IDEAS home Printed from https://ideas.repec.org/a/gam/jmathe/v11y2023i6p1415-d1097724.html
   My bibliography  Save this article

Improved Golden Jackal Optimization for Optimal Allocation and Scheduling of Wind Turbine and Electric Vehicles Parking Lots in Electrical Distribution Network Using Rosenbrock’s Direct Rotation Strategy

Author

Listed:
  • Jing Yang

    (Department of Computer System and Technology, Faculty of Computer Science and Information Technology, Universiti Malaya, Kuala Lumpur 50603, Malaysia)

  • Jiale Xiong

    (Department of Computer System and Technology, Faculty of Computer Science and Information Technology, Universiti Malaya, Kuala Lumpur 50603, Malaysia)

  • Yen-Lin Chen

    (Department of Computer Science and Information Engineering, National Taipei University of Technology, Taipei 106344, Taiwan)

  • Por Lip Yee

    (Department of Computer System and Technology, Faculty of Computer Science and Information Technology, Universiti Malaya, Kuala Lumpur 50603, Malaysia)

  • Chin Soon Ku

    (Department of Computer Science, Universiti Tunku Abdul Rahman, Kampar 31900, Malaysia)

  • Manoochehr Babanezhad

    (Department of Statistics, Faculty of Sciences, Golestan University, Gorgan 49138-15759, Golestan, Iran)

Abstract

In this paper, a multi-objective allocation and scheduling of wind turbines and electric vehicle parking lots are performed in an IEEE 33-bus radial distribution network to reach the minimum annual costs of power loss, purchased grid energy, wind energy, PHEV energy, battery degradation cost, and network voltage deviations. Decision variables, such as the site and size of wind turbines and electric parking lots in the distribution system, are found using an improved golden jackal optimization (IGJO) algorithm based on Rosenbrock’s direct rotational (RDR) strategy. The results showed that the IGJO finds the optimal solution with a lower convergence tolerance and a better (lower) objective function value compared to conventional GJO, the artificial electric field algorithm (AEFA), particle swarm optimization (PSO), and manta ray foraging optimization (MRFO) methods. The results showed that using the proposed method based on the IGJO, the energy loss cost, grid energy cost, and network voltage deviations were reduced by 29.76%, 65.86%, and 18.63%, respectively, compared to the base network. Moreover, the statistical analysis results proved their superiority compared to the conventional GJO, AEFA, PSO, and MRFO algorithms. Moreover, considering vehicles battery degradation costs, the losses cost, grid energy cost, and network voltage deviations have been reduced by 3.28%, 1.07%, and 4.32%, respectively, compared to the case without battery degradation costs. In addition, the results showed that the decrease in electric vehicle availability causes increasing losses for grid energy costs and weakens the network voltage profile, and vice versa.

