SPWM based Hybrid Converter for Nano Grid Applications
A PFC- Bridgeless SEPIC converter with Multiplier Cell for Universal Input Voltage Applications
Dynamic Modeling of Series Vectorial Compensator
Implementation of Artificial Neural Network on Temperature Control Process
Calculation of Transmission Prices for Bilateral Contracts and Optimization of Pool Contracts Using Intelligent Techniques
A Pedal-Assisted E-bike Model
Design Of Double-Input DC-DC Converter (DIC) Solar PV-Battery Hybrid Power System
Design and Development Of Paddy Cutter Using Solar Energy
A Three Phase Power Flow Method for Unbalanced Radial Distribution systems with Inclusion of Voltage Regulator and Transformer Modeling
Speed Control of Switched Reluctance Motor with Torque Ripple Reduction Using Fractional Order PID Controller and Cuckoo Search Algorithm
Effect Of Stochastic Nature Of Wind EnergyOn Power System
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
In the present scenario, the renewable energy sources solar and wind are used locally by creating a Nano grid. In the integration of these sources to the Nano grid, hybrid converters play an important role to provide both AC and DC loads. Existing hybrid converters suffer with limitations such as no protection for shoot through condition and separate converters are used to supply AC & DC loads, which increases the size and cost of the system. A boost derived hybrid converter which provides both AC and DC output has overcome the above limitations. Further, this converter operation is unstable under unbalanced loading conditions and also its boost gain is low. To improve the performance of boost derived converter the proposed work presents a SPWM scheme based boost derived hybrid converter. The proposed hybrid converter is modeled in MATLAB/PLECS Simulink and its performance is verified under no load and different loading conditions. A laboratory hardware model is developed to validate the Simulink model results. It has been observed that both laboratory model results and Simulink model results are in good agreement with each other. It has been seen that boost derived converter with SPWM scheme has performed better than the PWM based converter.
In this paper a new Power factor correction bridgeless Single Ended primary Inductor Converter (SEPIC) is designed for universal input voltage applications is presented in this paper. Now a days entire our electrical grid connected with nonlinear loads, so there is a need to improve power factor implied on the grid as well as power quality. The main drawbacks of the conventional SEPIC PFC is lower efficiency due to the conduction losses of the diodes. To improve efficiency of the system, a modified bridgeless SEPIC converter is proposed in this paper. The proposed modified PFC coverter offer higher operating efficiency with high gain. The high gain is obtained by multiplier circuits. The main advantages of the proposed system is diode bridge circuits completely eliminated for conventional circuits and also control circuit is very simple. The proposed converter is analysed interms of THD and also analysed gain of the converter with respect to the different duty cycle varying from 10% to 90%. The proposed converter is analysed with mathematical expressions. The results of the modified PFC have been verified using MATLAB Simulink.
This study presents the theory and modelling of a novel controller based on PWM - based Series Vectorial Compensator (SVeC). This is a new series Flexible AC Transmission System (FACTS) controller for active power flow control in a transmission line and damping of low-frequency oscillations (LFO). This paper presents the basic module, steady- state operation, mathematical analysis, current injection model and dynamic model of SVeC. The main contribution of this work is that a current injection model of the SVeC for studying the effect of the SVeC on the LFO is proposed. A brief comparison of the Coordinated Control (COC) of SVeC and Power System Stabilizer (PSS) with without control is presented for dynamic series compensation of transmission lines. The multi machine network is used for comparison purpose. The performance of the proposed controller is checked through eigen-value analysis and non-linear time domain simulations under nominal load operation. The results obtained show that the proposed control is efficient for studying the effects of SVeC on the electro mechanical oscillations and it has better oscillation damping characteristics than without control.
Neural network controllers are network systems which have been inspired from biological neurons. Artificial neural networks ( ANN) work on the principle of learning, where the networks learn based on the data provided to the network. The paper constitutes of implementation of ANN on temperature-controlled process like Single Board Heater System (SBHS). Feed forward back propagation algorithm has been used for system learning. ANN controller learning is done using Levenberg Margaret Algorithm, which is the fastest algorithm for supervised learning (Yang and Kim, 2000). The ANN controller used has three layers, namely input layer, hidden layer, and output layer. The training data set which has been provided to the controller is the open loop response of the system. The responses performance plots, time series plot, and regression plots for a variety of input data sets have been plotted.
The objective of ELD is to determine economic sharing of generating power from different generating stations to meet the demand while satisfying the constraints. Power scheduling is one of the most important problems in the optimization of operation price of the power system. In deregulated power system environment Economic load dispatch (ELD) has the objective of generation allocation to the power generators such that the total prices paid to Gencos is minimized and all operating constraints are satisfied. Various techniques are available to address ELD and other power system optimization problems. The soft computing techniques like particle swarm optimization (PSO), GA and lemda iteration are being used to improve the optimization results. This paper presents and compares the performance of the PSO, GA, and ABC with conventional ELD method for optimization of pool prices. A study on IEEE 26 Bus System has been made for calculating transmission Prices for Bilateral Contracts between GENCOs and DISCOs at different buses. Intelligent techniques have been applied to optimize pool prices and minimizing transmission losses. Transmission pricing are calculated using MWmile method. The results of these techniques are compared, which show better performance of ELD+PSO method over ELD+ABC and ELD+GA methods both.
The goal of this research paper is to promote the use of clean energy by incorporating it into a bicycle. In today's fast forwarding world where one is always in transit from one place to another, has greatly exploited the conventional energy resources, thus compromising environment as well as one's own physical health. Hence this paper not only aims at utilizing a clean energy source but also promote a healthy lifestyle in such a busy world. Our project “pedal assisted ebicycle” allows the rider to make use of an electric motor providing a higher speed and comfort along with pedaling at a more even terrain. Current scenario of use of e vehicles has greatly diverted the attention of the people towards adopting such means of transport thereby increasing the chances of success of our project.