IDEAS home Printed from https://ideas.repec.org/a/eee/appene/v300y2021ics0306261921008242.html
   My bibliography  Save this article

A hybrid robust-stochastic framework for strategic scheduling of integrated wind farm and plug-in hybrid electric vehicle fleets

Author

Listed:
  • Zeynali, Saeed
  • Nasiri, Nima
  • Marzband, Mousa
  • Ravadanegh, Sajad Najafi

Abstract

This paper focuses on cooperative scheduling of the integrated plug-in hybrid electric vehicle fleets and wind farm system (IWPHEVS) in the day-ahead wholesale market (DWM), as well as its effects on the market outcomes and price, as a price-maker player. In this regard, a multi-objective two-stage bi-level hybrid stochastic-robust offering/bidding and scheduling strategy is developed. The upper-level problem, which is that of the IWPHEVS operator, encompasses two objectives, namely cost and emission. The cost objective is comprised of operational costs and the cost of power that is purchased in DWM. Additionally, the plug-in hybrid electric vehicles (PHEVs) are congregated into distinct fleets through k-means clustering. To inscribe PHEVs’ battery erosion, a comprehensive battery erosion model is comprehended, which is linearized by semi-integer variables. The uncertain data sets, such as vehicle fleets arrival/departure timings and their travelled miles are represented as scenarios according to their empirical distribution, which is acquired from the National household travel survey (NHTS). On the flip side, the wind power, which is a more unpredictable parameter, is designed as a robust optimization (RO) set, as it is apt to enhance the reliability issues regarding wind volatilities. The lower-level, embodies the wholesale market operator that has the objective of maximizing social welfare. Conclusively, different case studies of dump, smart and multi-objective charging are meticulously investigated to testify the potency of the proposed method. Based on the obtained findings on the proposed smart multi-objective framework, the IWPHEVS as a price-maker player, can manipulate locational marginal price as much as 4.4%, while the emissions can be curtailed by 40%.

