Optimum Power Flow

This code focuses on the minimization of active power losses.
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Updated 16 Apr 2019

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This code focuses on the minimization of active power losses.
First, we acquire the data from the desired power system, then we define the parameters of the optimization algorithm such as number of iterations, size of the population and the minimum and maximum value of the desition variables. The desition variables are: The values of TAPs, bus voltage, and shunts.
After defining the optimization algorithm parameters, the classical power flow program is executed, and the value of the optimization function is computed.
Now the iterative process began after the algorithm has reached the default number of iterations it shows a comparison between the initial values of the desition variables and the new ones from the optimization algorithm, also, it shows the process of evolution of the optimum value as well as the active power losses.
In the folder, there is an image of how the Jaya algorithm works.

Note: The code is designed to work with any power system, just added to the folder and call it in the code. Remember that the optimization process may take from seconds to minutes to converge depending on the number of desition variables and the number of iterations.
To know more about the Jaya algorithm:
http://www.growingscience.com/ijiec/Vol7/IJIEC_2015_32.pdf

If you are facing any trouble you can contact me by email.
my email is: orramirezba@ittepic.edu.mx

MATLAB Release Compatibility
Created with R2019a
Compatible with any release
Platform Compatibility
Windows macOS Linux

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Version Published Release Notes
1.0.0