2. Thesis and Dissertations

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Optimized Design of Collector System for Offshore Wind Farms and Development of A Hybrid Controller for Single VSC-HVDC and Multi-Terminal VSC-HVDC System
(National Institute of Technology Karnataka, Surathkal, 2020) Srikakulapu, Ramu.; U, Vinatha.
This thesis deals with the optimal design of the electrical collector system of offshore wind farms (OSWFs) and the design of a robust controller for the grid-integrated OSWF with voltage source converter (VSC)- high voltage direct current (HVDC) transmission system. The worldwide installation of offshore wind farms consists of hundreds of higher rated wind turbines, which have been significantly increased in number due to their economic benefits. First part of the work in this report describes an efficient approach for improving the wind farm power production by appropriate placement of wind turbines in OSWF using the larsen and jensen wake models. A new optimization approach based on (a) elitist ant colony optimization for travelling salesman problem and multiple travelling salesmen problem and (b) firefly algorithm for travelling salesman problem and multiple travelling salesmen problem are applied to design an optimal electrical collector system for OSWF with the objective of minimizing inter-array cable length and there by reducing the cost of power production. The objective function of the electrical collector system design is expressed based on the levelized production cost and aims to minimize the levelized production cost, minimize the length of the inter-array cable between the wind turbines, achieve wake loss reduction, and optimize the power production of OSWF. The proposed approach is tested using North Hoyle and Horns Rev OSWFs with 30 and 80 wind turbines, respectively and the results obtained is observed as a valid optimal electrical collector system design. The thesis further proposes a new hybrid controller for AC grid integrated offshore wind farm with VSC-HVDC transmission system and AC grid integrated offshore wind farms with multi-terminal VSC-HVDC transmission system. It is combination of proportional{integral (PI) based inner and sliding mode control based outer controller. With the hybrid controller, the VSCs of the HVDC transmission system are connected for control of the AC voltage, DC-link voltage, reactive power and effective power transfer between the OSWFs and an onshore AC grid. An evolutionary algorithm and proportional{integral{derivative (PID) tool are iiiutilized to realize the tuned gain parameters for hybrid and conventional controllers. The FRT capability, small signal analysis, and controller stability of the VSC-HVDC systems are analyzed. To check the stability of the system, small signal stability analysis is carried out with the hybrid controller and performance is compared with conventional PI controller. To examine the fault ride through (FRT) capability, a symmetrical fault and unsymmetrical fault are applied at an onshore AC grid side and the performances of the system based on the hybrid and PI controllers are analyzed. Dynamic model and linerized state-space model of the VSC-HVDC systems with hybrid and conventional controllers are developed. The analysis of the VSC-HVDC systems with hybrid and conventional controllers is conducted in the software environment of the MATLAB/Simulink. The simulation results show that the proposed control scheme provides effective active power transmission, AC voltage control, minimum reactive power transfer among the VSCs, and DC-link voltage regulation in the presence of system uncertainties and faulty condition. The controller stability is observed with the help of the Nyquist plot and eigenvalue analysis. The effect of parameter uncertainty on total system stability is examined with the help of eigenmatrix of the VSC-HVDC system.
Development of Advanced Smart Energy Management Framework Integrated with Optimization Techniques and Prediction Models for Demand Side Consumers Based on IoT Platform
(National Institute of Technology Karnataka, Surathkal, 2020) Pawar, Prakash.; K, Panduranga Vittal.