Suggested Citation

  • Zeynali, Saeed & Nasiri, Nima & Marzband, Mousa & Ravadanegh, Sajad Najafi, 2021. "A hybrid robust-stochastic framework for strategic scheduling of integrated wind farm and plug-in hybrid electric vehicle fleets," Applied Energy, Elsevier, vol. 300(C).
    • Handle: RePEc:eee:appene:v:300:y:2021:i:c:s0306261921008242
    DOI: 10.1016/j.apenergy.2021.117432
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0306261921008242
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.apenergy.2021.117432?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. Nimalsiri, Nanduni I. & Ratnam, Elizabeth L. & Mediwaththe, Chathurika P. & Smith, David B. & Halgamuge, Saman K., 2021. "Coordinated charging and discharging control of electric vehicles to manage supply voltages in distribution networks: Assessing the customer benefit," Applied Energy, Elsevier, vol. 291(C).
    2. Abbasi, Mohammad Hossein & Taki, Mehrdad & Rajabi, Amin & Li, Li & Zhang, Jiangfeng, 2019. "Coordinated operation of electric vehicle charging and wind power generation as a virtual power plant: A multi-stage risk constrained approach," Applied Energy, Elsevier, vol. 239(C), pages 1294-1307.
    3. Zhang, Bingying & Li, Qiqiang & Wang, Luhao & Feng, Wei, 2018. "Robust optimization for energy transactions in multi-microgrids under uncertainty," Applied Energy, Elsevier, vol. 217(C), pages 346-360.
    4. Li, Yang & Yang, Zhen & Li, Guoqing & Mu, Yunfei & Zhao, Dongbo & Chen, Chen & Shen, Bo, 2018. "Optimal scheduling of isolated microgrid with an electric vehicle battery swapping station in multi-stakeholder scenarios: A bi-level programming approach via real-time pricing," Applied Energy, Elsevier, vol. 232(C), pages 54-68.
    5. Kucevic, Daniel & Englberger, Stefan & Sharma, Anurag & Trivedi, Anupam & Tepe, Benedikt & Schachler, Birgit & Hesse, Holger & Srinivasan, Dipti & Jossen, Andreas, 2021. "Reducing grid peak load through the coordinated control of battery energy storage systems located at electric vehicle charging parks," Applied Energy, Elsevier, vol. 295(C).
    6. Welzel, Fynn & Klinck, Carl-Friedrich & Pohlmann, Yannick & Bednarczyk, Mats, 2021. "Grid and user-optimized planning of charging processes of an electric vehicle fleet using a quantitative optimization model," Applied Energy, Elsevier, vol. 290(C).
    7. Guo, Ningyuan & Zhang, Xudong & Zou, Yuan & Guo, Lingxiong & Du, Guodong, 2021. "Real-time predictive energy management of plug-in hybrid electric vehicles for coordination of fuel economy and battery degradation," Energy, Elsevier, vol. 214(C).
    8. Ran, Cuiling & Zhang, Yanzi & Yin, Ying, 2021. "Demand response to improve the shared electric vehicle planning: Managerial insights, sustainable benefits," Applied Energy, Elsevier, vol. 292(C).
    9. Tuchnitz, Felix & Ebell, Niklas & Schlund, Jonas & Pruckner, Marco, 2021. "Development and Evaluation of a Smart Charging Strategy for an Electric Vehicle Fleet Based on Reinforcement Learning," Applied Energy, Elsevier, vol. 285(C).
    10. Lyu, Cheng & Jia, Youwei & Xu, Zhao, 2021. "Fully decentralized peer-to-peer energy sharing framework for smart buildings with local battery system and aggregated electric vehicles," Applied Energy, Elsevier, vol. 299(C).
    11. Qiao, Baihao & Liu, Jing, 2020. "Multi-objective dynamic economic emission dispatch based on electric vehicles and wind power integrated system using differential evolution algorithm," Renewable Energy, Elsevier, vol. 154(C), pages 316-336.
    12. Song, Ke & Ding, Yuhang & Hu, Xiao & Xu, Hongjie & Wang, Yimin & Cao, Jing, 2021. "Degradation adaptive energy management strategy using fuel cell state-of-health for fuel economy improvement of hybrid electric vehicle," Applied Energy, Elsevier, vol. 285(C).
    13. Nizami, M.S.H. & Hossain, M.J. & Amin, B.M. Ruhul & Fernandez, Edstan, 2020. "A residential energy management system with bi-level optimization-based bidding strategy for day-ahead bi-directional electricity trading," Applied Energy, Elsevier, vol. 261(C).
    14. Taljegard, M. & Göransson, L. & Odenberger, M. & Johnsson, F., 2019. "Impacts of electric vehicles on the electricity generation portfolio – A Scandinavian-German case study," Applied Energy, Elsevier, vol. 235(C), pages 1637-1650.
    15. Lai, Shuying & Qiu, Jing & Tao, Yuechuan & Zhao, Junhua, 2021. "Risk hedging for gas power generation considering power-to-gas energy storage in three different electricity markets," Applied Energy, Elsevier, vol. 291(C).
    16. Lee, Yerim & Hur, Jin, 2019. "A simultaneous approach implementing wind-powered electric vehicle charging stations for charging demand dispersion," Renewable Energy, Elsevier, vol. 144(C), pages 172-179.
    17. Wang, Shuai & Li, Bin & Li, Guanzheng & Yao, Bin & Wu, Jianzhong, 2021. "Short-term wind power prediction based on multidimensional data cleaning and feature reconfiguration," Applied Energy, Elsevier, vol. 292(C).
