Proceedings of International Conference on Power Electronics and Renewable Energy Systems

The video and its compression become prominent with the emergence of digital video technology and common use of video acquisition devices. The traditional video compression needs upgradation with artificial intelligence, machine learning, neural network, and deep learning. Apart from normal signal processing the deep learning technologies are advantages as they can deal with content analysis than dealing only with neighboring pixels. The initial steps in video compression, intra/inter frame prediction provide a better percentage in overall compression. The computational complexity of existing intra prediction method is more. This paper proposes a deep learning based intra prediction method using CNN. This deep depth prediction algorithm trains the network to provide depth of the CTU with reduced computation and less time. The experimental results show a dip in the encoding time, about 71.3% compared to existing method.

In the power system, the occurrence of a short circuit in transmission lines is the major challenge in planning, designing, and operating with an excessive high-voltage. The new model incorporates the actual geometrical two dimensions of insulators, property of materials, and self-adaptive measurement of the components. 11-kV non-ceramic insulator designs are simulated using ANSYS software. The insulators are free from contamination. Finite element method (FEM) is a numerical method with 2–3 space variables to solve partial differential equations is employed to identify the electrical stress issues in high-voltage fields. For all surface conditions, the electric field distribution, maximum electrical field strength and its location, voltage distribution, and heat generated on the surface are examined. The simulation findings were introduced and analyzed for non-ceramic insulator designs.

A new multilevel zeta converter which converts fixed DC voltage to multilevel DC output voltage is discussed in this paper. Proposed converter has stable voltage feedback capacity and produces high gain output voltages with less input current. Voltage supplied by the PV panel or the fuel cell is at an output of a low voltage. These output voltages can be interfaced with standalone (or) grid connected inverter system by employing the proposed converter. By using a single transistor with the multilevel capacitor geometric structure, the proposed converter is able to generate an output voltage that is much higher and has ripple free output current with a higher step-up conversion ratio. It allows for operation at much higher frequencies for a much longer period of time. Additionally, it does not require for the electrical transformer for high gain. The output of the zeta converter generates four output level voltages which are simulated and verified with theoretical results.

A denoising method for medical images through hybrid technique is presented in this paper. The hybrid technique is the combination of wavelet and neural network (WaveNet). Proposed algorithm has been validated through benchmark image, and medical images both are degraded by the variety of noise density through Gaussian noise and visual property. The performances of denoised images are also analyzed with wavelet techniques and compare the results with proposed technique. The proposed strategy is developed in MATLAB platform. Simulation results are evidence for the proposed work

Nowadays the majority of the industrial drives are employed with induction motors as a load. Induction motor receives input from the output of MLIs, which requires quality power in terms of lower or negligible total harmonic distortion (THD). In order to provide quality power, in this paper, modeling of cascaded multilevel inverter (MLI) for harmonics mitigation of induction motor is proposed. In recent years, cascaded H-bridge MLI technology has emerged as a crucial to offer a quality output for industrial drives. In this work, three-phase five- and seven-level inverters are developed, modeled and simulation carried out using MATLAB/Simulink. Comparisons of simulation as well as prototype solutions are presented.

Currently, the operation of Finite Control Set Model Predictive Control (FCS-MPC) schemes in electric motor drives domain is emerging. Its distinguished features are: intuitive, simple and easy insertion of multi-objectives. The application of FCS-MPC in permanent magnet synchronous motor (PMSM) drive has several benefits in terms of improving the performance when compared with direct torque control (DTC)-operated PMSM drive. The FCS-MPC scheme is categorized into two: predictive torque control (PTC) and predictive current control (PCC). This paper deals with comparative evaluation of these control schemes for PMSM drive operation concerning flux and torque ripple, and current THD. Therefore, the gained results are analyzed for PMSM drive highlighting the benefits of FCS-MPC over DTC.

In this paper, a closed-loop discrete controller is implemented for Zeta converter modules. Discrete controller offers good dynamic response, fine voltage regulation, and it can be programmable without external passive components. Zeta converter is capable of producing non-pulsating output current and has good adaptability. An analog proportional–integral–derivative (PID) and discrete PID controllers are designed, and their performances are compared. Effectiveness of the controllers is demonstrated and validated with experimental results. Achieved result shows that the discrete controller provides good transient response. Further, the performance of connecting dual snubber with Zeta converter has been analyzed. Dual snubber is connected in the Zeta converter, and the conducted EMI results have been observed. Simulation model of a solar module and Zeta converter to control the voltage to the DC motor has been developed using PSPICE software. From the experimental results, it is inferred that the dual snubber reduces the switching losses and suppresses the dv/dt and di/dt effects.

In telecommunication systems, the most crucial challenge is to recover a signal corrupted by noise. Adaptive filters are widely utilized for signal de-noising applications with least mean square adaptive algorithm being the most desired. Even though LMS algorithm is simple in structure and robust; it suffers from slow convergence speed and has high mean square error (MSE) value. Therefore, in this paper, we introduce a structural optimization of adaptive filters using conventional LMS adaptive algorithm. Here, a multi-stage cascaded LMS adaptive filter model is proposed for adaptive noise cancellation (ANC) systems, and the novelty is that the number of filter stages to be cascaded is adjusted automatically to provide optimum performance. The simulation is carried out for a signal de-noising application and the efficiency of the proposed filter model is tested with regards to MSE, SNR and ANR. The advantages of the proposed filter model are proved in the results.

