Horse Herd Optimization MPPT for PV System

Version 1.0.01 (1.65 KB) by PIRC
Horse Herd Optimization (HHO) algorithm for Maximum Power Point Tracking (MPPT) in a Photovoltaic (PV) system.
438 Downloads
Updated 19 Aug 2023

View License

MATLAB code demonstrates the use of the Horse Herd Optimization (HHO) algorithm for Maximum Power Point Tracking (MPPT) in a Photovoltaic (PV) system. Here's a brief explanation of the key components:
  1. Parameters: The code begins by setting various parameters, such as the maximum number of iterations, the number of horses in the herd, a constant for position updates, and an attack factor.
  2. PV System Parameters: Essential parameters of the PV system are defined, including the open circuit voltage (Voc), short circuit current (Isc), voltage and current at the maximum power point (Vmpp and Impp), and maximum/minimum voltage limits.
  3. Initialization: The positions of the horses in the herd are initialized randomly within the voltage limits of the PV system.
  4. Main Loop: The main loop iterates for a predefined number of times (max_iter). For each iteration, it processes each horse in the herd.
  5. Fitness Calculation: The fitness value of each horse's position is calculated. In the context of MPPT, the fitness value is the difference between the current power output of the PV system (using the horse's voltage position) and the maximum power output achievable at the MPP.
  6. Updating Best Position: The algorithm tracks the best fitness value and corresponding position encountered so far. If a horse's fitness is better than the current best, the best fitness and position are updated.
  7. Position Update: The new position for each horse is calculated using a formula involving random values and the best position found so far. This update equation simulates the horse's movement towards the best position.
  8. Boundary Constraints: The calculated new position is then constrained within the PV system's voltage limits to ensure the validity of the solution.
  9. Display: The best position found in each iteration is displayed on the screen.
  10. Final Result: After the iterations are complete, the code displays the final best position found by the algorithm.
For more information : www.pirc.co.in

Cite As

PIRC (2024). Horse Herd Optimization MPPT for PV System (https://www.mathworks.com/matlabcentral/fileexchange/133842-horse-herd-optimization-mppt-for-pv-system), MATLAB Central File Exchange. Retrieved .

MATLAB Release Compatibility
Created with R2023a
Compatible with any release
Platform Compatibility
Windows macOS Linux

Community Treasure Hunt

Find the treasures in MATLAB Central and discover how the community can help you!

Start Hunting!
Version Published Release Notes
1.0.01

image

1.0.0