PV-grid Performance improvement through Integrated Intelligent Water Drop Optimization with Neural Network for Maximum Power Point Tracking
A Digital Healthcare Monitoring System with Real-Time Analysis
Advancements in Smart Meter Design and Integration for Enhanced Energy Management and Efficiency
Electric Vehicles in Modern Transportation: Environmental Impacts, Configurations, and Future Trends – A Review
GTO Technique Based Hybrid Power System Controller Design
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
The implementation of a smart power grid is at present, an active area of research for different utilities and countries. Functionally, a smart grid should be able to provide new capabilities such as self-healing, high reliability, energy management, and real-time pricing. A smart grid is expected to respond to threats, material failures, and other destabilizing influences by preventing or containing the spread of disturbances. In addition Smart grid can have major impacts on improving energy distribution and optimising energy usage which will result in reduction of CO2 emission. The Smart Grid will rely on smart sensors deployed across the grid to monitor the system and provide data to enable applications. These sensors must be reliable, have low installed cost and leverage existing communications infrastructure that may include automatic metering infrastructure or even the public cellular networks. This article describes the basic features of smart grid and the role of smart sensors and the accompanying technology in the implementation of a smart grid.
In this paper neuro-fuzzy controller for Doubly Fed Asynchronous Motor (DFAM) drive is proposed. First, a mathematical model of DFAM written in an appropriate d-q reference frame is established to investigate simulations. In order to control the rotor currents of DFAM, a torque tracking control law is synthesized using PI controllers, under conditions of the stator side power factor is controlled at unity level. A four layer Neural Network (NN) is used to adjust input and output parameters of membership functions in a fuzzy logic controller (FLC). The back propagation learning algorithm is used for training this network. The performances of neuro-fuzzy controller (NFC) which is based on the torque tracking control algorithm are investigated and compared to those obtained from the PI controller. Results obtained in Matlab/Simulink environment show that the NFC is more robust, superior dynamic performance and hence found to be a suitable replacement of the conventional PI controller for the high performance drive applications.
Modulation scheme is one of the most important characteristics to note in the monitoring activity and identification of radio signals. Modulation recognition system must be able to make the correct classification of the modulation scheme of the received signal under interference. AMR is required in both military and civilian applications, such as surveillance, electronic warfare, threat assessment, signal confirmation, interference identification, software defined radio, and spectrum management. AMR is also believed to play an important role in the implementation of the 4th-Generation (4G) communication system. A generalized modulation identification scheme is developed and presented. With the help of this scheme, the automatic modulation classification and recognition of digitally modulated speech signals with a priori unknown parameters are possible effectively. The developed scheme based on wavelet transform and statistical parameters has been used to identify M-ary PSK, M-ary QAM, and M-ary FSK modulations. Various speech signals corrupted by noise have been used as sample signals .Statistical parameters are calculated and compared against certain threshold values to detect the modulation type. The simulated results show that the correct modulation identification is possible to a lower bound of 15 dB.
The purpose of this study is to develop a general algorithm to solve the short-term hydroelectric scheduling problem in a robust, flexible and fast way, and which retains the same performances for either a small or a large-scale problem. The solution is based on the discrete maximum principle. Gradient method is used to solve the two-point boundary value problem. To deal with difficulties posed by the state variable constraints we use the augmented Lagrangian method. This paper is particularly concerned with the handling of bonds on the state variables utilizing augmented Lagrangian method.
In this paper an image authentication technique that embeds a color watermark into a host color image is proposed. Watermarking is used for copyright protection using Distributed multiresolution discrete cosine transform (D-MR-DCT) and singular value decomposition. The core idea of the proposed scheme is to decompose an image into four frequency sub-bands using D-MR-DCT and then singular values of every sub-band are modified with the singular values of the watermark.
Optimal Power Flow (OPF) is allocating loads to plants for minimum cost while meeting the network constraints .It is formulated as an optimization problem of minimizing the total fuel cost of all committed plant while meeting the network constraints or power flow constraints. The variants of the problem are numerous which model the objective and the constraints in different ways. Optimal Power flow deals with minimizing generation cost while maintaining set of equality and equality constraints. Power system must be operated in such a way that both real and reactive powers are optimized simultaneously. Reactive powers should be optimized to provide better voltage profile as well as to reduce system losses. Thus the objective of reactive power optimization problem can be seen as minimization of real power loss over the transmission lines. In this paper an attempt has been made to optimize each objective individually using Particle Swarm Optimization (PSO). In this method the system is initialized with a population of random solutions and searches for optima by updating generations. PSO has no evolution operators such as crossover and mutation. In PSO, the potential solutions called particles fly through the problem space by following the current optimum particles. The so developed algorithm for Optimization of each objective is tested on two systems i.e. on IEEE 26 and IEEE 30 bus system. Simulation results of IEEE 26 bus and IEEE 30 bus network are presented to show the effectiveness of the proposed method.
Feeder reconfiguration and capacitor placement are generally used for power loss reduction and voltage profile enhancement in radial distribution systems. This paper presents a joint optimization algorithm of combining feeder reconfiguration and capacitor placement for loss reduction. Genetic Algorithm (GA) is chosen to solve this combined optimization problem. The advantage of this method is that it can provide a global or near global optimum for feeder reconfiguration and capacitor placement. The effectiveness of the proposed method is illustrated with 33-node radial distribution system.
This paper presents a simple method of evaluating the first swing stability of a large power system in the presence of Unified Power Flow Controller (UPFC) device. First a UPFC and the associated transmission line are considered and represented by an equivalent p—circuit model. The above model is then interfaced to the power network to obtain the system reduced admittance matrix which is needed to generate the machine swing curves. The above p —circuit model can also be used to represent other FACTS devices (SSSC and STATCOM) by selecting appropriate values of control parameters of the UPFC. The complex voltage at two end buses of the p-circuit model is also evaluated during simulation to implement various existing control strategies of FACTS devices and to update the reduced admittance matrix. The effectiveness of the proposed method of generating dynamic response and hence evaluating first swing stability of a power system in the presence of UPFC device will be tested on the ten-machine New England system.
This paper presents a multilevel inverter with harmonics reduction along with the reduction in number of switches. The reduction in harmonic content in the three-level neutral-point-clamped (NPC), capacitor clamped inverter with inductive load is obtained by simulation. Similarly the reduction in harmonic content in the cascaded multilevel inverter is obtained. The percentage (%) THD is calculated for various levels (3, 7 and 9 level). Finally the percentage (%) THD obtained from various levels is compared. The functionality verification of the multilevel inverter circuit is done using PSPICE and MATLAB. The harmonic reduction is achieved by selecting appropriate switching angles.
