IDEAS home Printed from https://ideas.repec.org/a/abk/jajeba/ajebasp.2022.1.11.html
   My bibliography  Save this article

Optimization of Integrated Energy Systems in a Developing Economy using Technology

Author

Listed:
  • Joseph Uchenna Ezekwugo
  • Anthony Ibe
  • Alwell Nteegah

Abstract

This study uses a Low Emissions Analysis Program (LEAP) model to optimize the integrated energy systems of a developing economy (Nigeria) over 2020 - 2050 modelling period using Technology. It attempts to address the perennial energy dearth challenge, which plagues developing economies, while minimizing associated environmental impact GHG Emissions. The study models existing conditions within the developing economy as a baseline and evaluates a technology application scenario. The results obtained indicate that the application of technology has a significant impact with as much as 70.6% reduction in energy demand and 64.8% reduction in GHG emissions within the modelling period. The application of technology is therefore critical for sustainably meeting the future energy demands of the developing economy modelled (Nigeria). The study recommends that specifically applicable technology identified should be implemented in the developing country to address the energy dearth by enhancing supply while keeping the associated Green House Gas (GHG) emissions low.

Suggested Citation

  • Joseph Uchenna Ezekwugo & Anthony Ibe & Alwell Nteegah, 2022. "Optimization of Integrated Energy Systems in a Developing Economy using Technology," American Journal of Economics and Business Administration, Science Publications, vol. 14(1), pages 1-11, March.
  • Handle: RePEc:abk:jajeba:ajebasp.2022.1.11
    DOI: 10.3844/ajebasp.2022.1.11
    as

    Download full text from publisher

    File URL: https://thescipub.com/pdf/ajebasp.2022.1.11.pdf
    Download Restriction: no

    File URL: https://thescipub.com/abstract/ajebasp.2022.1.11
    Download Restriction: no

    File URL: https://libkey.io/10.3844/ajebasp.2022.1.11?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
    ---><---

