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A Probabilistic Model for Minimization of Solar Energy Operation Costs as Well as CO 2 Emissions in a Multi-Carrier Microgrid (MCMG)

Author

Listed:
  • Hassan Ranjbarzadeh

    (School of Engineering, Deakin University, Geelong, VIC 3216, Australia)

  • Seyed Masoud Moghaddas Tafreshi

    (Electrical Engineering Department, University of Guilan, Rasht P.O. Box 1841, Iran)

  • Mohd Hasan Ali

    (Electrical and Computer Engineering Department, University of Memphis, Memphis, TN 38152, USA)

  • Abbas Z. Kouzani

    (School of Engineering, Deakin University, Geelong, VIC 3216, Australia)

  • Suiyang Khoo

    (School of Engineering, Deakin University, Geelong, VIC 3216, Australia)

Abstract

This paper proposes a probabilistic model with the aim to reduce the solar energy operation cost and CO 2 emissions of a multi-carrier microgrid. The MCMG in this study includes various elements such as combined heat and power (CHP), electrical heat pump (EHP), absorption chiller, solar panels, and thermal and electrical storages. A MILP model is proposed to manage the commitment of energy producers, energy storage equipment, the amount of selling/buying of energy with the upstream network, and the energy consumption of the responsible electrical loads for the day-ahead optimal operation of this microgrid. The proposed operation model is formulated as a multi-objective optimization model based on two environmental and economic objectives, using a weighted sum technique and a fuzzy satisfying approach. In this paper, the 2 m + 1-point estimate strategy has been used to model the uncertainties caused by the output power of solar panels and the upstream power supply price. In order to evaluate the performance of the proposed model, and also for minimizing cost and CO 2 emissions, the simulation was conducted on two typical cold and hot days. Numerical results show the proposed model’s performance and the effect of electrifying the heating and cooling of the microgrid through the EHP unit on greenhouse gas emissions in the scenarios considered.

Suggested Citation

  • Hassan Ranjbarzadeh & Seyed Masoud Moghaddas Tafreshi & Mohd Hasan Ali & Abbas Z. Kouzani & Suiyang Khoo, 2022. "A Probabilistic Model for Minimization of Solar Energy Operation Costs as Well as CO 2 Emissions in a Multi-Carrier Microgrid (MCMG)," Energies, MDPI, vol. 15(9), pages 1-24, April.
  • Handle: RePEc:gam:jeners:v:15:y:2022:i:9:p:3088-:d:800328
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    References listed on IDEAS

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    1. Mudhafar Al-Saadi & Maher Al-Greer & Michael Short, 2021. "Strategies for Controlling Microgrid Networks with Energy Storage Systems: A Review," Energies, MDPI, vol. 14(21), pages 1-45, November.
    2. Moghaddas Tafreshi, Seyed Masoud & Ranjbarzadeh, Hassan & Jafari, Mehdi & Khayyam, Hamid, 2016. "A probabilistic unit commitment model for optimal operation of plug-in electric vehicles in microgrid," Renewable and Sustainable Energy Reviews, Elsevier, vol. 66(C), pages 934-947.
    3. Najafi, Arsalan & Falaghi, Hamid & Contreras, Javier & Ramezani, Maryam, 2016. "Medium-term energy hub management subject to electricity price and wind uncertainty," Applied Energy, Elsevier, vol. 168(C), pages 418-433.
    4. Orehounig, Kristina & Evins, Ralph & Dorer, Viktor, 2015. "Integration of decentralized energy systems in neighbourhoods using the energy hub approach," Applied Energy, Elsevier, vol. 154(C), pages 277-289.
    5. Rastegar, Mohammad & Fotuhi-Firuzabad, Mahmud & Aminifar, Farrokh, 2012. "Load commitment in a smart home," Applied Energy, Elsevier, vol. 96(C), pages 45-54.
    6. Kamyab, Farhad & Bahrami, Shahab, 2016. "Efficient operation of energy hubs in time-of-use and dynamic pricing electricity markets," Energy, Elsevier, vol. 106(C), pages 343-355.
    7. 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.
    8. Khayyam, Hamid & Abawajy, Jemal & Javadi, Bahman & Goscinski, Andrzej & Stojcevski, Alex & Bab-Hadiashar, Alireza, 2013. "Intelligent battery energy management and control for vehicle-to-grid via cloud computing network," Applied Energy, Elsevier, vol. 111(C), pages 971-981.
    9. Moghaddam, Iman Gerami & Saniei, Mohsen & Mashhour, Elaheh, 2016. "A comprehensive model for self-scheduling an energy hub to supply cooling, heating and electrical demands of a building," Energy, Elsevier, vol. 94(C), pages 157-170.
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