    18. Nakaishi, Tomoaki, 2021. "Developing effective CO2 and SO2 mitigation strategy based on marginal abatement costs of coal-fired power plants in China," Applied Energy, Elsevier, vol. 294(C).
    19. Guevara, Esnil & Babonneau, Fréderic & Homem-de-Mello, Tito & Moret, Stefano, 2020. "A machine learning and distributionally robust optimization framework for strategic energy planning under uncertainty," Applied Energy, Elsevier, vol. 271(C).
    20. Daryabari, Mohamad K. & Keypour, Reza & Golmohamadi, Hessam, 2021. "Robust self-scheduling of parking lot microgrids leveraging responsive electric vehicles," Applied Energy, Elsevier, vol. 290(C).
    21. Xu, Yueru & Zheng, Yuan & Yang, Ying, 2021. "On the movement simulations of electric vehicles: A behavioral model-based approach," Applied Energy, Elsevier, vol. 283(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. Alwesabi, Yaseen & Avishan, Farzad & Yanıkoğlu, İhsan & Liu, Zhaocai & Wang, Yong, 2022. "Robust strategic planning of dynamic wireless charging infrastructure for electric buses," Applied Energy, Elsevier, vol. 307(C).
    2. Sun, Yunpeng & Razzaq, Asif & Sun, Huaping & Irfan, Muhammad, 2022. "The asymmetric influence of renewable energy and green innovation on carbon neutrality in China: Analysis from non-linear ARDL model," Renewable Energy, Elsevier, vol. 193(C), pages 334-343.
    3. Sun, Shitong & Kazemi-Razi, S. Mahdi & Kaigutha, Lisa G. & Marzband, Mousa & Nafisi, Hamed & Al-Sumaiti, Ameena Saad, 2022. "Day-ahead offering strategy in the market for concentrating solar power considering thermoelectric decoupling by a compressed air energy storage," Applied Energy, Elsevier, vol. 305(C).
    4. Bagheri Tookanlou, Mahsa & Pourmousavi, S. Ali & Marzband, Mousa, 2023. "A three-layer joint distributionally robust chance-constrained framework for optimal day-ahead scheduling of e-mobility ecosystem," Applied Energy, Elsevier, vol. 331(C).
    5. Ming, Fangzhu & Gao, Feng & Liu, Kun & Li, Xingqi, 2023. "A constrained DRL-based bi-level coordinated method for large-scale EVs charging," Applied Energy, Elsevier, vol. 331(C).
    6. Zeynali, Saeed & Nasiri, Nima & Ravadanegh, Sajad Najafi & Marzband, Mousa, 2022. "A three-level framework for strategic participation of aggregated electric vehicle-owning households in local electricity and thermal energy markets," Applied Energy, Elsevier, vol. 324(C).
    7. Khalili, Reza & Khaledi, Arian & Marzband, Mousa & Nematollahi, Amin Foroughi & Vahidi, Behrooz & Siano, Pierluigi, 2023. "Robust multi-objective optimization for the Iranian electricity market considering green hydrogen and analyzing the performance of different demand response programs," Applied Energy, Elsevier, vol. 334(C).
    8. Saleh Aghajan-Eshkevari & Sasan Azad & Morteza Nazari-Heris & Mohammad Taghi Ameli & Somayeh Asadi, 2022. "Charging and Discharging of Electric Vehicles in Power Systems: An Updated and Detailed Review of Methods, Control Structures, Objectives, and Optimization Methodologies," Sustainability, MDPI, vol. 14(4), pages 1-31, February.
    9. Shan, Lian-Zhu & Yamane, Kenichiro & Ono, Tetsushi & Kawamura, Tsutomu & Wu, Wen-Chuan & Hu, Ze-Chun & Wang, Qi & Wen, Yi-Lin, 2024. "Distributed Energy Resource Management System with improved convergence," Applied Energy, Elsevier, vol. 371(C).
    10. Dey, Bishwajit & Misra, Srikant & Garcia Marquez, Fausto Pedro, 2023. "Microgrid system energy management with demand response program for clean and economical operation," Applied Energy, Elsevier, vol. 334(C).
    11. Sadeghi, Delnia & Ahmadi, Seyed Ehsan & Amiri, Nima & Satinder, & Marzband, Mousa & Abusorrah, Abdullah & Rawa, Muhyaddin, 2022. "Designing, optimizing and comparing distributed generation technologies as a substitute system for reducing life cycle costs, CO2 emissions, and power losses in residential buildings," Energy, Elsevier, vol. 253(C).
    12. Zhao, Yang & Wang, Zhenpo & Shen, Zuo-Jun Max & Zhang, Lei & Dorrell, David G. & Sun, Fengchun, 2022. "Big data-driven decoupling framework enabling quantitative assessments of electric vehicle performance degradation," Applied Energy, Elsevier, vol. 327(C).
    13. Zeng, Ziling & Wang, Tingsong & Qu, Xiaobo, 2024. "En-route charge scheduling for an electric bus network: Stochasticity and real-world practice," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 185(C).
    14. Tostado-Véliz, Marcos & Jordehi, Ahmad Rezaee & Mansouri, Seyed Amir & Jurado, Francisco, 2023. "A two-stage IGDT-stochastic model for optimal scheduling of energy communities with intelligent parking lots," Energy, Elsevier, vol. 263(PD).
    15. Golmohamadi, Hessam, 2022. "Demand-side management in industrial sector: A review of heavy industries," Renewable and Sustainable Energy Reviews, Elsevier, vol. 156(C).