The switching modulation techniques of high switching frequencies are not recommended in medium voltage drive applications with a power of megawatts because of high power losses and low converter performance. Fundamental strategies like selective harmonic elimination (SHE) are a popular alternative. Since the transcendental equations formulated by SHE are simply nonlinear in nature, it has proven to be an important challenge for the scientists to achieve a viable solution on the desired modulation index. This article presents the comparison analysis of the GA and PSO approach with good initial guess, and its hybrid optimization of PSO-GA is used for solution of the SHE equation set to various modulation index values. The %THD generated at various modulation index values is also consistent with the harmonic standards of IEEE 519-1992.

Superparamagnetic nanoparticles offer a wide range of applications in the emerging field of electronic devices. Recent developments have identified them as components for a new type of magnetoresistance sensor. A novel measuring method is used where increased field sensitivity is bought at the value of an inherent device noise. The proposed GMR sensor has many advantages, yet its output is feeble due to noise, and hence, there is a requirement for designing a signal conditioning circuit to improve the signal strength. The objective is to analyze the low concentration (sample) with a better signal conditioning circuit for the GMR sensor.

This article addresses the system connected to the solar PV grid by the DC to DC converter and inverter (VSC) for the supply of electricity to the power grid, addressing the major device elements, which include the first one 20-kW solar array, second one grid side inverter and third one boost converter, mathematical modeling and THD change by irradiation effect. This paper begins with a PV system model, simulation circuit and discussion. This paper has a concise overview of all part included in this system and considers environmental temperature and solar radiation practical data at BVRIT campus. It also addressed a common algorithm for MPP monitoring. The results of simulations demonstrate how the variations in solar radiations will influence the production of any PV module and shows THD of the photovoltaic-grid connected.

The aim of this work is to model firstly the different components of a two-bed adsorption cooling system with continuous cold production fed by hot water from biogas or thermal sensors, then in a second step, to the numerical resolution in order to determine the evolution of the various temperatures at the level of the adsorber, the desorber, and to evaluate the COPs. For the validation of the model, the zeolite–water couple was compared with the literature. The results of the analysis show that the COP of zeolite–water is 0.38, lower than that of silica–gel–water which is 0.62. The evaporating temperature reached is between 0 and 5 °C and the cooling temperature between 8.01 and 8.55 °C. This temperature range is acceptable as it is intended for dairy products. The variation in the desorbed fraction is between 1.36 and 1.47 kg/kg s (decrease in the desorbed fraction), during adsorption, it is between −1.1 and −1.05 kg/kg s (increase in the adsorbed fraction). The desorption temperatures reached are 56.8 °C for silica–gel and 51.25 °C for zeolite–water.

The significant issues which are associated with grid code during grid fault are the fault ride through (FRT) capability of wind farms. This paper presents a detailed investigation of different hybrid fault ride through schemes in DFIG-based wind system under both symmetrical and unsymmetrical fault conditions. This work analyzed the performance of hybrid FRT combinations like crowbar resistance with RL circuit, DC chopper associated with crowbar resistance, DC chopper connected with series dynamic resistor, voltage control scheme with crowbar resistance are developed and studied under symmetrical and unsymmetrical fault conditions. The simulation results are obtained using MATLAB Simulink version 2019b, and the hardware real-time simulation is implemented in OPAL-RT real-time simulator. The proposed hybrid FRT schemes provide promising results improving the system parameters under different fault scenarios in grid-connected wind system.

To empower the abstraction of maximum power from the solar panel using MPPT with P&O algorithm, this proposed work enlightens the practice of single-axis solar tracker exploitation by Arduino Uno. The introduction of IoT into the project helps in remote monitoring of the entire system and also the analysis with the neat graphical representation of the data over a course of time. The significant characteristic for monitoring, supervising and performances estimations of integration of Internet of Things (IoT) technology which is an efficient wireless communication technology is considered which disables the difficulties faced in physical monitoring of solar photovoltaic (PV) and getting the values of voltage and current.

In modern era, in electric vehicles charger regularization, the following phase to make the charging procedure more convenient is to eradicate the usage of wired cable sandwiched by linking the electric vehicles and charger to accomplish wireless charging of electric vehicles, and a wireless power transfer (WPT) system ought to be depicted with respective ground clearance of electric vehicle. It is an innovation technology which can be applied for all electric vehicles (EVs) as it helps to get rid of user involvement. The crucial impediment for acquiring wireless charging is ground clearance which downgrades the power transfer efficiency. The theory of WPT for different ground clearance is elucidated, and the corresponding cordless charger device is analysed. The portrayed cordless charger device has capacity to distribute the power of about 45v utmost ground clearance of 20 cm. The battery designed is 4.5KWh and the super capacitor (SC) of 3.8KWh which is sufficient to charge electric vehicle.

The five-level packed U-cell (PUC) inverter topology is designed as an active power filter to reduce the harmonics present in the nonlinear system. The packed U-cell is a newly emerged multilevel inverter that can generate different levels by utilizing capacitors at the output side. It is called packed U-cell since it has a capacitor and a couple of power switches arranged in U shape. The energy conversion takes place using a limited number of power semiconductor devices and capacitors, thus reducing the cost of production. The model of a five-level PUC inverter is designed, and the simulated waveforms along with their THD are discussed.

