IUP Publications Online
Home About IUP Magazines Journals Books Archives
     
Recommend    |    Subscriber Services    |    Feedback    |     Subscribe Online
 
The IUP Journal of Electrical and Electronics Engineering:
Evolutionary and Swarm Methods for Load Shedding
:
:
:
:
:
:
:
:
:
 
 
 
 
 
 
 

Evolutionary and swarm optimization methods such as Genetic Algorithm (GA), Evolutionary Programming (EP) and Particle Swarm Optimization (PSO) have been used extensively in various applications. This paper looks at the applications of these methods in the area of load shedding. EP, GA within Evolutionary Algorithm (EA) and PSO stand out among the methods due to their simplicity of theory and application. Hybrid methods consisting of a combination of evolutionary and swarm techniques are potentially effective methods for finding global optimized solutions for optimal load shedding problems as they mesh strong points from both classes of methods.

 
 

Classical optimization methods have been used extensively in literature to find optimum solutions for continuous and differentiable functions (Abril and Quintero, 2003; Johansen et al., 2004; Ma and Wang, 2006; Hu et al., 2008; and Liang et al., 2008). However, these methods are not able to handle highly nonlinear, non-continuous and non-differentiable fitness functions which are usually the case for most power systems-related problems.

Population-based optimization techniques such as evolutionary and swarm methods are gaining popularity due to their capability to alleviate limitations of classical methods in terms of achieving global optimization, convergence speed and robustness. These methods have increasing potential as global optimization techniques to solve constrained optimization problems in the fields of science and engineering (Li and Liang, 2007).

 
 
 

Evolutionary Algorithm (EA), Genetic Algorithm (GA), Evolutionary Programming (EP), Particle Swarm Optimization (PSO)