Theses supervised by Osman Kükrer
12 theses · Eastern Mediterranean University
Novel Robust Adaptive Beamforming Algorithms with Improved Estimation of Array Covariance Matrix and Signal Steering Vector
Robust adaptive beamforming has long been an attractive research topic over several decades due to wide applications in vast fields of signal processing such as, radar, sonar, wireless communications, medical imaging, microphone array speech processing and other areas. Adaptive beamforming improves the reception of desired signals in the presence of interference signals automatically by sensing the presence of interferences and suppressing them while simultaneously enhancing desired signal reception without prior knowledge of the signal and interference environment. However, under certain circumstances, adaptive beamformers suffer performance degradation due to several reasons which include small sample size, the presence of the desired signal in the training data, the presence of nonstationary interference, or imprecise knowledge of the steering vector of the desired signal. Moreover, conventional approaches are very sensitive to these types of mismatches, do not provide sufficient robustness and may suffer from severe performance degradation in such situations. In this thesis, we propose three different types of novel adaptive beamforming techniques to resolve the effects caused by some of the aforementioned difficulties. A general goal in adaptive beamforming is to adaptively steer a beam towards a desired signal, while placing nulls at interference directions. The well-known minimum variance distortionless response (MVDR) adaptive beamformer is designed to linearly combine the outputs of the sensors in order to minimize the array output power, while maintaining a fixed response towards the desired signal. However, it is well known that the MVDR beamformer is quiet sensitive to the mismatch between the actual steering vector and the assumed one, which could be caused by any array imperfection. In the first approach, a robust adaptive beamforming technique based on a modification of the robust Capon beamforming approach is introduced which estimates the steering vector using eigenspace projection-based approximation. The steering vector is estimated as a reasonable approximation for the orthogonal projection of the presumed steering vector of the desired signal onto the signal-plus-interference subspace. In this approach, the optimal diagonal loading factor corresponds to the minimum of the estimated beamformer output power. Also, estimation of the desired signal’s direction-of-arrival is utilized to update the presumed steering vector. On the other hand, during the past decade, many approaches based on the processing of the sample covariance matrix have been proposed. However, since the desired signal component is usually included in this matrix, the beamformer is sensitive to slight mismatches. Although, some techniques have been proposed to remove the signal-of-interest (SOI) component from the signal covariance matrix using the reconstruction of the interference-plus-noise covariance (IPNC) matrix, these have a number of drawbacks. In the second approach, we introduce a low complexity procedure for IPNC matrix construction. The main motivation of this algorithm is to simplify the estimation of the IPNC matrix using its theoretical expression which is based on projection processing for covariance matrix construction and desired-signal steering vector estimation. In this accordance, the optimal minimum variance distortion-less response beamformer is closely achieved through approximating the interference-plus-noise covariance matrix by utilizing the eigenvalue decomposition of the received signal’s covariance matrix. Moreover, the direction-of-arrival (DOA) of the desired signal is estimated by maximizing the beamformer output power in a certain angular sector. In particular, the proposed beamformer utilizes the aforementioned DOA in order to estimate the desired-signal’s steering vector for general steering vector mismatches. In addition, adaptive beamforming methods are sensitive to underlying assumptions on the environment, sources, or sensor array violation, especially when interferences are moving fast. In recent years, research efforts have been devoted to the development of beamforming using covariance matrix taper (CMT) or additional constraints in the optimization programming for suppression of pre-defined angular ranges. This research presents an innovative beamforming approach in which the nonstationary interference source is estimated during the period in which snapshots are taken. Then, a new interference-plus-noise covariance matrix reconstruction is introduced which is derived from a simplified power spectral density function that can be used to shape the directional response of the beamformer. Finally, the beamformer is designed to impose nulls toward the regions of the moving interference based on the reconstructed covariance matrix. The essence of the proposed method is to express the inverse of the reconstructed covariance matrix in such a way that significantly reduces computational complexity. Theoretical analysis and simulation results indicate the superior performance of the introduced proposed approaches in the presence of mismatches relative to other some existing methods.