In this paper, performance analysis of 100-kW rooftop PV plant in library building of SRM Institute of Science and Technology, Kattankulathur, Chennai, is carried out. The site description and the plant capacity are mentioned as the details obtained by the department, and calculation was performed on the same data. The performance of the system over last three academic years has been compared. Furthermore, the analysis is extended by comparing this 100-kW PV plant with the similar PV plant in the institute. The configuration of the PV plant taken for the comparison is the same 100-kW with similar structure. The findings from the study and comparison are added finally with the causes of the shortfall in the performance of the system. Finally, the inferences are concluded which will guide the researchers to find the solutions for the cause and effect observed in this 100-kW PV plant.

This paper proposes the design and implementation of a low-cost automatic mini heliostat solar tracker system. The tracking system is designed as open loop control based on astronomical equations. The experimental device consists of a 0.3 × 0.3 m2 reflector, 3-mm thick with an Arduino card and two stepper motors. The prototype tracking system has been tested during three days. The influence of the different parameters like number of the day, time, heliostat position and references of the tracking axis was analysed. The results obtained show some improvement with RMSE of 0.050 and 0.085, respectively, for the altitude and azimuth. This system can be used for small applications in rural areas

The exploitation of information and communication technology (ICT) and the development of smart electricity networks have become the main concerns worldwide. To leverage ICT in the existing electrical power network, 5G wireless systems are integrated toward the development of smart grid networks. For reliable, efficient, and secure communication infrastructure in a smarter electricity network, the non-orthogonal asynchronous transmission is essential. Besides, a massive number of smart meters (SMs) measure energy consumption and convey instantaneous information to the utility through communications networks. However, data rates beyond 10 Gbps, connectivity to support 1 million per sq km device density, and sub-millisecond latencies are challenging issues when implementing a smart distribution grid. Therefore, this paper presents the non-orthogonal multiple access (NOMA) scheme and optimized power control strategy for smart microgrids to integrate numerous sensor devices with higher data transfer rates and lower latencies. This new microgrid configuration enables multiple electricity users to transmit and receive data simultaneously using the same frequency and enables optimized power flow with high flexibility.

A microgrid can be characterized as force group of disseminated generation, burden, and energy stockpiling gadget gathered together nearby to one another. It offers freedom to use sustainable power hotspots for green and clean climate. This work mainly deals with the analysis, modeling and simulation of DC microgrid with solar powered system alone, DC microgrid with battery alone, DC microgrid with wind alone, DC microgrid with solar powered system and battery, DC microgrid with solar powered system and airstream & DC microgrid with solar powered system, battery and wind. The outcomes are compared in terms of output voltage and output power. The outcome represents the superior performance of DC microgrid through solar powered system, battery and wind sources.

All over the world various semiconductor manufacturing industries dealing with the accidents that occur due to the leakage of hazardous or lethal gases that are involved in the process of making semiconductors and accidents due to the noise of the machineries used. As it is an emerging problem in the production of semiconductor, a safety system is being proposed. The proposed embedded based safety indication system would ensure that the leakage of gas such as hydrogen and any deviation from the safety limit of sound, accidents happening all over without any leakage of gases is being detected and an immediate alert to this leakage or deviation is being sent to the representative of the industry. The message may be sent to their number, displaying the alert, turning off the supply to the system and ringing an alarm to indicate the above cases of accident. In this paper, the effectiveness of the proposed ARM controller-based safety system is implemented using proteus virtual system modelling is using, would ensure the absolute safety.

DC-DC converters are utilized to interface the Photovoltaic source to the battery for charging purposes. A non-isolated (NI) DC-DC buck-boost converter has been employed as a maximum power point tracking (MPPT) system to derive the photovoltaic power present. The MPPT control is utilized to extricate the greatest power available from the photovoltaic source. The MPPT gets the solar irradiation and solar cell temperature as contributions to decide the optimized duty cycle to acquire maximum power. In this work, a non-isolated buck-boost converter is utilized as MPP tracker for battery charging applications. The performance of the converter is simulated and validated through the experimental results.

In the proposed work, a feed forward neural network (FFNN) based MPPT controller is implemented in which back-propagation algorithm is used to extract maximum power and reduce peak overshoot from 1.26 kW PEMFC. To step up the PEMFC voltage, an Ultra High Step Up converter (UPHC) is designed and its steady state analysis is carried out. The duty cycle of UPHC is controlled using FFNN MPPT controller to extract optimum power from fuel cell whose result is compared with conventional Fuzzy Logic controller. A simulation work has been carried out using MATLAB/Simulink environment and discussed the results.

Internet of Things (IOT) is swiftly increasing technology nowadays global in internet world. IOT is mixture of communication system and embedded device that is used to attach hardware devices to the community or net. IOT is used for transmission and reception of information. These structures are used to check the processes in industries and its applications were through implementing industry standard protocols using IOT. In this machine small scale commercial packages like liquid level control, power monitoring and so on can be analyzed wirelessly via Wi-Fi gadgets, mobiles and laptops. The principle purpose is to epitomize the importance of IOT as a way to survey small scale commercial packages.