    References listed on IDEAS

    as
    1. Maroufmashat, Azadeh & Elkamel, Ali & Fowler, Michael & Sattari, Sourena & Roshandel, Ramin & Hajimiragha, Amir & Walker, Sean & Entchev, Evgueniy, 2015. "Modeling and optimization of a network of energy hubs to improve economic and emission considerations," Energy, Elsevier, vol. 93(P2), pages 2546-2558.
    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. Mavromatidis, Georgios & Petkov, Ivalin, 2021. "MANGO: A novel optimization model for the long-term, multi-stage planning of decentralized multi-energy systems," Applied Energy, Elsevier, vol. 288(C).
    2. Mohamed, Mohamed A. & Tajik, Elham & Awwad, Emad Mahrous & El-Sherbeeny, Ahmed M. & Elmeligy, Mohammed A. & Ali, Ziad M., 2020. "A two-stage stochastic framework for effective management of multiple energy carriers," Energy, Elsevier, vol. 197(C).
    3. Perera, A.T.D. & Nik, Vahid M. & Mauree, Dasaraden & Scartezzini, Jean-Louis, 2017. "Electrical hubs: An effective way to integrate non-dispatchable renewable energy sources with minimum impact to the grid," Applied Energy, Elsevier, vol. 190(C), pages 232-248.
    4. Ren, Fukang & Wei, Ziqing & Zhai, Xiaoqiang, 2022. "A review on the integration and optimization of distributed energy systems," Renewable and Sustainable Energy Reviews, Elsevier, vol. 162(C).
    5. Zou, Juan & Yang, Xu & Liu, Zhongbing & Liu, Jiangyang & Zhang, Ling & Zheng, Jinhua, 2021. "Multiobjective bilevel optimization algorithm based on preference selection to solve energy hub system planning problems," Energy, Elsevier, vol. 232(C).
    6. Sajad Aliakbari Sani & Azadeh Maroufmashat & Frédéric Babonneau & Olivier Bahn & Erick Delage & Alain Haurie & Normand Mousseau & Kathleen Vaillancourt, 2022. "Energy Transition Pathways for Deep Decarbonization of the Greater Montreal Region: An Energy Optimization Framework," Energies, MDPI, vol. 15(10), pages 1-18, May.
    7. Patrick Sunday Onen & Geev Mokryani & Rana H. A. Zubo, 2022. "Planning of Multi-Vector Energy Systems with High Penetration of Renewable Energy Source: A Comprehensive Review," Energies, MDPI, vol. 15(15), pages 1-25, August.
    8. Gabrielli, Paolo & Gazzani, Matteo & Mazzotti, Marco, 2018. "Electrochemical conversion technologies for optimal design of decentralized multi-energy systems: Modeling framework and technology assessment," Applied Energy, Elsevier, vol. 221(C), pages 557-575.
    9. Wakui, Tetsuya & Hashiguchi, Moe & Sawada, Kento & Yokoyama, Ryohei, 2019. "Two-stage design optimization based on artificial immune system and mixed-integer linear programming for energy supply networks," Energy, Elsevier, vol. 170(C), pages 1228-1248.
    10. Mavromatidis, Georgios & Orehounig, Kristina & Carmeliet, Jan, 2018. "Design of distributed energy systems under uncertainty: A two-stage stochastic programming approach," Applied Energy, Elsevier, vol. 222(C), pages 932-950.
    11. Kim, SangYoun & Heo, SungKu & Nam, KiJeon & Woo, TaeYong & Yoo, ChangKyoo, 2023. "Flexible renewable energy planning based on multi-step forecasting of interregional electricity supply and demand: Graph-enhanced AI approach," Energy, Elsevier, vol. 282(C).
    12. Mohammadi, Mohammad & Noorollahi, Younes & Mohammadi-ivatloo, Behnam & Yousefi, Hossein, 2017. "Energy hub: From a model to a concept – A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 80(C), pages 1512-1527.
    13. Ahmadisedigh, Hossein & Gosselin, Louis, 2019. "Combined heating and cooling networks with waste heat recovery based on energy hub concept," Applied Energy, Elsevier, vol. 253(C), pages 1-1.
    14. Wakui, Tetsuya & Hashiguchi, Moe & Yokoyama, Ryohei, 2020. "A near-optimal solution method for coordinated operation planning problem of power- and heat-interchange networks using column generation-based decomposition," Energy, Elsevier, vol. 197(C).
    15. Reynolds, Jonathan & Ahmad, Muhammad Waseem & Rezgui, Yacine & Hippolyte, Jean-Laurent, 2019. "Operational supply and demand optimisation of a multi-vector district energy system using artificial neural networks and a genetic algorithm," Applied Energy, Elsevier, vol. 235(C), pages 699-713.
    16. Alberto Fichera & Mattia Frasca & Rosaria Volpe, 2020. "A cost-based approach for evaluating the impact of a network of distributed energy systems on the centralized energy supply," Energy & Environment, , vol. 31(1), pages 77-87, February.
    17. Liu, Tianhao & Tian, Jun & Zhu, Hongyu & Goh, Hui Hwang & Liu, Hui & Wu, Thomas & Zhang, Dongdong, 2023. "Key technologies and developments of multi-energy system: Three-layer framework, modelling and optimisation," Energy, Elsevier, vol. 277(C).
    18. Liu, Liuchen & Cui, Guomin & Chen, Jiaxing & Huang, Xiaohuang & Li, Di, 2022. "Two-stage superstructure model for optimization of distributed energy systems (DES) part I: Model development and verification," Energy, Elsevier, vol. 245(C).
    19. Mohammadi, Mohammad & Noorollahi, Younes & Mohammadi-ivatloo, Behnam & Hosseinzadeh, Mehdi & Yousefi, Hossein & Khorasani, Sasan Torabzadeh, 2018. "Optimal management of energy hubs and smart energy hubs – A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 89(C), pages 33-50.
    20. Lu, Xinhui & Liu, Zhaoxi & Ma, Li & Wang, Lingfeng & Zhou, Kaile & Yang, Shanlin, 2020. "A robust optimization approach for coordinated operation of multiple energy hubs," Energy, Elsevier, vol. 197(C).

    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:abk:jajeba:ajebasp.2022.1.11. 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: Jeffery Daniels (email available below). General contact details of provider: https://thescipub.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.