Energy Yield Optimization of a Large-Scale PV Power Plant in Self-Consumption Mechanism
The objective of this thesis is to optimize the design parameters of a large scale photovoltaic power plant in order to find its optimal size having the lowest payback period. A methodology is proposed to guide the investors and technical staff in the design of such a system, with core emphasis on self-consumption policy. A flowchart of the process, that uses site survey, system components, associated costs, meteorological data, load analysis, is created. A three-step algorithm is developed in order to solve the optimization problem that searches for the PV plant size having the lowest payback period. The first phase of the algorithm is to minimize the energy fed into the grid for free of charge. In other words the self-consumption is maximized. The decision variables such as the tilt angle of the PV modules, number of PV modules connected in series across a string, number of strings connected to an inverter and the number of inverters are calculated in this phase. The second phase involves maximizing the occupied land area and determining layout of the PV plant. The layout is based on consecutive PV blocks in the installation area. Number of rows and columns in a PV block are obtained in this phase. Last phase is based on the calculation of the optimal size of the PV plant, which has the lowest payback period, by using an iterative approach. Net present value analysis is used as a supplementary tool in order to allow the investor to make better judgment on the project. A case study is carried out in Cyprus International University campus in order to support the proposed methodology. The lowest payback period is achieved at 6.18 years with the total installed capacity of 712 kWp. The payback period results iv calculated by the proposed algorithm and PV*SOL Premium, which is one of the most commonly used PV planning software in the PV market, for each increment in the PV plant size are compared. The difference between the payback periods obtained from the proposed algorithm and PV*SOL Premium is 1.79% on average and 0.34% at the optimum PV plant capacity. According to the case study, a 712 kWp self-consumption PV plant can be installed on 9055 m2 of land area. The initial investment cost is calculated as € 1,063,700. The system can consume 97.92% of its own annual production while only 2.08% of the annual PV energy generation is exported to the grid. The system reaches a self-sufficiency ratio of 25.02%. The net present value is calculated as € 7,091,000. Keywords: Solar energy, large-scale PV power plant, non-incentivized self-consumption, design optimization.
Sliding Mode Controller for Single Phase Grid Connected Voltage Source Inverter with LCL Filter
ABSTRACT: Many researchers have focused widely on suppressing the steady state sinusoidal tracking error and the total harmonic distortion in grid-connected inverter systems. In this thesis, a sliding mode control strategy with integral and mutli-resonant controllers is used to control a single phase voltage source grid connected inverter. This method leads to a sliding surface where all the states of the system remain on and sliding until reaching the equilibrium point which is the origin in the steady state. Integral term for grid current error is added to suppress the magnitude of the error in grid current but the results show that this term has no effect on the harmonic distortion of the system especially when an external disturbance is applied to the system from the grid voltage. So, another term called multi-resonant is added. This multi-resonant term is able to suppress the magnitude of the disturbance and the total harmonic distortion in the system. Simulation results for single-phase grid-connected inverter is shown using Simulink (matlab 2015) to prove the effectiveness of the proposed control strategy. These results are compared with the results in [11] where the tracking precision of the grid current is improved from 0.91% to 0.17% and the THD of the grid current from 0.76% to 0.05%. Keyword: Voltage source inverter (VSI), LCL filter, Sliding mode control (SMC), Integral controller, Multi-resonant controller, Grid current tracking error, Total Harmonic Distortion (THD)
Distributed Generation Placement Based on Voltage Stability Using Genetic Algorithm
In this thesis, a genetic algorithm (GA) based optimization is used to improve the voltage stability of a power network using Distributed Generation (DG) Units. GA determines the best places of DG Units in the power network. Also, the number and sizes of DGs used are calculated by the proposed algorithm. First, we have solved the problem without using GA. In this step, just one DG with constant size is considered. The main reason of using GA to solve the problem is that finding the best places of DGs could be very complicated and time consuming, considering the number and size of DGs. To evaluate and compare the possible solutions, an index called Voltage Index (VI), is proposed which shows the voltage stability of the power network. A Forward/Backward load flow is used to determine the bus voltages, and consequently the VI of the network. The results show that by using DGs the voltage stability of the network is improved. In addition, GA, as an optimization algorithm, can find the best solution for the problem considering number, size and place of DGs after a specific number of iterations. The best solution for the problem and the results of the load flow for best state are shown as the results of the thesis. Keywords: Power Systems, Distributed Systems, Distributed Generation, Renewable Energy Systems