Smart grid framework plays an indispensable role in dealing with the usage of available electrical energy proficiently. However, to manage power supply effectively, electrical appliances and devices at home and building environment should have smart energy management capability. Further, Smart Energy Management System (SEMS) can be unified with the smart grid for effective power consumption. SEMS can be used to control the status of the electrical appliances and devices by monitoring environmental conditions with the associated sensors and the context in which the appliance is being operated. In addition, SEMS can be used to reduce the standby power consumption of the appliances by turning off the supply to it. The SEMS system can be associated with a Grid or the distributed generation, and thus power negotiation techniques can be applied depending on the availability of the power or tariff information. In this research work, the emphasis is given to the design of a smart energy management system and deployment of power negotiating algorithms for effective power utilization. The proposed SEMS replaces the scenario of a complete power outage in a particular region with partial load shedding in a controlled manner as per consumer’s priority. The hardware experiments are demonstrated assuming a demand response event, taking into account the constraints of maximum demand limits in various cases of changing priorities. The cost optimization algorithms are deployed by scheduling the appliances, considering the Time of Usage (ToU) and minimum slab rate. Sensory information’s and indicators are used to control the loads with user comfort settings and alarm the user during peak hour usage, respectively. Reliable ZigBee communication is established in the Application Transparent (AT) mode of configuration with a self-diagnostic mechanism. Internet of Things (IoT) environment is created for uploading the data, storing it in the database with load wise data analysis daily and monthly basis with Graphical User Interface (GUI). The challenge of energy shortages requires an optimized solution to demandside consumer issues. Energy demand factors contribute to the implementation of variable tariff’s and reward consumer’s electricity usage during off-hours rather than during peak hours. In addition, the surge in tariffs iiiand price volatility emphasize the need to carefully schedule the operation of large devices to minimize power consumption. In this task, a genetic algorithm is used to find the optimal load schedule that minimizes the cost spent on power according to considerations such as user comfort, maximum allowable demand, load characteristic’s, environmental factors and so on. Further, this work will focus on testing the Binary Backtracking Search and Artificial Bee Colony algorithms against the Binary Particle Swarm algorithm benchmark to find the optimal load scheduling in terms of complexity, cost optimization, and execution time. On the other hand, the challenge in energy management lays focus on the efficient utilization of available power sources without limiting power consumption. Above issue seeks for design and development of an intelligent system with day-ahead planning and prior forecasting of energy availability. Hence there is a need for accurate energy prediction technique to minimize imbalance in the power sector. In this context, an Intelligent Smart Energy Management Systems (ISEMS) is proposed to handle energy demand in a smart grid environment with penetration of renewable sources. The proposed scheme compares several prediction models for accurate forecasting of energy for hourly and day-ahead planning. Based on the predicted information, ISEMS negotiates the available power and dispatch the control action depending on the consumer assigned priority for an appliance. Several energy prediction models are evaluated and it is found that the Particle Swarm Optimization (PSO) based Support Vector Regressors (SVR) outperforms over other prediction models in terms of performance accuracy.
Application of Surface Electromyography based Pattern Recognition for Efficient Control of Upper Limb Prostheses
(National Institute of Technology Karnataka, Surathkal, 2020) Powar, Omkar S.; C, Krishnan C. M.
The main aim of the hand prostheses is to help people restore human hand functions using artificial limbs. Electromyogram (EMG) signals have been used as a control signal, and this control scheme is referred to as Myoelectric Control (MEC). The conventional prostheses use a proportional control scheme based on the amplitude of the EMG signal. However, these schemes cannot achieve more than two degrees of freedom. This limited functionality is the key reason for the rejection of prosthesis by the amputees. If additional degrees of freedom are required, then Pattern Recognition (PR) based MEC offers favorable control. This research work aims at improving the classification accuracy of surface EMG driven pattern recognition (PR) system. Many factors affect the classification efficiency of PR based MEC. Significant challenges and practical limitations need to be addressed before making the PR scheme commercially available. The goal is to tackle these problems and to provide a solution using novel strategies developed in this research work. Surface Electromyogram (sEMG) signals are contaminated with a wide variety of noise, and this causes problems in PR. Noise sources such as power-line interference, motion artifact, ambient noise, characteristic instability of the signal, and noise due to electronic and recording equipment could be present in the sEMG signal. Noises can be decreased but cannot be removed totally by using high-quality equipment and intelligent circuits. Conventional filtering methods are commonly used to remove noise. But, if the noise from the recording instrument lies in the usable frequency range, it becomes hard to eliminate noise using conventional filters. In the pre-processing of sEMG signals, the challenge lies in the suppression of noise associated with the measurement and signal conditioning. The first contribution of the thesis is overcoming this limitation by proposing a novel pre-processing method. The method differentiates the original sEMG from noise using higher order statistics such as kurtosis, which is the fourth moment of distribution. The effectiveness of the method is demonstrated in terms of the improvement in PR performance. A significant number of studies have been performed on the various stages iiiof sEMG-based PR. There have been problems during the clinical implementation of the system even though the previous studies have reported a high classification accuracy of more than 90%. PR has shown great promise in predefined settings in laboratory conditions. The real-time factors which affect the performance have to be taken into consideration for PR to be commercially available. There are various other factors that also affect the performance of the PR system, such as variation in limb position, variation in forearm orientation, variation in electrode position, variation in force level, and change in the characteristics of the sEMG signal. It is becoming crucial to test the PR with these various factors due to the difference between ideal laboratory conditions and practical application of the MEC prostheses. The second contribution of the thesis is to address the robustness aspect of the PR-based control by developing a novel classification scheme that can function well under such changing conditions. Specifically, the focus was given to variations in force levels and wrist orientations. The proposed scheme achieved a significant improvement in classification accuracy when compared to the traditional method. To demonstrate that this research can be translated to clinical applications, study has been conducted on sEMG data set of upper limb amputees. This distinguishes the study from most of the previous studies done on non-amputee subjects. The findings of this work could improve the quality of life of amputees with better interaction to the outer world.
