The summary for global optimization and control theory of electric vehicles' energy system based on V2G mode

Author(s):  
Zhenpo Wang ◽  
Xiaohui Sun
2011 ◽  
Author(s):  
Russell W Bent ◽  
Michael Chertkov ◽  
Scott Backhaus

AIChE Journal ◽  
2014 ◽  
Vol 60 (7) ◽  
pp. 2546-2556 ◽  
Author(s):  
Milana Trifkovic ◽  
W. Alex Marvin ◽  
Prodromos Daoutidis ◽  
Mehdi Sheikhzadeh

2021 ◽  
Vol 257 ◽  
pp. 02009
Author(s):  
Peng Ye ◽  
Shuo Yang ◽  
Feng Sun ◽  
Mingli Zhang ◽  
Na Zhang

In order to rationally design the capacity of each energy coupling unit of the integrated energy system, effectively coordinate and optimize the control of the integrated energy system equipment. This paper proposes an improved cloud adaptive particle swarm algorithm design control method. First, three busbars and multi-energy coupling equipment models based on electric, thermal, and gas loads are established, and then the model has better global optimization capabilities and defenses. Then, an improved cloud adaptive particle swarm algorithm with better global optimization capabilities and anti-premature convergence characteristics is used to optimize the annual economic optimization model established to meet the power balance constraints of each bus and energy coupling equipment. Finally, under the conditions of output constraints and system energy purchase constraints, taking a typical park as an example, the simulation verifies the effectiveness of the method proposed in this paper in the optimization design and control operation of the integrated energy system.


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