The aim of this paper is to build a prototype electric vehicle out of structural materials. It is influential in the development of a modern, safe, and environmentally sustainable mode of public mobility. The objective of its design is to create a lightweight, compact three-wheeled electric vehicle frame. The design phase entails the creation of a 3D model, a practical prototype, and frame refinement using CAD software and the material parameters. The electrical and mechanical study is performed, the results recorded 125 km per charge, and the weight of the vehicle is 180 kg. The top speed is 40kmph along with >80% efficiency of the BLDC hub motor.

This work proposes the utilization of Inductive Power Transmission (IPT), for charging the E-Vehicle’s battery with the help of an efficient DC TO DC converter. In this IPT method, the DC TO DC converter is operated with the inclusion of transmitting and receiving coils. The required power for transmitting coil from the input source (AC Source or solar energy) is controlled and supplied by the DC TO DC converter 1. Meanwhile from the receiving coil side of IPT system, the obtained power supply will be controlled by DC TO DC converter 2 for charging the battery. In order to identify the efficient DC TO DC converter, two types of converters namely VMC (Voltage multiplier cell) based DC TO DC converter and LUO converters are taken into account for comparison.

In this paper, minimization of operating cost of DC microgrids is formulated. Utility grid, solar, wind and battery is associated with this formulation. In this optimization problem, both with and without losses are considered in the power flow model. Impact of renewable energy sources on reduction in operating cost is discussed. Based on the solar radiation and air density, power generation from solar and wind are calculated respectively. Heuristic method is used to solve this minimization problem. To analyze the operating cost, a six-bus customized system is used. To calculate the cost structure, three different cases are considered. The first case considers the system without any renewable energy sources or battery storage. In the second case, a solar and a Wind Energy Conversion system are added to the system and in the third case, the battery is included with the existing system. With the inclusion of renewable energy system, dynamic pricing and various load conditions, the proposed algorithm is minimizing the operating cost considerably.

Nature ester oil is the alternative to mineral oil in transformer for cooling purposes. This paper mainly focuses on a comparative study of field distribution properties of three types of oil (coconut oil, peanut oil, sunflower oil) with different gap spacing values. The three types of oil have different conductivity and permittivity values. The electrodes are immersed in oils. The electrodes are made of copper material. The arc length versus electric potential graph is obtained. Using comparative study analysis we find out the oil which has the best field distribution properties. Electrical breakdown or dielectric breakdown is a cycle that happens when an electrical protecting material, exposed to a sufficiently high voltage, out of nowhere turns into an electrical channel and electric flow moves through it. All protecting materials go through a breakdown when the electric field brought about by an applied voltage surpasses the material's dielectric quality. The voltage at which a given protecting article becomes conductive is called its breakdown voltage and relies upon its size and shape. Under adequate electrical potential, an electrical breakdown can happen inside solids, fluids, gases, or vacuum. Notwithstanding, the particular breakdown components are diverse for every sort of dielectric medium. The electrical breakdown might be a flashing occasion (as in an electrostatic release) or may prompt a persistent electric curve if defensive gadgets neglect to intrude on the flow in a force circuit. For this situation, an electrical breakdown can cause calamitous disappointment of electrical hardware, and fire risks.

The demand Side Management (DSM) considered as the utmost key strategy applied to a Smart Grid (SG), which prepares consumers to yield accurate results regarding their consumption of electrical energy and supports the utility to curtail the peak load demand and restructure the demand curve. In this paper, a load shifting strategy has been applied for the DSM with huge number of controllable devices. To curtail the peak demand, decrease the electricity bill and to minimize the PAR, the load-shifting problem has been approached in hourly manner, throughout the 24 h in a day. Antlion Optimization (ALO) algorithm has been used to accomplish the objective of load shifting through minimization problem to the DSM and has been employed in residential loads of SG.

In recent years, one of the major concerns in the distribution system is the quality of power at the consumer side. Out of all power quality issues, voltage sag is the most frequent one. The Dynamic Voltage Restorer (DVR) is one of the effective ways for protecting sensitive loads from Voltage sag/swell conditions. In this paper design and analysis of DVR for mitigating voltage sag is done by means of MATLAB/SIMULINK. The results of conventional DVR controller using PI are compared with Artificial Neural Network (ANN).

This project work aims in exploring a quadratic boost converter which has low voltage ripple achieved using extreme duty cycles and PWM strategy. Normal quadratic boost converter topologies require a higher amount of stored energy by available in the capacitors used. The energy stored capability is directly proportional to the size of the capacitors. By using the minimum stored energy method, the converter size reduces. Also this transformer less proposed topology is suitable for renewable energy applications.

In transmission frameworks, insulators have a huge impact on the better presentation of the devices. The outside insulators are introduced to an environment that has a high temperature, clamminess similar to pollution from the beachfront and industries. On deposition of contaminants, pollution builds gradually, and spillage current starts to stream on a surface level. Partial Discharge (PD) deteriorates the insulation and leads to the breakdown of the device. The effect of conductive pollution on PD is seen through tests performed on both earthenware and non-ceramic protectors at different pollution levels. To achieve complete information about PD, it is gotten through a PD acknowledgment system that records the PD waveforms close to the regular PD. A couple of sorts of PD signals are difficult to recognize at a starting stage. To crush the test, a Convolutional Neural Network (CNN) based profound learning procedure for PD plan affirmation is presented in this paper. The acquired PD signal is changed into a 3-D (ɸ-q-n) picture. To anticipate such a PD the 3-D (ɸ-q-n) picture is feed as a input to Deep Learning Algorithm. It uses Convolutional Neural Networks (CNN) for picture gathering. In this, Alex Net is used for perceiving the unmistakable PD.

