Optimal Location of STATCOM in Nigerian 330kv Network Using Ant Colony Optimization Meta-Heuristic
Keywords:
STATCOM, 330kv nigerian network, ant colony optimization (ACO), FACTS devices
Abstract
This paper introduces the ant colony meta-heuristic technique to optimally locate STATCOM in 330kV Nigerian Network. The Ant Colony Optimization (ACO) algorithms used the STATCOM parameters and probabilistic model to generate solutions to the problem of siting STATCOM in Nigerian network. The optimal location of STATCOM in Nigerian network is evidenced in bus voltage profile enhancement and minimization of transmission losses. The probabilistic model is called pheromone model which consists of a set of model parameters, often referred to as pheromone values. At runtime, the ACO algorithms try to update the pheromone values from previously generated solutions in such a way that the probability to generate high quality solutions increases over time. Finally, the graph of pheromone trail and path treaded by the ants along the various nodes are captured whose codes are validated using the Matrix Laboratory Software (MATLAB) environment.
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Published
2014-03-15
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Copyright (c) 2014 Authors and Global Journals Private Limited
This work is licensed under a Creative Commons Attribution 4.0 International License.