IDEAS home Printed from https://ideas.repec.org/a/gam/jeners/v14y2021i21p7084-d668428.html
   My bibliography  Save this article

Optimising Electrical Power Supply Sustainability Using a Grid-Connected Hybrid Renewable Energy System—An NHS Hospital Case Study

Author

Listed:
  • Fadi Kahwash

    (School of Engineering and the Built Environment, Edinburgh Napier University, Edinburgh EH10 5DT, UK
    These authors contributed equally to this work.)

  • Basel Barakat

    (School of Computer Science, University of Sunderland, St Peter Campus, St Peters Way, Sunderland SR6 0DD, UK
    These authors contributed equally to this work.)

  • Ahmad Taha

    (James Watt School of Engineering, University of Glasgow, Glasgow G12 8QQ, UK
    These authors contributed equally to this work.)

  • Qammer H. Abbasi

    (James Watt School of Engineering, University of Glasgow, Glasgow G12 8QQ, UK)

  • Muhammad Ali Imran

    (James Watt School of Engineering, University of Glasgow, Glasgow G12 8QQ, UK)

Abstract

This study focuses on improving the sustainability of electrical supply in the healthcare system in the UK, to contribute to current efforts made towards the 2050 net-zero carbon target. As a case study, we propose a grid-connected hybrid renewable energy system (HRES) for a hospital in the south-east of England. Electrical consumption data were gathered from five wards in the hospital for a period of one year. PV-battery-grid system architecture was selected to ensure practical execution through the installation of PV arrays on the roof of the facility. Selection of the optimal system was conducted through a novel methodology combining multi-objective optimisation and data forecasting. The optimisation was conducted using a genetic algorithm with two objectives (1) minimisation of the levelised cost of energy and (2) CO 2 emissions. Advanced data forecasting was used to forecast grid emissions and other cost parameters at two year intervals (2023 and 2025). Several optimisation simulations were carried out using the actual and forecasted parameters to improve decision making. The results show that incorporating forecasted parameters into the optimisation allows to identify the subset of optimal solutions that will become sub-optimal in the future and, therefore, should be avoided. Finally, a framework for choosing the most suitable subset of optimal solutions was presented.

Suggested Citation

  • Fadi Kahwash & Basel Barakat & Ahmad Taha & Qammer H. Abbasi & Muhammad Ali Imran, 2021. "Optimising Electrical Power Supply Sustainability Using a Grid-Connected Hybrid Renewable Energy System—An NHS Hospital Case Study," Energies, MDPI, vol. 14(21), pages 1-23, October.
    • Handle: RePEc:gam:jeners:v:14:y:2021:i:21:p:7084-:d:668428
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1996-1073/14/21/7084/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/1996-1073/14/21/7084/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Wang, Rui & Xiong, Jian & He, Min-fan & Gao, Liang & Wang, Ling, 2020. "Multi-objective optimal design of hybrid renewable energy system under multiple scenarios," Renewable Energy, Elsevier, vol. 151(C), pages 226-237.
    2. Sean J. Taylor & Benjamin Letham, 2018. "Forecasting at Scale," The American Statistician, Taylor & Francis Journals, vol. 72(1), pages 37-45, January.
    3. Gu, Chenghong & Yan, Xiaohe & Yan, Zhang & Li, Furong, 2017. "Dynamic pricing for responsive demand to increase distribution network efficiency," Applied Energy, Elsevier, vol. 205(C), pages 236-243.
    4. Bilir, Levent & Yildirim, Nurdan, 2018. "Modeling and performance analysis of a hybrid system for a residential application," Energy, Elsevier, vol. 163(C), pages 555-569.
    5. Basel Barakat & Ahmad Taha & Ryan Samson & Aiste Steponenaite & Shuja Ansari & Patrick M. Langdon & Ian J. Wassell & Qammer H. Abbasi & Muhammad Ali Imran & Simeon Keates, 2021. "6G Opportunities Arising from Internet of Things Use Cases: A Review Paper," Future Internet, MDPI, vol. 13(6), pages 1-29, June.
    6. Baruah, Abhinandan & Basu, Mousumi & Amuley, Deeshank, 2021. "Modeling of an autonomous hybrid renewable energy system for electrification of a township: A case study for Sikkim, India," Renewable and Sustainable Energy Reviews, Elsevier, vol. 135(C).
    7. Bajpai, Prabodh & Dash, Vaishalee, 2012. "Hybrid renewable energy systems for power generation in stand-alone applications: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 16(5), pages 2926-2939.
    8. Sinha, Sunanda & Chandel, S.S., 2014. "Review of software tools for hybrid renewable energy systems," Renewable and Sustainable Energy Reviews, Elsevier, vol. 32(C), pages 192-205.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Maria Psillaki & Nikolaos Apostolopoulos & Ilias Makris & Panagiotis Liargovas & Sotiris Apostolopoulos & Panos Dimitrakopoulos & George Sklias, 2023. "Hospitals’ Energy Efficiency in the Perspective of Saving Resources and Providing Quality Services through Technological Options: A Systematic Literature Review," Energies, MDPI, vol. 16(2), pages 1-21, January.
    2. Chro Hama Radha, 2023. "Retrofitting for Improving Indoor Air Quality and Energy Efficiency in the Hospital Building," Sustainability, MDPI, vol. 15(4), pages 1-20, February.
    3. Alfonso Angel Medina-Santana & Leopoldo Eduardo Cárdenas-Barrón, 2022. "Optimal Design of Hybrid Renewable Energy Systems Considering Weather Forecasting Using Recurrent Neural Networks," Energies, MDPI, vol. 15(23), pages 1-28, November.

