IDEAS home Printed from https://ideas.repec.org/a/gam/jeners/v15y2022i9p3088-d800328.html
   My bibliography  Save this article

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
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1996-1073/15/9/3088/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/1996-1073/15/9/3088/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. 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.
    2. 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.
    3. 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.
    4. 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.
    5. 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.
    6. 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.
    7. Rastegar, Mohammad & Fotuhi-Firuzabad, Mahmud & Aminifar, Farrokh, 2012. "Load commitment in a smart home," Applied Energy, Elsevier, vol. 96(C), pages 45-54.
    8. 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.
    9. 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.
    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. 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.
    2. Bostan, Alireza & Nazar, Mehrdad Setayesh & Shafie-khah, Miadreza & Catalão, João P.S., 2020. "Optimal scheduling of distribution systems considering multiple downward energy hubs and demand response programs," Energy, Elsevier, vol. 190(C).
    3. 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).
    4. Amiri, S. & Honarvar, M. & sadegheih, A., 2018. "Providing an integrated Model for Planning and Scheduling Energy Hubs and preventive maintenance," Energy, Elsevier, vol. 163(C), pages 1093-1114.
    5. Ahmadisedigh, Hossein & Gosselin, Louis, 2022. "Combined heating and cooling networks with part-load efficiency curves: Optimization based on energy hub concept," Applied Energy, Elsevier, vol. 307(C).
    6. 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.
    7. Lasemi, Mohammad Ali & Arabkoohsar, Ahmad & Hajizadeh, Amin & Mohammadi-ivatloo, Behnam, 2022. "A comprehensive review on optimization challenges of smart energy hubs under uncertainty factors," Renewable and Sustainable Energy Reviews, Elsevier, vol. 160(C).
    8. Kiani-Moghaddam, Mohammad & Soltani, Mohsen N. & Kalogirou, Soteris A. & Mahian, Omid & Arabkoohsar, Ahmad, 2023. "A review of neighborhood level multi-carrier energy hubs—uncertainty and problem-solving process," Energy, Elsevier, vol. 281(C).
    9. 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.
    10. Majidi, Majid & Nojavan, Sayyad & Zare, Kazem, 2017. "A cost-emission framework for hub energy system under demand response program," Energy, Elsevier, vol. 134(C), pages 157-166.
    11. Liu, Qian & Li, Wanjun & Zhao, Zhen & Jian, Gan, 2024. "Optimal operation of coordinated multi-carrier energy hubs for integrated electricity and gas networks," Energy, Elsevier, vol. 288(C).
    12. Beigvand, Soheil Derafshi & Abdi, Hamdi & La Scala, Massimo, 2017. "A general model for energy hub economic dispatch," Applied Energy, Elsevier, vol. 190(C), pages 1090-1111.
    13. Xu, Yijun & Zhang, Xuan & Li, Ji, 2024. "Multiple energy planning in the energy hub considering renewable sources, electric vehicles and management in the daily electricity market with wind multi-objective optimization algorithm," Energy, Elsevier, vol. 309(C).
    14. Ghanbari, Ali & Karimi, Hamid & Jadid, Shahram, 2020. "Optimal planning and operation of multi-carrier networked microgrids considering multi-energy hubs in distribution networks," Energy, Elsevier, vol. 204(C).
    15. 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.
    16. O’Dwyer, Edward & Pan, Indranil & Acha, Salvador & Shah, Nilay, 2019. "Smart energy systems for sustainable smart cities: Current developments, trends and future directions," Applied Energy, Elsevier, vol. 237(C), pages 581-597.
    17. Shan Deng & Qinghua Wu & Zhaoxia Jing & Lilan Wu & Feng Wei & Xiaoxin Zhou, 2017. "Optimal Capacity Configuration for Energy Hubs Considering Part-Load Characteristics of Generation Units," Energies, MDPI, vol. 10(12), pages 1-19, November.
    18. Zhang, Ning & Sun, Qiuye & Yang, Lingxiao, 2021. "A two-stage multi-objective optimal scheduling in the integrated energy system with We-Energy modeling," Energy, Elsevier, vol. 215(PB).
    19. 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.
    20. 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.

    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:15:y:2022:i:9:p:3088-:d:800328. 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.