructed, and a method for analyzing the influencing factors of metro energy consumption is proposed. The total energy consumption of a metro (TEC), train traction energy consumption (TTEC), environmental control energy consumption (ECEC), station lighting energy consumption (SLEC), station equipment energy consumption (SEEC) and the operating distance (OD) and passenger flow (PF) variables are analyzed. Using cointegration and an impulse response function, the dynamic relationships between the various energy consumption factors and operating distance and passenger flow are evaluated. The results show that there are substantial differences in the effects of OD and PF and their degree of influence on metro energy consumption. (1) OD affects mainly TTEC and TEC. The degree of influence of OD on TTEC reaches 97.8%, and the degree of influence of OD on TEC reaches 65.9%. (2) PF affects mainly ECEC and SEEC, and the degrees of influence of PF on ECEC and SEEC are 32.2% and 41.3%, respectively. (3) Considering that OD is the key factor affecting TTEC and TEC, train marshaling schemes, train running intervals and train stopping scheme optimization countermeasures are proposed, which can provide decision support for metro energy consumption management and control.

Suggested Citation

  • Feng, Zongbao & Chen, Weiya & Liu, Yang & Chen, Hongyu & Skibniewski, Mirosław J., 2023. "Long-term equilibrium relationship analysis and energy-saving measures of metro energy consumption and its influencing factors based on cointegration theory and an ARDL model," Energy, Elsevier, vol. 263(PD).
    • Handle: RePEc:eee:energy:v:263:y:2023:i:pd:s0360544222028511
    DOI: 10.1016/j.energy.2022.125965
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    as
    1. Onatski, Alexei & Wang, Chen, 2019. "Extreme canonical correlations and high-dimensional cointegration analysis," Journal of Econometrics, Elsevier, vol. 212(1), pages 307-322.
    2. Shi, Jungang & Yang, Lixing & Yang, Jing & Gao, Ziyou, 2018. "Service-oriented train timetabling with collaborative passenger flow control on an oversaturated metro line: An integer linear optimization approach," Transportation Research Part B: Methodological, Elsevier, vol. 110(C), pages 26-59.
    3. Liu, Renming & Li, Shukai & Yang, Lixing, 2020. "Collaborative optimization for metro train scheduling and train connections combined with passenger flow control strategy," Omega, Elsevier, vol. 90(C).
    4. Olivier Damette & Antonio C. Marques, 2019. "Renewable energy drivers: a panel cointegration approach," Applied Economics, Taylor & Francis Journals, vol. 51(26), pages 2793-2806, June.
    5. Nasreen, Samia & Mbarek, Mounir Ben & Atiq-ur-Rehman, Muhammad, 2020. "Long-run causal relationship between economic growth, transport energy consumption and environmental quality in Asian countries: Evidence from heterogeneous panel methods," Energy, Elsevier, vol. 192(C).
    6. M. Hashem Pesaran & Yongcheol Shin & Richard J. Smith, 2001. "Bounds testing approaches to the analysis of level relationships," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 16(3), pages 289-326.
    7. Yuan, Weichang & Frey, H. Christopher, 2020. "Potential for metro rail energy savings and emissions reduction via eco-driving," Applied Energy, Elsevier, vol. 268(C).
    8. Galán-Gutiérrez, Juan Antonio & Martín-García, Rodrigo, 2021. "Cointegration between the structure of copper futures prices and Brexit," Resources Policy, Elsevier, vol. 71(C).
    9. Daniel Ştefan Armeanu & Camelia Cătălina Joldeş & Ştefan Cristian Gherghina, 2019. "On the Linkage between the Energy Market and Stock Returns: Evidence from Romania," Energies, MDPI, vol. 12(8), pages 1-21, April.
    10. Jianqiang Liu & Nan Zhao, 2017. "Research on Energy-Saving Operation Strategy for Multiple Trains on the Urban Subway Line," Energies, MDPI, vol. 10(12), pages 1-19, December.
    11. Apergis, Nicholas, 2019. "The impact of fracking activities on Oklahoma's housing prices: A panel cointegration analysis," Energy Policy, Elsevier, vol. 128(C), pages 94-101.
    12. Víctor Cuevas, 2018. "The impact of the yuan†dollar exchange rate on Mexican manufacturing exports to the US: A cointegration approach," The World Economy, Wiley Blackwell, vol. 41(3), pages 866-883, March.
    13. Potter, Simon M., 2000. "Nonlinear impulse response functions," Journal of Economic Dynamics and Control, Elsevier, vol. 24(10), pages 1425-1446, September.
    14. Feng, Zongbao & Wu, Xianguo & Chen, Hongyu & Qin, Yawei & Zhang, Limao & Skibniewski, Miroslaw J., 2022. "An energy performance contracting parameter optimization method based on the response surface method: A case study of a metro in China," Energy, Elsevier, vol. 248(C).
    15. Shen, Xiaojun & Wei, Hongyang & Wei, Li, 2020. "Study of trackside photovoltaic power integration into the traction power system of suburban elevated urban rail transit line," Applied Energy, Elsevier, vol. 260(C).
