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An energy performance contracting parameter optimization method based on the response surface method: A case study of a metro in China

Author

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  • Feng, Zongbao
  • Wu, Xianguo
  • Chen, Hongyu
  • Qin, Yawei
  • Zhang, Limao
  • Skibniewski, Miroslaw J.

Abstract

As an effective mechanism for improving energy efficiency, energy performance contracting (EPC) is receiving increasing attention. However, due to many uncertain factors that affect contract parameters, a reasonable distribution of participants' interests is necessary. To reasonably determine EPC contract parameters, this paper proposes a framework based on Geometric Brownian motion (GBM) and the response surface method (RSM) to optimize EPC contract parameters. First, GBM is used to simulate the energy prices, energy savings, energy-saving revenue allocation, etc. Then, the RSM is proposed to optimize multiple contract parameters. Finally, the proposed method is applied to the Wuhan Metro Line 2 lighting system renovation project. The results demonstrate that (a) the contract parameter optimization framework based on the GBM-RSM provides an effective method for optimizing the combination of EPC contract parameters. (b) The GBM-based method of quantitative simulation effectively expresses the uncertain factors of energy-saving performance in EPC renovation and provides reasonable data support for optimizing EPC contract parameters. (c) The established response surface optimization model of EPC contract parameters is an efficiently fitted model. A comparison between the optimization results and actual application results shows the feasibility of response surface optimization of EPC contract parameters, which improves the benefits for the owner of energy-saving renovation and thus increases the owner's enthusiasm, while guaranteeing a reasonable return for energy-saving companies. Hence, this study provides an effective method for optimizing EPC contract parameters and offers a reference for similar problems.

Suggested Citation

  • 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).
  • Handle: RePEc:eee:energy:v:248:y:2022:i:c:s0360544222005151
    DOI: 10.1016/j.energy.2022.123612
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    References listed on IDEAS

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    1. Wenjie Zhang & Hongping Yuan, 2019. "Promoting Energy Performance Contracting for Achieving Urban Sustainability: What is the Research Trend?," Energies, MDPI, vol. 12(8), pages 1-18, April.
    2. Lu, Zhijian & Shao, Shuai, 2016. "Impacts of government subsidies on pricing and performance level choice in Energy Performance Contracting: A two-step optimal decision model," Applied Energy, Elsevier, vol. 184(C), pages 1176-1183.
    3. Töppel, Jannick & Tränkler, Timm, 2019. "Modeling energy efficiency insurances and energy performance contracts for a quantitative comparison of risk mitigation potential," Energy Economics, Elsevier, vol. 80(C), pages 842-859.
    4. E, Jianwei & Ye, Jimin & He, Lulu & Jin, Haihong, 2019. "Energy price prediction based on independent component analysis and gated recurrent unit neural network," Energy, Elsevier, vol. 189(C).
    5. Wenjie Zhang & Hongping Yuan, 2019. "A Bibliometric Analysis of Energy Performance Contracting Research from 2008 to 2018," Sustainability, MDPI, vol. 11(13), pages 1-23, June.
    6. Wang, Zhenfeng & Xu, Guangyin & Lin, Ruojue & Wang, Heng & Ren, Jingzheng, 2019. "Energy performance contracting, risk factors, and policy implications: Identification and analysis of risks based on the best-worst network method," Energy, Elsevier, vol. 170(C), pages 1-13.
    7. Hongquan Ruan & Xin Gao & Chaoxuan Mao, 2018. "Empirical Study on Annual Energy-Saving Performance of Energy Performance Contracting in China," Sustainability, MDPI, vol. 10(5), pages 1-25, May.
    8. Viktor Stojkoski & Trifce Sandev & Lasko Basnarkov & Ljupco Kocarev & Ralf Metzler, 2020. "Generalised geometric Brownian motion: Theory and applications to option pricing," Papers 2011.00312, arXiv.org.
    9. Giulia Bernardi & Josep Freixas, 2018. "The Shapley value analyzed under the Felsenthal and Machover bargaining model," Public Choice, Springer, vol. 176(3), pages 557-565, September.
    10. Chen, Zhan-Ming & Chen, Pei-Lin & Ma, Zeming & Xu, Shiyun & Hayat, Tasawar & Alsaedi, Ahmed, 2019. "Inflationary and distributional effects of fossil energy price fluctuation on the Chinese economy," Energy, Elsevier, vol. 187(C).
    11. Barış Tan, 2020. "Design of balanced energy savings performance contracts," International Journal of Production Research, Taylor & Francis Journals, vol. 58(5), pages 1401-1424, March.
    12. Shang, Tiancheng & Liu, Peihong & Guo, Junxiong, 2020. "How to allocate energy-saving benefit for guaranteed savings EPC projects? A case of China," Energy, Elsevier, vol. 191(C).
    13. Zhang, Sheng & Sun, Yongjun & Cheng, Yong & Huang, Pei & Oladokun, Majeed Olaide & Lin, Zhang, 2018. "Response-surface-model-based system sizing for Nearly/Net zero energy buildings under uncertainty," Applied Energy, Elsevier, vol. 228(C), pages 1020-1031.
    14. Alejandro Mosiño & Alejandro Tatsuo Moreno-Okuno, 2018. "On modeling fossil fuel prices: geometric Brownian motion vs. variance-gamma process," Economics Bulletin, AccessEcon, vol. 38(1), pages 509-519.
    15. Xie, Yiwei & Hu, Pingfang & Zhu, Na & Lei, Fei & Xing, Lu & Xu, Linghong, 2020. "Collaborative optimization of ground source heat pump-radiant ceiling air conditioning system based on response surface method and NSGA-II," Renewable Energy, Elsevier, vol. 147(P1), pages 249-264.
    16. Wang, Lu & Zhang, Rong & Yang, Lin & Su, Yang & Ma, Feng, 2018. "Pricing geometric Asian rainbow options under fractional Brownian motion," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 494(C), pages 8-16.
    17. Zhang, Mingshun & Wang, Mujie & Jin, Wei & Xia-Bauer, Chun, 2018. "Managing energy efficiency of buildings in China: A survey of energy performance contracting (EPC) in building sector," Energy Policy, Elsevier, vol. 114(C), pages 13-21.
    18. Herrera, Gabriel Paes & Constantino, Michel & Tabak, Benjamin Miranda & Pistori, Hemerson & Su, Jen-Je & Naranpanawa, Athula, 2019. "Long-term forecast of energy commodities price using machine learning," Energy, Elsevier, vol. 179(C), pages 214-221.
    19. Sezgen, Osman & Goldman, C.A. & Krishnarao, P., 2007. "Option value of electricity demand response," Energy, Elsevier, vol. 32(2), pages 108-119.
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    Cited by:

    1. Chao Tu & Yingfang Shi, 2023. "Market-Incentive Environmental Regulation and the Quality of Corporate Innovation," Sustainability, MDPI, vol. 15(7), pages 1-17, March.
    2. 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).
    3. Huang, Xinyu & Li, Fangfei & Li, Yuanji & Meng, Xiangzhao & Yang, Xiaohu & Sundén, Bengt, 2023. "Optimization of melting performance of a heat storage tank under rotation conditions: Based on taguchi design and response surface method," Energy, Elsevier, vol. 271(C).

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