TSKARNA-norm Adaption Based NLMS with Optimized Fractional Order PID Controller Gains for Voltage Power Quality

The operation of a dynamic voltage restorer(DVR)is studied using a three-phase voltage source converter(VSC)-based topology to alleviate voltage anomalies from a polluted supply voltage.The control algorithm used included two components.The first is an adaptive Takagi-Sugeno-Kang(TSK)-based adaptive reweighted L1 norm adaption-based normalized least mean square(TSK-ARNA-NLMS)unit,which is proposed for the extraction of fundamental active and reactive components from the non-ideal supply and is further employed to generate the load reference voltage and switching pulse for the VSC.The step size was evaluated using the proposed TSK-ARNA-NLMS controller,and the TSK unit was optimized by integration with the marine predator algorithm(MPA)for a faster convergence rate.The second,a fractional-order PID controller(FOPID),was employed for AC-and DC-link voltage regulation and was approximated using the Oustaloup technique.The FOPID()PI Dγμprovides more freedom for tuning the settling time,rise time,and overshoot.The FOPID coefficients(Ki,Kd,Kp,γ,andμ)were optimized by employing an advanced ant lion optimization(ALO)meta-heuristics technique to minimize the performance index,namely,the integral time absolute error(ITAE)and assess the accuracy of controllers.The DVR performance was validated under dynamic-and steady-state conditions.

Designing an On-board Charger to Efficiently Charge Multiple Electric Vehicles

An on-board charger for efficiently charging multiple battery-operated electric vehicles(EVs)is introduced.It has evolved as a single-input dual-output(SIDO)integrated boost-single ended primary inductor converter(SEPIC)fly-back converter,offering cost-effectiveness,reliability,and higher efficiency compared to conventional chargers with equivalent specifications.The proposed system includes an additional regulated output terminal,in addition to an existing terminal for charging the EV battery of a 4-wheeler,which can be used to charge another EV battery,preferably a 2-wheeler.With the aid of control techniques,unity power factor operations are obtained during constant-voltage(CV)/constant-current(CC)charging for the grid-to-vehicle(G2V)operating mode.Using mathematical modelling analysis,the proposed system is developed in a Matlab/Simulink environment,and the results are validated in a real-time simulator using dSPACE-1104.The proposed system is employed for charging the batteries of two EVs with capacities of 400 V,40 A·h and 48 V,52 A·h for the 4-wheeler and 2-wheeler,respectively.Its performance is investigated under different operating modes and over a wide range of supply voltage variations to ensure safe and reliable operation of the charger.

Control Algorithm Based on Limit Cycle Oscillator-FLL for UPQC-S with Optimized PI Gains

This paper involves a limit cycle oscillator-frequency lock loop(LCO-FLL)based control algorithm for unified power quality controllers-S type(UPQC-S)for compensation of reactive power,to maintain a unity power factor,regulate constant voltage at the PCC,mitigate sag,swell and to eliminate harmonics.In this approach,an extraction of fundamental in-phase and quadrature components for the estimation of reference signals are taken from the LCO-FLL circuit.The control LCO-FLL provides a high grade of protection against sag-swell voltages,unbalance loading and harmonics present in the utility grid.In addition to that,it has advantageous characteristics of synchronization with the grid frequency at any previously mentioned conditions without use of phase locked loops or trigonometric functions.Other advantages of the LCO-FLL are to give useful information to estimate fundamental components from a highly polluted grid scenario.The values obtained from the JAYA optimization algorithm are used to fine-tune the proportional integral(PI)controller gains,so that it maintains DC link voltage to the desired level.The mean square error(MSE)is employed as an objective function for optimizing the error between actual and reference values.The control algorithm based on LCO-FLL is developed in MATLAB/Simulink software and it is tested for power conditioning features.

Control of UPQC Based on Steady State Linear Kalman Filter for Compensation of Power Quality Problems

A frequency lock loop(FLL)based steady state linear Kalman filter(SSLKF)for unified power quality conditioner(UPQC)control in three-phase systems is introduced.The SSLKF provides a highly accurate and fast estimation of grid frequency and the fundamental components(FCs)of the input signals.The Kalman filter is designed using an optimized filtering technique and intrinsic adaptive bandwidth architecture,and is easily integrated into a multiple model system.Therefore,the Kalman state estimator is fast and simple.The fundamental positive sequence components(FPSCs)of the grid voltages in a UPQC system are estimated via these SSLKF-FLL based filters.The estimation of reference signals for a UPQC controller is based on these FPSCs.Therefore,both active filters of a UPQC can perform one and more functions towards improving power quality in a distribution network.In addition to the SSLKF-FLL based algorithm,a bat optimization algorithm(based on the echolocation phenomenon of bats)is implemented to estimate the value of the proportional integral(PI)controller gains.The bat algorithm has a tendency to automatically zoom into a region where a promising alternative solution occurs,preventing the solution from becoming trapped in a local minima.The complete three-phase UPQC is simulated in the Matlab/Simulink platform and the hardware is tested under various power quality problems.

