IDEAS home Printed from https://ideas.repec.org/a/eee/energy/v283y2023ics0360544223024635.html
   My bibliography  Save this article

Enhanced coati optimization algorithm-based optimal power flow including renewable energy uncertainties and electric vehicles

Author

Listed:
  • Hasanien, Hany M.
  • Alsaleh, Ibrahim
  • Alassaf, Abdullah
  • Alateeq, Ayoob

Abstract

Power systems now face new issues due to incorporating electric vehicles (EVs) and renewable energy resources (RERs). This paper proposes a novel Enhanced Coati Optimization Algorithm (ECOA) for obtaining the optimal solution of the probabilistic optimal power flow (POPF) problems. The ECOA is a metaheuristic optimization algorithm that is robust and efficient for solving complex problems. It is used to tackle the OPF problem, which considers the stochastic characteristics of RERs. Moreover, EVs are included in the presented power systems in this paper. The novel approach is tested and verified on the IEEE-57 and IEEE-118 networks. The effectiveness of the proposed method is demonstrated by making a comparison with other metaheuristic-based methods. To obtain a practical study, real data of wind speed, solar irradiance, and electric vehicles profile are incorporated in the dynamic analyses. The simulation results show that the ECOA is robust and efficient for solving the OPF problem. It can also improve the performance of power systems with RESs and EVs. The findings of this research demonstrate that the suggested approach is promising for power system optimization problems, including RERs and EVs.

