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Optimal Design of a Multi-Carrier Microgrid (MCMG) Considering Net Zero Emission

Author

Listed:
  • Vahid Amir

    (Department of Electrical Engineering, Faculty of Electrical Engineering, Science and Research Branch, Islamic Azad University, Tehran 14778-93855, Iran)

  • Shahram Jadid

    (Department of Electrical Engineering, Faculty of Electrical Engineering, Iran University of Science and Technology, Tehran 16846-13114, Iran)

  • Mehdi Ehsan

    (Department of Electrical Engineering, Faculty of Electrical Engineering, Sharif University of Science and Technology, Tehran 11365-11155, Iran)

Abstract

In this paper, a two-stage optimum planning and design method for a multi-carrier microgrid (MCMG) is presented in the targeted operation period considering energy purchasing and the component’s maintenance costs. An MCMG is most likely owned by a community or small group of public and private sectors comprising loads and distributed energy resources (DERs) with the ability of self-supply to regulate the flows of various energies to local consumers. The operation cost is undoubtedly reduced by selecting the proper components. In the proposed model, the investment and operation and maintenance costs of MCMG are simultaneously carried out in order to choose the right component and its size in the given period. Moreover, in this innovative model, net zero emission (NZE) is regarded as an environmental constraint. The genetic algorithm of MATLAB and the mixed-integer nonlinear programming (MINLP) technique of GAMS (general algebraic modeling system) software are used to solve the optimization problem. Illustrative examples show the efficiency of the proposed model.

Suggested Citation

  • Vahid Amir & Shahram Jadid & Mehdi Ehsan, 2017. "Optimal Design of a Multi-Carrier Microgrid (MCMG) Considering Net Zero Emission," Energies, MDPI, vol. 10(12), pages 1-22, December.
    • Handle: RePEc:gam:jeners:v:10:y:2017:i:12:p:2109-:d:122666
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    References listed on IDEAS

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    3. Swaminathan Ganesan & Sanjeevikumar Padmanaban & Ramesh Varadarajan & Umashankar Subramaniam & Lucian Mihet-Popa, 2017. "Study and Analysis of an Intelligent Microgrid Energy Management Solution with Distributed Energy Sources," Energies, MDPI, vol. 10(9), pages 1-21, September.
    4. Koeppel, Gaudenz & Andersson, Göran, 2009. "Reliability modeling of multi-carrier energy systems," Energy, Elsevier, vol. 34(3), pages 235-244.
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    Cited by:

    1. 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).
    2. Lorestani, Alireza & Gharehpetian, G.B. & Nazari, Mohammad Hassan, 2019. "Optimal sizing and techno-economic analysis of energy- and cost-efficient standalone multi-carrier microgrid," Energy, Elsevier, vol. 178(C), pages 751-764.
    3. Garmabdari, R. & Moghimi, M. & Yang, F. & Lu, J., 2020. "Multi-objective optimisation and planning of grid-connected cogeneration systems in presence of grid power fluctuations and energy storage dynamics," Energy, Elsevier, vol. 212(C).
    4. Vu Ba Hau & Munir Husein & Il-Yop Chung & Dong-Jun Won & William Torre & Truong Nguyen, 2018. "Analyzing the Impact of Renewable Energy Incentives and Parameter Uncertainties on Financial Feasibility of a Campus Microgrid," Energies, MDPI, vol. 11(9), pages 1-24, September.
    5. Soheil Mohseni & Alan C. Brent & Daniel Burmester, 2021. "Off-Grid Multi-Carrier Microgrid Design Optimisation: The Case of Rakiura–Stewart Island, Aotearoa–New Zealand," Energies, MDPI, vol. 14(20), pages 1-28, October.

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