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PI controller design via ABC algorithm for MPPT of PV system supplying DC motor–pump load

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Abstract

Artificial Bee Colony (ABC) algorithm has various features that make it more attractive than other algorithms. Particularly, it is simple, it uses fewer control parameters and its convergence is independent of the initial conditions. In this paper, a new MPPT system has been suggested for photovoltaic (PV)-DC motor–pump system by designing two PI controllers via ABC algorithm. The first one is used to reach MPPT by monitoring the voltage and current of the PV array and adjusting the duty cycle of the DC/DC converter. The second PI controller is designed for speed control of DC series motor by setting the voltage fed to the DC series motor through another DC/DC converter. The suggested design problem of MPPT and speed controller is formulated as an optimization task which is solved by ABC to search for optimal parameters of PI controllers. Simulation results have shown the validity of the developed technique in delivering MPPT to DC series motor–pump system under atmospheric conditions and tracking the reference speed of motor. Moreover, the performance of the ABC algorithm is compared with Genetic Algorithm (GA) for various disturbances to prove its robustness.

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Abbreviations

\(i_\mathrm{a} \) :

The armature current

\(V_\mathrm{t} \) :

The motor terminal voltage

\(R_\mathrm{a} ,L_\mathrm{a} \) :

The armature resistance and inductance

\(R_\mathrm{f} ,L_\mathrm{f} \) :

The field resistance and inductance

\(\omega _\mathrm{r} \) :

The motor angular speed

\(J_\mathrm{m} \) :

The moment of inertia

\(T_\mathrm{L} \) :

The load torque

f :

The friction coefficient

\(M_{\mathrm{af}}\) :

The mutual inductance between the armature and field

I and V :

Module output current and voltage

\(I_\mathrm{c} \) and \(V_\mathrm{c} \) :

Cell output current and voltage

\(I_{\mathrm{ph}} \) and \(V_{\mathrm{ph}} \) :

The light generation current and voltage

\(I_\mathrm{s} \) :

Cell reverse saturation current

\(I_{\mathrm{sc}} \) :

The short circuit current

\(I_\mathrm{o} \) :

The reverse saturation current

\(R_\mathrm{s} \) :

The module series resistance

T :

Cell temperature

K :

Boltzmann’s constant

\(q_\mathrm{o} \) :

Electronic charge

KT:

(0.0017 \(\hbox {A}/^\circ \hbox {C}\)) short circuit current temperature coefficient

G :

Solar illumination in \(\hbox {W/m}^{2}\)

\(E_\mathrm{g} \) :

Band gap energy for silicon

A :

Ideality factor

\(T_\mathrm{r} \) :

Reference temperature

\(I_{\mathrm{or}} \) :

Cell rating saturation current at \(T_\mathrm{r} \)

\(n_\mathrm{s} \) :

Series connected solar cells

\(k_i \) :

Cell temperature coefficient

\(V_\mathrm{B}\) and \(I_\mathrm{B} \) :

The output converter voltage and current, respectively

k :

The duty cycle of the pulse width modulation (PWM)

\(e_1 \) :

The error in the MPPT control loop

\(e_2 \) :

The error in the speed control loop

J :

The objective function

\( K_{\mathrm{P}1}\) and \(K_{\mathrm{I}1} \) :

The parameters of first PI controller for MPPT control loop

\( K_{\mathrm{P}2}\) and \(K_{\mathrm{I}2} \) :

The parameters of second PI controller for speed control loop

\(t_{\mathrm{sim}} \) :

The time of simulation

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Correspondence to E. S. Ali.

Appendix

Appendix

The system data are as shown below:

  1. (a)

    DC series motor parameters are shown below.

    DC motor parameters

    Values

    Motor rating

    3.5 HP

    Motor rated voltage

    240 V

    Motor rated current

    12 A

    Inertia constant \(J_\mathrm{m} \)

    \(0.0027\,\hbox {kg}\,\hbox {m}^{2}\)

    Damping constant B

    0.0019 N m s/rad

    Armature resistance \(R_\mathrm{a} \)

    \(1.63\,\Omega \)

    Armature inductance \(L_\mathrm{a} \)

    0.0204 H

    Motor speed

    2000 rpm

    Full load torque

    19 N m

  2. (b)

    The parameters of ABC are as follows: the number of colony size \(=\) 50; the number of food sources equals to the half of the colony size; the number of cycles \(=\) 100; the limit \(=\) 100.

  3. (c)

    The parameters of GA are as follows: max generation \(=\) 100; population size \(=\) 50; crossover probabilities \(=\) 0.75; mutation probabilities \(=\) 0.1.

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Oshaba, A.S., Ali, E.S. & Elazim, S.M.A. PI controller design via ABC algorithm for MPPT of PV system supplying DC motor–pump load. Electr Eng 99, 505–518 (2017). https://doi.org/10.1007/s00202-016-0371-8

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  • DOI: https://doi.org/10.1007/s00202-016-0371-8

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