Suggested Citation

  • Jing Yang & Jiale Xiong & Yen-Lin Chen & Por Lip Yee & Chin Soon Ku & Manoochehr Babanezhad, 2023. "Improved Golden Jackal Optimization for Optimal Allocation and Scheduling of Wind Turbine and Electric Vehicles Parking Lots in Electrical Distribution Network Using Rosenbrock’s Direct Rotation Strat," Mathematics, MDPI, vol. 11(6), pages 1-23, March.
    • Handle: RePEc:gam:jmathe:v:11:y:2023:i:6:p:1415-:d:1097724
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2227-7390/11/6/1415/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2227-7390/11/6/1415/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Claude Ziad El-Bayeh & Mohamed Zellagui & Navid Shirzadi & Ursula Eicker, 2021. "A Novel Optimization Algorithm for Solar Panels Selection towards a Self-Powered EV Parking Lot and Its Impact on the Distribution System," Energies, MDPI, vol. 14(15), pages 1-28, July.
    2. Norouzi, Mohammadali & Aghaei, Jamshid & Pirouzi, Sasan & Niknam, Taher & Fotuhi-Firuzabad, Mahmud, 2022. "Flexibility pricing of integrated unit of electric spring and EVs parking in microgrids," Energy, Elsevier, vol. 239(PB).
    3. Javidsharifi, Mahshid & Niknam, Taher & Aghaei, Jamshid & Mokryani, Geev, 2018. "Multi-objective short-term scheduling of a renewable-based microgrid in the presence of tidal resources and storage devices," Applied Energy, Elsevier, vol. 216(C), pages 367-381.
    4. Naderipour, Amirreza & Kamyab, Hesam & Klemeš, Jiří Jaromír & Ebrahimi, Reza & Chelliapan, Shreeshivadasan & Nowdeh, Saber Arabi & Abdullah, Aldrin & Hedayati Marzbali, Massoomeh, 2022. "Optimal design of hybrid grid-connected photovoltaic/wind/battery sustainable energy system improving reliability, cost and emission," Energy, Elsevier, vol. 257(C).
    5. Amirreza Naderipour & Zulkurnain Abdul-Malek & Saber Arabi Nowdeh & Foad H. Gandoman & Mohammad Jafar Hadidian Moghaddam, 2019. "A Multi-Objective Optimization Problem for Optimal Site Selection of Wind Turbines for Reduce Losses and Improve Voltage Profile of Distribution Grids," Energies, MDPI, vol. 12(13), pages 1-15, July.
    6. Sun, Hongyue & Ebadi, Abdol Ghaffar & Toughani, Mohsen & Nowdeh, Saber Arabi & Naderipour, Amirreza & Abdullah, Aldrin, 2022. "Designing framework of hybrid photovoltaic-biowaste energy system with hydrogen storage considering economic and technical indices using whale optimization algorithm," Energy, Elsevier, vol. 238(PA).
    7. Laith Abualigah & Ali Diabat & Raed Abu Zitar, 2022. "Orthogonal Learning Rosenbrock’s Direct Rotation with the Gazelle Optimization Algorithm for Global Optimization," Mathematics, MDPI, vol. 10(23), pages 1-42, November.
    8. Awasthi, Abhishek & Venkitusamy, Karthikeyan & Padmanaban, Sanjeevikumar & Selvamuthukumaran, Rajasekar & Blaabjerg, Frede & Singh, Asheesh K., 2017. "Optimal planning of electric vehicle charging station at the distribution system using hybrid optimization algorithm," Energy, Elsevier, vol. 133(C), pages 70-78.
    9. Hafez, Omar & Bhattacharya, Kankar, 2017. "Optimal design of electric vehicle charging stations considering various energy resources," Renewable Energy, Elsevier, vol. 107(C), pages 576-589.
    10. Tabatabaee, Sajad & Mortazavi, Seyed Saeedallah & Niknam, Taher, 2017. "Stochastic scheduling of local distribution systems considering high penetration of plug-in electric vehicles and renewable energy sources," Energy, Elsevier, vol. 121(C), pages 480-490.
    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. Hongyan Dui & Yulu Zhang & Yun-An Zhang, 2023. "Grouping Maintenance Policy for Improving Reliability of Wind Turbine Systems Considering Variable Cost," Mathematics, MDPI, vol. 11(8), pages 1-20, April.

