1,721,012 research outputs found
Parameter Estimation Based On Particle Swarm Optimization for Short Term Load Forecasting
No full textM.E. (EIED)Load forecasting is an important component for power system energy management system.
Precise load forecasting helps the electric utility to make unit commitment decisions, reduce
spinning reserve capacity and schedule device maintenance plan properly. Besides playing a
key role in reducing the generation cost, it is also essential to the reliability of power systems.
The algorithms and networks were having been demonstrated using simulation studies. The
techniques proposed in this thesis have been simulated using data obtained from State Load
Dispatch Centre, Ablowal, Punjab and Rajasthan for the duration of one week and technique
is used to estimate the parameters of linear and quadratic model and the results obtain for
peak load forecasting are compared with the least error square method
Investigation of Response of Load-Frequency Controller in Two Area Restructured System with Non-Linear Governor Characteristics
No full textM.E. (EIED)The objective of automatic generation control (AGC) is to maintain the system frequency and
tie-line flows within the scheduled values. Adaptive control of frequency has become more
significant owing to increased size, complexity and restructure of power system. In this
dissertation, a framework of automatic generation control with linear and non-linear governor
characteristics in restructured power system has been presented. Conventional AGC with nonlinear
governor characteristics is reported to be dynamically unstable. To stabilize the frequency
and tie-line power flow oscillations, the frequency stabilizer equipped with energy storage
system is modeled. The gains of the integral controller and PID controller and parameters of
frequency stabilizer are optimized using meta heuristic technique namely Genetic Algorithm.
The transient response of optimized load frequency controller is simulated for two-area system
comprising non-linear hydro-hydro and thermal-thermal systems. The response of simulated
model is also studied under different Poolco transactions and bilateral transactions in restructured
electricity market.Electrical & Instrumentation Engg. Dept
Investigation of Optimal Allocation of Wind DG in Distribution System
No full textME Dissertation of Kavita Yadav (ME Power Systems) submitted to Electrical & Instrumentation Engg Dept at Thapar Univ PatialaDistributed Generation (DG) has gained more importance to meet the increased load demand.
Its integration in a distribution system in comparison to conventional system stacks numerous
potential benefits related to losses reduction, improvement in voltage profile, etc. Some of
the issues of distributed generation is its rating, technology, sizing, siting, mode of operation,
penetration level, etc. The thesis focuses on one of the issue that is optimal allocation of DG
unit as the placement of dg unit at non-optimal places leads to increase in system loss and
reduction in bus voltage profile. Alternative sources of energy based distributed generation
has one of the considerable benefit as environmental friendliness. Hence, allocation of
distributed generation units in proper place is an important aspect for maximizing the benefits
stated above. Analysis of distribution network using power flow study plays an important role
in the power system. The optimal location of wind based dg unit is determined using newton
raphson method for obtaining the voltage profile with the analytical approach. The analytical
expression used are based on exact loss formula. The proposed methodology has been tested
and validated on IEEE 14 bus and 33 bus distribution systems. Results are obtained for normal
load and with the increased load. The outcomes shows that by proper placement of wind based
dg unit at relevant bus location the real power losses are minimized and corresponding bus
voltages are improved
Optimal Management of Microgrid Using Heuristic Search Algorithm
No full textM.E. (EIED)A microgrid is a small scale power system that operates either independently or in combination
with the main gird. The intent of using the microgrid is to act as a backup power supply or to
boost the main grid during the heavy load demand. Microgrid consists of renewable energy
sources like wind turbine and photovoltaic cell to enhance the stability and reliability of the
power system. The management of the microgrid takes into account the optimization of the
operating cost of the generation unit within the operating limits and the emission rate of the
gases. Battery output power which is used to find optimized results is forecasted using fuzzy
logic technique. The optimized operation of the microgrid is performed by using Back tracking
search algorithm. Back tracking search algorithm (BSA) is a heuristic search technique based on
the single control parameter having crossover and mutation operator. In BSA, randomly
generated population is stored in the memory for calculating the search direction matrix and the
explore the search space bounded by the constraints. In order to show the effectiveness of the
global search technique, it is applied on the five scenarios of the microgrid.Electrical & Instrumentation Engg. Dept
Weather Sensitive Short Term Load Forecasting using Non-fully connected Feed Forward Neural Network
No full textM.E. (Power Systems & Electric Drives)ABSTRACT
Optimal daily operation of electric power generating plants is very essential to reduce
input costs and possibly the prices of electricity in general. Load forecasting is extremely
important for energy suppliers, financial institutions, and other participants in electric energy
generation, transmission, distribution, and markets. An accurate and reliable electric load
forecasting systems are absolutely required. Precise load forecasting helps the electric utility to
make unit commitment decisions, reduce spinning reserve capacity and schedule device
maintenance plan properly.
