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  4. Optimized Strategic Planning of Future Norwegian Low-Voltage Networks with a Genetic Algorithm Applying Empirical Electric Vehicle Charging Data
 
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2021
Journal Article
Titel

Optimized Strategic Planning of Future Norwegian Low-Voltage Networks with a Genetic Algorithm Applying Empirical Electric Vehicle Charging Data

Abstract
This article outlines methods to facilitate the assessment of the impact of electric vehicle charging on distribution networks at planning stage and applies them to a case study. As network planning is becoming a more complex task, an approach to automated network planning that yields the optimal reinforcement strategy is outlined. Different reinforcement measures are weighted against each other in terms of technical feasibility and costs by applying a genetic algorithm. Traditional reinforcements as well as novel solutions including voltage regulation are considered. To account for electric vehicle charging, a method to determine the uptake in equivalent load is presented. For this, measured data of households and statistical data of electric vehicles are combined in a stochastic analysis to determine the simultaneity factors of household load including electric vehicle charging. The developed methods are applied to an exemplary case study with Norwegian low-voltage networks. Different penetration rates of electric vehicles on a development path until 2040 are considered.
Author(s)
Wruk, J.
Cibis, K.
Resch, M.
Saele, H.
Zdrallek, M.
Zeitschrift
Electricity
DOI
10.3390/electricity2010006
File(s)
N-649165.pdf (2.87 MB)
Language
English
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Fraunhofer-Institut für Solare Energiesysteme ISE
Tags
  • Wasserstofftechnologi...

  • electric vehicle

  • genetic algorithm

  • Power system planning...

  • probabilistic network...

  • Leistungselektronik

  • Netze und Intelligent...

  • intelligentes Netz

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