Robust Iteration-dependent Least Mean Square-based Distribution Static Compensator Using Optimized PI Gains

A robust iteration-dependent least mean square(RIDLMS)algorithm-based fundamental extractor is developed to estimate the fundamental components of the load current for a four-wire DSTATCOM with a nonlinear load.The averaging parameter for calculating the variable step size is iteration dependent and uses variable tuning parameters.Rather than using the current value,the previous learning rate was used in this method to achieve a more adaptive solution.This additional control factor aids in determining the exact learning rate,resulting in reliable and convergent outcomes.Its faster convergence rate and the avoidance of local minima make it advantageous.The estimation of the PI controller gains is achieved through a self-adaptive multi-population algorithm.The adaptive change in the group number will increase exploration and exploitation.The self-adaptive nature of the algorithm was used to determine the subpopulation number needed according to the fitness value.The main advantage of this self-adaptive nature is the multi-population spread throughout the search space for a better optimal solution.The estimated gains of the PI controllers are used for the DC bus and AC terminal voltage error minimization.The RIDLMS-based control with PI gains obtained using the proposed optimization algorithm showed better power quality performance.The considered RIDLMS-supported control was demonstrated experimentally using d-SPACE-1104.

Adaptive Observer for Dynamic Voltage Restorer with Optimized Proportional Integral Gains

An algorithm based on a sliding-mode adaptive observer is proposed for the effective control of dynamic voltage restorers(DVRs).Three single-phase voltage source converter-based topologies are implemented for the DVR.In this control,frequency adaption is considered for estimating the phase angle,system frequency,and fundamental component of the disturbed input voltage signals.The estimated fundamental component of the supply voltage is used to generate the DVR reference load voltage.The phase jump in the supply voltage is also considered for DVR compensation studies along with voltage sag,swell,and voltage distortions.For this purpose,the gains of the proportional integral(PI)controllers used in this control algorithm are estimated using a nature-inspired optimization approach for the desired response.A moth flame optimization algorithm is implemented for PI controller gain tuning owing to the advantage of finding the best solution by each moth’s search and updating it.Through Matlab simulation and hardware testing,the performance of the DVR with an adaptive observer is found to be satisfactory for supply voltage sag,swell,phase jump,and voltage distortions.

Ant Lion Algorithm for Optimized Controller Gains for Power Quality Enrichment of Off-grid Wind Power Harnessing Units

The proposed system uses an algorithm that works on the admittance of the system,for estimating the reference values of generated currents for an off-grid wind power harnessing unit(WPHU).The controller controls the voltage and maintains the frequency within the limits while working with both linear and nonlinear loads for varying wind speeds.The admittance algorithm is simple and easy to implement and works very efficiently to generate the triggering signals for the controller of the WPHU.The wind power harnessing unit comprising of a squirrel cage induction generator,a star-delta transformer,a battery storage system and the control unit are modeled using Matlab/Simulink R2019.An isolated transformer with a star-delta configuration connects the load and the generator circuit with the controller to reduce the dc bus voltage and mitigate current in the neutral line.The response of the system during the dynamic loading depends on the best possible compensator proportional-integral(PI)gains.The antlion optimization algorithm is compared with particle swarm optimization and grey wolf optimization and is found to have the advantages of good convergence,high efficiency and fast calculating speed.It is therefore used to extract the optimal values of frequency and voltage PI gains.The simulation results of the control algorithm for the WPHU are validated in a real-time environment in a dSpace1104 laboratory set up.This algorithm is proven to have a quick response,maintain the required frequency,suppress the current harmonics,regulate voltage,help in balancing the load and compensating for the neutral current.

Optimized Controller Gains Using Grey Wolf Algorithm for Grid Tied Solar Power Generation with Improved Dynamics and Power Quality

This study proposes a control algorithm based on synchronous reference frame theory with unit templates instead of a phase locked loop for grid-connected photovoltaic(PV)solar system,comprising solar PV panels,DC-DC converter,controller for maximum power point tracking,resistance capacitance ripple filter,insulated-gate bipolar transistor based controller,interfacing inductor,linear and nonlinear loads.The dynamic performance of the grid connected solar system depends on the effect operation of the control algorithm,comprising two proportional-integral controllers.These controllers estimate the reference solar-grid currents,which in turn generate pulses for the three-leg voltage source converter.The grey wolf optimization algorithm is used to optimize the controller gains of the proportional-integral controllers,resulting in excellent performance compared to that of existing optimization algorithms.The compensation for neutral current is provided by a star-delta transformer(non-isolated),and the proposed solar PV grid system provides zero voltage regulation and eliminates harmonics,in addition to load balancing.Maximum power extraction from the solar panel is achieved using the incremental conductance algorithm for the DC-DC converter supplying solar power to the DC bus capacitor,which in turn supplies this power to the grid with improved dynamics and quality.The solar system along with the control algorithm and controller is modeled using Simulink in Matlab 2019.