    16. Cai, Yifei & Chang, Tsangyao & Inglesi-Lotz, Roula, 2018. "Asymmetric persistence in convergence for carbon dioxide emissions based on quantile unit root test with Fourier function," Energy, Elsevier, vol. 161(C), pages 470-481.
    17. Liping Liao & Minzhe Du & Bing Wang & Yanni Yu, 2019. "The Impact of Educational Investment on Sustainable Economic Growth in Guangdong, China: A Cointegration and Causality Analysis," Sustainability, MDPI, vol. 11(3), pages 1-16, February.
    18. Zhang, Rongmao & Chan, Ngai Hang, 2018. "Portmanteau-type tests for unit-root and cointegration," Journal of Econometrics, Elsevier, vol. 207(2), pages 307-324.
    19. Huang, Yeran & Yang, Lixing & Tang, Tao & Gao, Ziyou & Cao, Fang, 2017. "Joint train scheduling optimization with service quality and energy efficiency in urban rail transit networks," Energy, Elsevier, vol. 138(C), pages 1124-1147.
    20. Raghoo, Pravesh & Surroop, Dinesh, 2020. "Price and income elasticities of oil demand in Mauritius: An empirical analysis using cointegration method," Energy Policy, Elsevier, vol. 140(C).
    21. Matteo Barigozzi & Marco Lippi & Matteo Luciani, 2020. "Cointegration and Error Correction Mechanisms for Singular Stochastic Vectors," Econometrics, MDPI, vol. 8(1), pages 1-23, February.
    22. Zoundi, Zakaria, 2017. "CO2 emissions, renewable energy and the Environmental Kuznets Curve, a panel cointegration approach," Renewable and Sustainable Energy Reviews, Elsevier, vol. 72(C), pages 1067-1075.
    23. Ozturk, Ilhan & Acaravci, Ali, 2011. "Electricity consumption and real GDP causality nexus: Evidence from ARDL bounds testing approach for 11 MENA countries," Applied Energy, Elsevier, vol. 88(8), pages 2885-2892, August.
    24. Johansen, Soren, 1988. "Statistical analysis of cointegration vectors," Journal of Economic Dynamics and Control, Elsevier, vol. 12(2-3), pages 231-254.
    25. Jorge Garza-Rodriguez, 2019. "Tourism and Poverty Reduction in Mexico: An ARDL Cointegration Approach," Sustainability, MDPI, vol. 11(3), pages 1-10, February.
    26. Shahbaz, Muhammad & Kumar Tiwari, Aviral & Nasir, Muhammad, 2013. "The effects of financial development, economic growth, coal consumption and trade openness on CO2 emissions in South Africa," Energy Policy, Elsevier, vol. 61(C), pages 1452-1459.
    27. Soren Jordan & Andrew Q. Philips, 2018. "Cointegration testing and dynamic simulations of autoregressive distributed lag modelsJournal: Stata Journal," Stata Journal, StataCorp LP, vol. 18(4), pages 902-923, December.
    28. Liu, Zhijian & Liu, Yuanwei & He, Bao-Jie & Xu, Wei & Jin, Guangya & Zhang, Xutao, 2019. "Application and suitability analysis of the key technologies in nearly zero energy buildings in China," Renewable and Sustainable Energy Reviews, Elsevier, vol. 101(C), pages 329-345.
    29. Kris Ivanovski & Sefa Awaworyi Churchill & Ahmed Salim Nuhu, 2020. "Modelling the Australian J‐Curve: An ARDL Cointegration Approach," Economic Papers, The Economic Society of Australia, vol. 39(2), pages 167-184, June.
    30. He, Deqiang & Yang, Yanjie & Chen, Yanjun & Deng, Jianxin & Shan, Sheng & Liu, Jianren & Li, Xianwang, 2020. "An integrated optimization model of metro energy consumption based on regenerative energy and passenger transfer," Applied Energy, Elsevier, vol. 264(C).
    31. Rith, Monorom & Fillone, Alexis M. & Biona, Jose Bienvenido Manuel M., 2020. "Energy and environmental benefits and policy implications for private passenger vehicles in an emerging metropolis of Southeast Asia – A case study of Metro Manila," Applied Energy, Elsevier, vol. 275(C).
    32. Granger, C. W. J. & Newbold, P., 1974. "Spurious regressions in econometrics," Journal of Econometrics, Elsevier, vol. 2(2), pages 111-120, July.
    33. McCallum, Bennett T., 2010. "Is the spurious regression problem spurious?," Economics Letters, Elsevier, vol. 107(3), pages 321-323, June.
    34. Gulay, Emrah & Duru, Okan, 2020. "Hybrid modeling in the predictive analytics of energy systems and prices," Applied Energy, Elsevier, vol. 268(C).
    35. Yang, Lixing & Qi, Jianguo & Li, Shukai & Gao, Yuan, 2016. "Collaborative optimization for train scheduling and train stop planning on high-speed railways," Omega, Elsevier, vol. 64(C), pages 57-76.
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