Neighborhood electric vehicle charging scheduling using particle swarm optimization

2014 ◽  
Author(s):  
Jouni Peppanen ◽  
Santiago Grijalva
Keyword(s):  
Particle Swarm Optimization ◽  
Electric Vehicle ◽  
Particle Swarm ◽  
Swarm Optimization ◽  
Electric Vehicle Charging ◽  
Vehicle Charging

Optimized sizing of photovoltaic grid‐connected electric vehicle charging system using particle swarm optimization

2018 ◽  
Vol 43 (1) ◽  
pp. 500-522 ◽  
Author(s):  
Abdul Rauf Bhatti ◽  
Zainal Salam ◽  
Beenish Sultana ◽  
Nadia Rasheed ◽  
Ahmed Bilal Awan ◽  
...  
Keyword(s):  
Particle Swarm Optimization ◽  
Electric Vehicle ◽  
Particle Swarm ◽  
Swarm Optimization ◽  
Charging System ◽  
Electric Vehicle Charging ◽  
Vehicle Charging

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 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.

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