Since in power systems the next day’s power generation must be scheduled every day, dayahead
short-term load forecasting (STLF) is a necessary daily task for power dispatch. Its
accuracy affects the economic operation and reliability of the system greatly. Under prediction of
STLF leads to insufficient reserve capacity preparation and, in turn, increases the operating cost
by using expensive peaking units. On the other hand, over prediction of STLF leads to the
unnecessarily large reserve capacity, which is also related to high operating cost.
This thesis presents a solution methodology using fuzzy logic approach and artificial neural
network for short term load forecasting and is implemented on historical weather sensitive data
i.e. temperature, humidity, wind speed and historical load data for forecasting the load. The
proposed fuzzy logic approach is implemented on weather sensitive data and the accuracy of the
result is compared using two different membership functions. Artificial neural network approach
is implemented on the proposed non-fully connected neural network consists of five fully
connected supporting networks representing weather variables, day type and load data as inputs.
Jodhpur Vidyut Nigam hourly load data used for training and testing collected from State Load
Dispatch and Communication Centre, Rajasthan Vidyut Parasaran Nigam. The results are
obtained from two different approaches are compared and accuracy of neural network is reportedElectrical & Instrumentation engineering department, Thapar university, patial
Investigation of Optimal Power Flow with TCSC using Differential Evolution
No full textME, EIEDOptimal Power Flow (OPF) plays an important role in power system operation and planning. The OPF mainly aims to optimize the selected objective function such as fuel cost, active power loss via optimal adjustment of power system control variables, while at the same time satisfying various equality and inequality constraints. In recent years, FACTS devices have opened a new world in power system control. They have made the power systems operation more flexible and secure. In the power flow studies, circuit impedance, voltage magnitude and phase angle are important parameters. In this dissertation work, the TCSCs are incorporated using reactance model at fixed locations and power flow studies are carried out using Newton Raphson method. Differential evolution strategy is used to optimize the parameters like bus voltages, angles, generation cost and the reactance values of TCSC. The proposed strategy which is best suited for solving non-convex optimization problems, has been implemented on IEEE 14 bus system and it shows better results when compared with conventional iterative procedure.Electrical & instrumentation Engg. Dept., Thapar University, Patial
Design Optimization of Residential Air Conditioner for Quality Enhancement and Failure Reduction
No full textLG Electronics India Pvt. Ltd. has provided a great platform to gain some extremely valuable
experiences, knowledge and skills that too in a very helpful, caring and professional
environment.
The project is titled as “Design optimization of residential air conditioner for quality
enhancement and failure reduction”. At the QA (RAC,FQM) LGEIL, the work mainly consisted
of concept development and its feasibility for various other aspects, plus testing of the different
components of the product. The new development modelled along-with some modifications in
existing machine. The main focus is how to reduce field failure rate by applying improvements
in design so as to reduce field failures. It also consisted of study of various electronic, electrical
and mechanical components being used in white goods and exploring new possibilities for
improvement in quality or reduction in cost. Major components of air conditioner along with
their functioning and their build inside out is analyzed to determine about the circuit behaviour
and mechanism of different parts and the complete functioning of split air conditioner.
