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Stochastic Analysis for Forecasting the MW Load of Plug-In Electric Vehicles

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Swarm, Evolutionary, and Memetic Computing (SEMCCO 2013)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 8298))

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Abstract

This paper proposes a Monte Carlo analysis for forecasting the MW load of plug-in electric vehicles. The method considers the number of vehicles in a city, Wh/km, km per vehicle, vehicles on chargers, and power factor of chargers. Using the Monte Carlo method, the range of the MW load is forecasted, considering the associated ranges of the various parameters and variables.

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Author information

Authors and Affiliations

  1. Indian Institute of Technology, Delhi, India

    C. S. Indulkar

  2. Airports Authority of India, Delhi, India

    K. Ramalingam

Authors
  1. C. S. Indulkar
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  2. K. Ramalingam
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Editor information

Editors and Affiliations

  1. Electrical Engineering Dept, IIT Delhi, Hauz Khas, 110016, New Delhi, India

    Bijaya Ketan Panigrahi

  2. School of Electrical and Electronic Engineering, Nanyang Technological University, 639798, Singapore

    Ponnuthurai Nagaratnam Suganthan

  3. Electronics and Communication Sciences Unit, Indian Statistical Institute, 700108, Kolkata, India

    Swagatam Das

  4. SRM Engineering College, Department of Electrical and Electronics Engineering, SRM University, Potheri, Kattankulathur, 603203, Kancheepuram, Tamil Nadu, India

    Shubhransu Sekhar Dash

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© 2013 Springer International Publishing Switzerland

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Indulkar, C.S., Ramalingam, K. (2013). Stochastic Analysis for Forecasting the MW Load of Plug-In Electric Vehicles. In: Panigrahi, B.K., Suganthan, P.N., Das, S., Dash, S.S. (eds) Swarm, Evolutionary, and Memetic Computing. SEMCCO 2013. Lecture Notes in Computer Science, vol 8298. Springer, Cham. https://doi.org/10.1007/978-3-319-03756-1_21

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  • DOI: https://doi.org/10.1007/978-3-319-03756-1_21

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-03755-4

  • Online ISBN: 978-3-319-03756-1

  • eBook Packages: Computer ScienceComputer Science (R0)

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