IDEAS home Printed from https://ideas.repec.org/a/eee/appene/v352y2023ics0306261923012412.html
   My bibliography  Save this article

A framework for the assessment of optimal and cost-effective energy decarbonisation pathways of a UK-based healthcare facility11The short version of the paper was presented at ICAE2022, Bochum, Germany, Aug 8–11, 2022. This paper is a substantial extension of the short version of the conference paper

Author

Listed:
  • Morales Sandoval, Daniel A.
  • Saikia, Pranaynil
  • De la Cruz-Loredo, Ivan
  • Zhou, Yue
  • Ugalde-Loo, Carlos E.
  • Bastida, Héctor
  • Abeysekera, Muditha

Abstract

In light of the global energy and climate crises, integration of low-carbon technologies into energy systems is being considered to mitigate the high energy costs and carbon footprint. The wide range of available capacities, efficiencies, and investment costs of these technologies and their different possible operating schedules can unlock several pathways towards decarbonisation. This paper presents an optimisation framework for a public healthcare facility to determine the optimal operation schedule of the site's energy system. A detailed techno-economic analysis of low-carbon power generation, conversion, and energy storage technologies that can be incorporated into the system based on real historical data was carried out for different scenarios. The results reveal that a heat pump with a capacity of 1800 kW can replace gas boilers on-site to meet the heat demand while recovering the investment in 5 years and providing an operating and carbon cost saving of 22.47% compared to the base case. The analysis shows that a more electrified mode of operation is favoured during high gas prices, thus making electrical energy storage more attractive than thermal energy storage. While handling real data, the optimisation algorithm was sensitised to discriminate conventional energy supplies from clean energy sources by considering their carbon impact so that it minimises energy bills in a smart and eco-friendly way. The optimisation algorithm and the subsequent techno-economic analysis provide a comprehensive framework to decision-makers for facilitating energy investment decisions. The framework can be used based on the short and long term goals of the energy system, visualising the evolution of financial benefits over equipment lifetime, and understanding the environmental impacts of integrating renewable energy.

Suggested Citation

  • Morales Sandoval, Daniel A. & Saikia, Pranaynil & De la Cruz-Loredo, Ivan & Zhou, Yue & Ugalde-Loo, Carlos E. & Bastida, Héctor & Abeysekera, Muditha, 2023. "A framework for the assessment of optimal and cost-effective energy decarbonisation pathways of a UK-based healthcare facility11The short version of the paper was presented at ICAE2022, Bochum, German," Applied Energy, Elsevier, vol. 352(C).
  • Handle: RePEc:eee:appene:v:352:y:2023:i:c:s0306261923012412
    DOI: 10.1016/j.apenergy.2023.121877
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0306261923012412
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.apenergy.2023.121877?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. Barthwal, Mohit & Dhar, Atul & Powar, Satvasheel, 2021. "The techno-economic and environmental analysis of genetic algorithm (GA) optimized cold thermal energy storage (CTES) for air-conditioning applications," Applied Energy, Elsevier, vol. 283(C).
    2. Wang, Jiangjiang & Huo, Shuojie & Yan, Rujing & Cui, Zhiheng, 2022. "Leveraging heat accumulation of district heating network to improve performances of integrated energy system under source-load uncertainties," Energy, Elsevier, vol. 252(C).
    3. Wang, Jiangjiang & Zhai, Zhiqiang (John) & Jing, Youyin & Zhang, Chunfa, 2010. "Particle swarm optimization for redundant building cooling heating and power system," Applied Energy, Elsevier, vol. 87(12), pages 3668-3679, December.
    4. Frida Berglund & Salman Zaferanlouei & Magnus Korpås & Kjetil Uhlen, 2019. "Optimal Operation of Battery Storage for a Subscribed Capacity-Based Power Tariff Prosumer—A Norwegian Case Study," Energies, MDPI, vol. 12(23), pages 1-24, November.
    5. Wang, Y. & Wang, J. & He, W., 2022. "Development of efficient, flexible and affordable heat pumps for supporting heat and power decarbonisation in the UK and beyond: Review and perspectives," Renewable and Sustainable Energy Reviews, Elsevier, vol. 154(C).
    6. Nordgård-Hansen, Ellen & Kishor, Nand & Midttømme, Kirsti & Risinggård, Vetle Kjær & Kocbach, Jan, 2022. "Case study on optimal design and operation of detached house energy system: Solar, battery, and ground source heat pump," Applied Energy, Elsevier, vol. 308(C).
    7. Satriya Sulistiyo Aji & Young Sang Kim & Kook Young Ahn & Young Duk Lee, 2018. "Life-Cycle Cost Minimization of Gas Turbine Power Cycles for Distributed Power Generation Using Sequential Quadratic Programming Method," Energies, MDPI, vol. 11(12), pages 1-21, December.
    Full references (including those not matched with items on IDEAS)