Suggested Citation

  • Hasanien, Hany M. & Alsaleh, Ibrahim & Alassaf, Abdullah & Alateeq, Ayoob, 2023. "Enhanced coati optimization algorithm-based optimal power flow including renewable energy uncertainties and electric vehicles," Energy, Elsevier, vol. 283(C).
  • Handle: RePEc:eee:energy:v:283:y:2023:i:c:s0360544223024635
    DOI: 10.1016/j.energy.2023.129069
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0360544223024635
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.energy.2023.129069?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. Lauvergne, Rémi & Perez, Yannick & Françon, Mathilde & Tejeda De La Cruz, Alberto, 2022. "Integration of electric vehicles into transmission grids: A case study on generation adequacy in Europe in 2040," Applied Energy, Elsevier, vol. 326(C).
    2. Roald, Line A. & Pozo, David & Papavasiliou, Anthony & Molzahn, Daniel K. & Kazempour, Jalal & Conejo, Antonio, 2023. "Power systems optimization under uncertainty: a review of methods and applications," LIDAM Reprints CORE 3257, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    3. Sumair, Muhammad & Aized, Tauseef & Aslam Bhutta, Muhammad Mahmood & Siddiqui, Farrukh Arsalan & Tehreem, Layba & Chaudhry, Abduallah, 2022. "Method of Four Moments Mixture-A new approach for parametric estimation of Weibull Probability Distribution for wind potential estimation applications," Renewable Energy, Elsevier, vol. 191(C), pages 291-304.
    4. Kamani, D. & Ardehali, M.M., 2023. "Long-term forecast of electrical energy consumption with considerations for solar and wind energy sources," Energy, Elsevier, vol. 268(C).
    5. Xiao, Hao & Pei, Wei & Wu, Lei & Ma, Li & Ma, Tengfei & Hua, Weiqi, 2023. "A novel deep learning based probabilistic power flow method for Multi-Microgrids distribution system with incomplete network information," Applied Energy, Elsevier, vol. 335(C).
    6. Huang, Kangdi & Liu, Pan & Kim, Jong-Suk & Xu, Weifeng & Gong, Yu & Cheng, Qian & Zhou, Yong, 2023. "A model coupling current non-adjustable, coming adjustable and remaining stages for daily generation scheduling of a wind-solar-hydro complementary system," Energy, Elsevier, vol. 263(PB).
    7. Mimica, Marko & Dominković, Dominik F. & Kirinčić, Vedran & Krajačić, Goran, 2022. "Soft-linking of improved spatiotemporal capacity expansion model with a power flow analysis for increased integration of renewable energy sources into interconnected archipelago," Applied Energy, Elsevier, vol. 305(C).
    8. Mohamed A. M. Shaheen & Hany M. Hasanien & Rania A. Turky & Martin Ćalasan & Ahmed F. Zobaa & Shady H. E. Abdel Aleem, 2021. "OPF of Modern Power Systems Comprising Renewable Energy Sources Using Improved CHGS Optimization Algorithm," Energies, MDPI, vol. 14(21), pages 1-21, October.
    9. Li, Hang & Hou, Kai & Xu, Xiandong & Jia, Hongjie & Zhu, Lewei & Mu, Yunfei, 2022. "Probabilistic energy flow calculation for regional integrated energy system considering cross-system failures," Applied Energy, Elsevier, vol. 308(C).
    10. Mohamed S. Hashish & Hany M. Hasanien & Haoran Ji & Abdulaziz Alkuhayli & Mohammed Alharbi & Tlenshiyeva Akmaral & Rania A. Turky & Francisco Jurado & Ahmed O. Badr, 2023. "Monte Carlo Simulation and a Clustering Technique for Solving the Probabilistic Optimal Power Flow Problem for Hybrid Renewable Energy Systems," Sustainability, MDPI, vol. 15(1), pages 1-25, January.
    11. Mangipinto, Andrea & Lombardi, Francesco & Sanvito, Francesco Davide & Pavičević, Matija & Quoilin, Sylvain & Colombo, Emanuela, 2022. "Impact of mass-scale deployment of electric vehicles and benefits of smart charging across all European countries," Applied Energy, Elsevier, vol. 312(C).
    12. Benedetto-Giuseppe Risi & Francesco Riganti-Fulginei & Antonino Laudani, 2022. "Modern Techniques for the Optimal Power Flow Problem: State of the Art," Energies, MDPI, vol. 15(17), pages 1-20, September.
    13. Yu, Hang & Niu, Songyan & Shang, Yitong & Shao, Ziyun & Jia, Youwei & Jian, Linni, 2022. "Electric vehicles integration and vehicle-to-grid operation in active distribution grids: A comprehensive review on power architectures, grid connection standards and typical applications," Renewable and Sustainable Energy Reviews, Elsevier, vol. 168(C).
    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. Hasanien, Hany M. & Alsaleh, Ibrahim & Tostado-Véliz, Marcos & Zhang, Miao & Alateeq, Ayoob & Jurado, Francisco & Alassaf, Abdullah, 2024. "Hybrid particle swarm and sea horse optimization algorithm-based optimal reactive power dispatch of power systems comprising electric vehicles," Energy, Elsevier, vol. 286(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. Moon-Jong Jang & Taehoon Kim & Eunsung Oh, 2023. "Data-Driven Modeling of Vehicle-to-Grid Flexibility in Korea," Sustainability, MDPI, vol. 15(10), pages 1-16, May.