Denoising Using Low-Pass Filtering Combined With Total Variation Filtering
Generally LTI filters are appropriate to denoise a signal that have low-frequency band. On the other hand, total variation denoising is appropriate to filter a signal having sparse representation. Some signals cannot be classified as having specific frequency band, or having sparse representation, such as the signal comprised in biomedical applications (near infrared spectroscopic imaging and nano-particle biosensing). This thesis introduces a new approach for denoising signals based on low-pass filtering combined with total variation denoising, assuming that the noisy observation is near infrared spectroscopic time series measurement, which can be modelled as a sum of two components, one of them low frequency and the other sparse or sparse derivative. The problem is formulated in terms of an optimization problem, and the cost function of the optimization problem is convex. As a consequence, two iterative algorithms are presented; the first one is derived using the majorization-minimization technique, and models the signals as consisted of low frequency and sparse derivative components. On the other hand, the second algorithm is derived using alternative direction method of multipliers, and models the signals as consisted of low frequency, sparse and sparse derivative components. In view of the above, simulation algorithms based on existing noisy observations are developed for validation and verification of the proposed approach. The simulation results show that the proposed approach for denoising signals recovers the signals well. Furthermore, it was found that the proposed approach is better in terms of run time. Keywords: NIRS, low-pass filter, total variation denoising, sparse derivative.
Control Methods for Multilevel Converters
This thesis aims to develop new control methodologies for the Packed U-Cell (PUC) converter. The main problem lies in the structure of the PUC converter, where it is a hybrid type of multilevel converter (MLC) similar to cascaded H-bridge converters. From the control prospective, the topology has discrete digital control inputs, thus conventional modulation techniques cannot be directly applied to the converter. Proper control methods have to be introduced in order to make use of the great advantages of the PUC converter. These control methods have to be simple in implementation for industrial environment with low switching frequency. Additionally, the newly proposed control methods should have advantages over the existing ones. In the first attempt of this thesis, a modified version of model predictive control (MPC) has been integrated to control grid connected PUC inverters. Mainly, the cost function is formulated to guarantee the stability of the controlled system. Then, the gains associated with the controlled variables are eliminated in order to simplify the control. The proposed controller has shown great features in terms of stability and low average switching frequency. In the second attempt of this thesis, the interesting features of sliding mode theory are utilized to serve the control problem in a better way. The proposed controller is very simple to implement with low computation time, which reduces the computational burden on the controller. The controller aims to allocate the control input which stabilizes both the grid current and the auxiliary capacitor voltage in the grid connected PUC inverter. Lastly, the control problem of the PUC rectifier with a dual output is targeted using Lyapunov-based MPC. This attempt is done in order to prove the workability of the controller for three control variables. In this method Lyapunov-based MPC doesn’t require gain tuning as in the PUC inverter problem. Load current measurements are eliminated by making use of the mathematical model of the PUC converter. This significantly reduces the cost and simplifies the control algorithm, where no current sensors are used for the load measurements. For all proposed methods, simulations and experimental tests were done in order to justify the correctness of the proposed methods. Dynamic tests and parameter mismatch tests are carried out to measure the controller response and to show the robustness feature of the proposed controllers. Keywords: Finite control set, Lyapunov control, model predictive control, multilevel converter, packed U-Cell converter, sliding mode control.
