Voltage Dynamic Response Research Articles

Gradient descent based dynamic optimization for VSG dominated microgrid

AbstractAs the integration of distributed generation units into the power grid continues to grow, the system becomes increasingly vulnerable to power fluctuations and potential failures, which significantly challenge grid stability. Virtual synchronous generators (VSGs) have emerged as a key technology to enhance grid stability by emulating the behavior of traditional synchronous generators. However, with multiple VSGs operating within independent microgrids, coordinating their control parameters becomes critical to ensuring stable and reliable operation. This article proposes an optimization method based on the gradient descent algorithm to fine‐tune the control parameters of multiple VSGs in independent microgrids. A small‐signal model for microgrids with multiple VSGs is developed to analyze the system's dynamic behavior under small disturbances. The proposed method optimizes VSG control parameters to improve the frequency and voltage dynamic response and enhance the overall system stability. The simulation results demonstrate that the proposed multi‐VSG control parameter optimization method significantly enhances the frequency and voltage dynamic response, as well as the stability of the independent microgrid under small disturbances, offering a practical solution for improving microgrid performance in real‐world applications.

Dynamic Multi-Physics Modelling of a PEM Stack for a Digital Twin Application

Electrolysis plants producing green hydrogen often face fluctuating renewable power availability and prices. Proton-Exchange-Membrane (PEM) electrolysis technology offers a potential solution, as fast dynamic load changes are possible. With expeditious adjustments to the power availability, a PEM plant can contribute to grid stability while using economically attractive excess power. Alternatively, adapting to fluctuating product demands can reduce the required energy for intermediate storage of hydrogen in liquid form or in pressure tanks.To consistently operate the plant at the optimal load point, precise monitoring of plant performance, integrity, and state is vital. A digital twin running concurrently with the plant increases the available information of the stack data, as well as it simultaneously offers a platform to engage in anomaly detection and diagnosis processes. The goal is to increase reliability, availability, and maintainability, which is made possible through data provided by virtual sensors (calculated sensor values from the digital twin).With a digital twin, critical states of non-measurable conditions in a PEM cell, such as hydrogen crossover, temperature gradients, or the state of degradation, can be determined and addressed in real-time. With all additional information accessible, the digital twin can visualize plant operation and helps in determining efficient transitions between operating points, augmenting plant operation and optimally utilizing the PEM plant’s load flexibility.To leverage these advantages, a digital twin is developed for PEM electrolysis plants. Its structure consists of a dynamic plant model, an interface to the plant, and a state estimation algorithm. The modelling focus lies on the PEM stacks, for which a detailed dynamic multi-physics model is developed. It is structured into the submodels of mass transport, voltage, temperature, and pressure, which combine into an equation-based model solved by a DAE solver. Main features are the membrane discretization for mass transport via the Stefan-Maxwell equations and the one-dimensionally resolved temperature profile across the cell. The voltage model is represented in form of an equivalent circuit, modelling the electric effects of each individual cell layer.Validation and results of the dynamic model are shown, especially highlighting the interaction and dependencies between the sub-models. The mass transport model shows non-linear concentration profiles of crossover components inside the membrane. Consequently, an assessment of the different positions of additional recombination catalyst layers inside the membrane is presented, including the influence of different operating conditions and dynamic loads. Following, temperature profiles across the cell and dynamic voltage responses for operation are shown. All results are discussed in the context of a simulated PEM electrolysis plant in dynamic operation, which is especially expedient concerning automatic load change and automatic start-up strategies.

Using the nonlinearity of a PEM water electrolyzer cell for its dynamic model characterization

The voltage response of a water electrolyzer at low frequencies is characterized by a combination of a static polarization curve and dynamic, capacitive effects. In this paper, a model combining these two phenomena is created, which incorporates the Butler–Volmer equation in parallel with a capacitance in order to produce differential equations for the activation overpotentials separately on both electrodes. A parameter fitting methodology is then developed for obtaining the seven model parameters from a set of low-frequency, high-amplitude dynamic waveform measurements. The method is further implemented in an electrolyzer modeling toolbox for MATLAB. The model built in this study is proven to predict well both static and dynamic voltage responses down to the 1Hz frequency. At higher frequencies and at small amplitudes the model reduces to the Randles equivalent circuit, and in a static case to the polarization curve of the cell. The proposed methodology can be used for probing individual electrode properties with full-cell measurements and providing a reliable tool for simulating water electrolyzer voltage responses with arbitrary waveforms and amplitudes.