The objective of the project is to identify the issues and defects found from the customer end and
based on that improvement in design and specification is suggested and validated in various parts
of residential air conditioner .In this project, not only electrical and electronic components but
also the mechanical components of air conditioners are dealt. The reasons and causes of field
failure of various components of air conditioners along with some product liability cases are
analyzed and the different AC components that have failed in field and are brought up for the
purpose of analysis are tested with proper structural procedures to find common errors and
troubleshot accordingly . These field failures are analyzed and discussed among different
respective departments like R & D and Quality and actions taken accordingly to improve the
quality and reducing the cost to company.Thapar Institute of Engineering and Technology, Patiala and LG Electronics India Pvt Ltd. Greater Noida, U
Self-Organising Particle Swarm Optimisation for Economic Generation Dispatch Incorporating Wind Power
No full textMaster of Engineering-PSEDThe focus of this dissertation is to explore the potential of energy savings through wind power source in coordination with thermal power generation to meet the losses and continuously varying load demand with due considerations to technical constraints imposed by units. The power output from thermal units is considered deterministic whereas wind power output is intermittent due to stochastic nature of wind speed. The intermittent wind power is modelled by discontinuous Weibull probability distribution function. The optimal generation allocation among thermal units and wind based units is based on the operating cost of thermal units and cost of wind power. The wind unit cost accounts for linearly incremental cost due to unused available wind power, penalty cost to account for overestimation and underestimation of wind power and direct cost pertaining to the issue of ownership of wind generators. The proposed optimization model is solved for ten and forty thermal units with valve point loading effect and two, five, one wind unit to meet 24 hour load demand using self-organizing particle swarm optimization technique that can handle the problem of convergence to sub-optimum solutions prematurely. B-coefficient method is used to include transmission losses. The results show that the total cost of system decreases as the wind power scheduling increases and hence the thermal fuel cost decreases. Self- organizing PSO (SOPSO) gives better results.Electrical and Instrumentation Engieering, Thapar University, Patial
Speed Control of Brushless DC Motor Using Artificial Neural Network Tuned PID Controller
No full textM.E. (Power Systems and Electric Drives)In automotive industry, high performance drives are gaining popularity due to their high
efficiency, good dynamic response and low maintenance. The precise rotor movement over a
period of time in certain applications such as robotics, guided manipulation and dynamic
actuation must be achieved even when the system loads, inertia and other controlling parameters
are varying. To do this, the speed control strategy must be adaptive, robust, accurate, and simple
to implement.
The conventional feedback controllers those are based on linear control theory and are much
easier to understand and implement but suffer the disadvantages when the operating points of the
process or the plant parameters are changed due to disturbances. Fixed-gain feedback controllers
need to be returned to obtain the new optimal settings. For the processes with variable time
delays, varying plant parameters, large non-linearties and considerable process noise, the PID
controller does not give optimal performance.
In view of this an adaptive controller that can modify its behaviour in response to the dynamical
changes in the process and the disturbances is developed. Artificial Neural Network (ANN) based
intelligent controller can mimic adaptive nature of controller used in non-linear system through
its highly parallel and distributed structure. Neural network can generate a nonlinear mapping
between the inputs and outputs of a system without the need for a predetermined model.
The aim of the thesis is to design a simulation model of brushless dc motor and to control its
speed at different values of load torques. The accurate speed control is proposed to achieve
through PID controller. The parameters of PID controller are tuned by on line training of the
artificial neural network. The performance of the PID type controller with fixed gain,
conventional integral controller (PI) and ANN based PID controller have been compared through
MATLAB simulation results with focus on feasibility, reliability and accuracy for BLDC
permanent magnet synchronous motor drive system. The qualitative and quantitative comparison
have shown the superiority of the performance of PID tuned through artificial neural network
over integral and PID controller in terms of the reliability and feasibility. The reported
percentage overshoot error is well within the permissible limits and rise time is also very low.Electrical and Instrumentation Engineering Deptartment, Thapar University, Patial
Modelling and Analysis of TCSC Application to Transmission System
No full textM.E. (PSED)The need for more efficient electricity systems management has given rise to
innovative technologies in power generation and transmission. Flexible AC
Transmission Systems (FACTS) is one of such technologies that respond to these
needs. It significantly alters the way transmission systems are developed and
controlled together with improvement in asset utilization, system flexibility and
system performance. Different types of FACTS devices are being used now-a-days.
Thyristor Controlled Series Compensator is one of the series compensating FACTS
devices.
Thyristor Controlled Series Compensator (TCSC) consists of a series
compensating capacitor shunted by a Thyristor Controlled Reactor (TCR). The basic
idea behind the TCSC scheme is to provide continuously variable impedance by
means of partially canceling the effective compensating capacitance by the TCR.
Transmission lines compensation by means of TCSC can be used to increase the
power transfer capability, improve transient stability, reduce transmission losses and
dampen power system oscillations.
In this thesis work device modelling of TCSC has been carried out along with
development of transmission system using MATLAB7.5/Simulink. Then this device
has been applied to the transmission network using Power System blockset. The
response of transmission systems has been studied for various types of faults with and
without TCSC, thus analyzing the impact of TCSC on the performance of
transmission line in terms of various parameters, under consideration. Impact of
variation of degree of compensation on power flow has also been studied which
shows that for a fixed angular difference, with the increase in degree of compensation
power flow increases.EC
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