Optimal location planning method of fast charging station for electric vehicles considering operators, drivers, vehicles, traffic flow and power grid

Kong, Weiwei; Luo, Yugong; Gao, Feng; Li, Keqiang; Peng, Huei

doi:10.1016/j.energy.2019.07.156

Cited by 134 publications

(57 citation statements)

References 22 publications

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“…Nevertheless, their cost is very high and if proper planning is neglected, then they can overload the electrical power system [1]. In [19], fast-charging station planning is done considering cost and traffic in a distribution network. Nash bargaining theory is used to optimize the profit of operators by optimally placing and sizing fast-charging stations in [20].…”

Section: Introductionmentioning

confidence: 99%

Optimal Placement of Electric Vehicle Charging Stations in the Active Distribution Network

et al. 2020

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Electrification of the transportation sector can play a vital role in reshaping smart cities. With an increasing number of electric vehicles (EVs) on the road, deployment of well-planned and efficient charging infrastructure is highly desirable. Unlike level 1 and level 2 charging stations, level 3 chargers are super-fast in charging EVs. However, their installation at every possible site is not techno-economically justifiable because level 3 chargers may cause violation of critical system parameters due to their high power consumption. In this paper, we demonstrate an optimized combination of all three types of EV chargers for efficiently managing the EV load while minimizing installation cost, losses, and distribution transformer loading. Effects of photovoltaic (PV) generation are also incorporated in the analysis. Due to the uncertain nature of vehicle users, EV load is modeled as a stochastic process. Particle swarm optimization (PSO) is used to solve the constrained nonlinear stochastic problem. MATLAB and OpenDSS are used to simulate the model. The proposed idea is validated on the real distribution system of the National University of Sciences and Technology (NUST) Pakistan. Results show that an optimized combination of chargers placed at judicious locations can greatly reduce cost from $3.55 million to $1.99 million, daily losses from 787kWh to 286kWh and distribution transformer congestion from 58% to 22% when compared to scenario of optimized placement of level 3 chargers for 20% penetration level in commercial feeders. In residential feeder, these statistics are improved from $2.52 to $0.81 million, from 2167kWh to 398kWh and from 106% to 14%, respectively. It is also realized that the integration of PV improves voltage profile and reduces the negative impact of EV load. Our optimization model can work for commercial areas such as offices, university campuses, and industries as well as residential colonies. INDEX TERMS Charging stations placement, distribution system, electric vehicles (EVs), optimization. NOMENCLATURE SETS N Set of buses in the system T Set of time periods M Set of line sections O Set of types of chargers E Set of electric vehicles INDICES i Index of bus number t Index of time period j Index of line section l Index of level of charging station e Index of electric vehicle The associate editor coordinating the review of this manuscript and approving it for publication was Zhiyi Li. PARAMETERS P j,loss Power loss of jth line section C Charging power of a charger SOC init Initial state of charge of a battery c Cost of a charger c p,l Per unit electrical energy cost S j,max Maximum transfer capacity of line section j η ch Charging efficiency of EV d max Maximum range when EV is fully charged VARIABLES n Number of charging station V i,t Voltage magnitude of bus i at time interval t S j,t Power flow through line section j at time interval t dist trav,e Travelled distance by electric vehicle e

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Section: Introductionmentioning

confidence: 99%

Optimal Placement of Electric Vehicle Charging Stations in the Active Distribution Network

et al. 2020

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“…An optimal location for EVCS plays a key role in mitigating the range of anxiety among the consumers of electric vehicles [51,52]. Various factors influence the location of charging station, which includes drivers' charging satisfactory, economy problem of operators, the power loss of vehicles, the safety of the power grid, and traffic jam of transportation system [53][54][55][56][57]. Table 1 describes some of the latest researches and developments in finding the optimal location for the EV charging station.…”

Section: Optimal Location For Electric Vehicle Charging Stationsmentioning

confidence: 99%

A Comprehensive Review on Developments in Electric Vehicle Charging Station Infrastructure and Present Scenario of India

et al. 2021

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The transportation sector of the world is in the transformation stage, shifting from conventional fossil fuel-powered vehicles to zero or ultra-low tailpipe emission vehicles. To support this transformation, a proper charging station (CS) infrastructure in combination with information technology, smart distributed energy generating units, and favorable government policies are required. The motive of this paper is to address the key aspects to be taken care of while planning for the charging station infrastructure for electric vehicles. The paper also provides major indagation and developments in planning and technological aspects that are going on for the enhancement of the design and efficient management of charging station infrastructure. The paper addresses the present scenario of India related to electric vehicle charging station developments. The paper specially provides a critical review on the research and developments in the charging station infrastructure, the problems associated with it, and the efforts that are going on for its standardization to help the researchers address the problems.

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“…As a valuable method for siting service facilities, facility location models have been widely used in numerous applications, including determining the location of defense facilities considering a time horizon 10 , optimal placement of sensors in watercourses 11 , determining the location and size of charging stations for electric vehicles 12 , positioning distribution centers for emergency stockpiles to improve preparedness in the event of a disaster 13 , positioning water quality monitoring stations 14 , solving hub location problems in urban transport and liner shipping network design 15 , designing supply chain networks 16 , choosing the location of facilities in a humanitarian relief chain responding to quick-onset disasters 17 , and examining service systems applied to the distribution of policemen in highway networks 18 . Covering problems are among the most popular facility location models.…”

Section: Introductionmentioning

confidence: 99%

Optimal location of water level sensors for monitoring mine water inrush based on the set covering model

Zhao

et al. 2021

Sci Rep

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Water inrush is one of the major mining disasters that may lead to numerous casualties. The development of information techniques makes it possible to monitor the occurrence and evolution of water inrush. Then, locating monitors for water inrush becomes a primary problem. This study presents a method of optimal location of water level sensors by constructing a set covering model. The monitoring scope of the water level sensor at each location in a given time is computed first based on the numerical simulation of water spreading along mine tunnels. In this simulation, the water inrush quantity is assigned using the mine drainage capability over which an accident may occur. Then the greedy algorithm is used to optimize the number and positions of water level sensors. As results, a mine water disaster can be monitored in the given time after it happened. The proposed method is then verified in the Beiyangzhuang coal mine in the North China. The results show that at least 22, 36, 42, 64 and 106 water level sensors are needed to monitor water disasters in the whole mine within 60, 30, 20, 10 and 5 min, respectively.

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Optimal location planning method of fast charging station for electric vehicles considering operators, drivers, vehicles, traffic flow and power grid

Cited by 134 publications

References 22 publications

Optimal Placement of Electric Vehicle Charging Stations in the Active Distribution Network

Optimal Placement of Electric Vehicle Charging Stations in the Active Distribution Network

A Comprehensive Review on Developments in Electric Vehicle Charging Station Infrastructure and Present Scenario of India

Optimal location of water level sensors for monitoring mine water inrush based on the set covering model

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