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Optimal vehicle to grid planning and scheduling using double layer multi-objective algorithm

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  • Tan, Kang Miao
  • Ramachandaramurthy, Vigna K.
  • Yong, Jia Ying

Abstract

Vehicle to grid is a revolutionary technology that allows energy exchange between electric vehicles and power grid for mutual advantages. The implementation of appropriate vehicle to grid energy management system can maximize the potential of electric vehicles to provide grid ancillary services. This paper proposes an optimal vehicle to grid planning and scheduling by utilizing a novel double layer multi-objective algorithm. This optimization algorithm utilizes the grid-connected electric vehicles to perform peak load shaving and load levelling services to minimize the power grid load variance in the first layer optimization. Meanwhile, the second layer optimization minimizes the reactive power compensation for grid voltage regulation and therefore, optimizes the vehicle to grid charger's capacitor sizing. The second layer optimization algorithm utilizes an approximated formula from the simulation of a vehicle to grid charger. The proposed vehicle to grid optimization algorithm considers various power grid and electric vehicle constraints for practicality purpose. With the real time implementation of the proposed algorithm, the optimization results show that the power load curve is effectively followed the preset constant target loading, while the grid voltage is successfully regulated to the predetermined voltage level with minimal amount of reactive power supply from the optimal charger's capacitor.

