IDEAS home Printed from https://ideas.repec.org/a/eee/energy/v241y2022ics0360544221031339.html
   My bibliography  Save this article

Stochastic multi-objective optimal energy management of grid-connected unbalanced microgrids with renewable energy generation and plug-in electric vehicles

Author

Listed:
  • Zandrazavi, Seyed Farhad
  • Guzman, Cindy Paola
  • Pozos, Alejandra Tabares
  • Quiros-Tortos, Jairo
  • Franco, John Fredy

Abstract

Microgrids (MGs) contribute to the integration of renewable energy-based distributed generation (DG) units and electric vehicles (EVs) in a smart, secure, sustainable, and economic fashion. However, the unbalanced nature of MGs along with the probabilistic nature of renewable energy, electricity prices, and EV demand complicate the energy management process. To overcome that challenge, a stochastic multi-objective optimization model for grid-connected unbalanced MGs is proposed here to minimize the total operational cost and the voltage deviation. The epsilon-constraint method and fuzzy satisfying approach are used to solve the multi-objective optimization problem and to obtain compromise solutions. Uncertainties are considered by employing the roulette wheel mechanism for generating scenarios regarding renewable energy generations, EV charging demands, electric loads, and electricity prices. In addition, to avoid adopting infeasible and impractical solutions, a three-phase power flow is integrated in the proposed model. The proposed method is assessed in a modified IEEE 34-bus test system consisting of EVs, battery systems, wind turbine units, photovoltaic units, and diesel generators. The results show the effectiveness and benefits of the proposed model for handling uncertainties while minimizing both operational cost and voltage deviation index and providing more realistic and reliable solutions that can be applied by MG operators.

