Abstract
Distribution network planning because of involving many variables and constraints is a multiobjective, discrete, nonlinear, and large-scale optimization problem. Harmony search (HS) algorithm is a metaheuristic algorithm inspired by the improvisation process of music players. HS algorithm has several impressive advantages, such as easy implementation, less adjustable parameters, and quick convergence. But HS algorithm still has some defects such as premature convergence and slow convergence speed. According to the defects of the standard algorithm and characteristics of distribution network planning, an improved harmony search (IHS) algorithm is proposed in this paper. We set up a mathematical model of distribution network structure planning, whose optimal objective function is to get the minimum annual cost and constraint conditions are overload and radial network. IHS algorithm is applied to solve the complex optimization mathematical model. The empirical results strongly indicate that IHS algorithm can effectively provide better results for solving the distribution network planning problem compared to other optimization algorithms.
Highlights
Distribution network planning can reduce the probability of blackouts, reduce transmission loss, and improve power quality, so that it is an important part of power distribution automation system
In the practical application of the distribution network planning, it always falls into local optimum prematurely and converging slowly; there may even be infeasible solutions; Particle Swarm Optimization (PSO) is a classic biological intelligence algorithm and has some advantages over other similar optimization techniques such as PSO which is easier to implement and there are fewer parameters to adjust, but it is prone to premature convergence [6]; Ant Colony System (ACS) is a swarm intelligence algorithm based on distributed parallel search mechanism
According to the defects of the standard algorithm and characteristics of distribution network planning, this paper proposed an improved harmony search (IHS) algorithm with the mechanism for dynamically adjusting parameters
Summary
Distribution network planning can reduce the probability of blackouts, reduce transmission loss, and improve power quality, so that it is an important part of power distribution automation system. In the practical application of the distribution network planning, it always falls into local optimum prematurely and converging slowly; there may even be infeasible solutions; PSO is a classic biological intelligence algorithm and has some advantages over other similar optimization techniques such as PSO which is easier to implement and there are fewer parameters to adjust, but it is prone to premature convergence [6]; ACS is a swarm intelligence algorithm based on distributed parallel search mechanism It has strong robustness, but it has some defects such as long calculation time, prone to stagnation and premature convergence [7, 8]. The simulation of example obviously shows that the solution is superior to that of other optimization algorithms
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