Enhancing PEM fuel cell dynamic performance: Co-optimization of cathode catalyst layer composition and operating conditions using a novel surrogate model

Optimizing the cathode catalyst layer (CCL) composition and operating conditions to enhance the dynamic performance of proton exchange membrane fuel cells garners significant attention. Although machine learning surrogate models are efficient for fuel cell analysis and optimization, the varied voltage dynamic response patterns (e.g., loading failure, voltage undershoot, and voltage hysteresis) challenge regression surrogate models designed for steady-state performance predictions. In response, this study introduces a joint framework combining classification and regression models for dynamic performance prediction. For training, a transient, two-phase, non-isothermal fuel cell model with integrated catalyst agglomerate is developed. The dynamic voltage deviation (σV) is proposed as an index to characterize the dynamic performance of the fuel cell. This joint surrogate model achieves correlation coefficients of 0.9976 and 0.9961 for predicting σV in training and test sets, respectively. Through this model, sensitivity analyses of the CCL composition and operating conditions are conducted to quantify their impact and interactions on the fuel cell's dynamic performance. Besides, the analysis reveals a trade-off between dynamic performance and steady-state output. To balance these, a multi-objective optimization is conducted. The results indicate that, compared to the base case, dynamic and steady-state performance improved by 44 % and 8 %, respectively.

Dynamic Fractional-Order Model of Proton Exchange Membrane Fuel Cell System for Sustainability Improvement

The proton exchange membrane fuel cell (PEMFC) stands at the forefront of advancing energy sustainability. Effective monitoring, control, diagnosis, and prognosis are crucial for optimizing the PEMFC system’s sustainability, necessitating a dynamic model that can capture the transient response of the PEMFC. This paper uses a dynamic fractional-order model to describe the behaviors of a stationary micro combined heat and power (mCHP) PEMFC stack. Based on the fractional-order equivalent circuit model, the applied model accurately represents the electrochemical impedance spectroscopy (EIS) and the dynamic voltage response under transient conditions. The applied model is validated through experiments on an mCHP PEMFC stack under various fault conditions. The EIS data is analyzed under different current densities and various fault conditions, including the stoichiometry of the anode and cathode, the stack temperature, and the relative humidity. The dynamic voltage response of the applied model shows good correspondence with experimental results in both phase and amplitude, thereby affirming the method’s precision and solidifying its role as a reliable tool for enhancing the sustainability and operational efficiency of PEMFC systems.

Improvement of grid injected currents in single-phase inverters rejecting DC link voltage oscillations based on multi-resonant filtering

The operation of grid-tied single-phase inverters generates oscillations in its DC link voltage. If only active/reactive power is controlled by the inverter, this oscillation is at twice the grid frequency. In situations where the inverter output current and/or the grid voltage also has harmonic components, the DC link voltage becomes also polluted by oscillating components at even multiple frequencies of the grid voltage. Such oscillations are propagated through the DC link voltage control loop, increasing the THD index of grid current reference signal. To solve this drawback, this article proposes the insertion of a multi-resonant filter into the DC link voltage control loop, ensuring a harmonic free grid current reference signal. With the proposed filter and without any increase in the power circuit, the use of smaller capacitances in the DC link is allowed, since the DC link voltage oscillation does not interfere in the power quality indexes of the controlled current. A filter tuning methodology is presented to ensure that the design of each filter and of the DC link voltage controller is independent, relating the filter settling time and the system stability. At the same time, the use of the proposed filter allows the voltage controller to be tuned at higher frequencies, improving the DC link voltage dynamic response. The proposal is experimentally validated through a single-phase grid-tied double-stage photovoltaic (PV) system, that can also operate only as a parallel active power filter (PAPF) or, simultaneously as a multifunctional PAPF + PV system.

