IDEAS home Printed from https://ideas.repec.org/a/eee/appene/v322y2022ics0306261922008339.html
   My bibliography  Save this article

An optimization planning framework for allocating multiple distributed energy resources and electric vehicle charging stations in distribution networks

Author

Listed:
  • Adetunji, Kayode E.
  • Hofsajer, Ivan W.
  • Abu-Mahfouz, Adnan M.
  • Cheng, Ling

Abstract

In developing a sustainable and efficient power systems network while reducing carbon footprint, renewable energy (RE)-based Distribution Generation (DG) units are highly recommended. Furthermore, Battery Energy Storage Systems (BESS) and other passive electronic units are adopted to improve grid performance and mitigate the effects of high variability from RE power. Hence, planning frameworks are developed to optimally allocate these units to distribution networks. However, current planning mechanisms do not consider the relative effect of different allocated units in planning frameworks. To bridge this gap, this paper presents a novel comprehensive planning framework for allocating DG units, BESS units, and Electric Vehicle Charging Station (EVCS) facilities in a distribution network while optimizing its technical, economic, and environmental benefits. The proposed framework uses a recombination technique to generate more solutions by dynamically updating the DG and BESS units’ locations in one iteration. A Reinforcement Learning (RL)-based algorithm is introduced to coordinate EV charging that suggests the optimal EVCS location in relation to other units’ locations. To cope with the complexity ensuing from searching a larger solution space, a multi-stage, hybrid optimization scheme is developed to produce optimal allocation variables. A category-based multiobjective framework is further developed to simultaneously optimize many objective functions — power loss, voltage stability, voltage deviation, installation and operation cost, and emission cost. Through numerical simulations on the IEEE 33- and 118-bus distribution network, it is shown that the proposed optimization scheme achieves higher metric values than the adopted benchmark optimization schemes. A validation process was also carried out on the proposed multiobjective optimization approach, comparing it with other approaches. Using the Spacing metric, the proposed approach proves to be efficient, depicting a good spread of Pareto optimal solutions.

