Optimal Planning of Electric Vehicle Charging Stations Location Based on Hybrid Particle Swarm Optimization

2013 ◽  
Vol 724-725 ◽  
pp. 1355-1360 ◽  
Author(s):  
Zhe Ci Tang ◽  
Chun Lin Guo ◽  
Peng Xin Hou ◽  
Yu Bo Fan ◽  
Dong Ming Jia
Keyword(s):  
Particle Swarm Optimization ◽  
Electric Vehicles ◽  
Particle Swarm ◽  
Operating Costs ◽  
Swarm Optimization ◽  
Charging Station ◽  
Electric Vehicle Charging ◽  
Electric Car ◽  
Hybrid Particle Swarm Optimization ◽  
Charging Stations

In order to determine the layout of electric car charging stations, a model for optimizing charging stations location is developed after charging-demand districts are divided, the number of electric vehicles and the center of each charging district are ready. This model takes the minimization of electric vehicles charging stations total cost which includes initial fixed investment costs, operating costs and charging costs as the objective function, some related constraints which include service radius, capacity of charging station etc. are considered. Particle swarm optimization based on hybridization is proposed to solve this problem. The example verifies feasibility of this method.

scholarly journals Optimal Planning of Electric Vehicle Charging Station Considering Mutual Benefit of Users and Power Grid

2021 ◽  
Vol 12 (4) ◽  
pp. 244
Author(s):  
Hui Hou ◽  
Junyi Tang ◽  
Bo Zhao ◽  
Leiqi Zhang ◽  
Yifan Wang ◽  
...  
Keyword(s):  
Particle Swarm Optimization ◽  
Electric Vehicle ◽  
Power Grid ◽  
Particle Swarm ◽  
Optimal Planning ◽  
Mutual Benefit ◽  
Swarm Optimization ◽  
Charging Station ◽  
Electric Vehicle Charging ◽  
Charging Stations

A reasonable plan for charging stations is critical to the widespread use of electric vehicles. In this paper, we propose an optimal planning method for electric vehicle charging stations. First of all, we put forward a forecasting method for the distribution of electric vehicle fast charging demand in urban areas. Next, a new mathematical model that considers the mutual benefit of electric vehicle users and the power grid is set up, aiming to minimize the social cost of charging stations. Then, the model is solved by the Voronoi diagram combined with improved particle swarm optimization. In the end, the proposed method is applied to an urban area, simulation results demonstrate that the proposed method can yield optimal location and capacity of each charging station. A contrasting case is carried out to verify that improved particle swarm optimization is more effective in finding the global optimal solution than particle swarm optimization.

scholarly journals Optimal Cost Analysis of Battery Swapping Station for EV Using PSO

2021 ◽  
Vol 9 (11) ◽  
pp. 2060-2067
Author(s):  
Prafull Bhumarkar
Keyword(s):  
Particle Swarm Optimization ◽  
Electric Vehicles ◽  
Flow Analysis ◽  
Particle Swarm ◽  
Load Flow ◽  
Swarm Optimization ◽  
Optimal Cost ◽  
Charging Station ◽  
Load Flow Analysis ◽  
Current Scenario

Abstract: Electric vehicles are the demand of the current scenario to fight with the increasing levels of pollution. Electric vehicles operate by getting power from the battery which needs to be charged after a particular duration. Battery swapping stations are used for providing the optimal power for charging these batteries. An algorithm known as Particle swarm optimization can be used to find the optimal cost of these battery swapping stations. The project presents an expository study about ParticleSwarm Optimization and thus various factors related to it. Keywords: Battery Swapping Station, Battery Charging Station, Load flow Analysis, Particle Swarm Optimization

scholarly journals Optimal Photovoltaic/Battery Energy Storage/Electric Vehicle Charging Station Design Based on Multi-Agent Particle Swarm Optimization Algorithm

2019 ◽  
Vol 11 (7) ◽  
pp. 1973 ◽  
Author(s):  
Qiongjie Dai ◽  
Jicheng Liu ◽  
Qiushuang Wei
Keyword(s):  
Particle Swarm Optimization ◽  
Energy Storage ◽  
Electric Vehicle ◽  
Particle Swarm ◽  
Swarm Optimization ◽  
Battery Energy Storage ◽  
Charging Station ◽  
Electric Vehicle Charging ◽  
Multi Agent ◽  
Battery Energy

In order to effectively improve the utilization rate of solar energy resources and to develop sustainable urban efficiency, an integrated system of electric vehicle charging station (EVCS), small-scale photovoltaic (PV) system, and battery energy storage system (BESS) has been proposed and implemented in many cities around the world. This paper proposes an optimization model for grid-connected photovoltaic/battery energy storage/electric vehicle charging station (PBES) to size PV, BESS, and determine the charging/discharging pattern of BESS. The multi-agent particle swarm optimization (MAPSO) algorithm solves this model is solved, which combines multi-agent system (MAS) and the mechanism of particle swarm optimization (PSO). In this model, a load simulation model is presented to simulate EV charging patterns and to calculate the EV charging demand at each time interval. Finally, a case in Shanghai, China is conducted and three scenarios are analyzed to prove the effectiveness of the proposed model. A comparative analysis is also performed to show the superiority of MAPSO algorithm.

scholarly journals Electric Vehicle Charging Coordination on Distribution Network by using Particle Swarm Optimization and Genetic Algorithm

2019 ◽  
Vol 8 (12) ◽  
pp. 5673-5676
Keyword(s):  
Genetic Algorithm ◽  
Particle Swarm Optimization ◽  
Electric Vehicles ◽  
Distribution Network ◽  
Particle Swarm ◽  
Combustion Method ◽  
Swarm Optimization ◽  
Electric Vehicle Charging ◽  
Electric Distribution Network ◽  
Line Overload

The Electric Vehiclesbecoming very popular in the recent years. Typically, Electric Vehicles propulsion systems come from one or more electrical motors built inside the vehicles. This motor used electricity as energy combustion method. Due to the limited energy storage capacity, Electric Vehicles need to replenish by plugging into an electrical source. The problems appear during multiple Electric Vehicles perform charging process in an Electric Distribution Network. This process willbe causing line overload and efficiency degradation of Distribution Network. In performance to evaluate the potential of different of charging coordination, a classification has been made. The new coordinated process may consider minimum power losses and acceptable voltage limit. The process also needs to define the optimal uncoordinated and coordinated charging point. Therefore, a simulation-based framework will be performed, that use two algorithms which are Particle Swarm Optimization and Genetic Algorithm.

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