    2. Li, Xiaohui & Wang, Zhenpo & Zhang, Lei & Sun, Fengchun & Cui, Dingsong & Hecht, Christopher & Figgener, Jan & Sauer, Dirk Uwe, 2023. "Electric vehicle behavior modeling and applications in vehicle-grid integration: An overview," Energy, Elsevier, vol. 268(C).
    3. 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.
    4. Cheng, Qian & Liu, Pan & Xia, Qian & Cheng, Lei & Ming, Bo & Zhang, Wei & Xu, Weifeng & Zheng, Yalian & Han, Dongyang & Xia, Jun, 2023. "An analytical method to evaluate curtailment of hydro–photovoltaic hybrid energy systems and its implication under climate change," Energy, Elsevier, vol. 278(C).
    5. Li, Zepeng & Wu, Qiuwei & Li, Hui & Nie, Chengkai & Tan, Jin, 2024. "Distributed low-carbon economic dispatch of integrated power and transportation system," Applied Energy, Elsevier, vol. 353(PA).
    6. Zhang, Nan & Lu, Yiji & Kadam, Sambhaji & Yu, Zhibin, 2023. "A fuel cell range extender integrating with heat pump for cabin heat and power generation," Applied Energy, Elsevier, vol. 348(C).
    7. Hasan Huseyin Coban & Wojciech Lewicki & Ewelina Sendek-Matysiak & Zbigniew Łosiewicz & Wojciech Drożdż & Radosław Miśkiewicz, 2022. "Electric Vehicles and Vehicle–Grid Interaction in the Turkish Electricity System," Energies, MDPI, vol. 15(21), pages 1-19, November.
    8. Syed Taha Taqvi & Ali Almansoori & Azadeh Maroufmashat & Ali Elkamel, 2022. "Utilizing Rooftop Renewable Energy Potential for Electric Vehicle Charging Infrastructure Using Multi-Energy Hub Approach," Energies, MDPI, vol. 15(24), pages 1-21, December.
    9. Shen, Haotian & Zhang, Hualiang & Xu, Yujie & Chen, Haisheng & Zhang, Zhilai & Li, Wenkai & Su, Xu & Xu, Yalin & Zhu, Yilin, 2024. "Two stage robust economic dispatching of microgrid considering uncertainty of wind, solar and electricity load along with carbon emission predicted by neural network model," Energy, Elsevier, vol. 300(C).
    10. Loke Kok Foong & Binh Nguyen Le, 2022. "Teaching–Learning–Based Optimization (TLBO) in Hybridized with Fuzzy Inference System Estimating Heating Loads," Energies, MDPI, vol. 15(21), pages 1-20, November.
    11. Schledorn, Amos & Charousset-Brignol, Sandrine & Junker, Rune Grønborg & Guericke, Daniela & Madsen, Henrik & Dominković, Dominik Franjo, 2024. "Frigg 2.0: Integrating price-based demand response into large-scale energy system analysis," Applied Energy, Elsevier, vol. 364(C).
    12. Liang, Weikun & Lin, Shunjiang & Liu, Mingbo & Sheng, Xuan & Pan, Yue, 2024. "Risk-based distributionally robust optimal dispatch for multiple cascading failures in regional integrated energy system using surrogate modeling," Applied Energy, Elsevier, vol. 353(PA).
    13. Mittelman, Gur & Eran, Ronen & Zhivin, Lev & Eisenhändler, Ohad & Luzon, Yossi & Tshuva, Moshe, 2023. "The potential of renewable electricity in isolated grids: The case of Israel in 2050," Applied Energy, Elsevier, vol. 349(C).
    14. Yichao Xie & Bowen Zhou & Zhenyu Wang & Bo Yang & Liaoyi Ning & Yanhui Zhang, 2023. "Industrial Carbon Footprint (ICF) Calculation Approach Based on Bayesian Cross-Validation Improved Cyclic Stacking," Sustainability, MDPI, vol. 15(19), pages 1-35, September.
    15. Cheng, Qian & Liu, Pan & Feng, Maoyuan & Cheng, Lei & Ming, Bo & Luo, Xinran & Liu, Weibo & Xu, Weifeng & Huang, Kangdi & Xia, Jun, 2023. "Complementary operation with wind and photovoltaic power induces the decrease in hydropower efficiency," Applied Energy, Elsevier, vol. 339(C).
    16. Akansha Jain & Masoud Karimi-Ghartemani, 2022. "Mitigating Adverse Impacts of Increased Electric Vehicle Charging on Distribution Transformers," Energies, MDPI, vol. 15(23), pages 1-26, November.
    17. Gómez-Pérez, Jesús D. & Latorre-Canteli, Jesus M. & Ramos, Andres & Perea, Alejandro & Sanz, Pablo & Hernández, Francisco, 2024. "Improving operating policies in stochastic optimization: An application to the medium-term hydrothermal scheduling problem," Applied Energy, Elsevier, vol. 359(C).
    18. Nam Hoai Nguyen & Quynh T. Tran & Thao V. Nguyen & Nam Tran & Leon Roose & Saeed Sepasi & Maria Luisa Di Silvestre, 2023. "A Method for Assessing the Feasibility of Integrating Planned Unidirectional EV Chargers into the Distribution Grid: A Case Study in Danang, Vietnam," Energies, MDPI, vol. 16(9), pages 1-16, April.
    19. Muhammad Bachtiar Nappu & Ardiaty Arief & Willy Akbar Ajami, 2023. "Energy Efficiency in Modern Power Systems Utilizing Advanced Incremental Particle Swarm Optimization–Based OPF," Energies, MDPI, vol. 16(4), pages 1-13, February.
    20. Gábor Horváth & Attila Bai & Sándor Szegedi & István Lázár & Csongor Máthé & László Huzsvai & Máté Zakar & Zoltán Gabnai & Tamás Tóth, 2023. "A Comprehensive Review of the Distinctive Tendencies of the Diffusion of E-Mobility in Central Europe," Energies, MDPI, vol. 16(14), pages 1-29, July.

    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:283:y:2023:i:c:s0360544223024635. 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.