A novel fast version of particle swarm optimization method applied to the problem of optimal capacitor placement in radial distribution systems

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Author(s) 
M.Pourmahmood Aghababa, A.M.Shotorbani, R.Alizadeh, R.M.Shotorbani 

KEYWORDS 
convergence speed, fast PSO, capacitor placement, particle swarm optimization, radial distribution system


ABSTRACT 
Particle swarm optimization (PSO) is a popular and robust strategy for optimization problems. One main difficulty in applying PSO to realworld applications is that PSO usually needs a large number of fitness evaluations before a satisfying result can be obtained. This paper presents a modified version of PSO method that can converge to the optima with less function evaluation than standard PSO. The main idea is inserting two additional terms to the particles velocity expression. In any iteration, the value of the objective function is a criterion presenting the relative improvement of current movement with respect to the previous one. Therefore, the difference between the values of the objective function in subsequent iterations can be added to velocity of particles, interpreted as the particle acceleration. By this modification, the convergence becomes fast due to new adaptive step sizes. This new version of PSO is called Fast PSO (FPSO). To evaluate the efficiency of FPSO, a set of benchmark functions are employed, and an optimal capacitor selection and placement problem in radial distribution systems is evaluated in order to minimize cost of the equipment, installation and power loss under the additional constraints. The results show the efficiency and superiority of FPSO method rather than standard PSO and genetic algorithm.


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