ABSTRACT
This paper aims to present an alternative methodology
to improve the tuning of proportional integral multi-resonant (PI-MR)
controller applied to the current control loop of a shunt active power filter
(SAPF) by using differential evolution (DE) metaheuristic method. For computing
the PI-MR controller gains, the methodology based on Naslin polynomial (NP) can
be employed, although its performance is limited. On the other hand, tuning
procedures accomplished by trial-and error methods have been largely used. In
order to fill the lack of methodological procedures to determine the PI-MR controller
gains, the use of DE metaheuristic optimization algorithm is proposed to
perform an optimal adjustment. The DE algorithm operates minimizing an
appropriate cost function, taking into account the total harmonic distortion of
the source current, the error of the compensation\ current control loop, and
the saturation limit of the control action. The effectiveness of the proposed
methodology is compared to the NP-based method, applied to a single phase SAPF.
The proposed methodology is validated by means of both simulation and
experimental results. The evaluation of the static and dynamic performances is
obtained from experimental tests performed based on digital signal processor.
KEYWORDS:
1.
Differential evolution
2.
Multi-resonant
controller
3.
Optimization
4.
Shunt active
power filter.
SOFTWARE: MATLAB/SIMULINK
CIRCUIT
DIAGRAM:
Fig. 1. Single-phase SAPF scheme.
EXPECTED SIMULATION RESULTS:
Fig.
2. Simulation results of SAPF operating with Load 1 (utility voltage vs(200V/div),
utility current is and compensation current ic(20A/div),
load current iL(30A/div)): (a) PI controller; (b) PI-MRNP
controller; (c) PI-MRDE controller.
Fig.
3.Simulation results of SAPF operating with Load 2 (utility voltage vs(200V/div),
utility current is and compensation current ic(20A/div),
load current iL(30A/div)): (a) PI controller; (b) PI-MRNP
controller; (c) PI-MRDE controller.
Fig. 4. Harmonic spectra and THD of the source current obtained from simulation results with PI, PI-MRNP and PI-MRDE controllers: (a) Load 1; (b) Load 2.
CONCLUSION
This
paper proposes an alternative methodology using DE metaheuristic optimization
algorithm for obtaining systematic procedures to achieve the PI-MR controller
gains employed in the current control loop of a SAPF. A comparative analysis involving
the classical PI controller and two other PI-MR controllers was performed. The
classical PI controller was tuned using the well-known frequency response
method, while the MR controllers were tuned considering the NP-based approach,
as well as DE metaheuristic optimization algorithm.Extensive simulation and
experimental results proved that superior performance is achieved when the SAPF
operates with the DE-based PI-MR controller. Therefore, it can be concluded
that the DE metaheuristic method represents a promising approach for tuning
PI-MR controller for active power filtering applications.
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