Suggested Citation

  • Zandrazavi, Seyed Farhad & Guzman, Cindy Paola & Pozos, Alejandra Tabares & Quiros-Tortos, Jairo & Franco, John Fredy, 2022. "Stochastic multi-objective optimal energy management of grid-connected unbalanced microgrids with renewable energy generation and plug-in electric vehicles," Energy, Elsevier, vol. 241(C).
  • Handle: RePEc:eee:energy:v:241:y:2022:i:c:s0360544221031339
    DOI: 10.1016/j.energy.2021.122884
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0360544221031339
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.energy.2021.122884?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
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. SoltaniNejad Farsangi, Alireza & Hadayeghparast, Shahrzad & Mehdinejad, Mehdi & Shayanfar, Heidarali, 2018. "A novel stochastic energy management of a microgrid with various types of distributed energy resources in presence of demand response programs," Energy, Elsevier, vol. 160(C), pages 257-274.
    2. Karimi, Hamid & Jadid, Shahram, 2020. "Optimal energy management for multi-microgrid considering demand response programs: A stochastic multi-objective framework," Energy, Elsevier, vol. 195(C).
    3. MansourLakouraj, Mohammad & Shahabi, Majid & Shafie-khah, Miadreza & Ghoreishi, Niloofar & Catalão, João P.S., 2020. "Optimal power management of dependent microgrid considering distribution market and unused power capacity," Energy, Elsevier, vol. 200(C).
    4. 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.
    5. Shams, Mohammad H. & Shahabi, Majid & Khodayar, Mohammad E., 2018. "Stochastic day-ahead scheduling of multiple energy Carrier microgrids with demand response," Energy, Elsevier, vol. 155(C), pages 326-338.
    6. Mazidi, Mohammadreza & Rezaei, Navid & Ghaderi, Abdolsalam, 2019. "Simultaneous power and heat scheduling of microgrids considering operational uncertainties: A new stochastic p-robust optimization approach," Energy, Elsevier, vol. 185(C), pages 239-253.
    7. Nikpour, Ahmad & Nateghi, Abolfazl & Shafie-khah, Miadreza & Catalão, João P.S., 2021. "Day-ahead optimal bidding of microgrids considering uncertainties of price and renewable energy resources," Energy, Elsevier, vol. 227(C).
    8. Zhang, M.Y. & Chen, J.J. & Yang, Z.J. & Peng, K. & Zhao, Y.L. & Zhang, X.H., 2021. "Stochastic day-ahead scheduling of irrigation system integrated agricultural microgrid with pumped storage and uncertain wind power," Energy, Elsevier, vol. 237(C).
    9. Gomes, I.L.R. & Melicio, R. & Mendes, V.M.F., 2021. "A novel microgrid support management system based on stochastic mixed-integer linear programming," Energy, Elsevier, vol. 223(C).
    10. Norberto Martinez & Alejandra Tabares & John F. Franco, 2021. "Generation of Alternative Battery Allocation Proposals in Distribution Systems by the Optimization of Different Economic Metrics within a Mathematical Model," Energies, MDPI, vol. 14(6), pages 1-17, March.
    11. Graça Gomes, J. & Xu, H.J. & Yang, Q. & Zhao, C.Y., 2021. "An optimization study on a typical renewable microgrid energy system with energy storage," Energy, Elsevier, vol. 234(C).
    12. Shaterabadi, Mohammad & Jirdehi, Mehdi Ahmadi, 2020. "Multi-objective stochastic programming energy management for integrated INVELOX turbines in microgrids: A new type of turbines," Renewable Energy, Elsevier, vol. 145(C), pages 2754-2769.
    13. Cindy Paola Guzman & Nataly Bañol Arias & John Fredy Franco & Marcos J. Rider & Rubén Romero, 2020. "Enhanced Coordination Strategy for an Aggregator of Distributed Energy Resources Participating in the Day-Ahead Reserve Market," Energies, MDPI, vol. 13(8), pages 1-22, April.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Zhang, Chao & Yin, Wanjun & Wen, Tao, 2024. "An advanced multi-objective collaborative scheduling strategy for large scale EV charging and discharging connected to the predictable wind power grid," Energy, Elsevier, vol. 287(C).
    2. Ahmad Alzahrani & Ghulam Hafeez & Sajjad Ali & Sadia Murawwat & Muhammad Iftikhar Khan & Khalid Rehman & Azher M. Abed, 2023. "Multi-Objective Energy Optimization with Load and Distributed Energy Source Scheduling in the Smart Power Grid," Sustainability, MDPI, vol. 15(13), pages 1-21, June.
    3. Chakraborty, Amit & Ray, Saheli, 2023. "Operational cost minimization of a microgrid with optimum battery energy storage system and plug-in-hybrid electric vehicle charging impact using slime mould algorithm," Energy, Elsevier, vol. 278(PA).
    4. Abdallah Abdellatif & Hamza Mubarak & Shameem Ahmad & Tofael Ahmed & G. M. Shafiullah & Ahmad Hammoudeh & Hamdan Abdellatef & M. M. Rahman & Hassan Muwafaq Gheni, 2022. "Forecasting Photovoltaic Power Generation with a Stacking Ensemble Model," Sustainability, MDPI, vol. 14(17), pages 1-21, September.
    5. Luiz Almeida & Ana Soares & Pedro Moura, 2023. "A Systematic Review of Optimization Approaches for the Integration of Electric Vehicles in Public Buildings," Energies, MDPI, vol. 16(13), pages 1-26, June.
    6. Elkholy, M.H. & Senjyu, Tomonobu & Metwally, Hamid & Farahat, M.A. & Irshad, Ahmad Shah & Hemeida, Ashraf M. & Lotfy, Mohammed Elsayed, 2024. "A resilient and intelligent multi-objective energy management for a hydrogen-battery hybrid energy storage system based on MFO technique," Renewable Energy, Elsevier, vol. 222(C).
    7. Zhang, Hui & Wang, Jiye & Zhao, Xiongwen & Yang, Jingqi & Bu sinnah, Zainab Ali, 2023. "Modeling a hydrogen-based sustainable multi-carrier energy system using a multi-objective optimization considering embedded joint chance constraints," Energy, Elsevier, vol. 278(C).
    8. Khaligh, Vahid & Ghezelbash, Azam & Mazidi, Mohammadreza & Liu, Jay & Ryu, Jun-Hyung, 2023. "P-robust energy management of a multi-energy microgrid enabled with energy conversions under various uncertainties," Energy, Elsevier, vol. 271(C).
    9. Simolin, Toni & Rauma, Kalle & Rautiainen, Antti & Järventausta, Pertti, 2022. "Increasing charging energy at highly congested commercial charging sites through charging control with load balancing functionality," Applied Energy, Elsevier, vol. 326(C).
    10. Tan, Bifei & Lin, Zhenjia & Zheng, Xiaodong & Xiao, Fu & Wu, Qiuwei & Yan, Jinyue, 2023. "Distributionally robust energy management for multi-microgrids with grid-interactive EVs considering the multi-period coupling effect of user behaviors," Applied Energy, Elsevier, vol. 350(C).
    11. Duan, Zhu & Liu, Hui & Li, Ye & Nikitas, Nikolaos, 2022. "Time-variant post-processing method for long-term numerical wind speed forecasts based on multi-region recurrent graph network," Energy, Elsevier, vol. 259(C).
    12. Marzi, Emanuela & Morini, Mirko & Saletti, Costanza & Vouros, Stavros & Zaccaria, Valentina & Kyprianidis, Konstantinos & Gambarotta, Agostino, 2023. "Power-to-Gas for energy system flexibility under uncertainty in demand, production and price," Energy, Elsevier, vol. 284(C).
    13. Lu, Xinhui & Li, Haobin & Zhou, Kaile & Yang, Shanlin, 2023. "Optimal load dispatch of energy hub considering uncertainties of renewable energy and demand response," Energy, Elsevier, vol. 262(PB).
    14. Olkkonen, Ville & Lind, Arne & Rosenberg, Eva & Kvalbein, Lisa, 2023. "Electrification of the agricultural sector in Norway in an effort to phase out fossil fuel consumption," Energy, Elsevier, vol. 276(C).