Industries scaled down the size but the supply voltage was still in the 1 V range for a decade. Reducing power consumption needs supply voltage to be reduced especially for Dynamic Random-Access Memory (DRAM) which is a storage device whose dynamic power consumption is proportional to the square of the power supply. In this work, design of low power consuming DRAM and Static Random-Access Memory (SRAM) with Ferro Electric Field Effect Transistor (FEFET) as transistor nodes which has higher subthreshold swing due to negative capacitance, hence a lower power supply can be applied and changing process parameter to find Static Noise Margin (SNM) of SRAM and characteristics of DRAM. The simulations are carried out with cadence for 32 nm Verilog-a model and are analyzed with Python.

Signal processing faces the quandary of not being able to separate non-stationary noise from speech signal. Traditional methodologies relied on spectral subtraction for the same; however, such techniques relied on approximation of spectral mask of the noise. This paper proposes an effective and novel convolutional encoder–decoder architecture to effectuate clean speech from the input audio through denoising the audio input. The architecture uses skip connections to increase information flow from encoder to decoder, which helped the authors bolster the performance of the network. The generated output is evaluated on objective and subjective metrics like signal-to-noise ratio (SDR), perceptual evaluation of speech quality (PESQ) and short time objective intelligibility (STOI). The proposed system outperforms the state-of-the-art systems with respect to SDR, PESQ and STOI. The architecture finds applications in various fields such as speech recognition, machine translation and telecommunication.

In this paper, the heterogeneous comprehensive learning particle swarm optimization is proposed for the tuning of multivariable proportional integral derivative (PID) for Wood and Berry system. This simulation work is done for both the decentralized and centralized PID controller. For comparison, results from the tuning of multivariable PID controller by particle swarm optimization (PSO) algorithm is considered. Here, our objective is to minimize the integral absolute error (IAE) value of the system. For the simulation of the system and algorithm, MATLAB/SIMULINK software is used. Statistical performance of evolutionary algorithms such as best value, mean value, and standard deviation are going to be evaluated based on ten independent initial conditions. In this work, it is observed that HCLPSO give more consistent performance compared to PSO algorithm.

Recently, small-scale grid-connected PV systems are acquiring familiarity in institutions and industries mainly due to their clean and climate-friendly attribute. A 104 kW grid-connected PV system at Kattankulathur, Tamil Nadu, is discussed in this paper. A software tool is essential to estimate and predict solar energy power generation for a particular location. This paper mainly deliberates the design aspects using a suitable software tool for the grid-connected PV system. The best approach for designing and evaluating energy production in PV systems is PVsyst software. Therefore, this paper demonstrates the step-by-step procedure followed for creating the 104 kW PV system. The approach towards loss distribution and performance ratio analysis is also presented. This paper is proposed as a guide for the researchers working in this field of designing a PV system based on the load requirement.

Security plays an essential role in IoT as there are several components connected to the network. An effective intrusion detection system is required to detect all vulnerabilities in wireless networks using machine learning and also to reduce the false alarm rate. The various machine learning algorithms were analyzed in terms of various performance metrics and finally evaluated the best classifier in terms of prediction time, training time, and accuracy. Using confusion matrix, various classes of attacks were analyzed, and results revealed that various machine learning algorithms were compared, And our proposed work was able to predict all the five types of attacks effectively with an accuracy of 94% achieved using extra tree classifier.

The main purpose of the proposed system is to design a low-cost universal PV battery charger for electric vehicle application. The proposed system is integrated with a slope-compensated current controller which controls the charging current that corresponds to maximum power point of the PV module. As an interface converter, the proposed system consists of a buck converter to control the flow of the charging current and to find out the reference current Iref from the PV array at MPP. The battery control circuit is implemented by measuring the state of charge (SOC) of the battery, and an LCD display has been used to monitor the battery parameters. This proposed system acts as a smart and efficient PV battery charger for e-vehicles.

Solar irradiation levels in South Africa compare favourably with the rest of the world. However, developers and installers in South Africa must know how the irradiation levels affect solar PV production within different cities. An investigation was carried out to compare the PV generation production in nine cities situated in each of the nine provinces in South Africa to understand how solar PV generation varies in each city. The city of Durban was used for the base case with its solar production compared to that of other cities. Technical and non-technical factors affecting solar PV generation production/installations in Durban were then investigated, and a case study of simulated vs. actual plant production in Durban was compared.

