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  4. datafev - A Python framework for development and testing of management algorithms for electric vehicle charging infrastructures
 
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2023
Journal Article
Title

datafev - A Python framework for development and testing of management algorithms for electric vehicle charging infrastructures

Abstract
datafev is an open-source Python framework for developing and testing management strategies for electric vehicle (EV) charging. It includes several algorithms related to EV charging such as schedule optimization, and reference routines to generate charging events based on statistical inputs such as conditional probability distributions of arrival/departure times. datafev provides reference dynamic simulation routines to represent the temporal and logical sequence of the events taking place in an EV charging environment including EV drivers, aggregators, and charger cluster operators. An illustrative code example demonstrates the framework's use for testing user-defined energy management strategies.
Author(s)
Gümrükcü, Erdem
Ahmadifar, Amir
Yavuzer, Aytug
Ponci, Ferdinanda
Monti, Antonello  
Fraunhofer-Institut für Angewandte Informationstechnik FIT  
Journal
Software impacts  
DOI
10.1016/j.simpa.2023.100467
Language
English
Fraunhofer-Institut für Angewandte Informationstechnik FIT  
Keyword(s)
  • Dynamic simulations

  • Electric vehicle charging infrastructure

  • Optimization

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