    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. Lin, Zhiyi & Song, Chunyue & Zhao, Jun & Yin, Huan, 2022. "Improved approximate dynamic programming for real-time economic dispatch of integrated microgrids," Energy, Elsevier, vol. 255(C).
    2. Nemanja Mišljenović & Matej Žnidarec & Goran Knežević & Damir Šljivac & Andreas Sumper, 2023. "A Review of Energy Management Systems and Organizational Structures of Prosumers," Energies, MDPI, vol. 16(7), pages 1-32, March.
    3. Seshu Kumar, R. & Phani Raghav, L. & Koteswara Raju, D. & Singh, Arvind R., 2021. "Impact of multiple demand side management programs on the optimal operation of grid-connected microgrids," Applied Energy, Elsevier, vol. 301(C).
    4. 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).
    5. Nikmehr, Nima, 2020. "Distributed robust operational optimization of networked microgrids embedded interconnected energy hubs," Energy, Elsevier, vol. 199(C).
    6. Mitul Ranjan Chakraborty & Subhojit Dawn & Pradip Kumar Saha & Jayanta Bhusan Basu & Taha Selim Ustun, 2022. "System Profit Improvement of a Thermal–Wind–CAES Hybrid System Considering Imbalance Cost in the Electricity Market," Energies, MDPI, vol. 15(24), pages 1-25, December.
    7. Nikzad, Mehdi & Samimi, Abouzar, 2021. "Integration of designing price-based demand response models into a stochastic bi-level scheduling of multiple energy carrier microgrids considering energy storage systems," Applied Energy, Elsevier, vol. 282(PA).
    8. Yang, Jun & Su, Changqi, 2021. "Robust optimization of microgrid based on renewable distributed power generation and load demand uncertainty," Energy, Elsevier, vol. 223(C).
    9. Kalim Ullah & Quanyuan Jiang & Guangchao Geng & Rehan Ali Khan & Sheraz Aslam & Wahab Khan, 2022. "Optimization of Demand Response and Power-Sharing in Microgrids for Cost and Power Losses," Energies, MDPI, vol. 15(9), pages 1-22, April.
    10. Torkan, Ramin & Ilinca, Adrian & Ghorbanzadeh, Milad, 2022. "A genetic algorithm optimization approach for smart energy management of microgrids," Renewable Energy, Elsevier, vol. 197(C), pages 852-863.
    11. Gomes, I.L.R. & Melicio, R. & Mendes, V.M.F., 2021. "A novel microgrid support management system based on stochastic mixed-integer linear programming," Energy, Elsevier, vol. 223(C).
    12. Seyed Reza Seyednouri & Amin Safari & Meisam Farrokhifar & Sajad Najafi Ravadanegh & Anas Quteishat & Mahmoud Younis, 2023. "Day-Ahead Scheduling of Multi-Energy Microgrids Based on a Stochastic Multi-Objective Optimization Model," Energies, MDPI, vol. 16(4), pages 1-17, February.
    13. MansourLakouraj, Mohammad & Shahabi, Majid & Shafie-khah, Miadreza & Catalão, João P.S., 2022. "Optimal market-based operation of microgrid with the integration of wind turbines, energy storage system and demand response resources," Energy, Elsevier, vol. 239(PB).
    14. Jianying Li & Minsheng Yang & Yuexing Zhang & Jianqi Li & Jianquan Lu, 2023. "Micro-Grid Day-Ahead Stochastic Optimal Dispatch Considering Multiple Demand Response and Electric Vehicles," Energies, MDPI, vol. 16(8), pages 1-15, April.
    15. Marzi, Emanuela & Morini, Mirko & Saletti, Costanza & Vouros, Stavros & Zaccaria, Valentina & Kyprianidis, Konstantinos & Gambarotta, Agostino, 2023. "Power-to-Gas for energy system flexibility under uncertainty in demand, production and price," Energy, Elsevier, vol. 284(C).
    16. Morales-España, Germán & Martínez-Gordón, Rafael & Sijm, Jos, 2022. "Classifying and modelling demand response in power systems," Energy, Elsevier, vol. 242(C).
    17. Bingyin Lei & Yue Ren & Huiyu Luan & Ruonan Dong & Xiuyuan Wang & Junli Liao & Shu Fang & Kaiye Gao, 2023. "A Review of Optimization for System Reliability of Microgrid," Mathematics, MDPI, vol. 11(4), pages 1-30, February.
    18. Qian Zhang & Lisheng Wei & Benben Yang, 2022. "Research on Improved BBO Algorithm and Its Application in Optimal Scheduling of Micro-Grid," Mathematics, MDPI, vol. 10(16), pages 1-18, August.
    19. Àlex Alonso-Travesset & Helena Martín & Sergio Coronas & Jordi de la Hoz, 2022. "Optimization Models under Uncertainty in Distributed Generation Systems: A Review," Energies, MDPI, vol. 15(5), pages 1-40, March.
    20. Khaligh, Vahid & Ghezelbash, Azam & Mazidi, Mohammadreza & Liu, Jay & Ryu, Jun-Hyung, 2023. "P-robust energy management of a multi-energy microgrid enabled with energy conversions under various uncertainties," Energy, Elsevier, vol. 271(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:eee:energy:v:241:y:2022:i:c:s0360544221031339. 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: Catherine Liu (email available below). General contact details of provider: http://www.journals.elsevier.com/energy .

    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.