Current Pulse-Based Measurement Technique for Zinc–Air Battery Parameters

Zinc–air batteries possess advantages such as high energy density, low operational costs, and abundant reserves of raw materials, demonstrating broad prospects for applications in areas like stationary power supplies and emergency power sources. However, despite significant advancements in zinc–air battery technology, a comprehensive measurement model for zinc–air battery parameters is still lacking. This paper utilizes a gas diffusion model to separately calculate the concentration polarization of zinc–air batteries, decoupling it from electrochemical polarization and ohmic polarization, simplifying the equivalent circuit model of zinc–air batteries into a first-order RC circuit. Subsequently, based on the simplified equivalent circuit model and gas diffusion model, a zinc–air battery parameter measurement technique utilizing current pulse methods is proposed, with predictions made for the dynamic voltage response during current pulse discharges. Validation of this method was conducted through single current pulses and step current pulses. Experimental results demonstrate the method’s capability to accurately measure zinc–air battery parameters and predict the dynamic voltage response.

Time-Scale Separation Control for a Class of Current Distribution Strategy in AMBs-Rotor System With Bounded Bus Voltage

In active magnetic bearings (AMBs) systems, good dynamic characteristics and low power consumption are two important concerns, which are difficult to be obtained simultaneously if considering bounded bus voltage. This paper proposes a universal current distribution constraint format and a related time-scale separation control scheme to achieve improvements in both aspects. Considering the bounded bus voltage and symmetrical configuration in one AMB control axis, a double-input three-order nonlinear model is established to describe the AMBs-rotor system. Subsequently, a constraint format is propounded to cover and improve existing current distribution strategies. The power consumption and voltage response are compared between different instances under this constraint format. Then, the double-input model is converted to a single-input cascaded nonlinear system, and a time-scale separation control scheme is designed accordingly. The scheme contains a nominal controller and a dynamic inversion. The nominal controller determines the dynamic characteristics of the AMBs-rotor system. The dynamic inversion compensates for the nonlinearity of the system based on the characteristics of the amplifier. This scheme can preserve the closed-loop stability by only adjusting the time-scale coefficient. Finally, experimental results demonstrate the advantages of the proposed method in aspects of dynamic performance, voltage response, and power consumption.

Dynamic resistance and voltage response of a REBCO bifilar stack under perpendicular DC-biased AC magnetic fields

The dynamic resistance of REBCO (REBa2Cu3O7-d, RE stands for rare earth), coated conductors (CCs) is a key parameter in many high-temperature superconductor applications where CCs carry DC currents exposed to AC and DC magnetic fields, such as field-triggered persistent current switches, flux pumps, and fault current limiters. In this work, dynamic resistance and dynamic voltage have been studied via experiments and finite element method (FEM) simulations in a REBCO bifilar stack at 77 K, under combined AC and DC magnetic fields with different magnitudes, frequencies, and waveforms. Our results show some distinct features of dynamic resistance and voltage from those under pure AC magnetic fields. With an increasing DC magnetic field, the dynamic resistance exhibits an obvious linearity with the applied AC magnetic field, and becomes less dependent on the AC field frequency. The fundamental frequency of the dynamic voltage under a DC magnetic field becomes the same as that of the applied AC field, which completely differs from the pure AC field case where the fundamental frequency doubles. For the first time, instantaneous threshold field (B th) values are obtained from the dynamic voltage, which are substantially different in the field-increasing and field-decreasing processes. These key differences are attributed to the dominant role of DC magnetic fields in determining the critical current of the superconductor, which significantly dwarfs the influence of AC fields. These new discoveries may help researchers better understand the electromagnetism of superconductors and be useful for relevant applications.

Electrochemical Impedance Spectroscopy‐Based Dynamic Modeling of Lithium‐Ion Batteries Using a Simple Equivalent Circuit Model

As one of the most commonly used models for describing the dynamic voltage response of lithium‐ion batteries (LIBs), the equivalent circuit model (ECM) is routinely parameterized using the time–domain experimental data from some dynamic tests. One downside of this time–domain approach is a lack of credible physical interpretation about the model parameters. In this article, a genuine electrochemical impedance spectroscopy (EIS)‐based dynamic modeling approach for LIBs is developed, which only uses low‐frequency EIS data in parameterization of the ECM. The EIS‐based modeling method combines simplicity, high accuracy, and clear physical interpretation. With the EIS‐based modeling method, a simple ECM, namely, a serial connection of a resistance (), describing Ohmic polarization and interfacial reactions, and an resistance–capacitance parallel branch (), describing diffusion polarization, suffice to accurately capture LIB dynamics in most applications.