Suggested Citation

  • Tan, Kang Miao & Ramachandaramurthy, Vigna K. & Yong, Jia Ying, 2016. "Optimal vehicle to grid planning and scheduling using double layer multi-objective algorithm," Energy, Elsevier, vol. 112(C), pages 1060-1073.
  • Handle: RePEc:eee:energy:v:112:y:2016:i:c:p:1060-1073
    DOI: 10.1016/j.energy.2016.07.008
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    1. Tan, Kang Miao & Ramachandaramurthy, Vigna K. & Yong, Jia Ying, 2016. "Integration of electric vehicles in smart grid: A review on vehicle to grid technologies and optimization techniques," Renewable and Sustainable Energy Reviews, Elsevier, vol. 53(C), pages 720-732.
    2. Noori, Mehdi & Gardner, Stephanie & Tatari, Omer, 2015. "Electric vehicle cost, emissions, and water footprint in the United States: Development of a regional optimization model," Energy, Elsevier, vol. 89(C), pages 610-625.
    3. Zhong, Jin & He, Lina & Li, Canbing & Cao, Yijia & Wang, Jianhui & Fang, Baling & Zeng, Long & Xiao, Guoxuan, 2014. "Coordinated control for large-scale EV charging facilities and energy storage devices participating in frequency regulation," Applied Energy, Elsevier, vol. 123(C), pages 253-262.
    4. Noori, Mehdi & Zhao, Yang & Onat, Nuri C. & Gardner, Stephanie & Tatari, Omer, 2016. "Light-duty electric vehicles to improve the integrity of the electricity grid through Vehicle-to-Grid technology: Analysis of regional net revenue and emissions savings," Applied Energy, Elsevier, vol. 168(C), pages 146-158.
    5. Prebeg, Pero & Gasparovic, Goran & Krajacic, Goran & Duic, Neven, 2016. "Long-term energy planning of Croatian power system using multi-objective optimization with focus on renewable energy and integration of electric vehicles," Applied Energy, Elsevier, vol. 184(C), pages 1493-1507.
    6. Yong, Jia Ying & Ramachandaramurthy, Vigna K. & Tan, Kang Miao & Mithulananthan, N., 2015. "A review on the state-of-the-art technologies of electric vehicle, its impacts and prospects," Renewable and Sustainable Energy Reviews, Elsevier, vol. 49(C), pages 365-385.
    7. Yang, Jun & He, Lifu & Fu, Siyao, 2014. "An improved PSO-based charging strategy of electric vehicles in electrical distribution grid," Applied Energy, Elsevier, vol. 128(C), pages 82-92.
    8. Amirioun, Mohammad Hassan & Kazemi, Ahad, 2014. "A new model based on optimal scheduling of combined energy exchange modes for aggregation of electric vehicles in a residential complex," Energy, Elsevier, vol. 69(C), pages 186-198.
    9. Sousa, Tiago & Morais, Hugo & Vale, Zita & Castro, Rui, 2015. "A multi-objective optimization of the active and reactive resource scheduling at a distribution level in a smart grid context," Energy, Elsevier, vol. 85(C), pages 236-250.
    10. Tolga Ercan & Mehdi Noori & Yang Zhao & Omer Tatari, 2016. "On the Front Lines of a Sustainable Transportation Fleet: Applications of Vehicle-to-Grid Technology for Transit and School Buses," Energies, MDPI, vol. 9(4), pages 1-22, March.
    11. Luo, Yugong & Zhu, Tao & Wan, Shuang & Zhang, Shuwei & Li, Keqiang, 2016. "Optimal charging scheduling for large-scale EV (electric vehicle) deployment based on the interaction of the smart-grid and intelligent-transport systems," Energy, Elsevier, vol. 97(C), pages 359-368.
    12. Novosel, T. & Perković, L. & Ban, M. & Keko, H. & Pukšec, T. & Krajačić, G. & Duić, N., 2015. "Agent based modelling and energy planning – Utilization of MATSim for transport energy demand modelling," Energy, Elsevier, vol. 92(P3), pages 466-475.
    13. Pavić, Ivan & Capuder, Tomislav & Kuzle, Igor, 2015. "Value of flexible electric vehicles in providing spinning reserve services," Applied Energy, Elsevier, vol. 157(C), pages 60-74.
    14. Zhao, Yang & Tatari, Omer, 2015. "A hybrid life cycle assessment of the vehicle-to-grid application in light duty commercial fleet," Energy, Elsevier, vol. 93(P2), pages 1277-1286.
    15. Karan, Ebrahim & Asadi, Somayeh & Ntaimo, Lewis, 2016. "A stochastic optimization approach to reduce greenhouse gas emissions from buildings and transportation," Energy, Elsevier, vol. 106(C), pages 367-377.
    16. Tarroja, Brian & Zhang, Li & Wifvat, Van & Shaffer, Brendan & Samuelsen, Scott, 2016. "Assessing the stationary energy storage equivalency of vehicle-to-grid charging battery electric vehicles," Energy, Elsevier, vol. 106(C), pages 673-690.
    17. Kamankesh, Hamidreza & Agelidis, Vassilios G. & Kavousi-Fard, Abdollah, 2016. "Optimal scheduling of renewable micro-grids considering plug-in hybrid electric vehicle charging demand," Energy, Elsevier, vol. 100(C), pages 285-297.
    18. Ercan, Tolga & Zhao, Yang & Tatari, Omer & Pazour, Jennifer A., 2015. "Optimization of transit bus fleet's life cycle assessment impacts with alternative fuel options," Energy, Elsevier, vol. 93(P1), pages 323-334.
    19. Salah, Florian & Ilg, Jens P. & Flath, Christoph M. & Basse, Hauke & Dinther, Clemens van, 2015. "Impact of electric vehicles on distribution substations: A Swiss case study," Applied Energy, Elsevier, vol. 137(C), pages 88-96.
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    4. Li, Shuangqi & Zhao, Pengfei & Gu, Chenghong & Huo, Da & Zeng, Xianwu & Pei, Xiaoze & Cheng, Shuang & Li, Jianwei, 2022. "Online battery-protective vehicle to grid behavior management," Energy, Elsevier, vol. 243(C).
    5. 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.
    6. Tan, Kang Miao & Ramachandaramurthy, Vigna K. & Yong, Jia Ying & Tariq, Mohd, 2021. "Experimental verification of a flexible vehicle-to-grid charger for power grid load variance reduction," Energy, Elsevier, vol. 228(C).
    7. Das, Ridoy & Wang, Yue & Putrus, Ghanim & Kotter, Richard & Marzband, Mousa & Herteleer, Bert & Warmerdam, Jos, 2020. "Multi-objective techno-economic-environmental optimisation of electric vehicle for energy services," Applied Energy, Elsevier, vol. 257(C).
    8. Vamsi Krishna Reddy, Aala Kalananda & Venkata Lakshmi Narayana, Komanapalli, 2022. "Meta-heuristics optimization in electric vehicles -an extensive review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 160(C).
    9. Li, Shuangqi & Gu, Chenghong & Zeng, Xianwu & Zhao, Pengfei & Pei, Xiaoze & Cheng, Shuang, 2021. "Vehicle-to-grid management for multi-time scale grid power balancing," Energy, Elsevier, vol. 234(C).
    10. Ma, Haiping & Yang, Zhile & You, Pengcheng & Fei, Minrui, 2017. "Multi-objective biogeography-based optimization for dynamic economic emission load dispatch considering plug-in electric vehicles charging," Energy, Elsevier, vol. 135(C), pages 101-111.
    11. Colmenar-Santos, Antonio & Muñoz-Gómez, Antonio-Miguel & Rosales-Asensio, Enrique & López-Rey, África, 2019. "Electric vehicle charging strategy to support renewable energy sources in Europe 2050 low-carbon scenario," Energy, Elsevier, vol. 183(C), pages 61-74.
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