IDEAS home Printed from https://ideas.repec.org/a/eee/energy/v143y2018icp961-972.html
   My bibliography  Save this article

A combined resource allocation framework for PEVs charging stations, renewable energy resources and distributed energy storage systems

Author

Listed:
  • Kandil, Sarah M.
  • Farag, Hany E.Z.
  • Shaaban, Mostafa F.
  • El-Sharafy, M. Zaki

Abstract

The massive deployment of plug-in electric vehicles (PEVs), renewable energy resources (RES), and distributed energy storage systems (DESS) has gained significant interest under the smart grid vision. However, their special features and operational characteristics have created a paradigm shift in distribution network resource allocation studies. This paper presents a combined model formulation for the concurrent optimal resource allocation of PEVs charging stations, RES and DESS in distribution networks. The formulation employs a general objective function that optimizes the total Annual Cost of Energy (ACOE). The decision variables in the formulation are the locations and capacities of PEVs charging stations, RES, and DESS units. A Markov Chain Monte Carlo (MCMC) simulation model is utilized to account for the uncertainties of PEVs charging demand and output generation of RES units. Also, in order to enhance the accuracy of the resource allocation problem, the coordinated control of PEVs charging, RES output power, and DESS charging/discharging are incorporated in the formulated model. The formulation is decomposed into two interdependent sub-problems and solved using a combination of metaheuristic and deterministic optimization techniques. A sample case study is presented to illustrate the performance of the algorithm.

Suggested Citation

  • Kandil, Sarah M. & Farag, Hany E.Z. & Shaaban, Mostafa F. & El-Sharafy, M. Zaki, 2018. "A combined resource allocation framework for PEVs charging stations, renewable energy resources and distributed energy storage systems," Energy, Elsevier, vol. 143(C), pages 961-972.
    • Handle: RePEc:eee:energy:v:143:y:2018:i:c:p:961-972
    DOI: 10.1016/j.energy.2017.11.005
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0360544217318546
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.energy.2017.11.005?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.

    Citations

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


    Cited by:

    1. Chao-Tsung Ma, 2019. "System Planning of Grid-Connected Electric Vehicle Charging Stations and Key Technologies: A Review," Energies, MDPI, vol. 12(21), pages 1-22, November.
    2. Li, Rui & Wang, Wei & Wu, Xuezhi & Tang, Fen & Chen, Zhe, 2019. "Cooperative planning model of renewable energy sources and energy storage units in active distribution systems: A bi-level model and Pareto analysis," Energy, Elsevier, vol. 168(C), pages 30-42.
    3. Adrian Tantau & András Puskás-Tompos & Laurentiu Fratila & Costel Stanciu, 2021. "Acceptance of Demand Response and Aggregators as a Solution to Optimize the Relation between Energy Producers and Consumers in order to Increase the Amount of Renewable Energy in the Grid," Energies, MDPI, vol. 14(12), pages 1-19, June.
    4. Ibrahim, Nurul Nadia & Jamian, Jasrul Jamani & Md Rasid, Madihah, 2024. "Optimal multi-objective sizing of renewable energy sources and battery energy storage systems for formation of a multi-microgrid system considering diverse load patterns," Energy, Elsevier, vol. 304(C).
    5. Luo, Lizi & Gu, Wei & Wu, Zhi & Zhou, Suyang, 2019. "Joint planning of distributed generation and electric vehicle charging stations considering real-time charging navigation," Applied Energy, Elsevier, vol. 242(C), pages 1274-1284.
    6. Xian Huang & Wentong Ji & Xiaorong Ye & Zhangjie Feng, 2023. "Configuration Planning of Expressway Self-Consistent Energy System Based on Multi-Objective Chance-Constrained Programming," Sustainability, MDPI, vol. 15(6), pages 1-20, March.
    7. Eltoumi, Fouad M. & Becherif, Mohamed & Djerdir, Abdesslem & Ramadan, Haitham.S., 2021. "The key issues of electric vehicle charging via hybrid power sources: Techno-economic viability, analysis, and recommendations," Renewable and Sustainable Energy Reviews, Elsevier, vol. 138(C).
    8. Luo, Lizi & Wu, Zhi & Gu, Wei & Huang, He & Gao, Song & Han, Jun, 2020. "Coordinated allocation of distributed generation resources and electric vehicle charging stations in distribution systems with vehicle-to-grid interaction," Energy, Elsevier, vol. 192(C).
    9. Lu, Xiaoxing & Li, Kangping & Xu, Hanchen & Wang, Fei & Zhou, Zhenyu & Zhang, Yagang, 2020. "Fundamentals and business model for resource aggregator of demand response in electricity markets," Energy, Elsevier, vol. 204(C).
    10. Meng, Linghao & Li, Mei & Yang, Hongzhi, 2024. "Enhancing energy efficiency in distributed systems with hybrid energy storage," Energy, Elsevier, vol. 305(C).
    11. Elio Chiodo & Maurizio Fantauzzi & Davide Lauria & Fabio Mottola, 2018. "A Probabilistic Approach for the Optimal Sizing of Storage Devices to Increase the Penetration of Plug-in Electric Vehicles in Direct Current Networks," Energies, MDPI, vol. 11(5), pages 1-20, May.
    12. Hyeon Woo & Yongju Son & Jintae Cho & Sungyun Choi, 2022. "Stochastic Second-Order Conic Programming for Optimal Sizing of Distributed Generator Units and Electric Vehicle Charging Stations," Sustainability, MDPI, vol. 14(9), pages 1-19, April.

    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:143:y:2018:i:c:p:961-972. 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.

    We have no bibliographic references for this item. You can help adding them by using 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.