Operation and Control of a Microgrid with Distributed Generation Systems
(National Institute of Technology Karnataka, Surathkal, 2020) D, Chethan Raj.; Gaonkar, Dattatraya N.
The energy has always played a crucial role in the development and progress of human society. People have long been aware of the drawbacks of traditional fossil energy, such as the limited resources, resulting in environmental pollution and other defects. However, due to the needs of social development and the constraints of backward technology, people have to use fossil energy as the main energy source. In recent years, with the rapid development of science and technology, how to effectively use renewable energy to generate electricity has become the focus of attention in many countries. Because of its unique advantages in the use of new energy, microgrids have received more and more research and development. The distributed power generation system based on microgrid technology is an important way to develop renewable energy, increase the reliability of power supply, and expand the capacity of the power supply system. The power supply of the distributed power system can be formed by a variety of energy sources through power conversion. The power supply units of the distributed power system are distributed and are all connected to the AC grid bus. The power supply unit of distributed generation micro-power system is generally a parallel inverter, and there are many parallel modes of inverter and the parallel mode of inverter power without interconnection line is especially suitable for distributed power generation system with grid-connected inverter. The ideal distributed generation microgrid system includes parallel DG inverter power modules, output line impedance, AC bus and loads connected to the AC bus. The DG inverter is the core of the distributed power generation system, which is responsible for transforming the distributed energy into electric energy and realizing the parallel network operation of the system.This thesis studies the droop controlled distributed generation inverters power decoupling and the restoration of frequency and voltage under resistive and inductive impedance microgrid environment. Summarized the research background, definition and characteristics of microgrid. Summarizes the existing control structure of the microgrid. The classification, comparison and analysis of control methods for power electronic converters,vi especially distributed generation inverters in microgrids are focused on. The topology of the distributed generation inverter main circuit and the filter circuit was chosen and filter parameters were designed. Then the mathematical model of distributed generation inverter in different coordinate were established. Since the output voltage strategy and output impedance of an distributed generation inverter always have an important influence on the DG inverter parallel system and power distribution. The instantaneous voltage closed-loop control in three-phase stationary coordinate and the inverter output voltage decoupling control strategy in dq rotating coordinate were analysized, in order to reduce variable numbers, while ensuring the DG inverter output voltage tracking with no difference to the reference voltage, the DG inverter output voltage control strategy based PI controller in dq coordinate is implemented and the influence of the controller parameters on closed-loop transfer function of output voltage and inverter equivalent output impedance were analysized. The droop control is widely employed when multiple distributed generation inverters operate in parallel. However, due to inconsistent line impedance and the local load, there exists power sharing errors when the droop control is adopted, thereby reducing the efficiency of the system. In addition, there is a coupling between the active power and reactive power with the direct droop control, which affects the stability of the system. Though the traditional power decoupling control is able to realize power decoupling, the actual real power and reactive power cannot be shared equally. To deal with the power sharing and power coupling problem, this chapter explicitly analyzes the causes of the power sharing error and power coupling with the direct droop control respectively, quantizes the power sharing error and the extent of power coupling and also gives the basic solution to reducing the power sharing error and solving the problem of power coupling. To solve the inaccurate power sharing problem of the direct droop control, virtual inductance is adopted. By adding the virtual inductance, can decouple the active and reactive power, but also achieve accurate power sharing. The simulation results verify the accuracy and effectiveness of the adopted control