Kamran AliID, Qudrat Khan, Shafaat Ullah, Ilyas Khan, Laiq Khan |

- 2020-07-14

- 30 M

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PV (Photovoltaic) cells have nonlinear current-voltage (I - V) and power-voltage

(P - V) characteristics with a distinct maximum power point (MPP) that entirely

depends on the ambient meteorological conditions (i.e. solar irradiance and

temperature). Hence, to continuously extract and deliver the maximum possible

power from the PV system, under given meteorological conditions, the maximum

power point tracking (MPPT) control strategy needs to be formulated that

continuously operates the PV system at its MPP. To achieve this goal, a hybrid

nonlinear, very fast and efficient MPPT control strategy, based on the robust

integral backstepping (RIB) control, is formulated in this research article. The

simulation testbed comprises a standalone PV array, a non-inverting buck-boost

(NIBB) DC-DC power converter, a purely resistive and a dynamic load (sound

system). The proposed MPPT control scheme consists of two loops, where the first

loop generates the real-time offline reference peak power voltage through an

adaptive neuro-fuzzy inference system (ANFIS) network, which is then utilized in

the second loop as a set-point value for generating a control signal and then

forcing the PV system to be operated at this set-point by continuously adjusting

the duty ratio of the power converter. This control strategy exhibits no overshoot,

fast convergence, good transient response, fast rising and settling times and

minimum output tracking error. The MATLAB/Simulink platform is used to test the

performance of the proposed MPPT strategy against varying meteorological

conditions, plant current and voltage faults and plant parametric uncertainties. To

validate the superiority of the proposed control strategy, a comparative analysis of

the proposed control strategy is presented with the nonlinear backstepping (B),

integral backstepping controller (IB) and conventional PID and P&O based MPPT

controllers.

1 : SIMULINK ⺻

1.1 SIMULINK 1

5

Ķ 7

ùķ̼ Ķ (Configuration Parameters) 8

ùķ̼ 9

Ķ ǥ 9

ǥ 11

2.2 ùķ̼ 13

̺й 17

º 23

DC ùķ̼ 24

Լ 29

й(difference equation) 34

Subsystem(νý) 37

2 :

Nonlinear robust integral backstepping based MPPT control for

stand-alone photovoltaic system

1. Introduction 41

2. Significant contributions 42

3. Reference peak power voltage estimation through Adaptive

Neuro-Fuzzy Inference System (ANFIS) 44

4. Robust integral backstepping MPPT controller design 51

5. Simulation results and discussion 57

6. Conclusions and future research recommendations 69

7. References 69