A Two-Stage Multi-objective Planning Strategy for Electric Vehicle Charging Stations Considering Power-loss Sensitivity in Distribution System

2018 ◽  
Author(s):  
Xinyi Zhao ◽  
Xinwei Shen ◽  
Hongkun Chen ◽  
Tian Xia ◽  
Oinglai Guo ◽  
...  
Keyword(s):  
Electric Vehicle ◽  
Distribution System ◽  
Power Loss ◽  
Two Stage ◽  
Planning Strategy ◽  
Multi Objective ◽  
Electric Vehicle Charging ◽  
Vehicle Charging ◽  
Charging Stations

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

Smart Cities ◽  
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.

Use of municipal real estate for the construction of public electric vehicle charging stations – legal and economic issues

2020 ◽  
Vol III (III) ◽  
pp. 7-21
Author(s):  
Wojciech Drożdż ◽  
Maciej Szmigiero ◽  
Jakub Dowejko
Keyword(s):  
Real Estate ◽  
Electric Vehicle ◽  
Power Distribution ◽  
Distribution System ◽  
Local Governments ◽  
Smart Cities ◽  
Power Distribution System ◽  
Electric Vehicle Charging ◽  
Vehicle Charging ◽  
Charging Stations

The development of electromobility is part of a broader trend of building smart cities, in which power distribution system operators actively participate. The fact that the legislator has delegated part of the tasks related to the construction of electric vehicle charging infrastructure to these entities should also mean equipping them with legal mechanisms for the implementation of public objectives, including those based on the provisions of the Real Estate Management Act. However, due to the imperfection of the regulations, these entities do not have the tools to preferentially purchase real estate for the development of charging stations, and the local governments lack the basis for making donations for this purpose. However, distribution system operators together with local authorities are natural partners in promoting electromobility in cities.

scholarly journals Optimal Network Reconfiguration with Distributed Generation and Electric Vehicle Charging Stations

2021 ◽  
Vol 6 (4) ◽  
pp. 1174-1185
Author(s):  
Surender Reddy Salkuti
Keyword(s):  
Renewable Energy ◽  
Electric Vehicle ◽  
Distributed Generation ◽  
Network Reconfiguration ◽  
Multi Objective ◽  
Electric Vehicle Charging ◽  
Optimal Network ◽  
Vehicle Charging ◽  
Charging Stations ◽  
Single Objective

This paper proposes an optimal network reconfiguration (ONR) by integrating the renewable energy (RE) based distributed generation (DG) resources, i.e., wind and solar photovoltaic (PV) modules, and electric vehicle charging stations (EVCS). The uncertainties related to renewable energy sources (RESs) are handled by using probability analysis. In this work, wind uncertainty is handled by using Weibull probability density function (PDF), and solar PV uncertainty is modeled by using Beta PDF. This paper also models the load of EVCSs. The ONR is a tool to operate distribution systems (DSs) at optimum cost/loss. In the literature, most of the ONR problems are solved as single objective type. This neccessiate the development of multi-objective based ONR problem and solved using the multi-objective algorithms by considering multiple objectives. Therefore in this paper, total cost of operation and power losses are considered as two objectives functions. The single objective-based ONR is solved using crow search algorithm (CSA) and multi-objective-based ONR is solved using multi-objective-based CSA. As the DS is unbalanced, the power flow for the unbalanced system will include the three-phase transformer. The ONR problem has been solved by considering 17 bus unbalanced and balanced DSs.

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