scheme. Using direct droop control, the active power and reactive power can be decoupled when the line impedance is mainly inductive. However, it is not applicable to the microgrid with low voltage when the line impedance is resistive. As a result, thevii active power and reactive power will be coupled and errors in preset ratio of power sharing will arise. Aiming at solving the problem about the inapplicability of direct droop control in low voltage micrigrid, this chapter implements reverse droop control. The influence of transmission impedance of distributed generation inverter to public load on power distribution, introduces virtual resistor and then uses reverse droop control strategy to distribute load in low voltage distributed power generation system. Analyzes the conditions that need to be met to accurately share the load according to the ratio of rated capacity for inverter power supply. In the actual distributed generation system, due to the distributed location of the distributed inverter power supply, the impedance of the line is uncertain and the traditional reverse droop control has certain limitations. The simulation model of DG inverter parallel operation is built under the matlab/simulink environment, the reverse droop control and the improved power allocation strategy using virtual resistance are simulated and compared, the correctness and validity of the adopted improved strategy are validated. The traditional centralized control method cannot solve the problem of the various modes of microgrid operation, for example, the probem of controlling the microgrid systems induced by hard to collect information signals and low controllable. But the distributed secondary control method based on direct and reverse droop control has obvious advantage to solve the problem of parallel connected DG inverters operation. Aiming at the problem of voltage and frequency differences caused by the direct and reverse droop control and considering the actual situation of inductive and resistive line impedance mismatch, this thesis proposes a distributed secondary control. The simulation verifies that the proposed distributed secondary control method can guarantee the voltage amplitude and frequency recovery.
Islanding Detection Using Computational Intelligence Techniques in a Smart Distribution Network
(National Institute of Technology Karnataka, Surathkal, 2020) Goud, M Santhosh Kumar.; Gaonkar, Dattatraya N.
Distributed generation (DG) offers solution to the ever increasing energy needs by generating the energy at the consumer end, in most cases by means of renewable energy sources. A microgrid with DGs will result in an enhanced performance in terms of continuity of the power supply for consumers. Microgrids may operate either in grid{connected or islanded mode. Islanding detection is one of the most important aspect of interconnecting a DG to the utility. Several islanding detection methods have been proposed over the years to improve the islanding detection in terms of detection time, accuracy. However, with the upcoming trends, such as smart grids, there is an imminent need for incorporating intelligence to the islanding detection methods. Also, it is important for the islanding detection methods to perform well at near zero power mismatch conditions and noisy conditions. This research work proposes islanding detection methods based on image classification techniques. Time{series data from point of common coupling is acquired and then converted to an image to enable this. A dataset for islanding detection based on several islanding and non{islanding events is created to be used in training and testing the machine learning and deep learning models. Three islanding detection methods are proposed in this research work. The first method is based on HOG feature extraction from the image and SVM classifier. The second method is based on transfer learning method. The third islanding detection method is based on custom designed CNN for islanding detection. In addition to islanding detection, a feature for early islanding detection is also proposed in this research work. Early islanding detection is proposed by monitoring the fault and normal conditions. Once a fault occurs, the time window between the operation of relay contacts and the opening of circuit breakers is utilized to detect the islanding event. All the methods are tested with the islanding dataset that is created which includes near zero power mismatch conditions and noisy data. The proposed methods demonstrate the potential of image classification techniques for islanding detection.
Design of Adaptive Robust Controllers for Renewable Energy Sources Integrated Smart Grid System
(National Institute of Technology Karnataka, Surathkal, 2020) G, Hemachandra.; Sharma, K Manjunatha.
