Search

The observer design for estimation of back EMF to control the Brushless DC (BLDC) motor is proposed in this paper. Rotor position of the BLDC motor is estimated using the sequence of estimated back EMF. During speed reversal of motor, the actual and estimated values of speed fail to track the reference speed and if corrective action is not taken by the observer, the motor goes into the unstable region. To overcome this problem, the speed estimation algorithm is proposed for BLDC motor control during its speed reversal operation. Infinite Impulse Response (IIR) Butterworth first order low-pass filters are used in the observer for smoothing the estimated back EMFs of the BLDC motor. A new controller scheme based on Modified Hybrid Fuzzy PI (MHFPI) controller is proposed to control the speed of the BLDC motor. The effectiveness of the proposed method has been validated through simulations for different disturbances such as step changes in the reference speed and load torque of the motor and results are compared with the existing methods.

Impedance reach of numerical distance relay is severely affected by Fault Resistance (RF), Fault Inception Angle (FIA), Fault Type (FT), Fault Location (FL), Power Flow Angle (PFA) and series compensation in transmission line. This paper presents a novel standalone adaptive distance protection algorithm for detection, classification and location of fault in presence of variable fault resistance. It is based on adaptive slope tracking method to detect and classify the fault in combination with modified Fourier filter algorithm for locating the fault. To realize the effectiveness of the proposed technique, simulations are performed in PSCAD using multiple run facility & validation is carried out in MATLAB® considering wide variation in power system disturbances. Due to adaptive setting of quadrilateral characteristics in accordance with variation in fault impedance, the proposed technique is 100 % accurate for detection & classification of faults with error in fault location estimation to be within 1 %. Moreover, the proposed technique provides significant improvement in response time and estimation of fault location as compared to existing distance relaying algorithms, which are the key attributes of multi-functional numerical relay

The direct power control (DPC) technique has been proposed as an alternative method to sophisticated current control techniques in order to synthesise the instantaneous active and reactive powers fed by the inverter into the grid. The method selects the voltage vector of the inverter based on the quantised values of the instantaneous active and reactive power errors and thereby controls the power exchange between inverter and the Point of Common Coupling (PCC) directly. The method has better dynamic performance, an inherent decoupling of active and reactive powers and robustness against parameter variations. However, the application of DPC to shunt active power filter (SAPF) requires high sampling frequency in the digital controller and at the same time suffers from the issue of the large variation in the switching frequency. This work proposes implementation of a modified switching table of DPC using multisector Discrete Space Vector Modulation(DSVM) concept for the SAPF to alleviate the problem of high sampling frequency requirement and variation in switching frequency and reduce burden on the controller. The performance of the method is evaluated in MATLAB Simulink® environment, verified with 2 kVA laboratory prototype under various load conditions and compared with constant switching frequency-predictive deadbeat DPC method. [ABSTRACT FROM AUTHOR]

A contemporary research topic of interest is hybrid nanofluids. The goal of this study is to see how hybrid nanoparticles in transformer oil affect the failure probability, reliability, and streamer dynamics when subjected to massive electrical stress. A 2D axisymmetric hydrodynamic driftdiffusion model is developed to study the streamer dynamics in a hybrid nanofluid with different charging times. Failure probability and reliability for different nanofluids are estimated using the Weibull distribution function. The statistical study reveals that the hybrid nanofluid is more reliable and less dangerous, extending the transformers' service life. When compared to mineral oil and individually dispersed nanoparticles, a homogeneous mixture of Fe3O4 and Al2O3 nanoparticles reduces failure rate by 73.94%, 56.29%, and 30.41%, respectively. For positive streamer dynamics, the influence of altering the charging time of distributed multiple nanoparticles was explored. The dispersion of hybrid nanoparticles in transformer oil has been found to minimize the ionization rate, streamer velocity, and streamer re-ignition rate. [ABSTRACT FROM AUTHOR]