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Business cases for isolated and grid connected microgrids: Methodology and applications

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  • Quashie, Mike
  • Bouffard, François
  • Joós, Géza

Abstract

Microgrids are receiving increasing attention from power systems planners as a means to integrate distributed energy resources (DER) including renewable energy resources into the grid, and as a means of balancing the variability of renewable resources and loads with flexible generation. A key to justifying microgrids is establishing their business case. This helps to set the structure and configuration of the microgrid, including defining the DER required to feed part or all of the loads and the level of control required from the microgrid controller. This paper proposes a systematic approach and methodology for formulating and quantifying a microgrid business case. The framework adapts the use case approach to the microgrid context. It defines stakeholders, benefits and beneficiaries and determines the dependency of the business case on microgrid technologies. A method to quantify and allocate benefits is proposed. Applications to practical microgrids are discussed, including remote communities, remote mining sites and grid connected critical distribution grids.

Suggested Citation

  • Quashie, Mike & Bouffard, François & Joós, Géza, 2017. "Business cases for isolated and grid connected microgrids: Methodology and applications," Applied Energy, Elsevier, vol. 205(C), pages 105-115.
    • Handle: RePEc:eee:appene:v:205:y:2017:i:c:p:105-115
    DOI: 10.1016/j.apenergy.2017.07.112
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    References listed on IDEAS

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    1. Stadler, Michael & Cardoso, Gonçalo & Mashayekh, Salman & Forget, Thibault & DeForest, Nicholas & Agarwal, Ankit & Schönbein, Anna, 2016. "Value streams in microgrids: A literature review," Applied Energy, Elsevier, vol. 162(C), pages 980-989.
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    5. Korkas, Christos D. & Baldi, Simone & Michailidis, Iakovos & Kosmatopoulos, Elias B., 2016. "Occupancy-based demand response and thermal comfort optimization in microgrids with renewable energy sources and energy storage," Applied Energy, Elsevier, vol. 163(C), pages 93-104.
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    Cited by:

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    2. Azimian, Mahdi & Amir, Vahid & Javadi, Saeid, 2020. "Economic and Environmental Policy Analysis for Emission-Neutral Multi-Carrier Microgrid Deployment," Applied Energy, Elsevier, vol. 277(C).
    3. Obara, Shin’ya & Fujimoto, Shoki & Sato, Katsuaki & Utsugi, Yuta, 2021. "Planning renewable energy introduction for a microgrid without battery storage," Energy, Elsevier, vol. 215(PB).
    4. Miguel Carpintero-Rentería & David Santos-Martín & Josep M. Guerrero, 2019. "Microgrids Literature Review through a Layers Structure," Energies, MDPI, vol. 12(22), pages 1-22, November.
    5. Wang, Richard & Hsu, Shu-Chien & Zheng, Saina & Chen, Jieh-Haur & Li, Xuran Ivan, 2020. "Renewable energy microgrids: Economic evaluation and decision making for government policies to contribute to affordable and clean energy," Applied Energy, Elsevier, vol. 274(C).
    6. Amir, Vahid & Azimian, Mahdi, 2020. "Dynamic Multi-Carrier Microgrid Deployment Under Uncertainty," Applied Energy, Elsevier, vol. 260(C).
    7. Kinnon, Michael Mac & Razeghi, Ghazal & Samuelsen, Scott, 2021. "The role of fuel cells in port microgrids to support sustainable goods movement," Renewable and Sustainable Energy Reviews, Elsevier, vol. 147(C).
    8. Ping Liu & Zexiang Cai & Peng Xie & Xiaohua Li & Yongjun Zhang, 2019. "A Computationally Efficient Optimization Method for Battery Storage in Grid-connected Microgrids Based on a Power Exchanging Process," Energies, MDPI, vol. 12(8), pages 1-19, April.
    9. Huo, Yuchong & Bouffard, François & Joós, Géza, 2021. "Decision tree-based optimization for flexibility management for sustainable energy microgrids," Applied Energy, Elsevier, vol. 290(C).
    10. Mehdizadeh, Ali & Taghizadegan, Navid & Salehi, Javad, 2018. "Risk-based energy management of renewable-based microgrid using information gap decision theory in the presence of peak load management," Applied Energy, Elsevier, vol. 211(C), pages 617-630.
    11. Ricardo Echeverri Mart nez & Eduardo Caicedo Bravo & Wilfredo Alfonso Morales & Juan David Garcia-Racines, 2020. "A Bi-level Multi-objective Optimization Model for the Planning, Design and Operation of Smart Grid Projects. Case Study: An Islanded Microgrid," International Journal of Energy Economics and Policy, Econjournals, vol. 10(4), pages 325-341.
    12. Huo, Yuchong & Bouffard, François & Joós, Géza, 2022. "Integrating learning and explicit model predictive control for unit commitment in microgrids," Applied Energy, Elsevier, vol. 306(PA).
    13. Razeghi, Ghazal & Gu, Fei & Neal, Russell & Samuelsen, Scott, 2018. "A generic microgrid controller: Concept, testing, and insights," Applied Energy, Elsevier, vol. 229(C), pages 660-671.

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