Energy supply and consumption from conventional fossil fuel is seen as a factor to global warming and deterioration of the environment. It is essential to use clean, non-polluting and alternative energy sources. Wind energy conversion technologies have proved attractive and competitive in terms of conventional fossil energy technologies with increased demand for electricity. It may reduce the negative impacts of traditional energy sources on the environment and reducing dependency on fossil fuels. Because of its high efficiency, the wind energy system can be an alternative source of energy for the future. The most frequently used variable-speed wind turbine is to enhance energy capture at distinct wind speeds. Self-excitation, elevated efficiency, power density, a wide variety of velocity, certainty and full isolation of the PMSG from the power grid have rendered it preferable for various wind systems. In addition to the wind power system, photovoltaic (PV) system developments are heightened the need for injecting the PV power in to the grid. PV array is composed of series and parallel PV cell combinations to maintain the required current and voltage levels operate in centralized grid connected inverter. However, substantial power losses have been reported due to the imbalanced generation between PV panels, which is mainly due to partial shading. Fuel cell (FC) act as continuous power source to mitigate the intermittent nature of PV and wind system. FC’s are clean and high efficient independent power generating source with zero emissions. Investigation of the performance of robust and non-linear controllers under varying wind speed scenarios is explored as a preliminary study. It is discovered that automated robust controller design is essential for the renewable power systems applications. Proposed research work intends to address the maximum power tracking issue for the autonomous wind power system and grid connected PMSG based wind energy conversion system, sub-module level PV system, and fuel cell. Genetic algorithm is used to design a new robust Quantitative Feedback Theory (QFT) controller based on automatic loop shaping methodology. The outcome of research work iiiis to extract the maximum power from hybrid renewable energy sources with automated robust QFT control strategy.
Investigations on Power Flow Control and Power Quality Improvement in Renewable Energy Sources Integrated Smart Grid
(National Institute of Technology Karnataka, Surathkal, 2020) C, Nagaraj.; Sharma, K Manjunatha.
Due to the growth of population along with suburban and urban industrials, the demand for power is growing day-by-day. As the power consumption rate is high, the supply from fossil fuels is not enough to meet consumer demand. Further, the depletion of fossil fuels and environmental concern forces the extraction of power from low carbon fuels causes generation problems due to its uncertainty and intermittent nature. So, low carbon fuels such as wind, solar, etc. can therefore, be incorporated into a more efficient hybrid system. This research work proposes a hybrid system configurations are the AC coupled micro-grid, DC coupled micro-grid, and the AC-DC coupled microgrid. However, a significant amount of non-linear power electronic loads in the system causes power quality problems. These issues have to be addressed adequately by developing an appropriate SAPF based bi-directional control methods. Firstly, the most implemented hybrid system around the globe is the AC coupled micro-grid. In this system, hybrid renewable energy sources or distributed generation are connected to the main-grid through individual DC-AC converters. This system is reliable because if any one of the DCAC converters fails, the other DC-AC converter can supply power to the loads. But, the control algorithm is very complex, and also there is a need for synchronization with the main-grid. Secondly, nowadays, more and more DC loads like LED lights are connected to the AC distribution system, which increases power quality problems and power conversion stages. These issues are taken into consideration by the DC coupled hybrid micro-grid system. This system is simpler because there is no reactive power control. Further, there is no need for synchronization to integrate renewable energy sources or distributed generations with the main-grid. However, this topology needs to restructure the current distribution system, and consequently, the cost increases drastically. Also, the DC protection system is more challenging than the AC protection system. iLastly, based on the benefits of the individual AC and DC coupled hybrid micro-grid systems, an AC-DC coupled hybrid micro-grid system is proposed in this research work. It consists of AC renewable energy sources, and the AC loads are connected to the AC bus, whereas the DC renewable energy sources and DC loads are connected to the DC bus, thereby reducing the power conversion stages. Further, the power conversion loss calculation is also discussed by compared with the AC-DC coupled hybrid micro-grid system over individual AC and DC coupled hybrid micro-grid systems. The shunt active power filter based 3φ 4-leg DC-AC bi-directional intermediate converter using d-q load current control without a phase-locked loop is proposed to achieve the inverter-based and rectifier-based power flow between the AC and DC bus with acceptable power quality as per IEEE 519 standards at a common connecting point. The hysteresis based current control is used to compare the actual current with a reference current to generate switching pulses to drive the bi-directional intermediate converter. The MATLAB simulation is carried out, and the performance of the proposed system is analyzed using the d-q load current control based fuzzy logic and PI controller. To validate the proposed control technique, different case studies are performed by considering balanced and unbalanced grid and load conditions with variation in renewable energy sources. The observed results demonstrate that the overall system performance improves with the d-q load current control based fuzzy logic controller.
