IDEAS home Printed from https://ideas.repec.org/a/gam/jeners/v15y2022i18p6698-d913928.html
   My bibliography  Save this article

Optimal Allocation of Renewable Distributed Generators and Electric Vehicles in a Distribution System Using the Political Optimization Algorithm

Author

Listed:
  • Nagaraju Dharavat

    (School of Electronics and Electrical Engineering, Lovely Professional University, Phagwara 144411, India)

  • Suresh Kumar Sudabattula

    (School of Electronics and Electrical Engineering, Lovely Professional University, Phagwara 144411, India)

  • Suresh Velamuri

    (Symbiosis Institute of Technology, Symbiosis International Deemed University, Pune 412115, India)

  • Sachin Mishra

    (School of Electronics and Electrical Engineering, Lovely Professional University, Phagwara 144411, India)

  • Naveen Kumar Sharma

    (Department of Electrical Engineering, I. K. Gujral Punjab Technical University, Jalandhar 144603, India)

  • Mohit Bajaj

    (Department of Electrical Engineering, Graphic Era (Deemed to be University), Dehradun 248002, India
    Department of Electrical and Electronics Engineering, National Institute of Technology, Delhi 110040, India)

  • Elmazeg Elgamli

    (Wolfson Centre for Magnetics, School of Engineering, Cardiff University, Cardiff CF24 3AA, UK)

  • Mokhtar Shouran

    (Wolfson Centre for Magnetics, School of Engineering, Cardiff University, Cardiff CF24 3AA, UK)

  • Salah Kamel

    (Electrical Engineering Department, Faculty of Engineering, Aswan University, Aswan 81542, Egypt)

Abstract

This paper proposes an effective approach to solve renewable distributed generators (RDGs) and electric vehicle charging station (EVCS) allocation problems in the distribution system (DS) to reduce power loss (P Loss ) and enhance voltage profile. The RDGs considered for this work are solar, wind and fuel cell. The uncertainties related to RDGs are modelled using probability distribution functions (PDF). These sources’ best locations and sizes are identified by the voltage stability index (VSI) and political optimization algorithm (POA). Furthermore, EV charging strategies such as the conventional charging method (CCM) and optimized charging method (OCM) are considered to study the method’s efficacy. The developed approach is studied on Indian 28 bus DS. Different cases are considered, such as a single DG, multiple DGs and a combination of DGs and EVs. This placement of multiple DGs along with EVs, considering proper scheduling patterns, minimizes P Loss and considerably improves the voltage profile. Finally, the proposed method is compared with other algorithms, and simulated results show that the POA method produces better results in all aspects.