Energy management and power quality improvement of microgrid system through modified water wave optimization

A comparative study of energy management strategies and PQ improvement schemes for a Fuel Cell, Battery, and SuperCapacitor integrated Microgrid system has been projected utilizing the MATLAB/Simulink architecture in this research article. For effective energy management and PQ enhancement, a Modified Water Wave Optimization algorithm based on adaptive population size and adaptive wavelength coefficient has been proposed. The MWWO method robustly and dynamically tunes the parameters of the Proportional Integral controller for effective operation. The efficiency of the proposed technique has been compared with the traditional methods regarding hydrogen consumption, load power deliberation, power quality and overall system efficiency. The results obtained and the numerical analysis confers the superiority of the suggested technique over other methods for enhanced dynamic voltage response, low fuel consumption, reduced harmonics and better efficacy thereby proving its real-time employment.

Achieving a Highly Stable Perovskite Photodetector with a Long Lifetime Fabricated via an All-Vacuum Deposition Process

Hybrid organic-inorganic metal halide perovskites (HOIP) have become a promising visible light sensing material due to their excellent optoelectronic characteristics. Despite the superiority, overcoming the stability issue for commercialization remains a challenge. Herein, an extremely stable photodetector was demonstrated and fabricated with Cs0.06FA0.94Pb(I0.68Br0.32)3 perovskite by an all-vacuum process. The photodetector achieves a current density up to 1.793 × 10-2 A cm-2 under standard one sun solar illumination while maintaining a current density as low as 8.627 × 10-10 A cm-2 at zero bias voltage. The linear dynamic range (LDR) and transient voltage response were found to be comparable to the silicon-based photodetector (Newport 818-SL). Most importantly, the device maintains 95% of the initial performance after 960 h of incessant exposure under one sun solar illumination. The achievements of these outstanding results contributed to the all-vacuum deposition process delivering a film with high stability and good uniformity, which in turn delays the degradation process. The degradation mechanism is further investigated by impedance spectroscopy to reveal the charge dynamics in the photodetector under different exposure times.

Design and analysis of a d15 mode piezoelectric energy generator using friction-induced vibration

Research works have been conducted on transverse and longitudinal mode piezoelectric energy generation to collect energy from ambient vibrations. However, the inconsistency with the frequency of the energy source and low output power density remain problems for high energy output. In this work, we propose a shear mode piezoelectric energy generator, which utilizes the friction-induced vibration (FIV) and high shear mode piezoelectric coefficient to improve the energy output. A piezoelectric coupled FIV mathematical model is developed to accurately calculate the dynamic vibration response and voltage output. The dynamic voltage response is validated by experiment, and it proves the possibility of continuous friction-induced high-frequency vibration. The energy generation process is evaluated by transient charging simulation of a storage capacitor through an iteration process, which was experimentally validated in the literature. Parameter studies have been conducted to investigate the influences of the piezoelectric patch dimensional parameters, vibration system parameters, friction model parameters, methods of electrical connections, and different piezoelectric materials on the energy generation performance to provide guidance for better design. Under ideal experiment conditions with proper parameters, a volume of m3 PZT4 piezoelectric material indicates root mean square (RMS) charging power density of Wm−3 and Wm−3 with electrically in parallel and electrically in series, respectively. While using the same amount of material and structural setup, the single crystal PMN-PT piezoelectric material shows RMS charging power density of Wm−3 and Wm−3 with electrically in parallel and electrically in series, correspondingly. These promising results demonstrate that close to W-level RMS charging power output may be realized by structure optimization of energy generator design and incorporating multiple generators together for operation. Possible incorporation into vehicle braking systems can be considered to utilize the wasted friction energy, and it may offer an energy supply for low-power wireless devices.

Machine learning for prediction models to mitigate the voltage deviation in photovoltaic-rich distributed network

<span lang="EN-US">The voltage deviation is one of the most crucial power quality issues that occur in electrical power systems. Renewable energy plays a vital role in electrical distribution networks due to the high economic returns. However, the presence of photovoltaic systems changes the nature of the energy flow in the grid and causes many problems such as voltage deviation. In this work, several predictive models are examined for voltage regulation in the Jordanian Sabha distribution network equipped with photovoltaic farms. The augmented grey wolf optimizer is used to train the different predictive models. To evaluate the performance of models, a value of one for regression factor and a low value for root mean square error, mean square error, and mean absolute error are used as standards. In addition, a comparison between nineteen predictive models has been made. The results have proved the capability of linear regression and the gaussian process to restore the bus voltages in the distribution network accurately and quickly and to solve the shortening in the voltage dynamic response caused by the iterative nature of the heuristic algorithm. </span>