Enhanced control of Photovoltaic Power Converters under Mismatching Conditions
(National Institute of Technology Karnataka, Surathkal, 2019) Ramana, Vanjari Venkata.; Venkatesaperumal, B.
Exhausting fossil fuel, a huge increase in oil prices, global warming, damage to environment, increasing energy demand are major problems being faced. In order to avoid these problems, power generation is being done using renewable energy sources. Among the renewable energy sources, solar photovoltaic (PV) is dominant because of long operational life, lesser emission, decreasing cost of solar photovoltaic panels. Photovoltaic sources exhibit unique maximum power point under uniform conditions. Under mismatching conditions, there will be multiple peak points because of the presence of bypass diodes. Maximum power point tracking algorithm is used to track the maximum power from the PV source. This thesis presents a literature review of maximum power point tracking (MPPT) algorithms for tracking the global peak. The methodology employed for tracking maximum power point is classified as empirical methods, perturbation methods, model-based methods, artificial intelligence methods, evolutionary computing methods, scanning-based methods, and modified perturbation methods. Based on the literature survey, research gaps are identified and are presented as objectives for this thesis. Four maximum power point tracking algorithms capable of tracking global peak under mismatching conditions are proposed. The first algorithm is based on searching technique and bisection method in which zone wise division of characteristics is performed based on open circuit voltage and panel characteristics. It is a duty ratio based control method and the value of duty ratio is calculated based on bisection method until the global peak is detected. Once the global peak is detected, conventional perturb and observe method is used to retain the operating point at GP. The second algorithm is based on current control in which reference current is moved in the forward and backward direction by multiplying or dividing PV current with 0.9. The movement of PV current is continued in the backward direction until the operating voltage is less than minimum voltage below which there is no chance of occurrence of global peak. After that, the perturbation of PV current is continued in the forward direction until the operating current is less than minimum current below iiiwhich there is no chance of occurrence of global peak. During the process of perturbation, the maximum power point is identified and a conventional algorithm is used to retain the operating point at that point. The third algorithm uses reference voltage control and reference current control to track the global peak. The choice to use voltage or current control is made using a decision variable. The algorithm operates in the current control mode to find the nearest peak and operates in voltage control mode to identify the inflection point. Initially, the voltage below which there is no chance of occurrence of the global peak is identified and it is initialized as the reference voltage. Then the succeeding peak is identified using reference current control. Once the peak is determined, reference voltage control is used to identify the inflection point. This process is continued until the operating PV current is less than the minimum possible current. The fourth algorithm tracks the global peak by sampling variations in the transient period during charging of the input capacitor. The algorithm operates in three stages viz., scanning, correcting and retaining the operating point at MPP. In the scanning stage, the maximum power and voltage at maximum power are identified by changing the value of duty ratio from maximum to minimum value. The correcting stages bring the operating point close to the voltage at maximum power point by varying the duty ratio and retaining stage maintains the operating point at MPP. The simulation studies of all the four MPPT algorithms are performed in MATLAB. All the methods are compared with recent existing MPPT methods in the literature. Hardware implementation is performed using solar array simulator, the boost converter, and resistive load.
Investigation on Multi-cell and Hybrid Multilevel Inverters with Minimum Number of DC sources
(National Institute of Technology Karnataka, Surathkal, 2019) Venkataramanaiah J.; Suresh, Y.