Plug-In Hybrid Electric Vehicle’s Impact on Primary and Secondary Frequency Regulation
Plug-in hybrid electric vehicles (PHEV), while they are plugged-in, support the grid a distributed storage. With the advent of smart grid along with the developed communications related with it, PHEV could contribute to ancillary services such as frequency adjustment. An excellent service for PHEV is frequency regulation supply as the duration of supply is short. Moreover, with regard to the fact that frequency regulation is the highest priced ancillary service, the owners of vehicles benefit from PHEV financially. A reliable frequency measurements can be achieved by the coordinators of the system that can drive the trustworthy local automatic generation control (AGC) signals for vehicles which are participating in vehicle-to-grid (V2G) operation. A V2G controller as well as PHEV coordinator are extra controllers which estimate the battery state, recommended level of supply, and user preferences for V2G participation. The simulation part uses three sequences of cases for regulation supply when a sudden change in loading is detected: Providing frequency regulation using central generating units, using aggregate PHEVs storage as a contribution to primary regulation, and finally utilizing the storage as a contribution to primary as well as secondary regulation. Keywords: Plug-In Hybrid Electric Vehicle, Frequency Regulation, Automatic Generation Control, Area Control Error.
A Design Model and Comparison of Fixed and Tracking Photovoltaic Systems for a Single-Family House in Erbil, Iraq
This thesis reviewed the photovoltaic (PV) technology. It also analyzed the potential of the PV plants to solve the problem of power shortages in Iraq. The use of PV power is the most advanced renewable energy application; however, it has not been commercialized in the study location. In this thesis, three separate PV plant systems were assessed in Erbil, Kurdistan region for installation. The study examined the feasibility of the plants proposed and compares the efficiency of both a fixed and dual axis tracking systems for an off-grid PV system. This thesis presented a study on an off-grid photovoltaic system for electrification of a residential household in Erbil (36.18° N, 44.01 ° E, 392 m) using PVsyst software for household load estimation and solar energy requirements. According to meteorological data, Iraq is characterized by a solarity ranging from 1800 kWh/m2/year to 2390 kWh/m2/year of direct normal solar irradiation(Al-Kayiem,2019). Using the Meteonorm solar radiation map, a suitable location was selected for the plant, calculating PV arrays and arrangements to determine the appropriate number of panels, maximizing AC power generation, storage capacity of the battery, and charge controller size to fulfil the required load. To calculate the annual energy generation, the design data was used in a simulation. Three scenarios were simulated; fixed panels, East-West single, and dual-axis tracking systems based on the altitude of azimuth angle tracking. The study compared both the photovoltaic properties and the amount of energy generated by the installed systems: one with a fixed tilt angle, and the other fitted with solar trackers. The results showed that the dual-axis tracking system is 30% more efficient than the other systems, although the single-axis tracking system offers an economically better alternative. Keywords: photovoltaic system (PV), fixed-tilt PV installation, single-axis tracking system, dual-axis tracking system, off-grid system design, PVsyst software.
Projection Based Beamformer Algorithm for Adaptive Beamforming in Uniform Linear Array
Adaptive beamforming is a spatial filtering technique for uniform linear array of sensors that has application in numerous fields of signal processing such as wireless communications, radar, sonar, seismology and radio astronomy. Classically the minimum-variance-distortionless-response (MVDR) beamformer provides an acceptable solution to the problem of recovering the signal-of-interest (SOI) in the array input while minimizing the array output power. A number of problems exist in practice with the MVDR beamformer due to a number of non-ideal conditions such as mismatch in the direction of arrival (DOA) of the SOI, array calibration errors, local scattering of the incident signal and the finite sample approximation of the array covariance matrix. Several adaptive beamforming techniques, which have robustness against the problems cited above, have been developed to overcome these difficulties. However, these techniques have in general high computational complexity, as they depend on the eigenvalue decomposition (EVD) of the array covariance matrix. In this work we consider the application of the multiple signal classification (MUSIC) method to the solution of the beamforming problem. This involves the estimation of the unknown DOA of the SOI based on the MUSIC algorithm. The DOA of the SOI is estimated by minimizing a cost function in terms of the norm of an error vector, which is the difference between the presumed steering vector of the SOI, and the orthogonal projection of this vector on the signal subspace. Direct implementation of this approach, however, also comprises eigenvalue decomposition of the covariance matrix. We will investigate the possibility of performing the above-mentioned minimization without EVD by expressing the cost function in terms of a parameterized estimate of the signal steering vector. Keywords: Adaptive Beamforming, Minimum-Variance-Distortionless-Response, Mismatch, Direction Of Arrival, Signal Of Interest, Eigenvalue Decomposition