Dynamic Aggregation Method of Wind Farms with Virtual Synchronous Generator-Controlled Wind Turbines

The frequency and voltage dynamic processes of each wind turbine in the existing wind farm are different, and the available aggregation model of wind farms mainly focuses on the steady-state output power, lacking an effective dynamic aggregation mechanism. Wind turbines usually adopt the virtual synchronous generator method (VSG) to simulate the external characteristics of the traditional synchronous generator. Its frequency dynamic response is mainly affected by the virtual inertia and damping parameters, and the excitation regulator parameters determine the voltage dynamic response. Therefore, the aggregation method of the traditional synchronous generator is also applicable to such wind turbines. Firstly, the dynamic characteristics of the points of wind farms’ point of common coupling (PCC) are discussed. Then, the dynamic aggregation method of the VSG-wind farms is proposed based on the Kuramoto (KM) model and the small signal analysis of the wind turbines. Finally, a wind farm consisting of multiple VSG-wind turbines under disturbances is simulated in PSCAD/EMTDC to verify the effectiveness of the proposed dynamic aggregation method.

Transmission distribution coordination for DER fault ride through support

Rapid renewable energy sources (RESs) deployments in transmission and distribution networks have changed power systems’ operation and control mechanisms. This fundamental shift makes the interaction between transmission and distribution systems more sensitive and requires robust TSO–DSO coordination to ensure system stability and ancillary services for the entire network. This paper uses an electromagnetic transient (EMT) simulation tool using a real-time digital simulator (RTDS) to investigate the dynamic transmission–distribution coordination with a high share of RESs in fault ride-through (FRT) capability of distributed energy resources (DERs). Then, the paper implements fault current injection (FCI), incorporating inverter-based resources (IBRs) in the transmission system to support dynamic voltage responses for the distribution system. Different reactive current control schemes are examined to evaluate the FRT performance of DERs under different fault locations. Additionally, hardware in the loop simulation for the under-voltage protection relay is implemented to validate the low-voltage ride-through capability of DERs. The comparison results show that the transmission system can provide dynamic voltage support for the distribution system through FCI from IBRs to help DER ride through. The FCI from the transmission system also significantly enhances fault-induced delayed voltage recovery of voltage-sensitive load in the distribution system.

Analytical transfer function to simulate the dynamic response of the finite-length Warburg impedance in the time-domain

Based on fundamental electrode theory, an analytical transfer function to simulate the frequency impedance spectrum of the finite-length Warburg (FLW) impedance and the dynamic potential response of the FLW impedance in the time-domain has been developed in this study. Parameters reported in the literature estimated from experimental measurements carried out in polymer electrolyte fuel cells (PEFCs) have been considered to validate the new analytical transfer function. The analytical transfer function representing the FLW impedance can be considered in different equivalent electrical circuit configurations to simulate a more accurate dynamic output voltage of an electrochemical power system under the effect of diffusion phenomena. A Simulink model based on the Randles circuit and the new transfer function representing the FLW impedance is constructed to simulate the dynamic output voltage of a PEFC during a current-interrupt incident. In addition, a Simulink model based on an electrical circuit configuration and the new transfer function representing the FLW impedance is constructed to simulate the dynamic output voltage of a Li-ion battery. This study establishes a wider scope to relate the electrochemical impedance spectroscopy to the dynamic output voltage response of electrochemical power systems.

In Vivo Optogenetics Reveals Control of Cochlear Electromechanical Responses by Supporting Cells.

