Sidra Mumtaz, Laiq Khan, Saghir Ahmed, Rabiah Bader |

- 2020-07-10

- 20 M

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This paper focuses on the indirect adaptive tracking control of renewable energy

sources in a grid-connected hybrid power system. The renewable energy systems

have low efficiency and intermittent nature due to unpredictable meteorological

conditions. The domestic load and the conventional charging stations behave in an

uncertain manner. To operate the renewable energy sources efficiently for

harvesting maximum power, instantaneous nonlinear dynamics should be captured

online. A Chebyshev-wavelet embedded NeuroFuzzy indirect adaptive MPPT

(maximum power point tracking) control paradigm is proposed for variable speed

wind turbine-permanent synchronous generator (VSWT-PMSG). A Hermitewavelet

incorporated NeuroFuzzy indirect adaptive MPPT control strategy for photovoltaic

(PV) system to extract maximum power and indirect adaptive tracking control

scheme for Solid Oxide Fuel Cell (SOFC) is developed. A comprehensive simulation

test-bed for a gridconnected hybrid power system is developed in Matlab/Simulink.

The robustness of the suggested indirect adaptive control paradigms are evaluated

through simulation results in a grid-connected hybrid power system test-bed by

comparison with conventional and intelligent control techniques. The simulation

results validate the effectiveness of the proposed control paradigms.

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 :

Indirect adaptive soft computing based wavelet-embedded control

paradigms for WT/ PV/SOFC in a grid/charging station connected

hybrid power system

1. Introduction 41

2. Problem formulation 44

3. VSWT-PMSG MPPT subsystem adaptive control design 46

4. SOFC adaptive control problem 52

5. Mathematical modeling 54

6. Results and discussion 59

7. Conclusion 69

8. References 70