Fair load shedding solutions for developing countries
Fair load shedding solutions for developing countries
 
  In order to remain in operation by maintaining a balance between demand and supply, grid operators in many developing countries often resort to disconnecting the load on parts of the grid from supply. This measure, known as load shedding, is often necessitated by shortages in their supply capacity. A consequence of load shedding is that households in disconnected parts are left without supply. In addition, existing load shedding schemes do not take fairness into consideration at the household level, meaning that some homes bear the brunt of load shedding. Against this background, we present a number of fair household-level load shedding solutions in this thesis. We first simulate a representative dataset for formulating and evaluating our solutions from a Pecan Street Inc. dataset. Thereafter, we model homes as agents and, in so doing, create a vector of values (i.e., the comfort vector) to embody their electricity needs. Thereupon, we develop a first set of solutions which result in homes being connected to electricity for even durations. Following this, we develop a second set of solutions which make up for the limitations of the first, in that they factor the comfort values of agents into consideration. In developing the second set of solutions, we establish agent utilities in terms of the number of hours they are connected to supply, the comfort they derive from supply, and the level at which their demand is satisfied. Then, we model the solutions as Mixed Integer Programming (MIP) problems, with objectives and constraints that maximize the groupwise and individual utilities of agents and minimize the pairwise differences between their utilities. Using a number of experiments, we show how the MIP solutions outperform the heuristics, by producing results which outperform and Pareto dominate those of the heuristics in terms of all utilities. When taken together, this thesis establishes a set of benchmarks for fair load shedding schemes. In addition, it provides insights for designing fair allocation solutions for other scarce resources.
  
    University of Southampton
   
  
    
      Oluwasuji, Olabambo, Ifeoluwa
      
        b20f623c-d5cd-4db9-905c-5d00b9d95459
      
     
  
  
   
  
  
    
      June 2019
    
    
  
  
    
      Oluwasuji, Olabambo, Ifeoluwa
      
        b20f623c-d5cd-4db9-905c-5d00b9d95459
      
     
  
    
      Ramchurn, Sarvapali
      
        1d62ae2a-a498-444e-912d-a6082d3aaea3
      
     
  
       
    
 
  
    
      
  
 
  
  
  
    Oluwasuji, Olabambo, Ifeoluwa
  
  
  
  
   
    (2019)
  
  
    
    Fair load shedding solutions for developing countries.
  University of Southampton, Doctoral Thesis, 134pp.
  
   
  
    
      Record type:
      Thesis
      
      
      (Doctoral)
    
   
    
    
      
        
          Abstract
          In order to remain in operation by maintaining a balance between demand and supply, grid operators in many developing countries often resort to disconnecting the load on parts of the grid from supply. This measure, known as load shedding, is often necessitated by shortages in their supply capacity. A consequence of load shedding is that households in disconnected parts are left without supply. In addition, existing load shedding schemes do not take fairness into consideration at the household level, meaning that some homes bear the brunt of load shedding. Against this background, we present a number of fair household-level load shedding solutions in this thesis. We first simulate a representative dataset for formulating and evaluating our solutions from a Pecan Street Inc. dataset. Thereafter, we model homes as agents and, in so doing, create a vector of values (i.e., the comfort vector) to embody their electricity needs. Thereupon, we develop a first set of solutions which result in homes being connected to electricity for even durations. Following this, we develop a second set of solutions which make up for the limitations of the first, in that they factor the comfort values of agents into consideration. In developing the second set of solutions, we establish agent utilities in terms of the number of hours they are connected to supply, the comfort they derive from supply, and the level at which their demand is satisfied. Then, we model the solutions as Mixed Integer Programming (MIP) problems, with objectives and constraints that maximize the groupwise and individual utilities of agents and minimize the pairwise differences between their utilities. Using a number of experiments, we show how the MIP solutions outperform the heuristics, by producing results which outperform and Pareto dominate those of the heuristics in terms of all utilities. When taken together, this thesis establishes a set of benchmarks for fair load shedding schemes. In addition, it provides insights for designing fair allocation solutions for other scarce resources.
         
      
      
        
          
            
  
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      Published date: June 2019
 
    
  
  
    
  
    
  
    
  
    
  
    
  
    
  
    
  
    
  
  
        Identifiers
        Local EPrints ID: 433531
        URI: http://eprints.soton.ac.uk/id/eprint/433531
        
        
        
        
          PURE UUID: 479698dc-0831-4b6c-82e3-6bafd2c93547
        
  
    
        
          
            
          
        
    
        
          
            
              
            
          
        
    
  
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  Date deposited: 27 Aug 2019 16:30
  Last modified: 16 Mar 2024 08:08
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      Contributors
      
          
          Author:
          
            
              
              
                Olabambo, Ifeoluwa Oluwasuji
              
              
            
            
          
        
      
          
          Thesis advisor:
          
            
              
              
                Sarvapali Ramchurn
              
              
                 
              
            
            
          
         
      
      
      
    
  
   
  
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