Configuration optimization and benefit allocation model of multi-park integrated energy systems considering electric vehicle charging station to assist services of shared energy storage power station

2022 ◽  
pp. 130381
Author(s):  
Gao Jianwei ◽  
Gao Fangjie ◽  
Yang Yu ◽  
Wu Haoyu ◽  
Zhang Yi ◽  
...  
Keyword(s):  
Energy Storage ◽  
Electric Vehicle ◽  
Energy Systems ◽  
Configuration Optimization ◽  
Power Station ◽  
Allocation Model ◽  
Charging Station ◽  
Integrated Energy Systems ◽  
Electric Vehicle Charging ◽  
Benefit Allocation

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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