This study presents analyses of the results of selected experimental power quality (PQ) data obtained on a grid-tied photovoltaic (PV) system composed of different PV modules technologies and four PV inverters integrating the grid at the point of common coupling. A PQ analyzer is utilized to collect the data from the 110 kW PV system for two weeks. The measured PQ data was obtained by following South Africa and international power quality measurement standards. The data measured were RMS voltage, RMS current, voltage unbalance, frequency, voltage total harmonic distortion (THDV), current total harmonic distortion (THDI), active and reactive power. Voltage unbalance, frequency, voltage total harmonic distortion (THDV), current total harmonic distortion (THDI) have been appraised and juxtaposed with the requirements of the South Africa Renewable Energy Grid Code. These parameters were all found within the regulated limits, except for the current total harmonic distortion (THDI) that exceeded the grid code limit due to sudden voltage variations. This occurrence is observed primarily at dawn and dusk when the PV inverter output active power is at the lowest level. This study's performance analysis contributes to evaluating large-scale PV systems inverters’ behaviour and their impact on the distribution grid power quality at different power generation levels.

Microgrid gives a viable way to advance sustainable power source use through conveying multiple distributed generators (DGs) with energy storage systems (ESSs), loads, control gadgets, and ensure gadgets, which can work in either islanded mode or lattice associated mode. So as to organize the yield of various DGs and understand the capability of sustainable power source, vitality of the executives, and financial dispatch of the microgrid is required. Both distributed energy resources (DERs) and client stacks in microgrids have vulnerability qualities; so, the irregularity of the breeze speed and sunlight based radiation force is displayed by interim science, and the interim yield of the breeze turbine and photovoltaic (PV) age framework are obtained. At that point, a microgrid monetary enhancement model dependent on an interim advancement technique is proposed.

Hybrid Power Flow Controller (HPFC) discovers habitation amongst weak buses in multi-bus systems to condense the properties of voltage sag. This effort deals with power quality improvement of Four Bus System (FBS) using HPFC. This effort mainly deals with the simulation of FBS with and without HPFC (Hybrid Power Flow Controller). The outcomes are assessed in terms of real power, reactive power, and voltage. The simulation consequences characterize the aptitude of the HPFC in enlightening the power quality.

In this paper, intelligent fuzzy based microgrid fed distribution generating sources are presented. Optimal power electronic converters (PEC) are employed to produce and control the performance of PV-wind power. Double fed IG is employed as wind generator to obtain maximum power wind. Peak power is absorbed from solar with help of proposed fuzzy MPPT algorithm. The simulation results for steady state variation of wind speed and dynamic behavior of load variations are presented. Real/reactive power energy management is managed efficiently with fuzzy control algorithm. The proposed fuzzy controller scheme provided improved performance results and solved power quality issues at load side.

This research work is anxious with the issues of identification of objects placed on seabed captured on underwater sonar images. Image segmentation methods play a very important responsibility in partitioning dividing the image into segments. In this paper, we are applying watershed segmentation algorithm for detecting pipelines in underwater seabed using sonar images. Initially, we applied Gaussian and Laplacian pyramid for image resolution enhancement, fixing threshold automatically using Otsu threshold determination. Also, morphological operations were performed for identifying the foreground and background of the image. Followed by that for marking the regions on the image, we used watershed segmentation algorithm to detect the pipeline in underwater acoustic images.

In order to increase the driving range of plug-in hybrid electric vehicle, dual motor control strategy was proposed. This method will offer various mode of control and less energy consumption. This dynamic performance of system improved by using the rule-based algorithm of fuzzy logic. Power demand for vehicle propulsion and energy storage system parameter is estimated. The effect of this value based on the torque requirement for vehicle propulsion is calculated. Based on the total torque requirement and SoC of the battery, the corresponding mode of operation is identified by using the rule-based algorithm. The main controller will monitor the propulsion control and dynamic performance of the system. The power train configuration for dual motor with engine control is designed using Simulink. Most of period of control, torque requirement for the vehicle propulsion met by the single electric motor, i.e., vehicle operating in electric mode. The result shows the extension of driving range and reduced energy consumption.

Due to rising demand and constraints on the construction of new lines, modern power transmission networks are becoming more complex. Following a disruption, the loss of stability is one of the key issues with such a modern power system. Transient stability control is a vital principle that ensures the power system’s stable operation during faults and significant instabilities. FACTS tools have proven to be very effective in improving controllability and increasing power transfer capability while retaining the necessary stability margin in a power system transmission network. The improvement of transient stability of a three-machine, nine-bus power system using FACTS controllers (SSSC, SVC, and UPFC) is investigated in this paper. In the MATLAB/SIMULINK environment, the simulation results demonstrate the effectiveness and solidity of the FACTS devices in improving system transient stability.

Nowadays, renewable energy is attractive due to the depletion of fossil fuels. The energy requirement in most developed countries is met by solar and wind energies. In this paper, solar and wind energies are used in a safer way for power utilization and power quality improvement. Solar energy and wind energies are utilized by employing custom power devices (CPD). Interline dynamic voltage restorer (IDVR) is the most advanced CPD device for wind and solar energy utilization. IDVR is the combination of two DVRs which protect the sensitive loads in various distribution feeders. The solar energy source is connected with feeder 1 and wind energy is connected with feeder 2. If the power requirement in feeder 1 is more, the feeder 2 aid feeder 1 by compensating reactive power using IDVR and it is vice versa. IDVR helps to maintain the power continuity and power quality in both feeder 1 and 2. Simulation of two bus system using solar and wind energy with and without IDVR is simulated using MATLAB/Simulink and analyzed in terms of real and reactive power.