Suggested Citation

  • Adetunji, Kayode E. & Hofsajer, Ivan W. & Abu-Mahfouz, Adnan M. & Cheng, Ling, 2022. "An optimization planning framework for allocating multiple distributed energy resources and electric vehicle charging stations in distribution networks," Applied Energy, Elsevier, vol. 322(C).
    • Handle: RePEc:eee:appene:v:322:y:2022:i:c:s0306261922008339
    DOI: 10.1016/j.apenergy.2022.119513
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0306261922008339
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.apenergy.2022.119513?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. Mouwafi, Mohamed T. & El-Sehiemy, Ragab A. & El-Ela, Adel A. Abou, 2022. "A two-stage method for optimal placement of distributed generation units and capacitors in distribution systems," Applied Energy, Elsevier, vol. 307(C).
    2. Yann Dujardin & Iadine Chadès, 2018. "Solving multi-objective optimization problems in conservation with the reference point method," PLOS ONE, Public Library of Science, vol. 13(1), pages 1-16, January.
    3. Elattar, Ehab E., 2018. "Modified harmony search algorithm for combined economic emission dispatch of microgrid incorporating renewable sources," Energy, Elsevier, vol. 159(C), pages 496-507.
    4. Singh, Pushpendra & Meena, Nand K. & Yang, Jin & Vega-Fuentes, Eduardo & Bishnoi, Shree Krishna, 2020. "Multi-criteria decision making monarch butterfly optimization for optimal distributed energy resources mix in distribution networks," Applied Energy, Elsevier, vol. 278(C).
    5. Ma, Wei & Wang, Wei & Chen, Zhe & Wu, Xuezhi & Hu, Ruonan & Tang, Fen & Zhang, Weige, 2021. "Voltage regulation methods for active distribution networks considering the reactive power optimization of substations," Applied Energy, Elsevier, vol. 284(C).
    6. Zhang, Xizheng & Wang, Zeyu & Lu, Zhangyu, 2022. "Multi-objective load dispatch for microgrid with electric vehicles using modified gravitational search and particle swarm optimization algorithm," Applied Energy, Elsevier, vol. 306(PA).
    7. Mukhopadhyay, Bineeta & Das, Debapriya, 2020. "Multi-objective dynamic and static reconfiguration with optimized allocation of PV-DG and battery energy storage system," Renewable and Sustainable Energy Reviews, Elsevier, vol. 124(C).
    8. Das, Choton K. & Bass, Octavian & Mahmoud, Thair S. & Kothapalli, Ganesh & Mousavi, Navid & Habibi, Daryoush & Masoum, Mohammad A.S., 2019. "Optimal allocation of distributed energy storage systems to improve performance and power quality of distribution networks," Applied Energy, Elsevier, vol. 252(C), pages 1-1.
    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. Guo, Jiacheng & Wu, Di & Wang, Yuanyuan & Wang, Liming & Guo, Hanyuan, 2023. "Co-optimization method research and comprehensive benefits analysis of regional integrated energy system," Applied Energy, Elsevier, vol. 340(C).
    2. Kumar, Abhishek & Deng, Yan & He, Xiangning & Singh, Arvind R. & Kumar, Praveen & Bansal, R.C. & Bettayeb, M. & Ghenai, C. & Naidoo, R.M., 2023. "Impact of demand side management approaches for the enhancement of voltage stability loadability and customer satisfaction index," Applied Energy, Elsevier, vol. 339(C).
    3. Li, Da & Deng, Junjun & Zhang, Zhaosheng & Liu, Peng & Wang, Zhenpo, 2023. "Multi-dimension statistical analysis and selection of safety-representing features for battery pack in real-world electric vehicles," Applied Energy, Elsevier, vol. 343(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. Panyawoot Boonluk & Sirote Khunkitti & Pradit Fuangfoo & Apirat Siritaratiwat, 2021. "Optimal Siting and Sizing of Battery Energy Storage: Case Study Seventh Feeder at Nakhon Phanom Substation in Thailand," Energies, MDPI, vol. 14(5), pages 1-20, March.
    2. Ahmadi, Bahman & Ceylan, Oguzhan & Ozdemir, Aydogan & Fotuhi-Firuzabad, Mahmoud, 2022. "A multi-objective framework for distributed energy resources planning and storage management," Applied Energy, Elsevier, vol. 314(C).
    3. Md Jahidur Rahman & Tahar Tafticht & Mamadou Lamine Doumbia & Iqbal Messaïf, 2023. "Optimal Inverter Control Strategies for a PV Power Generation with Battery Storage System in Microgrid," Energies, MDPI, vol. 16(10), pages 1-36, May.
    4. A.S. Jameel Hassan & Umar Marikkar & G.W. Kasun Prabhath & Aranee Balachandran & W.G. Chaminda Bandara & Parakrama B. Ekanayake & Roshan I. Godaliyadda & Janaka B. Ekanayake, 2021. "A Sensitivity Matrix Approach Using Two-Stage Optimization for Voltage Regulation of LV Networks with High PV Penetration," Energies, MDPI, vol. 14(20), pages 1-24, October.
