Department of Electrical Engineering
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Item Unscented Kalman Filter Observer-Based Model(COMSATS University Islamabad Lahore Campus, 2022) Syeda Farwa Fatima; , FA19-REE-008; Dr. Muhammad Jawad, Assistant Profesor [Supervisor]; LHR TP 7605A doubly-fed induction generator (DFIG) is among the primary actuators for wind energy generation due to merits, such as low converter cost, controllable power factor, reduced power losses, variable speed operation, constant grid frequency, maximal wind energy production, and active/reactive power control. The control and estimation problems of the DFIGs are of prime importance to be accurately and properly investigated. The recent advancement in microprocessor technology has led to the implementation of more sophisticated and reliable control schemes such as direct power control, direct torque control, sliding mode control and predictive control. For the DFIGs, the conventional control system often lacks to attain satisfactory results during the transient period due to nonlinearity and a highly coupled control system. Finite control set model predictive control (FCS-MPC) seems to be a very promising solution to control the active and reactive power and to regulate the switching states of rotor side converter due to its flexibility in defining the control objectives, improved dynamic performance and constraint handling. Apart from the inherently non-linear nature of the DFIG, what makes the problem particularly challenging is the unavailability of the measurements such as rotor speed and position. The use of sensors for determining the rotor speed and position not only increases the size, hardware complexity and maintenance cost of the DFIG systems but also decreases the system robustness. The researchers have developed various sensorless algorithms such as unscented Kalman filter, extended Kalman filter, model reference adaptive system, sliding mode observer, luenberger observer for the estimation of parameters. The previous algorithms are less efficient in a way that some of them cause inadequate results for highly non-linear systems and others are unable to operate in the low-speed range. The unscented Kalman filter (UKF) comes to the rescue to deal with the aforementioned issues and generate better results by the estimation of the parameters without linearization. This thesis presents a novel hybrid technique of Finite Control Set Model Predictive Control (FCS-MPC) with Unscented Kalman Filter (UKF) to a challenging control and estimation problem of DFIG. The proposed technique deals with the inherently non linear nature of DFIG and the unavailability of the measurements such as rotor speed and position. FCS-MPC is used for regulating the switching states of the rotor side converter. UKF is selected as an observer to estimate the dynamic states of DFIG.Item A Novel Renewable Powered Stand Alone Electric(COMSATS University Islambad Lahore Campus, 2021) Hira Asghar,; SP19-REE-002; Dr. Muhammad Jawad, Assistant Profesor [Supervisor]; LHR TP 7476The depletion of fossil fuels, gradually increasing environmental pollution and global warming lead to the electrification of the transport sector because the transport sector is one of the main reasons for the rising environmental concerns. However, the increasing number of electric vehicles (EVs) entering the power grid upsurges the electricity demand from the grid as it requires a massive amount of electricity to fulfill its charging needs. The existing electric grid and EV infrastructure is not capable enough to support increasing penetration of EVs, therefore the anticipated increase in the EV count brings new challenges regarding the EV charging needs. Most of the existing works have shared a common drawback of charging EVs by electricity provided from the electric grid. Thus, the primary purpose of utilizing EVs as a solution to decrease pollution is emitted due to the shifting of carbon emission from transportation to the electricity generation sector. This necessitates the usage of renewable energy resources, for instance, solar and wind energy to charge the electric vehicles to attain the environmental and economic benefits of EVs. Although renewable energy seems to be a promising solution due to its instability it may lead to an insufficient energy supply and cause an incomplete or interrupted charging of EVs.Item Application Of Superconductors To Improve(COMSATS University Islambad Lahore Campus, 2020) Amjad Ali,; SP18-REE-016; Dr. Muhammad Jawad, Assistant Profesor [Supervisor]; LHR TP 7465With ever increasing demand of electricity and depleting conventional energy sources with their environmental concerns, renewable energy sources are an excellent alternative for producing clean energy. Among many renewable energy sources, wind energy has huge potential to contribute part of energy demand. However, as a result of unprecedented integration of wind energy in low voltage and high voltage grids, ensuring stability and power quality following grid codes is a challenge lately. Wind Energy Conversion System (WECS) suffers from two main problems, 1) fluctuations in output power due to unpredictable behavior of wind, and 2) retention of connection during grid faults. The optimal solution to increase Fault Ride Through (FRT) capability and smoothing of output power fluctuations in PMSG based WECS is still a point of research in literature. In this research Work, the application of superconductors to enhance the performance of Permanent Magnet Synchronous Generator (PMSG) based WECS is investigated. The presented work considers optimal integration of Superconducting Coil (SC) with PMSG based WECS. Fractional Order PI (FOPI) control is used for control of SC circuit. Harmony Search (HS) optimization technique is used for finding optimum parameter values of the SC and FOPI controllers. The proposed strategy is then compared with PI based control of SC for disturbance in the form of wind gust and grid fault.