ABSTRACT:
This paper presents a novel application of
continuous mixed -norm (CMPN) algorithm-based adaptive control strategy with
the purpose of enhancing the low voltage ride through (LVRT) capability of
grid-connected photovoltaic (PV) power plants. The PV arrays are connected to
the point of common coupling (PCC) through a DC-DC boost converter, a DC-link
capacitor, a gridside inverter, and a three-phase step up transformer. The
DC-DC converter is used for a maximum power point tracking operation based on
the fractional open circuit voltage method. The grid-side inverter is utilized
to control the DC-link voltage and terminal voltage at the PCC through a vector
control scheme. The CMPN algorithm-based adaptive proportional-integral (PI)
controller is used to control the power electronic circuits due to its very
fast convergence. The proposed algorithm updates the PI controller gains online
without the need to fine tune or optimize. For realistic responses, the PV
power plant is connected to the IEEE 39-bus New England test system. The
effectiveness of the proposed control strategy is compared with that obtained
using Taguchi approach- based an optimal PI controller taking into account
subjecting the system to symmetrical, unsymmetrical faults, and unsuccessful reclosing
of circuit breakers due to the existence of permanent fault. The validity of
adaptive control strategy is extensively verified by the simulation results,
which are carried out using PSCAD/EMTDC software. With the proposed
adaptive-controlled PV power plants, the LVRT capability of such system can be
improved
KEYWORDS:
1.
Adaptive
control
2.
Low voltage ride through (LVRT)
3.
Photovoltaic (PV) power systems
4.
Power system control
5.
Power system
dynamic stability
SOFTWARE: MATLAB/SIMULINK
BLOCK DIAGRAM:
Fig.
1. Grid-connected PV power plant. (a) Connection of PV power plant. (b) Single
line diagram of the IEEE 39-bus New England test system.
EXPECTED SIMULATION RESULTS:
Fig.
2. Responses for 3LG temporary fault. (a) Vpcc.
(b) Real power out of the PCC. (c) Reactive power out of the PCC. (d)Vdc. (e) Voltage at bus 18. (f) Inverter
currents with the proposed controller.
Fig.
3. Vpcc response for unsymmetrical
faults. (a) 2LG fault. (b) LL fault. (c) 1LG fault.
Fig.
4. Responses for 3LG permanent fault. (a) Vpcc.
(b) Real power out of the PCC. (c) Reactive power out of the PCC. (d) Vdc.
CONCLUSION:
This
paper has introduced a novel application of the CMPN algorithm-based adaptive
PI control strategy for enhancing the LVRT capability of grid-connected PV
power plants. The proposed control strategy was applied to the DC-DC boost
converter for a maximum power point tracking operation and also to the grid-side
inverter for controlling the Vpcc and Vdc.
The CMPN adaptive filtering algorithm was used to update the proportional and
integral gains of the PI controller online without the need to fine tune or
optimize. For realistic responses, the PV power plant was connected to the IEEE
39-bus New England test system. The simulation results have proven that the system
responses using the CMPN algorithm-based adaptive control strategy are faster,
better damped, and superior to that obtained using Taguchi approach-based an
optimal PI control scheme during the following cases:
1)
subject the system to a symmetrical 3LG temporary fault;
2)
subject the system to different unsymmetrical faults;
3)
subject the system to a symmetrical 3LG permanent fault and unsuccessful
reclosure of CBs.
It
can be claimed from the simulation results that the LVRT capability of
grid-connected PV power plants can be further enhanced using the proposed
adaptive control strategy whatever under grid temporary or permanent fault
condition. By this way, the PV power plants can contribute to the grid
stability and reliability, which represents a greater challenge to the network
operators. Moreover, the proposed algorithm can be also applied to other
renewable energy systems for the same purpose.
REFERENCES:
[1]
PV Power Plants 2014 Industry Guide [Online]. Available: http://www.
pvresources.com
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