Design and Analysis of Improved Mountain Gazelle Optimization Tuned PID and FOPID Controllers for PV MPPT System
Performance Analysis of Power System Dynamics with Facts Controllers: Optimal Placement and Impact of SSSC and STATCOM
Empowering Hybrid EVS with Bidirectional DC - DC Converter for Seamless V2G and G2V Integration
Solar Wireless Charging of Battery in Electrical Vehicle
Advancements in Multilevel Inverter Technologies for Photovoltaic-Z-Source Based EV Applications: A Comprehensive Analysis and Future Directions
Design and Development Of Paddy Cutter Using Solar Energy
Design Of Double-Input DC-DC Converter (DIC) Solar PV-Battery Hybrid Power System
Comparison of Harmonics, THD and Temperature Analysis of 3-Phase Induction Motor with Normal Inverter Drive and 5-Level DCMI Drive
Application of Whale Optimization Algorithm for Distribution Feeder Reconfiguration
Detection and Classification of Single Line to Ground Boundary Faults in a 138 kV Six Phase Transmission Line using Hilbert Huang Transform
The Modeling of Analogue Systems through an Object-Oriented Design Method
Circuit Design Techniques for Electromagnetic Compliance
A Technological Forecast for Growth in Solid-State Commercial Lighting using LED Devices
Testing of Analogue Design Rules Using a Digital Interface
Simulation and Transient Analysis of PWM Inverter Fed Squirrel Cage Induction Motor Drives
This paper considers transient response testing of amended analogue macros in mixed-signal systems. The stimulus employed for transient response testing is a single logic amplitude pulse which can be propagated through a digital interface scan path. However, the resulting response must either be readily accessible for processing at a primary output or somewhere routed off-chip. For a number of reasons this is usually considered impractical. This paper therefore considers the effects of sampling and quantising transient responses and extracting them through a digital scan path. The aim of this work is then to define a confidence limit in the accuracy of the test measurements obtained as a function of the number of samples taken, the resolution of the quantifier and the quantiser capture range.
The analysis and design of integrated circuits (ICs) of fully monolithic 1-Dimensional (1-D) AC-coupled Voltage-Controlled-Oscillators (VCOs) networks useful for phase array antennas is presented. The fully-integrated RF VCO arrays integrate on-chip inductors, varactors, MOSFETs, BJTs, and biasing current sources and they each contain an odd number of VCOs AC-coupled through switchable resistor arrays. We designed, simulated and fabricated several these 1-D VCOx5 arrays in a production 0.18µm BiCMOS process (i.e., IBM 7HP). Our design can control the phasing of the on-chip VCO array by means of tuning the edge VCO elements and/or by varying the coupling strength via different resistor values. Circuit-level SPICE simulation shows promising results allowing phase and amplitude configurations across the array to offer high directivity and element-to-element phase tuning arrangement that can be achieved by simply manipulating the on-chip coupling network with edge VCOs tuning. Moreover, circuit simulation shows that some of these conditions allow a ~±20o coverage from broadside without the need for phase shifters. These AC-coupled 1-D VCO arrays, therefore, shows great potential for RF active antennas applications to perform wide angle beam steering for the highly used 1-2GHz S-band.
Ultrasonic sensors are being used to detect the presence of wall thinning in oil and gas pipelines. The ultrasonic waves travel through the pipe material and the presence of defects will cause varying changes to the waves. These changes will be used to detect the type and location of the defects. The high frequency of the ultrasonic signals and the presence of noise make it necessary for high quality data acquisition systems and efficient processing techniques. This paper investigates pipeline defect detection using a data acquisition (DAQ) systems constructed using an off-the-shelf A/D converter. The data from these sensors will be classified using a powerful machine learning algorithm called Support Vector Machines (SVM). A machine learning tool is needed to here to identify the minor characteristic of ultrasound signal that changes with the presence of defects and thus removing human decision making as a factor. Results show that that the self-fabricated DAQ and Support Vector machine can detect the presence of wall thinning with a suitable degree of accuracy.