A Hybrid model with resistive touch and laser grid system is the solution proposed to rectify the problems faced by the existing industrial touch screen displays. Placing laser grid above the touch screen has improved the touch recognition and also reduces the possibility of erroneous inputs. Lasers and phototransistors are placed above the bezel of the display to form the laser grid. Laser grid forms a 2-dimensional co-ordinate system for navigation of input location on the display. In order to avoid unnecessary inputs caused by non-human entities like dust, flies, etc., inputs should be taken by both laser grid and resistive touch panel simultaneously. Touch input is taken into account only when the co-ordinates from both resistive touch screen and laser grid are the same. If not, co-ordinates from laser grid alone are taken to calibrate the resistive touch screen. If the calibration is not successful, then the touch functionality is fully taken over by laser grid system.

Electricity should be provided to the customers with good quality and continuity of power supply. To predict the future of distribution system performance, reliability assessment is one of the major factors that have to be considered. Reliability assessment helps in designing and planning of distribution system and also helps in analyzing the severity of the system failures. The system performance indices for reliability help in analyzing the severity of the system failures and thereby help in predicting the reliability of the system in future. In this paper, the system performance analysis has been simulated in ETAP on the Bus 2 of Roybillinton Test system (RBTS) for Feeder 1, 3 and 4. The system performance indices such as SAIFI, SAIDI, CAIFI, ASAI, ASUI, AENS and EENS under different scenarios of operations with and without distributed generator have also been analyzed.

This article gives a detailed report on the retrofitting of an IC engine vehicle with a specially designed DC motor. The emission losses of an old ICE vehicle increase and saturates to its highest value at around this time. The load and rpm analysis of ICE shows that the available usable torque to produce the desired RPM is in a very small range and thus replacing such engines with electric engines which have high torque to speed ratio will increase the performance of the vehicle greatly. The DC motor used in this application has been specially designed for the vehicle. The Total Tractive Effort (TTE) is calculated considering the curb weight of the chassis and then eliminating the components which are specific to the ICE such as engine and fuel tank. Other factors such as the static and dynamic friction, rolling resistances and other constants have been considered taking into account the road safety, road transportation and NHAI standards. The retrofitted vehicle has a curb weight less than that of the ICE counterpart. The high torque DC motor gives better acceleration and the high RPM provides better maximum speeds. The main goal is to have a used ICE vehicle and to completely renew it with a DC motor. This would eliminate the use of non-renewable fuels while also extending the life of the vehicle.

With the increasing need for renewable energy systems to reduce the dependence on conventional resources and fossil fuels and to counter the impact of their usage, more efficient and robust power generation, management and storage systems are required. To best augment the capabilities of such systems, it is imperative that a smart grid-based control strategy is adopted. This will improve the efficiency of such a system and will lead to better integration of the system with the grid. With increased penetration of such smart grid connected systems, the need for securing them from cyberattacks, having the potential to cripple strategic assets of nations, becomes quite necessary. In this paper, a Cascaded H-bridge-based Multilevel Inverter topology is proposed, for integration of PV systems in smart grid. A possible cloud control strategy using blackboard architecture and protection has also been discussed.

This work points on improving the unique time reaction of a PV and battery energy change framework in shut circle flying capacitor support converter-controlled force methodologies with SMC. This work manages displaying and recreation of SM-controlled current impediment of framework-associated inverter. Force procedures are a famous gadget inside the group of force framework gadget. The voltage security is carried out with voltage source inverter (VSI), and the exchanging beats are created utilizing sliding mode regulator. The dynamic channel is utilized for weakening of burden voltage and current sounds. The reenactment results are introduced to discover the impact of dynamic and responsive channel utilizing SMC. The reproduction results with PID and sliding mode (SM) controller-based voltage soundness are looked at, and the steady time–space restrictions are introduced. The outcomes show that sliding mode regulator framework has improved reaction than PID-controlled framework.

Dual-motor electric powertrain offers the independent control and less energy consumption in plug in hybrid electric vehicle model. The component sizing and control strategy are play the important role in dynamic control, power management and energy saving. The proposed system vehicle architecture comprises the dual motor, downsized engine and synchronizer. For optimizing the dynamic load sharing with the dual-motor powertrain configuration, rule-based fuzzy logic control strategy is implemented. The variable load will be managed by the way of selecting different transmission topologies using fuzzy logic control strategy. This dual-motor architecture configuration is simulated using Simulink software. Single motor propulsion drive control is engaged for all driving pattern except the peak load condition. In peak load, such as acceleration mode and high-speed mode, the dual-motor power transmission is engaged. The powertrain configuration is test at different dynamic and load conditions. As a result, it shows the better drivability, high efficiency and extended driving range.

Peak energy management (PEM) is an important tool in energy audit, which will manage and reduce the excess power demand required during peak hours. The role of PEM is to reduce the peak demand with the help of pricing tariffs and incentives for the consumers. The PEM is reviewed with techniques, applications, and ancillary services. Based on that, review new model is proposed. Here, we use a PV panel to charge the battery which is connected to the load through an inverter and switch. The grid is connected to the load through a switch as well. Hence, using this model enables us to supply power to the load with the help of a battery during peak hours, and the PV panel charges the battery during off-peak hours. Thus, it enables us to reduce the peak hour consumption and the bill cost as well.