Cochlear sensitivity, essential for communication and exploiting the acoustic environment, results from sensory-motor outer hair cells (OHCs) operating in a structural scaffold of supporting cells and extracellular cortilymph within the organ of Corti (OoC). Cochlear sensitivity control is hypothesized to involve interaction between the OHCs and OoC supporting cells (e.g., Deiters' cells [DCs] and outer pillar cells [OPCs]), but this has never been established in vivo Here, we conditionally expressed channelrhodopsins (ChR2) specifically in male and female mouse DCs and OPCs. Illumination of the OoC activated the nonselective ChR2 cation conductance and depolarized DCs when measured in vivo and in isolated OoC. Measurements of sound-induced cochlear mechanical and electrical responses revealed that OoC illumination suppressed the normal functions of OoC supporting cells transiently and reversibly. OoC illumination blocked normally occurring continuous minor adjustments of tone-evoked basilar membrane displacements over their entire dynamic range and OHC voltage responses to tones at levels and frequencies subject to cochlear amplification. OoC illumination altered the OHC mechanoelectrical transduction conductance operating point, which reversed the asymmetry of OHC voltage responses to high level tones. OoC illumination accelerated recovery from temporary loud sound-induced acoustic desensitization. We concluded that DCs and OPCs are involved in both the control of cochlear responses (which are essential for normal hearing) and the recovery from temporary acoustic desensitization. This is the first direct in vivo evidence for the interdependency of the structural, mechanical, and electrochemical arrangements of OHCs and OoC supporting cells that together provide fine control of cochlear responses.SIGNIFICANCE STATEMENT A striking feature of the mammalian cochlear sensory epithelium, the organ of Corti, is the cellular architecture and supporting cell arrangement that provides a structural scaffold for the sensory-motor outer hair cells. The role of the supporting cell scaffold, however, has never been elucidated in vivo, although in vitro and modeling studies indicate the scaffold is involved in exchange of forces between the outer hair cells and the organ of Corti. We used in vivo techniques, including optogenetics, that do not disrupt arrangements between the outer hair cells and supporting cells, but selectively, transiently, and reversibly interfere with supporting cell normal function. We revealed the supporting cells provide continuous adjustment of cochlear sensitivity, which is instrumental in normal hearing.

A novel method of parameter identification and state of charge estimation for lithium-ion battery energy storage system

Battery energy storage system (BESS) has been widely used for the expansion of the electricity grid. Accurate state of charge (SOC) estimation of BESS is essential for ensuring system safety and reliability. However, it is still a challenging work to improve the model accuracy and supress the cumulative error during the SOC estimation. This paper develops a parameter identification method based on the dynamic voltage responses in the practical constant current (CC) discharging process to identify the battery model parameters with the particle swarm optimization (PSO) method. Furthermore, to minimize system errors caused by the model, algorithm, and measurement system, a hybrid SOC estimation method is proposed. In the proposed hybrid method, an improved extended Kalman filter (EKF) method with constructed compensation error is employed to suppress system errors. PSO is again adopted to determine the dynamic compensation error based on the reliable increment of the ampere-hour counting (AHC) method over the whole SOC range. To validate the effectiveness of the proposed method, three CC discharging tests are carried out at 25 and 5 ℃. The results show the proposed model parameter identification method and the hybrid SOC estimation method can jointly provide more accurate SOC estimation.

Harmonic Profile Enhancement of Grid Connected Fuel Cell through Cascaded H-Bridge Multi-Level Inverter and Improved Squirrel Search Optimization Technique

The generation of energy by conventional systems leads to several environmental issues. Fuel Cell (FC), being a new renewable energy source, has emerged as one of the promising alternatives to obtain clean and efficient energy generation. This paper highlights the power quality enhancement of the grid connected FC through a boost converter and 25 level Cascaded H-Bridge (CHB) Multi-Level Inverter (MLI) using the classical PID controller. To drive the MLI connected to the grid for governing the Point of Common Coupling (PCC) voltage between the FC and the grid, two PID controllers have been utilized. The conventional evolutionary techniques such as Particle Swarm Optimization (PSO) and Squirrel Search Algorithm (SSA) are implemented to tune the PID controllers for dynamic operations. To further enhance the convergence speed of computation and precision of the classical techniques used, an Improved Squirrel Search Algorithm (ISSA) has been proposed in this work. The grid connected power network considered for study here is designed using MATLAB/Simulink environment. Moreover, the system is led to various rigorous voltage sag and swell conditions to test the effectiveness of the proposed controller. A detailed comparison between the conventional PID, PSO, SSA, and proposed ISSA techniques in voltage profile improvement, power quality enhancement, and reduced execution time has been featured. The results obtained highlight the proposed technique’s superiority over the classical methods in terms of improved dynamic voltage response, enhanced power quality, and reduced harmonics. The power quality indices are found out using Total Harmonic Distortion (THD) analysis. The values found out are well within the IEEE-547 indices for the proposed controller, thus justifying its real-time implementation.