Optimizing the path of transmission line piles based on improved Levi's flight particle swarm optimization algorithm
Abstract:
The optimization of transmission line pile paths plays an important role in power grid planning and design. This paper proposes an improved Levy Flight Particle Swarm Optimization (ILFPSO) algorithm to solve the problem of transmission line pile path optimization. First, we use the Shubert function to test the ILFPSO algorithm to verify its optimization effect. Then, we apply the algorithm to the optimization of the transmission line pile path, and verify its effectiveness in the power system through simulation experiments. Finally, we give the MATLAB source code of the algorithm.
Keywords: Particle Swarm Optimization, Levy's Flight, Optimization of Transmission Line Pile Path, Chaotic Particle Swarm, MATLAB
Introduction:
With the continuous development of the power system, the importance of transmission line planning has become increasingly prominent. The transmission line pile is the support structure on the transmission line, and its reasonable layout is very important to the safe and reliable operation of the power grid. Traditional transmission line pile path design usually uses artificial experience or simple heuristic algorithms, which cannot fully consider complex power system conditions and constraints. Therefore, an efficient algorithm is needed to realize the optimization of the transmission line pile path.
- Algorithm principle
1.1 Levy flight
Levy flight is a random walk algorithm based on Levy distribution, which has the characteristics of long-distance search and fast convergence. In the traditional particle swarm optimization algorithm, the position update of particles usually adopts normal distribution random numbers. In the improved ILFPSO algorithm, Levy flight is introduced to increase the search ability of the algorithm.
1.2 Improved Levi's flight particle swarm algorithm
Based on the traditional particle swarm algorithm and Levy's flight ideas, we propose an improved Levy's flight particle swarm algorithm. The main steps of the algorithm are as follows:
(1) Initialize the individual particle position and velocity;
(2) Calculate the fitness value of each particle;
(3) Update the optimal position of the particle and the global optimal position;
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