A popular form of technology used for securing data is ‘biometrics’. Biometrics are stored as templates, which are nothing but a digital reference of the unique characteristics extracted from the biometric, usually stored in a database which are used for authorizations and encryption. The concern for security of storage of templates is mainly due to the fact that the templates may not always be securely stored, and if a hacker does manage to crack the database, the attacker may find all the data stored in the template use it pilfer other important data or obtain access to confidential secrets. This paper suggests a novel scheme where in the fingerprint are stored safely using multi-modal biometric, namely iris, salting and chunking. It also proposes an efficient way to detect presentation attacks which using salt.

The importance of special machines has become an utmost necessity in the current scenario. The implementation of the different types of special machines in various types of applications has become quite challenging, keeping their mechanical and electrical characteristics in mind. In this paper, we have proposed the hybrid stepper motor performance analysis. The performance of the given motor is controlled for user-defined value, and errors are reduced to make the system more reliable. The performance stepper motor analyzed in MATLAB and the corresponding verified through hardware implementation.

Rise in the power demand and existence of loss in transmission sector is increasing linearly. This is due to the increase in use of nonlinear load which causes voltage fluctuation in transmission lines. Some of the problems in it are sag, swell, voltage spikes, harmonics, open and short circuit faults. Among the above mentioned power quality issues, sag and swell will be considered as major fault, and it can be resolved and overcome by including the interline dynamic voltage restorer (IDVR). IDVR has enough capability to perform voltage compensation in an appropriate rate, and it maintains stable energy across DC link capacitor. The proposed method can have several DVRs connected to various distribution feeders in power system sharing common energy storage. A superconducting magnetic energy storage system (SMES) is selected to feed DVR, whenever DVR undergoes compensation. Further, fuzzy logic control also took part in it. The Simulink results convey the effectiveness and performance of proposed method.

The dynamic behavior of microgrid on the protection point of views such as modes of operation (grid-connected/islanded) and generation levels of renewable energy sources makes the fault current vary randomly. Subsequently, the relay operating conditions are to be changed based on the above factors so that relay can differentiate between fault condition and normal operating condition. The conventional protection schemes will be unable to differentiate between modes of operations. Further, the fault current is dynamic in nature. Hence, electromechanical or static relays may be replaced with processor-based relays. This paper proposes an adaptive protection scheme for the microgrid using machine learning algorithm. Multiple regression machine learning algorithm is used to develop adaptive protection scheme. The proposed model will be able to differentiate between normal operating condition and fault condition and trip the relay if needed. The hardware prototype developed for the adaptive relaying scheme has been tested successfully.

Levenberg—Marquardt (LM) algorithm-based current controller for shunt active harmonic filter (SAHF) is implemented for minimizing harmonic currents in power distribution network. A simple and versatile soft computing algorithm for implementing controller to minimize the current error of SAHF is developed for improving power quality (PQ) in conventional distribution grid. The effectiveness of the control algorithm proposed is analyzed considering group of balanced and unbalanced nonlinear supplied from a balanced sinusoidal AC power supply. The objective is to minimize the tracking error in the output of SAHF compensating current harmonics resulting in distortion-free source current. Simultaneous compensation of reactive power by SAHF results in unity power factor operation at the source. The algorithm is developed and implemented using MATLAB/Simulink environment using discrete solver.

The main objective this work is to analyze the total harmonic distortion for grid-connected photovoltaic system. A novel modified multiverse optimization algorithm (MMVO) is proposed to unravel the issues of the conventional maximum power point tracking (MPPT). The goal of this new methodology is to spice up the PV array efficiency. The proposed modified algorithm has a low convergence time and excessive efficiency compare to perturb and observe (P&O) algorithm.

This paper proposes a multiport converter-based idea of preparing a fully monitored UFEVCS. Different converters are utilized in order to test the achievement of ultrafast charging station. This charging station also seeks a factor of automation in battery management system. This battery management is accomplished by the use of IOT. A worldwide control project being designed to control different varieties of power flowing directions if anything unbalances in the system. The methods are thus simulated and therefore are being implemented on hardware. By the usage of CHB converter, the SOC of a system can balance itself. IOT-based battery management is carried in order to automate the charging station with much less efforts and more efficiency. The parameters calculated from the sensors are current (I), voltage (V) and power (W). These quantities from the sensors are transferred to things peak cloud. Thing speak cloud can be accessed from anywhere at any moment of time. Complete parameters of the battery of an EV can be uploaded to the user’s device

This article explains the load frequency control (LFC) of dual area interlinked reheat type thermal plant including nonlinearities such as generation rate constraint (GRC) and governor dead band (GDB) by employing fractional order proportional integral derivative (PIλDμ) controller. A PID controller is also separately implemented for performance comparison. The parameters corresponding to both the controllers are fine-tuned by application of a teaching learning based optimisation (TLBO) algorithm using integral time absolute error (ITAE) as the fitness function. A comparative performance analysis is accomplished between the two types of controllers by injecting an instantaneous load of 10% in area-1. It is seen that the TLBO optimised PIλDμ controller yields better transient response when compared with the other controller. Lastly, the robustness of the TLBO optimised PIλDμ controller is verified by applying a randomly varying step load in area-1.