How do integrated PSO MATLAB CODE with Backward forward sweep method for power loss minimization by network reconfiguration.

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How do integrated PSO MATLAB CODE with Backward forward sweep method for power loss minimization by network reconfiguration.
Can you give me a full MATLAB code of PSO integrated with BFS method.
  3 Kommentare
John D'Errico
John D'Errico am 1 Jan. 2025
Bearbeitet: John D'Errico am 1 Jan. 2025
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Antworten (1)

Jaimin
Jaimin am 30 Dez. 2024
Hi @TB
Integrating Particle Swarm Optimization (PSO) with the Backward/Forward Sweep (BFS) method for power loss minimization through network reconfiguration in MATLAB involves several steps.
Kindly refer following algorithm for understanding.
Initialize Parameters:
  • Set PSO parameters: number of particles, iterations, inertia weight, cognitive and social components.
  • Define network parameters: number of buses, lines, and line data (resistance, reactance).
Particle Initialization:
  • Randomly initialize particle positions and velocities.
  • Set personal best (pBest) to initial positions.
  • Initialize global best (gBest) as the best of initial positions.
Objective Function (BFS):
  • Calculate power loss using BFS:
  • Initialize bus voltages and loads.
  • Perform backward and forward sweeps to update currents and voltages.
  • Compute total power loss across lines.
PSO Iteration:
  • For each iteration:
  • Evaluate fitness of each particle using the objective function.
  • Update pBest and gBest based on fitness.
  • Update particle velocities and positions using PSO formulas.
  • Ensure positions remain within valid bounds.
Output Results:
  • After all iterations, output the optimal line configuration (gBest) and the corresponding minimum power loss.
For more information kindly refer following MathWorks documentation.
I hope this will be helpful.

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R2019a

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