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Impact of introducing penalty-cost on optimal design of renewable energy systems for net zero energy buildings

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  • Lu, Yuehong
  • Zhang, Xiao-Ping
  • Huang, Zhijia
  • Lu, Jinli
  • Wang, Dong

Abstract

It is well known that the high cost of installing renewable energy systems (RES) is still a barrier to overcome in the promotion of net-zero energy buildings (NZEB). The current practice in selecting the optimal RES system for NZEB basically involves a consideration of all possible design options, which is usually not a cost-effective process when compared with costs for no or for less RES in buildings. This study, therefore, introduces a penalty cost in the RES design process for NZEB, which aims to ensure that the cost-effective design option is the system which provides for a net-zero/positive energy building. The proposed penalty cost function is investigated in three scenarios (two scenarios with penalty costs and one scenario without a penalty cost) based on the Hong Kong Zero Carbon Building. It is found that the total cost of the building under a safety factor of 0.0 is increased by about 70% when a penalty cost is considered whilst it is reduced by 39% (for penalty cost 1) and 48.9% (for penalty cost 2) for the building under a safety factor of 1.0 (i.e., NZEB), respectively. In addition, three fitting formulas were derived for designers to better understand the relationship between the total cost and safety factor. The idea of developing a penalty cost mechanism provides a progressive perspective to assist the promotion of NZEB in terms of both governments as well as building designers/owners.

