Mechanism design for efficient allocation of electric vehicles to charging stations
Mechanism design for efficient allocation of electric vehicles to charging stations
  The electrification of transport can significantly reduce CO2 emissions and their negative impact on the environment. In this paper, we study the problem of allocating Electric Vehicles (EVs) to charging stations and scheduling their charging. We develop an offline solution that treats EV users as self-interested agents that aim to maximise their profit and minimise the impact on their schedule. We formulate the problem of the optimal EV to charging station allocation as a Mixed Integer Programming (MIP) one and we propose two pricing mechanisms: A fixed-price one, and another that is based on the well known Vickrey-Clark-Groves (VCG) mechanism. We observe that the VCG mechanism services on average 1.5% more EVs than the fixed-price one. In addition, when the stations get congested, VCG leads to higher prices for the EVs and higher profit for the stations, but lower utility for the EVs. However, the VCG mechanism guarantees truthful reporting of the EVs’ preferences.
  
  10-15
  
    
      Rigas, Emmanouil S.
      
        6f42da4c-ffea-41c0-8302-5a98c1d06a6d
      
     
  
    
      Gerding, Enrico
      
        d9e92ee5-1a8c-4467-a689-8363e7743362
      
     
  
    
      Stein, Sebastian
      
        cb2325e7-5e63-475e-8a69-9db2dfbdb00b
      
     
  
    
      Ramchurn, Sarvapali D.
      
        1d62ae2a-a498-444e-912d-a6082d3aaea3
      
     
  
    
      Bassiliades, Nick
      
        46e70a8f-015c-4888-890a-de879c9bff61
      
     
  
  
   
  
  
    
      September 2020
    
    
  
  
    
      Rigas, Emmanouil S.
      
        6f42da4c-ffea-41c0-8302-5a98c1d06a6d
      
     
  
    
      Gerding, Enrico
      
        d9e92ee5-1a8c-4467-a689-8363e7743362
      
     
  
    
      Stein, Sebastian
      
        cb2325e7-5e63-475e-8a69-9db2dfbdb00b
      
     
  
    
      Ramchurn, Sarvapali D.
      
        1d62ae2a-a498-444e-912d-a6082d3aaea3
      
     
  
    
      Bassiliades, Nick
      
        46e70a8f-015c-4888-890a-de879c9bff61
      
     
  
       
    
 
  
    
      
  
  
  
  
    Rigas, Emmanouil S., Gerding, Enrico, Stein, Sebastian, Ramchurn, Sarvapali D. and Bassiliades, Nick
  
  
  
  
   
    (2020)
  
  
    
    Mechanism design for efficient allocation of electric vehicles to charging stations.
  
  
  
  
   In SETN 2020: 11th Hellenic Conference on Artificial Intelligence. 
  
      
          
          
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   (doi:10.1145/3411408.3411434).
  
   
  
    
      Record type:
      Conference or Workshop Item
      (Paper)
      
      
    
   
    
    
      
        
          Abstract
          The electrification of transport can significantly reduce CO2 emissions and their negative impact on the environment. In this paper, we study the problem of allocating Electric Vehicles (EVs) to charging stations and scheduling their charging. We develop an offline solution that treats EV users as self-interested agents that aim to maximise their profit and minimise the impact on their schedule. We formulate the problem of the optimal EV to charging station allocation as a Mixed Integer Programming (MIP) one and we propose two pricing mechanisms: A fixed-price one, and another that is based on the well known Vickrey-Clark-Groves (VCG) mechanism. We observe that the VCG mechanism services on average 1.5% more EVs than the fixed-price one. In addition, when the stations get congested, VCG leads to higher prices for the EVs and higher profit for the stations, but lower utility for the EVs. However, the VCG mechanism guarantees truthful reporting of the EVs’ preferences.
         
      
      
        
          
            
  
    Text
 SETN_Mechanism_Final4
     - Accepted Manuscript
   
  
  
 
          
            
          
            
           
            
           
        
        
       
    
   
  
  
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      Published date: September 2020
 
    
  
  
    
  
    
  
    
  
    
  
    
  
    
  
    
  
    
  
  
        Identifiers
        Local EPrints ID: 446412
        URI: http://eprints.soton.ac.uk/id/eprint/446412
        
          
        
        
        
        
          PURE UUID: 3c77bee8-7c2a-494b-8d47-e760cd93a4c5
        
  
    
        
          
        
    
        
          
            
              
            
          
        
    
        
          
            
              
            
          
        
    
        
          
            
              
            
          
        
    
        
          
        
    
  
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  Date deposited: 08 Feb 2021 17:31
  Last modified: 17 Mar 2024 03:13
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      Contributors
      
          
          Author:
          
            
            
              Emmanouil S. Rigas
            
          
        
      
          
          Author:
          
            
              
              
                Enrico Gerding
              
              
                
              
            
            
          
         
      
          
          Author:
          
            
              
              
                Sebastian Stein
              
              
                
              
            
            
          
         
      
          
          Author:
          
            
              
              
                Sarvapali D. Ramchurn
              
              
                
              
            
            
          
         
      
          
          Author:
          
            
            
              Nick Bassiliades
            
          
        
      
      
      
    
  
   
  
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