From the energy saving perspective, it is essential to adopt highly efficient DC to AC conversion (inverter) system for high power and medium voltage applications. Indeed the conventional two-level inverters cannot handle high power system unless series/parallel arrangements of semiconductor switching devices are used. However, these reformations have severe problems such as misfiring the gating pulses, voltage unbalances between the series connected devices and so on. Again to get rid of these problems, large snubber capacitors and resistors (passive elements) are connected to each switch for compensating transient voltages and static charge balance. Nevertheless, these passive elements cause a higher switching loss and relatively long switching time. On the other hand, total harmonic distortion of the output voltage waveform of traditional two-level inverters is one of the severe problems as the power ratings of the devices goes high. In this critical situation, the multi-level inverters (MLIs) are successfully introduced to overcome all the issues as mentioned earlier for medium and high power applications. Ever since the inception of MLIs, cascaded H-bridge (CHB), neutral point clamped (NPC) and flying capacitor converters are among the earliest topologies that are deemed to be well-established. Each of them has advantages and disadvantages. An NPC-MLI requires additional clamping diodes for its extension whereas, CHB-MLI and flying capacitor MLI needs many isolated DC sources to generate a multistep output and multiple capacitors respectively. Since then, many derivatives and refinements to these classic topologies have been proposed. The motivation for this research work stems out from the demand to generate a substantial number of voltage levels while keeping the device count as low as possible. Therefore, by taking advantage of the basic MLI configurations, a few schemes emanating as a result of combining two or more MLIs in part or fully, referred to as hybrid MLIs are proposed. The offered solutions exhibit considerable topological improvements with reduced control complexity. In the present thesis, we have mainly concentrated on designing a novel hybrid multilevel inverter which can provide an inbuilt isolation for gridiiiconnected, FACTS devices and standalone applications. This MLI can attain nineteen level output waveform with only 12 semiconductor switches. Moreover, it can be extended to n number levels where the switch count is further reduced enormously. In addition to that, a new PWM switching technique is introduced to refine the harmonic profile of the proposed MLI’output voltage waveform. The new PWM can efficiently operate at a very low switching frequency. Thereby, the switching losses of the proposed configuration are minimised drastically. Later, we have kept consistent efforts to derive a new power circuit from our first proposed configuration. Herein the device count is further reduced from 12 to 10 switches to produce the same nineteen level output waveform. In addition to that, an innovative controlling approach is implemented which is a simple fundamental switching strategy so-called ‘FSQS’technique. Moreover, the switching technique can achieve the least harmonic distorted output voltage waveform, and it can be applied to any topology and ‘n’number of output levels. On the other hand, motor drive applications always prefer the efficient MLIs without any transformer involvement in their structures. In fact, most of the power drives are still running with traditional MLIs where the part count is a significant limitation. Thereby we designed a new MLI topology which can attain the modularity with less circuit complexity. It has been named as a multi-cell MLI where the power cell is built asymmetrically. In fact, the part count of the proposed configuration is an appreciable rate compared to the traditional and recent MLIs for the equivalent level generations. In the end, the thesis is devoted to design three unique configurations and two new modulation techniques to address the full range of MLI applications. All developed configurations and schemes are simulated extensively in MATLAB/Simulink. After that, the topologies are verified experimentally by advanced DSP controller and OPAL-RT (Real Time) Simulator on a prototype setup for recording the corresponding output voltage, current, and the THD results
Grid Connection of Wind-Solar Hybrid Renewable Energy System, with Active Power Filter Functionality
(National Institute of Technology Karnataka, Surathkal, 2019) Jayasankar, V. N.; Vinatha, U.
The incorporation of the abundantly available wind and solar energy to the grid using power electronic converter based interfaces makes a reliable hybrid renewable energy system. Assigning harmonic mitigation property to the grid interfacing inverter to mitigate the current harmonics created by the non-linear loads at the load centres, is a cost-effective solution. The inverter controller consists of an outer DC-link voltage control loop and an inner current harmonic mitigation loop. The limitations of existing DC-link voltage controllers are poor stability margin, steady-state error and chattering problem. The widely used pq theory based inner loop controller offers poor performance under non-ideal grid voltage conditions. The conventional low pass filter based fundamental component extraction methods used in pq theory possess some limitations such as additional time delays and low-frequency oscillations. The main focus of this research is the design, simulation, implementation and analysis of a grid-tied wind-solar hybrid renewable energy system with shunt and series active filtering functionalities, under different system conditions. A Backstepping controller based outer loop, with enhanced DC-link loss compensation capability is proposed for the shunt active filter to overcome the limitations of the existing DC-link voltage controllers. The limitations of conventional low pass filter based fundamental component extraction methods are overcome by employing a self-tuning filter in the inner loop of the shunt active filter. An additional self-tuning filter is incorporated to improve the effectiveness of pq theory under non-ideal grid conditions. A self-tuning filter and a Fuzzy logic-based voltage controller are employed to control the series active filter effectively. A laboratory prototype of the shunt active power filter is implemented. The control algorithm is realised in Xilinx Basys-3 FPGA. From the simulation and hardware test results under steady-state and dynamic conditions, it is found that the proposed controller offers better stability, robustness and speed compared to other existing control methods.

2. Thesis and Dissertations

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