    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. He, Zhaoyu & Guo, Weimin & Zhang, Peng, 2022. "Performance prediction, optimal design and operational control of thermal energy storage using artificial intelligence methods," Renewable and Sustainable Energy Reviews, Elsevier, vol. 156(C).
    2. Behzadi, Amirmohammad & Holmberg, Sture & Duwig, Christophe & Haghighat, Fariborz & Ooka, Ryozo & Sadrizadeh, Sasan, 2022. "Smart design and control of thermal energy storage in low-temperature heating and high-temperature cooling systems: A comprehensive review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 166(C).
    3. Yang, Weijia & Huang, Yuping & Zhao, Daiqing, 2023. "A coupled hydraulic–thermal dynamic model for the steam network in a heat–electricity integrated energy system," Energy, Elsevier, vol. 263(PC).
    4. Piacentino, Antonio & Barbaro, Chiara & Cardona, Fabio & Gallea, Roberto & Cardona, Ennio, 2013. "A comprehensive tool for efficient design and operation of polygeneration-based energy μgrids serving a cluster of buildings. Part I: Description of the method," Applied Energy, Elsevier, vol. 111(C), pages 1204-1221.
    5. Jie, Pengfei & Yan, Fuchun & Li, Jing & Zhang, Yumei & Wen, Zhimei, 2019. "Optimizing the insulation thickness of walls of existing buildings with CHP-based district heating systems," Energy, Elsevier, vol. 189(C).
    6. Ren, Fukang & Wei, Ziqing & Zhai, Xiaoqiang, 2021. "Multi-objective optimization and evaluation of hybrid CCHP systems for different building types," Energy, Elsevier, vol. 215(PA).
    7. Bostan, Alireza & Nazar, Mehrdad Setayesh & Shafie-khah, Miadreza & Catalão, João P.S., 2020. "Optimal scheduling of distribution systems considering multiple downward energy hubs and demand response programs," Energy, Elsevier, vol. 190(C).
    8. Guozheng Li & Rui Wang & Tao Zhang & Mengjun Ming, 2018. "Multi-Objective Optimal Design of Renewable Energy Integrated CCHP System Using PICEA-g," Energies, MDPI, vol. 11(4), pages 1-26, March.
    9. Mirzazade Akbarpoor, Ali & Haghighi Poshtiri, Amin & Biglari, Faraz, 2021. "Performance analysis of domed roof integrated with earth-to-air heat exchanger system to meet thermal comfort conditions in buildings," Renewable Energy, Elsevier, vol. 168(C), pages 1265-1293.
    10. Zhao, Yaohua & Liu, Zichu & Quan, Zhenhua & Jing, Heran & Yang, Mingguang, 2022. "Experimental investigation and multi-objective optimization of ice thermal storage device with multichannel flat tube," Renewable Energy, Elsevier, vol. 195(C), pages 28-46.
    11. Pablo Jimenez Zabalaga & Evelyn Cardozo & Luis A. Choque Campero & Joseph Adhemar Araoz Ramos, 2020. "Performance Analysis of a Stirling Engine Hybrid Power System," Energies, MDPI, vol. 13(4), pages 1-38, February.
    12. Wang, Jiangjiang & Sui, Jun & Jin, Hongguang, 2015. "An improved operation strategy of combined cooling heating and power system following electrical load," Energy, Elsevier, vol. 85(C), pages 654-666.
    13. Barber, Kyle A. & Krarti, Moncef, 2022. "A review of optimization based tools for design and control of building energy systems," Renewable and Sustainable Energy Reviews, Elsevier, vol. 160(C).
    14. Sara Ghaem Sigarchian & Anders Malmquist & Viktoria Martin, 2018. "Design Optimization of a Small-Scale Polygeneration Energy System in Different Climate Zones in Iran," Energies, MDPI, vol. 11(5), pages 1-19, May.
    15. Urbano, Eva M. & Martinez-Viol, Victor & Kampouropoulos, Konstantinos & Romeral, Luis, 2022. "Risk assessment of energy investment in the industrial framework – Uncertainty and Sensitivity Analysis for energy design and operation optimisation," Energy, Elsevier, vol. 239(PA).
    16. Xiong, Chengyan & Meng, Qinglong & Wei, Ying'an & Luo, Huilong & Lei, Yu & Liu, Jiao & Yan, Xiuying, 2023. "A demand response method for an active thermal energy storage air-conditioning system using improved transactive control: On-site experiments," Applied Energy, Elsevier, vol. 339(C).
    17. Hector Beltran & Pablo Ayuso & Emilio Pérez, 2020. "Lifetime Expectancy of Li-Ion Batteries used for Residential Solar Storage," Energies, MDPI, vol. 13(3), pages 1-18, January.
    18. Prada, A. & Gasparella, A. & Baggio, P., 2018. "On the performance of meta-models in building design optimization," Applied Energy, Elsevier, vol. 225(C), pages 814-826.
    19. Yun, Kyung Tae & Cho, Heejin & Luck, Rogelio & Mago, Pedro J., 2013. "Modeling of reciprocating internal combustion engines for power generation and heat recovery," Applied Energy, Elsevier, vol. 102(C), pages 327-335.
    20. Han, Jie & Ouyang, Leixin & Xu, Yuzhen & Zeng, Rong & Kang, Shushuo & Zhang, Guoqiang, 2016. "Current status of distributed energy system in China," Renewable and Sustainable Energy Reviews, Elsevier, vol. 55(C), pages 288-297.

    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:352:y:2023:i:c:s0306261923012412. 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.