    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. Al Busaidi, Ahmed Said & Kazem, Hussein A & Al-Badi, Abdullah H & Farooq Khan, Mohammad, 2016. "A review of optimum sizing of hybrid PV–Wind renewable energy systems in oman," Renewable and Sustainable Energy Reviews, Elsevier, vol. 53(C), pages 185-193.
    2. Hua, Jian & Shiu, Hong-Gwo, 2018. "Sustainable development of renewable energy on Wangan Island, Taiwan," Utilities Policy, Elsevier, vol. 55(C), pages 200-208.
    3. Nithya Saiprasad & Akhtar Kalam & Aladin Zayegh, 2019. "Triple Bottom Line Analysis and Optimum Sizing of Renewable Energy Using Improved Hybrid Optimization Employing the Genetic Algorithm: A Case Study from India," Energies, MDPI, vol. 12(3), pages 1-23, January.
    4. Diab, Fahd & Lan, Hai & Ali, Salwa, 2016. "Novel comparison study between the hybrid renewable energy systems on land and on ship," Renewable and Sustainable Energy Reviews, Elsevier, vol. 63(C), pages 452-463.
    5. Ackermann, Simon & Szabo, Andrei & Bamberger, Joachim & Steinke, Florian, 2022. "Design and optimization of performance guarantees for hybrid power plants," Energy, Elsevier, vol. 239(PA).
    6. Abhi Chatterjee & Daniel Burmester & Alan Brent & Ramesh Rayudu, 2019. "Research Insights and Knowledge Headways for Developing Remote, Off-Grid Microgrids in Developing Countries," Energies, MDPI, vol. 12(10), pages 1-19, May.
    7. Siddaiah, Rajanna & Saini, R.P., 2016. "A review on planning, configurations, modeling and optimization techniques of hybrid renewable energy systems for off grid applications," Renewable and Sustainable Energy Reviews, Elsevier, vol. 58(C), pages 376-396.
    8. Dufo-López, Rodolfo & Cristóbal-Monreal, Iván R. & Yusta, José M., 2016. "Optimisation of PV-wind-diesel-battery stand-alone systems to minimise cost and maximise human development index and job creation," Renewable Energy, Elsevier, vol. 94(C), pages 280-293.
    9. Dufo-López, Rodolfo & Cristóbal-Monreal, Iván R. & Yusta, José M., 2016. "Stochastic-heuristic methodology for the optimisation of components and control variables of PV-wind-diesel-battery stand-alone systems," Renewable Energy, Elsevier, vol. 99(C), pages 919-935.
    10. Cano, Antonio & Arévalo, Paul & Jurado, Francisco, 2022. "Evaluation of temporal resolution impact on power fluctuations and self-consumption for a hydrokinetic on grid system using supercapacitors," Renewable Energy, Elsevier, vol. 193(C), pages 843-856.
    11. Urban, Kristof L. & Scheller, Fabian & Bruckner, Thomas, 2021. "Suitability assessment of models in the industrial energy system design," Renewable and Sustainable Energy Reviews, Elsevier, vol. 137(C).
    12. Chauhan, Anurag & Saini, R.P., 2014. "A review on Integrated Renewable Energy System based power generation for stand-alone applications: Configurations, storage options, sizing methodologies and control," Renewable and Sustainable Energy Reviews, Elsevier, vol. 38(C), pages 99-120.
    13. Mahdavi, Meisam & Jurado, Francisco & Ramos, Ricardo Alan Verdú & Awaafo, Augustine, 2023. "Hybrid biomass, solar and wind electricity generation in rural areas of Fez-Meknes region in Morocco considering water consumption of animals and anaerobic digester," Applied Energy, Elsevier, vol. 343(C).
    14. Baruah, Abhinandan & Basu, Mousumi & Amuley, Deeshank, 2021. "Modeling of an autonomous hybrid renewable energy system for electrification of a township: A case study for Sikkim, India," Renewable and Sustainable Energy Reviews, Elsevier, vol. 135(C).
    15. Guo, Shaopeng & Liu, Qibin & Sun, Jie & Jin, Hongguang, 2018. "A review on the utilization of hybrid renewable energy," Renewable and Sustainable Energy Reviews, Elsevier, vol. 91(C), pages 1121-1147.
    16. Ullah, Zia & Elkadeem, M.R. & Kotb, Kotb M. & Taha, Ibrahim B.M. & Wang, Shaorong, 2021. "Multi-criteria decision-making model for optimal planning of on/off grid hybrid solar, wind, hydro, biomass clean electricity supply," Renewable Energy, Elsevier, vol. 179(C), pages 885-910.
    17. Goel, Sonali & Sharma, Renu, 2017. "Performance evaluation of stand alone, grid connected and hybrid renewable energy systems for rural application: A comparative review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 78(C), pages 1378-1389.
    18. Mehrjerdi, Hasan, 2020. "Modeling and optimization of an island water-energy nexus powered by a hybrid solar-wind renewable system," Energy, Elsevier, vol. 197(C).
    19. Hosseinalizadeh, Ramin & Shakouri G, Hamed & Amalnick, Mohsen Sadegh & Taghipour, Peyman, 2016. "Economic sizing of a hybrid (PV–WT–FC) renewable energy system (HRES) for stand-alone usages by an optimization-simulation model: Case study of Iran," Renewable and Sustainable Energy Reviews, Elsevier, vol. 54(C), pages 139-150.
    20. Mandelli, Stefano & Barbieri, Jacopo & Mereu, Riccardo & Colombo, Emanuela, 2016. "Off-grid systems for rural electrification in developing countries: Definitions, classification and a comprehensive literature review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 58(C), pages 1621-1646.

    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:gam:jeners:v:14:y:2021:i:21:p:7084-:d:668428. 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: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    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.