    16. Park, Sung-Won & Yu, Jung-Un & Lee, Jin-Wook & Son, Sung-Yong, 2024. "A comprehensive review of battery-based power service applications considering degradation: Research status and model integration," Applied Energy, Elsevier, vol. 374(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. 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.
    2. Guo, Shiliang & Li, Pengpeng & Ma, Kai & Yang, Bo & Yang, Jie, 2022. "Robust energy management for industrial microgrid considering charging and discharging pressure of electric vehicles," Applied Energy, Elsevier, vol. 325(C).
    3. Wang, Han & Yan, Jie & Han, Shuang & Liu, Yongqian, 2020. "Switching strategy of the low wind speed wind turbine based on real-time wind process prediction for the integration of wind power and EVs," Renewable Energy, Elsevier, vol. 157(C), pages 256-272.
    4. 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).
    5. Azim, M. Imran & Tushar, Wayes & Saha, Tapan K. & Yuen, Chau & Smith, David, 2022. "Peer-to-peer kilowatt and negawatt trading: A review of challenges and recent advances in distribution networks," Renewable and Sustainable Energy Reviews, Elsevier, vol. 169(C).
    6. Amjad, Muhammad & Farooq-i-Azam, Muhammad & Ni, Qiang & Dong, Mianxiong & Ansari, Ejaz Ahmad, 2022. "Wireless charging systems for electric vehicles," Renewable and Sustainable Energy Reviews, Elsevier, vol. 167(C).
    7. Tao, Yuechuan & Qiu, Jing & Lai, Shuying & Sun, Xianzhuo & Zhao, Junhua & Zhou, Baorong & Cheng, Lanfen, 2022. "Data-driven on-demand energy supplement planning for electric vehicles considering multi-charging/swapping services," Applied Energy, Elsevier, vol. 311(C).
    8. Qiu, Haifeng & Gu, Wei & Liu, Pengxiang & Sun, Qirun & Wu, Zhi & Lu, Xi, 2022. "Application of two-stage robust optimization theory in power system scheduling under uncertainties: A review and perspective," Energy, Elsevier, vol. 251(C).
    9. Saleh Aghajan-Eshkevari & Sasan Azad & Morteza Nazari-Heris & Mohammad Taghi Ameli & Somayeh Asadi, 2022. "Charging and Discharging of Electric Vehicles in Power Systems: An Updated and Detailed Review of Methods, Control Structures, Objectives, and Optimization Methodologies," Sustainability, MDPI, vol. 14(4), pages 1-31, February.
    10. Nandan Gopinathan & Prabhakar Karthikeyan Shanmugam, 2022. "Energy Anxiety in Decentralized Electricity Markets: A Critical Review on EV Models," Energies, MDPI, vol. 15(14), pages 1-40, July.
    11. Li, Mengyu & Lenzen, Manfred & Wang, Dai & Nansai, Keisuke, 2020. "GIS-based modelling of electric-vehicle–grid integration in a 100% renewable electricity grid," Applied Energy, Elsevier, vol. 262(C).
    12. Jin, Ruiyang & Zhou, Yuke & Lu, Chao & Song, Jie, 2022. "Deep reinforcement learning-based strategy for charging station participating in demand response," Applied Energy, Elsevier, vol. 328(C).
    13. Sehyeon Kim & Markus Holz & Soojin Park & Yongbeum Yoon & Eunchel Cho & Junsin Yi, 2021. "Future Options for Lightweight Photovoltaic Modules in Electrical Passenger Cars," Sustainability, MDPI, vol. 13(5), pages 1-7, February.
    14. Bogdanov, Dmitrii & Breyer, Christian, 2024. "Role of smart charging of electric vehicles and vehicle-to-grid in integrated renewables-based energy systems on country level," Energy, Elsevier, vol. 301(C).
    15. Hur, Jin, 2021. "Potential capacity factor estimates of wind generating resources for transmission planning," Renewable Energy, Elsevier, vol. 179(C), pages 1742-1750.
    16. Maria Taljegard & Lisa Göransson & Mikael Odenberger & Filip Johnsson, 2021. "To Represent Electric Vehicles in Electricity Systems Modelling—Aggregated Vehicle Representation vs. Individual Driving Profiles," Energies, MDPI, vol. 14(3), pages 1-25, January.
    17. Wang, Dongxiao & Qiu, Jing & Reedman, Luke & Meng, Ke & Lai, Loi Lei, 2018. "Two-stage energy management for networked microgrids with high renewable penetration," Applied Energy, Elsevier, vol. 226(C), pages 39-48.
    18. Zhang, Jiyuan & Tang, Hailong & Chen, Min, 2019. "Linear substitute model-based uncertainty analysis of complicated non-linear energy system performance (case study of an adaptive cycle engine)," Applied Energy, Elsevier, vol. 249(C), pages 87-108.
    19. Da Li & Shijie Zhang & Yunhan Xiao, 2020. "Interval Optimization-Based Optimal Design of Distributed Energy Resource Systems under Uncertainties," Energies, MDPI, vol. 13(13), pages 1-18, July.
    20. Zhou, Yu & Li, Zhengshuo & Wang, Guangrui, 2021. "Study on leveraging wind farms' robust reactive power range for uncertain power system reactive power optimization," Applied Energy, Elsevier, vol. 298(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:300:y:2021:i:c:s0306261921008242. 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.