    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. Davoudkhani, Iraj Faraji & Dejamkhooy, Abdolmajid & Nowdeh, Saber Arabi, 2023. "A novel cloud-based framework for optimal design of stand-alone hybrid renewable energy system considering uncertainty and battery aging," Applied Energy, Elsevier, vol. 344(C).
    2. Feng, Li & Liu, Jiajun & Lu, Haitao & Liu, Bingzhi & Chen, Yuning & Wu, Shenyu, 2022. "Robust operation of distribution network based on photovoltaic/wind energy resources in condition of COVID-19 pandemic considering deterministic and probabilistic approaches," Energy, Elsevier, vol. 261(PB).
    3. Saman Shahrokhi & Adel El-Shahat & Fatemeh Masoudinia & Foad H. Gandoman & Shady H. E. Abdel Aleem, 2021. "Sizing and Energy Management of Parking Lots of Electric Vehicles Based on Battery Storage with Wind Resources in Distribution Network," Energies, MDPI, vol. 14(20), pages 1-21, October.
    4. Morro-Mello, Igoor & Padilha-Feltrin, Antonio & Melo, Joel D. & Calviño, Aida, 2019. "Fast charging stations placement methodology for electric taxis in urban zones," Energy, Elsevier, vol. 188(C).
    5. Du, Zhili & Zheng, Lirong & Lin, Boqiang, 2024. "Influence of charging stations accessibility on charging stations utilization," Energy, Elsevier, vol. 298(C).
    6. Ahmed Abdalrahman & Weihua Zhuang, 2017. "A Survey on PEV Charging Infrastructure: Impact Assessment and Planning," Energies, MDPI, vol. 10(10), pages 1-25, October.
    7. Figueiredo, Raquel & Nunes, Pedro & Brito, Miguel C., 2017. "The feasibility of solar parking lots for electric vehicles," Energy, Elsevier, vol. 140(P1), pages 1182-1197.
    8. Harasis, Salman & Khan, Irfan & Massoud, Ahmed, 2024. "Enabling large-scale integration of electric bus fleets in harsh environments: Possibilities, potentials, and challenges," Energy, Elsevier, vol. 300(C).
    9. Zhang, Yue & Zhang, Qi & Farnoosh, Arash & Chen, Siyuan & Li, Yan, 2019. "GIS-Based Multi-Objective Particle Swarm Optimization of charging stations for electric vehicles," Energy, Elsevier, vol. 169(C), pages 844-853.
    10. Qiu, Rui & Zhang, Haoran & Wang, Guotao & Liang, Yongtu & Yan, Jinyue, 2023. "Green hydrogen-based energy storage service via power-to-gas technologies integrated with multi-energy microgrid," Applied Energy, Elsevier, vol. 350(C).
    11. Khan, Waqas & Somers, Ward & Walker, Shalika & de Bont, Kevin & Van der Velden, Joep & Zeiler, Wim, 2023. "Comparison of electric vehicle load forecasting across different spatial levels with incorporated uncertainty estimation," Energy, Elsevier, vol. 283(C).
    12. Yang, Jie & Yu, Fan & Ma, Kai & Yang, Bo & Yue, Zhiyuan, 2024. "Optimal scheduling of electric-hydrogen integrated charging station for new energy vehicles," Renewable Energy, Elsevier, vol. 224(C).
    13. Zhou, Jianguo & Xu, Zhongtian, 2023. "Optimal sizing design and integrated cost-benefit assessment of stand-alone microgrid system with different energy storage employing chameleon swarm algorithm: A rural case in Northeast China," Renewable Energy, Elsevier, vol. 202(C), pages 1110-1137.
    14. Morro-Mello, Igoor & Padilha-Feltrin, Antonio & Melo, Joel D. & Heymann, Fabian, 2021. "Spatial connection cost minimization of EV fast charging stations in electric distribution networks using local search and graph theory," Energy, Elsevier, vol. 235(C).
    15. Duan, Ditao & Poursoleiman, Roza, 2021. "Modified teaching-learning-based optimization by orthogonal learning for optimal design of an electric vehicle charging station," Utilities Policy, Elsevier, vol. 72(C).
    16. Shi, Mengshu & Wang, Weiye & Han, Yaxuan & Huang, Yuansheng, 2022. "Research on comprehensive benefit of hydrogen storage in microgrid system," Renewable Energy, Elsevier, vol. 194(C), pages 621-635.
    17. Bryam Paúl Lojano-Riera & Carlos Flores-Vázquez & Juan-Carlos Cobos-Torres & David Vallejo-Ramírez & Daniel Icaza, 2023. "Electromobility with Photovoltaic Generation in an Andean City," Energies, MDPI, vol. 16(15), pages 1-16, July.
    18. Bu, Yuntao & Yu, Hao & Ji, Haoran & Song, Guanyu & Xu, Jing & Li, Juan & Zhao, Jinli & Li, Peng, 2024. "Hybrid data-driven operation method for demand response of community integrated energy systems utilizing virtual and physical energy storage," Applied Energy, Elsevier, vol. 366(C).
    19. Lei Yao & Chongtao Bai & Hao Fu & Suhua Lou & Yan Fu, 2023. "Optimization of Expressway Microgrid Construction Mode and Capacity Configuration Considering Carbon Trading," Energies, MDPI, vol. 16(18), pages 1-17, September.
    20. Andriosopoulos, Kostas & Bigerna, Simona & Bollino, Carlo Andrea & Micheli, Silvia, 2018. "The impact of age on Italian consumers' attitude toward alternative fuel vehicles," Renewable Energy, Elsevier, vol. 119(C), pages 299-308.

    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:jmathe:v:11:y:2023:i:6:p:1415-:d:1097724. 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.