A simplified control algorithm for utilities to utilize plug-in electric vehicles to reduce distribution transformer overloading

Shokrzadeh, Shahab; Ribberink, Hajo; Rishmawi, Issa; Entchev, Evgueniy

doi:10.1016/j.energy.2017.04.152

Cited by 28 publications

(13 citation statements)

References 13 publications

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“…Several studies have investigated the optimal charging of electric vehicles and the provision of V2G services for peak power and ancillary markets [21][22][23][24][25][26][27][28][29][30][31][32][33]. In these studies, the objectives of the control algorithms vary significantly between maximizing economic factors and minimizing the impact on the power network.…”

Section: State Of the Art In Ev Scheduling And V2g Optimization For Nmentioning

confidence: 99%

Optimal Pricing of Vehicle-to-Grid Services Using Disaggregate Demand Models

2021

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The recent revolution in electric mobility is both crucial and promising in the coordinated effort to reduce global emissions and tackle climate change. However, mass electrification brings up new technical problems that need to be solved. The increasing penetration rates of electric vehicles will add an unprecedented energy load to existing power grids. The stability and the quality of power systems, especially on a local distribution level, will be compromised by multiple vehicles that are simultaneously connected to the grid. In this paper, the authors propose a choice-based pricing algorithm to indirectly control the charging and V2G activities of electric vehicles in non-residential facilities. Two metaheuristic approaches were applied to solve the optimization problem, and a comparative analysis was performed to evaluate their performance. The proposed algorithm would result in a significant revenue increase for the parking operator, and at the same time, it could alleviate the overloading of local distribution transformers and postpone heavy infrastructure investments.

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Section: State Of the Art In Ev Scheduling And V2g Optimization For Nmentioning

confidence: 99%

Optimal Pricing of Vehicle-to-Grid Services Using Disaggregate Demand Models

2021

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“…Another study has illustrated that EVs generate overload and shape impulses. Such grid problems have been solved through timetable changes and transformer hierarchy, as shown by MATLAB V9.5 software [22,23]. The solving method can change in each location, depending on related problem conditions, therefore, there (There will be various conditions at hand).…”

Section: Transformer Selectionmentioning

confidence: 99%

Electric Vehicle Charge Stations Location Analysis and Determination—Ankara (Turkey) Case Study

et al. 2019

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Locating electric vehicle charge stations has always been an important problem for electric distributers. Many basic and complex solutions have been provided by algorithms and methods to solve this problem in real and assumed grids. However, the data, which has been used in those algorithms, are not consistent with the diversity of locations, thus, do not meet the expected results. Grid locations are the most important aspects of this issue in the eyes of designers, investors, and the general public. Locating charge stations must be determined by plans which have influenced majority in the society. In some countries, power quality has been increased by storages, which are used in vehicle-to-grid (V2G) and similar operations. In this paper, all of the variables for locating charging stations are explained according to Ankara metropolitan. During the implemented analysis and literature reviews, an algorithm, based on location and grid priorities and infrastructures, are 154 kV and 33 kV, have been designed. Genetic algorithms have been used to demonstrate this method even though other algorithms can also be adopted to meet the priority.

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“…In relation to this, this paper considers different voltage control measures and fast charger connection methods to mitigate the impacts of some of these challenges. In addition, several other studies suggested the implementation of smart charging techniques and vehicle-to-grid (V2G) interfaces to control the EV charging [21], [28], [29]; however, these methods increase the cost and complexity of the systems [21].…”

Section: B Impacts Of Fast Chargers On Electrical Gridsmentioning

confidence: 99%

Using Electric Vehicles and Demand Side Response to Unlock Distribution Network Flexibility

Sonder

Cipcigan

Ugalde‐Loo

2019

2019 IEEE Milan PowerTech

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The transportation sector is one of the largest sources of greenhouse gas emissions. This has encouraged governments worldwide to fund the development of ultra-low carbon emission vehicles and replace internal combustion engine (ICE) vehicles with electric vehicles (EVs). Among EV drivers, 'range anxiety' is one of the main issues resulting from long charging durations. The reduction of charging duration by the introduction of DC fast/rapid charging stations is widely discussed in the literature. However, high charging demands due to fast charging stations may cause some challenges for power networks. In this paper, the impacts of different types of fast chargers on a UK generic distribution network are investigated. The most suitable and robust connection points of the network where fast chargers can be deployed are identified without affecting the stability and security of the system. The main findings show that network losses increase, voltages operate beyond strict limits, and system equipment becomes overloaded with increased fast charging activities in the network. Therefore, critical network points are reinforced with distributed generation units (DG) and static VAr compensator (SVC) devices to improve the system reliability and mitigate the impacts of such challenges.

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A simplified control algorithm for utilities to utilize plug-in electric vehicles to reduce distribution transformer overloading

Cited by 28 publications

References 13 publications

Optimal Pricing of Vehicle-to-Grid Services Using Disaggregate Demand Models

Optimal Pricing of Vehicle-to-Grid Services Using Disaggregate Demand Models

Electric Vehicle Charge Stations Location Analysis and Determination—Ankara (Turkey) Case Study

Using Electric Vehicles and Demand Side Response to Unlock Distribution Network Flexibility

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