ABSTRACT:
The
current power distribution system involves usage of nonlinear loads that cause
power quality problems.Further, the penetration of renewable energy sources is
increasing in the power networks to satisfy the consistently rising energy
demand, which changes the traditional network plan and control drastically.
This paper presents an intelligently controlled hybrid energy system (HES)
integrated with shunt active power filter (SAPF) to address the power quality
problems. Renewable sources like-Wind, PV and fuel cell (FC) are integrated
into HES and are regulated using artificial intelligence techniques that are
also implemented for maximum power point tracking (MPPT) in both PV and wind
energy systems. The dynamic performance of SAPF is optimized using fuzzy logic,
neural network and adaptive neuro-fuzzy inference system (ANFIS) based control
algorithms. These controllers provide the smooth DC-link voltage and minimize
the total harmonic distortion (THD) produced by the balanced/unbalanced and
nonlinear loads. Comparison of these reveal that the ANFIS based algorithm provides
minimum THD. The system is tested in real-time using hardware-in-the-loop (HIL)
setup. The control schemes are executed on FPGA based OPAL-RT4510computational
engine with microsecond step.
KEYWORDS:
Renewable
energy
Photovoltaic
Wind
energy
Fuel
cell
Maximum
power point tracking
Adaptive
neuro-fuzzy inference system
Shunt
active power filter
SOFTWARE: MATLAB/SIMULINK
PROPOSED SYSTEM CONFIGURATION:
Fig. 1. Proposed system configuration.
EXPERIMENTAL RESULTS:
Fig. 2. Performance
of system balanced & nonlinear load.
Fig. 3. Harmonic
spectrum of source current.
Fig. 4. Harmonic
spectrum of load current.
Fig. 5. Performance
of system under unbalanced & nonlinear load.
Fig. 6. Harmonic
spectrum of source current.
Fig. 7. Harmonic
spectrum of load current.
Fig. 8. Performance
under dynamically load changes.
Fig. 9. DC bus
voltage behavior under switching operation of RESs.
In
this paper, a PV-Wind-FC based adaptive HES has been proposed which is further
integrated with SRF based SAPF to eliminate the current harmonics in the source current. The system
injected the compensating current and decreased the harmonic level when
balanced/unbalanced & nonlinear
loads have been applied. Various control strategies like fuzzy logic, BP-ANN, RBF-ANN, and ANFIS has been
employed for SAPF control and MPPT
control. The ANFIS based strategies regulating the DC-link capacitor voltage have made it more robust
and less susceptible to system transients. The proposed control scheme based on
ANFIS has been validated through an HIL
using the hardware controller OPAL-RT. The performance of the combined system
had also been evaluated for dynamical switching (on/off) for different
renewable energy sources with different types of load. The proposed design has;
mitigated harmonics, minimized voltage variations, allowed feeding of surplus
power to the grid, better utilized the renewable energy sources, and hence has
improved the performance of the grid.
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