PWM Control Scheme for Quasi-Switched-Boost Inverter to Improve Modulation Index
The typical two stage power inverters, a boost DC – DC converter is utilized to make a constant DC bus voltage. Then a DC – AC inverter (H- Bridge) is used to invert the DC voltage to AC voltage but in this type both of the power switches in the leg of the H – bridge cannot be turned on at the same time because it makes a short circuit and thus may damage the device. Shoot-through protection is a way used to prevent and solve this problem by controlling the shoot through state in a single phase stage quasi-switched boost inverter (qSBI). However, it has different methods, the most common is the simple boost control (SBC). This thesis presents a new pulse width modulation (PWM) control scheme to improve the modulation index for the qSBI. In this thesis, a circuit is designed with 400W and 110V and 50 HZ output. The related circuits and the operating principles were analyzed using Matlab/Simulink. The analysis simulation results proved that the control scheme can enlarge the modulation index, reduce the voltage stress on the capacitor, diode and switches, as well as reduce the frequency of the inductor current, ripples of the capacitor voltage, lowering the shoot through current. Keywords: Pulse-Width Modulation (PWM), quasi-Z-Source Inverter (qZSI), quasi-Switched-Boost Inverter (qSBI), shoot-through, Simple Boost Control (SBC).
Single-Phase Current-Source Rectifier Closed-Loop Control with Active Power Decoupling Based on LC Resonator Emulation
ABSTRACT: AC-DC converters are power electronic systems which are used in a variety of industrial applications. These systems are better and more efficient than the regular AC-line commutated thyristor converters. The AC-DC converters can be regulated to draw sinusoidal currents from an AC source with variable power factor. Furthermore, they can produce smoother output voltages than the output voltages produced by the classical converters, especially in the three-phase usages. Nevertheless, in single-phase usages the output voltage of a PWM converter has a naturally occurring second harmonic component, which requires the use of a large output capacitor for separating this component. But even when using a large capacitor (which raises the proportions and cost of this me of converter) it is still not possible to eliminate the second harmonic completely. A better option for eliminating the second harmonic issue is to use an LC resonator that is modified or adjusted to eliminate this harmonic. This option can be easily applied in AC-DC converters of the current source type. In this thesis, the LC resonator-based single-phase converter will be considered. The work will be based on an IEEE Transaction paper. Firstly, the basic theory of this AC-DC converter will be revised, then the control strategy planned for eliminating the second harmonic component (which is based on active power decoupling) will be analyzed. Simulations on the single-phase current source converter will be done on Simulink. The simulations will be designed to assess the performance of the planned control strategy. Possible failures of the control strategy will be acknowledged, and adjustments will be made accordingly. Keywords: active power decoupling, LC Tank, ripple power, single-phase current source rectifier.
Design of Natural Damping Control for Three-phase Grid-Connected Voltage Source Inverters with LCL-Filters
Nowadays, researches have been carried out on reducing the total harmonics distortion when a voltage source inverter (VSI) is connected to the grid through a filter. LCL-filter reduces the harmonics contents when the switching frequencies are low and also the values of the inductance are low. Another advantage of LCL-filter is it has two possible current feedbacks that can be use for control. In this thesis, the current at the inverter side will be use for feedback control and no additional sensor is required. There was an observation that a natural damping term is present in the control loop, when the inverter side current is used for feedback control, instead of using active or passive damping technique. Steps to determine the values of the inductors at grid and inverter side are presented, so that ideal damping can be naturally obtained by using just the inverter side current control. When the steps to determine values of the inductors are not fulfilled, a notch filter with second order is used to extract the damping information from the converter current, then tuned the system damping with a compensation gain and due to its free of fundamental component, the compensation strategy will not cause an over modulation problem. Simulation results for both strategy are shown using Matlab Simulink to prove the effectiveness of the proposed control strategy. Keywords: Voltage source inverters (VSI), LCL filter, current control and resonance damping.