Suggested Citation

  • Nagaraju Dharavat & Suresh Kumar Sudabattula & Suresh Velamuri & Sachin Mishra & Naveen Kumar Sharma & Mohit Bajaj & Elmazeg Elgamli & Mokhtar Shouran & Salah Kamel, 2022. "Optimal Allocation of Renewable Distributed Generators and Electric Vehicles in a Distribution System Using the Political Optimization Algorithm," Energies, MDPI, vol. 15(18), pages 1-25, September.
    • Handle: RePEc:gam:jeners:v:15:y:2022:i:18:p:6698-:d:913928
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1996-1073/15/18/6698/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/1996-1073/15/18/6698/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Aijun Zhu & Zhanqi Gu & Cong Hu & Junhao Niu & Chuanpei Xu & Zhi Li, 2021. "Political optimizer with interpolation strategy for global optimization," PLOS ONE, Public Library of Science, vol. 16(5), pages 1-40, May.
    2. Liu, Jin-peng & Zhang, Teng-xi & Zhu, Jiang & Ma, Tian-nan, 2018. "Allocation optimization of electric vehicle charging station (EVCS) considering with charging satisfaction and distributed renewables integration," Energy, Elsevier, vol. 164(C), pages 560-574.
    3. Kayal, Partha & Chanda, C.K., 2015. "Optimal mix of solar and wind distributed generations considering performance improvement of electrical distribution network," Renewable Energy, Elsevier, vol. 75(C), pages 173-186.
    4. Li, Chengzhe & Zhang, Libo & Ou, Zihan & Wang, Qunwei & Zhou, Dequn & Ma, Jiayu, 2022. "Robust model of electric vehicle charging station location considering renewable energy and storage equipment," Energy, Elsevier, vol. 238(PA).
    5. Abdurrahman Shuaibu Hassan & Yanxia Sun & Zenghui Wang, 2022. "Water, Energy and Food Algorithm with Optimal Allocation and Sizing of Renewable Distributed Generation for Power Loss Minimization in Distribution Systems (WEF)," Energies, MDPI, vol. 15(6), pages 1-19, March.
    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. Dominic Savio Abraham & Balaji Chandrasekar & Narayanamoorthi Rajamanickam & Pradeep Vishnuram & Venkatesan Ramakrishnan & Mohit Bajaj & Marian Piecha & Vojtech Blazek & Lukas Prokop, 2023. "Fuzzy-Based Efficient Control of DC Microgrid Configuration for PV-Energized EV Charging Station," Energies, MDPI, vol. 16(6), pages 1-17, March.
    2. Sunday Adeleke Salimon & Gafari Abiola Adepoju & Isaiah Gbadegesin Adebayo & Harun Or Rashid Howlader & Samson Oladayo Ayanlade & Oludamilare Bode Adewuyi, 2023. "Impact of Distributed Generators Penetration Level on the Power Loss and Voltage Profile of Radial Distribution Networks," Energies, MDPI, vol. 16(4), pages 1-32, February.
    3. Ajit Kumar Mohanty & Perli Suresh Babu & Surender Reddy Salkuti, 2022. "Fuzzy-Based Simultaneous Optimal Placement of Electric Vehicle Charging Stations, Distributed Generators, and DSTATCOM in a Distribution System," Energies, MDPI, vol. 15(22), pages 1-22, November.
    4. Abdul Ghani Olabi & Enas Taha Sayed, 2023. "Developments in Hydrogen Fuel Cells," Energies, MDPI, vol. 16(5), pages 1-5, March.
    5. Soheil Younesi & Bahman Ahmadi & Oguzhan Ceylan & Aydogan Ozdemir, 2022. "Optimum Parallel Processing Schemes to Improve the Computation Speed for Renewable Energy Allocation and Sizing Problems," Energies, MDPI, vol. 15(24), pages 1-18, December.
    6. Nikhil Pachauri & Vigneysh Thangavel & Velamuri Suresh & Mvv Prasad Kantipudi & Hossam Kotb & Ravi Nath Tripathi & Mohit Bajaj, 2023. "A Robust Fractional-Order Control Scheme for PV-Penetrated Grid-Connected Microgrid," Mathematics, MDPI, vol. 11(6), pages 1-18, March.
    7. Pegah Alaee & Julius Bems & Amjad Anvari-Moghaddam, 2023. "A Review of the Latest Trends in Technical and Economic Aspects of EV Charging Management," Energies, MDPI, vol. 16(9), pages 1-28, April.
    8. Thangaraj Yuvaraj & Thirukoilur Dhandapani Suresh & Arokiasamy Ananthi Christy & Thanikanti Sudhakar Babu & Benedetto Nastasi, 2023. "Modelling and Allocation of Hydrogen-Fuel-Cell-Based Distributed Generation to Mitigate Electric Vehicle Charging Station Impact and Reliability Analysis on Electrical Distribution Systems," Energies, MDPI, vol. 16(19), pages 1-31, September.
    9. Zbigniew Kłosowski & Łukasz Mazur, 2023. "Influence of the Type of Receiver on Electrical Energy Losses in Power Grids," Energies, MDPI, vol. 16(15), pages 1-22, July.

