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Optimal Design and Planning of Electric Vehicles Within Microgrid

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Advanced Computational Methods in Energy, Power, Electric Vehicles, and Their Integration (ICSEE 2017, LSMS 2017)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 763))

Abstract

Optimal allocation and economic dispatch of the distributed generators (DGs) and electric vehicles (EVs) are very important to achieve resilience operating of future microgrids. This paper presents a new energy management concept of interfacing EV charging stations with the microgrids. Optimal scheduling operation of DGs and the EVs is used to minimize the total combined operating and emission costs of a hybrid microgrid. The problem was solved using a mixed integer quadratic programming (MIQP) approach. Different kinds of distributed generators with realistic constraints and charging stations for various EVs with the view to optimizing the overall microgrid performance are investigated. The results have convincingly revealed that discharging EVs could reduce the total cost of the microgrid operation.

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Author information

Authors and Affiliations

  1. Cranfield University, Bedford, MK43 0SX, UK

    Mohammed Alkhafaji & Patrick Luk

  2. Cranfield University, Shrivenham, Swindon, SN6 8LA, UK

    John Economou

Authors
  1. Mohammed Alkhafaji
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  2. Patrick Luk
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  3. John Economou
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Corresponding author

Correspondence to Patrick Luk .

Editor information

Editors and Affiliations

  1. Queen’s University Belfast, Belfast, United Kingdom

    Kang Li

  2. Nanjing Automation Research Institute, Nanjing, China

    Yusheng Xue

  3. Harbin Institute of Technology, Harbin, China

    Shumei Cui

  4. Shanghai University, Shanghai, China

    Qun Niu

  5. Queen’s University Belfast, Belfast, United Kingdom

    Zhile Yang

  6. Cranfield University, Bedford, United Kingdom

    Patrick Luk

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© 2017 Springer Nature Singapore Pte Ltd.

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Alkhafaji, M., Luk, P., Economou, J. (2017). Optimal Design and Planning of Electric Vehicles Within Microgrid. In: Li, K., Xue, Y., Cui, S., Niu, Q., Yang, Z., Luk, P. (eds) Advanced Computational Methods in Energy, Power, Electric Vehicles, and Their Integration. ICSEE LSMS 2017 2017. Communications in Computer and Information Science, vol 763. Springer, Singapore. https://doi.org/10.1007/978-981-10-6364-0_68

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  • DOI: https://doi.org/10.1007/978-981-10-6364-0_68

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-10-6363-3

  • Online ISBN: 978-981-10-6364-0

  • eBook Packages: Computer ScienceComputer Science (R0)

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