Suggested Citation

  • Lu, Yuehong & Zhang, Xiao-Ping & Huang, Zhijia & Lu, Jinli & Wang, Dong, 2019. "Impact of introducing penalty-cost on optimal design of renewable energy systems for net zero energy buildings," Applied Energy, Elsevier, vol. 235(C), pages 106-116.
    • Handle: RePEc:eee:appene:v:235:y:2019:i:c:p:106-116
    DOI: 10.1016/j.apenergy.2018.10.112
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    as
    1. Lu, Yuehong & Wang, Shengwei & Sun, Yongjun & Yan, Chengchu, 2015. "Optimal scheduling of buildings with energy generation and thermal energy storage under dynamic electricity pricing using mixed-integer nonlinear programming," Applied Energy, Elsevier, vol. 147(C), pages 49-58.
    2. Sun, Yongjun & Huang, Gongsheng & Xu, Xinhua & Lai, Alvin Chi-Keung, 2018. "Building-group-level performance evaluations of net zero energy buildings with non-collaborative controls," Applied Energy, Elsevier, vol. 212(C), pages 565-576.
    3. Huang, Zhijia & Lu, Yuehong & Wei, Mengmeng & Liu, Jingjing, 2017. "Performance analysis of optimal designed hybrid energy systems for grid-connected nearly/net zero energy buildings," Energy, Elsevier, vol. 141(C), pages 1795-1809.
    4. Lipp, Judith, 2007. "Lessons for effective renewable electricity policy from Denmark, Germany and the United Kingdom," Energy Policy, Elsevier, vol. 35(11), pages 5481-5495, November.
    5. Ritter, Matthias & Deckert, Lars, 2017. "Site assessment, turbine selection, and local feed-in tariffs through the wind energy index," Applied Energy, Elsevier, vol. 185(P2), pages 1087-1099.
    6. Kim, Kyoung-Kuk & Lee, Chi-Guhn, 2012. "Evaluation and optimization of feed-in tariffs," Energy Policy, Elsevier, vol. 49(C), pages 192-203.
    7. del Río, Pablo & Calvo Silvosa, Anxo & Iglesias Gómez, Guillermo, 2011. "Policies and design elements for the repowering of wind farms: A qualitative analysis of different options," Energy Policy, Elsevier, vol. 39(4), pages 1897-1908, April.
    8. Ayompe, L.M. & Duffy, A., 2013. "Feed-in tariff design for domestic scale grid-connected PV systems using high resolution household electricity demand data," Energy Policy, Elsevier, vol. 61(C), pages 619-627.
    9. Abolhosseini, Shahrouz & Heshmati, Almas, 2014. "The main support mechanisms to finance renewable energy development," Renewable and Sustainable Energy Reviews, Elsevier, vol. 40(C), pages 876-885.
    10. Lesser, Jonathan A. & Su, Xuejuan, 2008. "Design of an economically efficient feed-in tariff structure for renewable energy development," Energy Policy, Elsevier, vol. 36(3), pages 981-990, March.
    11. Bakhshi, Reza & Sadeh, Javad, 2018. "Economic evaluation of grid–connected photovoltaic systems viability under a new dynamic feed–in tariff scheme: A case study in Iran," Renewable Energy, Elsevier, vol. 119(C), pages 354-364.
    12. Lu, Yuehong & Wang, Shengwei & Yan, Chengchu & Huang, Zhijia, 2017. "Robust optimal design of renewable energy system in nearly/net zero energy buildings under uncertainties," Applied Energy, Elsevier, vol. 187(C), pages 62-71.
    13. Muhammad-Sukki, Firdaus & Ramirez-Iniguez, Roberto & Munir, Abu Bakar & Mohd Yasin, Siti Hajar & Abu-Bakar, Siti Hawa & McMeekin, Scott G. & Stewart, Brian G., 2013. "Revised feed-in tariff for solar photovoltaic in the United Kingdom: A cloudy future ahead?," Energy Policy, Elsevier, vol. 52(C), pages 832-838.
    14. Fridgen, Gilbert & Kahlen, Micha & Ketter, Wolfgang & Rieger, Alexander & Thimmel, Markus, 2018. "One rate does not fit all: An empirical analysis of electricity tariffs for residential microgrids," Applied Energy, Elsevier, vol. 210(C), pages 800-814.
    15. Zhang, M.M. & Zhou, D.Q. & Zhou, P. & Liu, G.Q., 2016. "Optimal feed-in tariff for solar photovoltaic power generation in China: A real options analysis," Energy Policy, Elsevier, vol. 97(C), pages 181-192.
    16. Wu, Wei & Skye, Harrison M. & Domanski, Piotr A., 2018. "Selecting HVAC systems to achieve comfortable and cost-effective residential net-zero energy buildings," Applied Energy, Elsevier, vol. 212(C), pages 577-591.
    17. Abedi, S. & Alimardani, A. & Gharehpetian, G.B. & Riahy, G.H. & Hosseinian, S.H., 2012. "A comprehensive method for optimal power management and design of hybrid RES-based autonomous energy systems," Renewable and Sustainable Energy Reviews, Elsevier, vol. 16(3), pages 1577-1587.
    18. Rigter, Jasper & Vidican, Georgeta, 2010. "Cost and optimal feed-in tariff for small scale photovoltaic systems in China," Energy Policy, Elsevier, vol. 38(11), pages 6989-7000, November.
    19. 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.
    20. Drechsler, Martin & Meyerhoff, Jürgen & Ohl, Cornelia, 2012. "The effect of feed-in tariffs on the production cost and the landscape externalities of wind power generation in West Saxony, Germany," Energy Policy, Elsevier, vol. 48(C), pages 730-736.
    21. Fais, Birgit & Blesl, Markus & Fahl, Ulrich & Voß, Alfred, 2014. "Comparing different support schemes for renewable electricity in the scope of an energy systems analysis," Applied Energy, Elsevier, vol. 131(C), pages 479-489.
    22. Schmidt, J. & Lehecka, G. & Gass, V. & Schmid, E., 2013. "Where the wind blows: Assessing the effect of fixed and premium based feed-in tariffs on the spatial diversification of wind turbines," Energy Economics, Elsevier, vol. 40(C), pages 269-276.
    23. Zheng, C.Y. & Wu, J.Y. & Zhai, X.Q. & Wang, R.Z., 2016. "Impacts of feed-in tariff policies on design and performance of CCHP system in different climate zones," Applied Energy, Elsevier, vol. 175(C), pages 168-179.
    24. Deng, S. & Wang, R.Z. & Dai, Y.J., 2014. "How to evaluate performance of net zero energy building – A literature research," Energy, Elsevier, vol. 71(C), pages 1-16.
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