    5. Mousavi, Navid & Kothapalli, Ganesh & Habibi, Daryoush & Das, Choton K. & Baniasadi, Ali, 2020. "A novel photovoltaic-pumped hydro storage microgrid applicable to rural areas," Applied Energy, Elsevier, vol. 262(C).
    6. Lu, Yu & Xiang, Yue & Huang, Yuan & Yu, Bin & Weng, Liguo & Liu, Junyong, 2023. "Deep reinforcement learning based optimal scheduling of active distribution system considering distributed generation, energy storage and flexible load," Energy, Elsevier, vol. 271(C).
    7. Zhang, Weiping & Maleki, Akbar, 2022. "Modeling and optimization of a stand-alone desalination plant powered by solar/wind energies based on back-up systems using a hybrid algorithm," Energy, Elsevier, vol. 254(PC).
    8. Wang, Yi & Qiu, Dawei & Sun, Mingyang & Strbac, Goran & Gao, Zhiwei, 2023. "Secure energy management of multi-energy microgrid: A physical-informed safe reinforcement learning approach," Applied Energy, Elsevier, vol. 335(C).
    9. Stelios Rozakis & Athanasios Kampas, 2022. "An interactive multi-criteria approach to admit new members in international environmental agreements," Operational Research, Springer, vol. 22(4), pages 3461-3487, September.
    10. Zhu, Xingxu & Hou, Xiangchen & Li, Junhui & Yan, Gangui & Li, Cuiping & Wang, Dongbo, 2023. "Distributed online prediction optimization algorithm for distributed energy resources considering the multi-periods optimal operation," Applied Energy, Elsevier, vol. 348(C).
    11. 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).
    12. Ting Zhang & Shuaishuai Cao & Lingying Pan & Chenyu Zhou, 2020. "A Policy Effect Analysis of China’s Energy Storage Development Based on a Multi-Agent Evolutionary Game Model," Energies, MDPI, vol. 13(23), pages 1-35, November.
    13. Hui Wang & Jun Wang & Zailin Piao & Xiaofang Meng & Chao Sun & Gang Yuan & Sitong Zhu, 2020. "The Optimal Allocation and Operation of an Energy Storage System with High Penetration Grid-Connected Photovoltaic Systems," Sustainability, MDPI, vol. 12(15), pages 1-22, July.
    14. Jerzy Andruszkiewicz & Józef Lorenc & Agnieszka Weychan, 2023. "Determination of the Optimal Level of Reactive Power Compensation That Minimizes the Costs of Losses in Distribution Networks," Energies, MDPI, vol. 17(1), pages 1-24, December.
    15. Mohamed Mohamed Khaleel & Mohd Rafi Adzman & Samila Mat Zali, 2021. "An Integrated of Hydrogen Fuel Cell to Distribution Network System: Challenging and Opportunity for D-STATCOM," Energies, MDPI, vol. 14(21), pages 1-26, October.
    16. Azeredo, Lucas F.S. & Yahyaoui, Imene & Fiorotti, Rodrigo & Fardin, Jussara F. & Garcia-Pereira, Hilel & Rocha, Helder R.O., 2023. "Study of reducing losses, short-circuit currents and harmonics by allocation of distributed generation, capacitor banks and fault current limiters in distribution grids," Applied Energy, Elsevier, vol. 350(C).
    17. Liu, Liuchen & Cui, Guomin & Chen, Jiaxing & Huang, Xiaohuang & Li, Di, 2022. "Two-stage superstructure model for optimization of distributed energy systems (DES) part I: Model development and verification," Energy, Elsevier, vol. 245(C).
    18. Li, Da & Zhang, Zhaosheng & Zhou, Litao & Liu, Peng & Wang, Zhenpo & Deng, Junjun, 2022. "Multi-time-step and multi-parameter prediction for real-world proton exchange membrane fuel cell vehicles (PEMFCVs) toward fault prognosis and energy consumption prediction," Applied Energy, Elsevier, vol. 325(C).
    19. Li, Chaoshun & Wang, Wenxiao & Chen, Deshu, 2019. "Multi-objective complementary scheduling of hydro-thermal-RE power system via a multi-objective hybrid grey wolf optimizer," Energy, Elsevier, vol. 171(C), pages 241-255.
    20. Gorman, Will & Barbose, Galen & Pablo Carvallo, Juan & Baik, Sunhee & Miller, Chandler & White, Philip & Praprost, Marlena, 2023. "County-level assessment of behind-the-meter solar and storage to mitigate long duration power interruptions for residential customers," Applied Energy, Elsevier, vol. 342(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:appene:v:322:y:2022:i:c:s0306261922008339. 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.elsevier.com/wps/find/journaldescription.cws_home/405891/description#description .

    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.