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Showing 1 to 5 of 5 for “"Electric Vehicle Charging Demand"”.

  1. Modeling Passenger Electric Vehicle Charging Demand with Machine Learning Using Telematics Data and Temperature

    Electric vehicles (EVs), with their potential to drastically reduce greenhouse gas emissions, pose a problem for energy distribution infrastructure which was not previously designed with hosting capacity capable of handling the additional demand generated by their mass adoption. Understanding when …

    mit Repository record for Modeling Passenger Electric Vehicle Charging Demand with Machine Learning Using Telematics Data and Temperature (opens in a new tab)

  2. Intelligent integration of prosumers with battery energy storage in smart distribution systems using optimal design and a transactive energy framework

    A legacy electric power distribution system is characterized by a unidirectional power flow from centralized power plants to customers. The role of these customers has been known for many years as power consumers and not power producers. In smart distribution systems, because of the widespread use …

    uoit Repository record for Intelligent integration of prosumers with battery energy storage in smart distribution systems using optimal design and a transactive energy framework (opens in a new tab)

  3. Spatio-Temporal Analysis of Urban Data and its Application for Smart Cities

    … diseases, emergency evacuation, share market and electricity demand etc. In this work, we perform spatio-temporal analysis of various urban datasets collected from different urban application areas. We start with presenting a framework for predicting traffic demand around a location of interest …

    vt Repository record for Spatio-Temporal Analysis of Urban Data and its Application for Smart Cities (opens in a new tab)

  4. Modeling and management of dynamic loads in power systems

    Submission published under a 24 month embargo labeled 'U of I Access', the embargo will last until 2019-08-01

    uiuc Repository record for Modeling and management of dynamic loads in power systems (opens in a new tab)