Among the various power quality problems, the voltage sags, is attracting a large amount of attention of researchers from industry. Dynamic Voltage Restorer(DVR) gives the solution to the above mentioned problem. The main function of DVR is to mitigate the voltage sag. It controls voltage applied to the load by injecting voltage of compensating amplitude, frequency and phase angle to the distribution line. The DVR is primarily responsible for restoring the quality of voltage delivered to the end user when the voltage from the source is not appropriate to be used for sensitive loads. Usage of DVR enables consumers to isolate and protect themselves from transients and disturbances caused- by sags. DVR is simulated using MatLab. The simulation results are compared with the analytical results.
This paper presents two voltage stability indices for the analysis of radial distribution systems, namely VSI (Voltage Stability Index) and FVSI (Fast Voltage Stability Index), which are more sensitive to voltage collapse. Analysis of these indices is carried out with respect to changes in the reactive power of the system. Five types of load modeling, namely Constant Power, Constant Current, Constant Impedance, Exponential and Composite load models are considered for the purpose of stability analysis and comparative analysis is presented. For analyzing the above, a load flow technique is proposed, which involves a simple algebraic equation for calculating the receiving end voltage. The effectiveness of the proposed technique is tested on 15 node and 69 node radial distribution systems.
Optimization is one of the most discussed topics in engineering and applied research. Many engineering problems can be formulated as optimization problems. During the last few decades, many general-purpose optimization algorithms have been proposed for finding optimal solutions, some of which are; Evolution strategies, evolutionary programming, Genetic algorithms (GA), Particle Swarm Optimization (PSO) and Differential Evolution (DE).This paper presents a comparative study of three popular, Evolutionary Algorithms (EA); Genetic Algorithms, Particle Swarm Optimization and Differential Evolution for optimal tuning of Proportional Integral (PI) speed controller in Permanent Magnet Synchronous Motor (PMSM) drive. Average gain function and weighted average gain function are also considered to improve the fitness function. Numerical results show the superior performance of DE in comparison to PSO and GA.
This paper presents the application of interval arithmetic technique for balanced radial distribution system power flow analysis with sparsity technique. Only single dimensional arrays are used for implementation of the proposed method. This reduces a lot of memory and CPU time as it minimizes the search process in identifying the adjacent nodes and branches beyond a particular node. Interval arithmetic takes care of the uncertainty in the input parameters and provides strict bounds for the solution of the problem. In this paper uncertainties only in the input load parameters are considered. Computationally the proposed method is very efficient and it requires less computer memory. The results obtained by the proposed method are compared with the results obtained from repeated load flow simulations.
This paper deals with the simulation of fixed capacitor thyristor controlled reactor system. The TCR system is simulated using MATLAB and the simulation results are presented. The power and control circuits are simulated. The current drawn by the TCR varies with the variation in the firing angle. The simulation results are compared with the theoretical results.
The rapid development of the Internet and digital information revolution caused significant changes in the global society. Digital watermarking has been proposed a new alternative method to enforce the intellectual property rights and protect digital media from tampering .In the recent past several watermarking algorithms have been proposed. The transforms used very often by watermarking algorithms are DFT, DCT and DWT. In this paper we consider content based features like texture, luminance, corners and the edges information to generate mask(JND: just Noticeable Distortion) that helps hidden water mark less perceptible to the human eye. It involves a process of embedding into a host signal a perceptually transparent digital signature, carrying a message about the host signal in order to mark its ownership. The digital signature is called the digital watermark.In particular watermarking algorithms which are based on the wavelet transform have been widely recognized to be more prevalent than others. This is due to the wavelets’ excellent spatial localization, frequency spread, and multi-resolution characteristics, which are similar to the theoretical models of human visual system. In this proposed method, we describe an imperceptible and a robust combined DWT-DCT digital image watermarking algorithm along with the JND values. Experimental results are evaluated with correlation and WPSNR. We can show that this method is more robust than the DCT with the JND values.