    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. Shafqat Jawad & Junyong Liu, 2020. "Electrical Vehicle Charging Services Planning and Operation with Interdependent Power Networks and Transportation Networks: A Review of the Current Scenario and Future Trends," Energies, MDPI, vol. 13(13), pages 1-24, July.
    2. Razavi, Seyed-Ehsan & Rahimi, Ehsan & Javadi, Mohammad Sadegh & Nezhad, Ali Esmaeel & Lotfi, Mohamed & Shafie-khah, Miadreza & Catalão, João P.S., 2019. "Impact of distributed generation on protection and voltage regulation of distribution systems: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 105(C), pages 157-167.
    3. Youssef Amry & Elhoussin Elbouchikhi & Franck Le Gall & Mounir Ghogho & Soumia El Hani, 2022. "Electric Vehicle Traction Drives and Charging Station Power Electronics: Current Status and Challenges," Energies, MDPI, vol. 15(16), pages 1-30, August.
    4. Davidov, Sreten, 2020. "Optimal charging infrastructure planning based on a charging convenience buffer," Energy, Elsevier, vol. 192(C).
    5. Verónica Anadón Martínez & Andreas Sumper, 2023. "Planning and Operation Objectives of Public Electric Vehicle Charging Infrastructures: A Review," Energies, MDPI, vol. 16(14), pages 1-41, July.
    6. Woo, Hyeon & Son, Yongju & Cho, Jintae & Kim, Sung-Yul & Choi, Sungyun, 2023. "Optimal expansion planning of electric vehicle fast charging stations," Applied Energy, Elsevier, vol. 342(C).
    7. Zhou, Guangyou & Zhu, Zhiwei & Luo, Sumei, 2022. "Location optimization of electric vehicle charging stations: Based on cost model and genetic algorithm," Energy, Elsevier, vol. 247(C).
    8. Abbas Rabiee & Ali Abdali & Seyed Masoud Mohseni-Bonab & Mohsen Hazrati, 2021. "Risk-Averse Scheduling of Combined Heat and Power-Based Microgrids in Presence of Uncertain Distributed Energy Resources," Sustainability, MDPI, vol. 13(13), pages 1-24, June.
    9. Najafi, Arsalan & Jasiński, Michał & Leonowicz, Zbigniew, 2022. "A hybrid distributed framework for optimal coordination of electric vehicle aggregators problem," Energy, Elsevier, vol. 249(C).
    10. Li, Yanbin & Wang, Jiani & Wang, Weiye & Liu, Chang & Li, Yun, 2023. "Dynamic pricing based electric vehicle charging station location strategy using reinforcement learning," Energy, Elsevier, vol. 281(C).
    11. Fayez Alanazi & Talal Obaid Alshammari & Abdelhalim Azam, 2023. "Optimal Charging Station Placement and Scheduling for Electric Vehicles in Smart Cities," Sustainability, MDPI, vol. 15(22), pages 1-23, November.
    12. Ji, Haoran & Wang, Chengshan & Li, Peng & Song, Guanyu & Yu, Hao & Wu, Jianzhong, 2019. "Quantified analysis method for operational flexibility of active distribution networks with high penetration of distributed generators," Applied Energy, Elsevier, vol. 239(C), pages 706-714.
    13. Kools, L. & Phillipson, F., 2016. "Data granularity and the optimal planning of distributed generation," Energy, Elsevier, vol. 112(C), pages 342-352.
    14. Shi, Lei & Wu, Rongxin & Lin, Boqiang, 2023. "Where will go for electric vehicles in China after the government subsidy incentives are abolished? A controversial consumer perspective," Energy, Elsevier, vol. 262(PA).
    15. O., Yugeswar Reddy & J., Jithendranath & Chakraborty, Ajoy Kumar & Guerrero, Josep M., 2022. "Stochastic optimal power flow in islanded DC microgrids with correlated load and solar PV uncertainties," Applied Energy, Elsevier, vol. 307(C).
    16. Mohammed, Nooriya A. & Al-Bazi, Ammar, 2021. "Management of renewable energy production and distribution planning using agent-based modelling," Renewable Energy, Elsevier, vol. 164(C), pages 509-520.
    17. Dougier, Nathanael & Garambois, Pierre & Gomand, Julien & Roucoules, Lionel, 2021. "Multi-objective non-weighted optimization to explore new efficient design of electrical microgrids," Applied Energy, Elsevier, vol. 304(C).
    18. Chaduvula, Hemanth & Das, Debapriya, 2023. "Analysis of microgrid configuration with optimal power injection from grid using point estimate method embedded fuzzy-particle swarm optimization," Energy, Elsevier, vol. 282(C).
    19. Fescioglu-Unver, Nilgun & Yıldız Aktaş, Melike, 2023. "Electric vehicle charging service operations: A review of machine learning applications for infrastructure planning, control, pricing and routing," Renewable and Sustainable Energy Reviews, Elsevier, vol. 188(C).
    20. Zhao, Dongwei & Jafari, Mehdi & Botterud, Audun & Sakti, Apurba, 2022. "Strategic energy storage investments: A case study of the CAISO electricity market," Applied Energy, Elsevier, vol. 325(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:gam:jeners:v:15:y:2022:i:18:p:6698-:d:913928. 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.