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The above researches focused on improving the power quality using a single type of DSR.
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This paper proposes a new technique for power quality assessment, using rule-based S-Transform (ST) as a feature extraction tool and Adaptive Boost (AdaBoost) as a classifier.
In [19] the smart grid approach is presented as a solution to grid power quality problems by using several power conversion techniques where the DC-DC stage is used to provide power conditioning the DC-DC stage.
The impact resulting from plug-in battery electric vehicles charging as single-phase loads in terms of reliability and power quality are quantified using a Monte Carlo Simulation.
The proposed methodology evaluates the power quality state estimation using the enhanced numerical differentiation (END) method, which obtains the periodic steady state solution of a power network.
The present paper proposes the design of a tool to quantify power quality (PQ) parameters using wavelets and fuzzy sets theory.
A system design for power quality security which uses solid oxide fuel cell (SOFC) technology is described.
This paper presents a classification method for power quality (PQ) disturbances by using efficient features of the PQ signals for an accurate classification with minimum computational complexity.
The proposed application not only can effectively reduce the circuit loss and improves phase balancing, but also enhances power quality efficiently under easily using environment.
In this paper, a current-source converter based unified power quality conditioner (UPQC) is used for the flexible integration of pitch controlled fixed speed wind generator (FSWG) to IEEE 13 node test feeder.
A power quality analyzer was also used in order to present steady-state plots for voltage and current phasor representations, and THD and FFT experimental plots and values in order to show system response to poor power quality conditions at the grid voltage.
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