Impact of electric vehicle charging systems on low voltage distribution networks

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.

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Impact of unbalanced electric vehicle charging on low-voltage grids

2020 IEEE PES Innovative Smart Grid Technologies Europe (ISGT-Europe) ◽

10.1109/isgt-europe47291.2020.9248754 ◽

2020 ◽

Author(s):

Sebastian Helm ◽

Ines Hauer ◽

Martin Wolter ◽

Christoph Wenge ◽

Stephan Balischewski ◽

...

Keyword(s):

Electric Vehicle ◽

Low Voltage ◽

Electric Vehicle Charging ◽

Vehicle Charging

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Sparse Measurement-Based Coordination of Electric Vehicle Charging Stations to Manage Congestions in Low Voltage Grids

Smart Cities ◽

10.3390/smartcities4010002 ◽

2020 ◽

Vol 4 (1) ◽

pp. 17-40

Author(s):

Daniel-Leon Schultis

Keyword(s):

Electric Vehicle ◽

Distribution System ◽

Low Voltage ◽

Congestion Management ◽

Load Flow ◽

Detection Accuracy ◽

System State ◽

Electric Vehicle Charging ◽

Vehicle Charging ◽

Charging Stations

The increasing use of distributed generation and electric vehicle charging stations provokes violations of the operational limits in low voltage grids. The mitigation of voltage limit violations is addressed by Volt/var control strategies, while thermal overload is avoided by using congestion management. Congestions in low voltage grids can be managed by coordinating the active power contributions of the connected elements. As a prerequisite, the system state must be carefully observed. This study presents and investigates a method for the sparse measurement-based detection of feeder congestions that bypasses the major hurdles of distribution system state estimation. Furthermore, the developed method is used to enable congestion management by the centralized coordination of the distributed electric vehicle charging stations. Different algorithms are presented and tested by conducting load flow simulations on a real urban low voltage grid for several scenarios. Results show that the proposed method reliably detects all congestions, but in some cases, overloads are detected when none are present. A minimal detection accuracy of 73.07% is found across all simulations. The coordination algorithms react to detected congestions by reducing the power consumption of the corresponding charging stations. When properly designed, this strategy avoids congestions reliably but conservatively. Unnecessary reduction of the charging power may occur. In total, the presented solution offers an acceptable performance while requiring low implementation effort; no complex adaptations are required after grid reinforcement and expansion.

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