Juri Jatskevich
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Dissertations completed in 2010 or later are listed below. Please note that there is a 6-12 month delay to add the latest dissertations.
No abstract available.
The ac–ac and ac–dc line-commutated converters are widely used in various high-power applications due to their high reliability and efficiency and low cost. Efficient and accurate computer simulations are necessary to analyze various aspects of power systems in both normal and unbalanced/faulty conditions where using detailed switching models of converters is computationally expensive due to switching. As an alternative, for system-level studies, the so-called parametric average-value modeling (PAVM) technique has been developed to achieve computationally efficient models of power-electronic converters that neglect the switching and capture the averaged dynamics of converters only. In this thesis, the PAVM methodology is extended to three-phase ac–ac class of converter systems. Furthermore, a generalized PAVM (GPAVM) is proposed for ac–dc converters that includes the ac harmonics in thyristor-controlled rectifier models considering their dependency on the line frequency. It is shown that any existing PAVM can be realized as a subset of the proposed GPAVM. Then, the PAVM methodology is extended to rectifiers with internal faults. The new formulation considers the asymmetrical operation of rectifiers by including the ac-side harmonics in both positive and negative sequences as well as dc components that may be present on ac variables. Finally, a new parametric methodology is presented that can provide continuous–detailed models of rectifiers which can also reconstruct the switching details similar to discrete–switching–detailed models. However, the proposed parametric–detailed model is continuous and can be simulated with much larger time-steps. Moreover, the new model can be easily converted to a PAVM by disabling the reconstruction of dc details/switching. All the models in this dissertation are verified by extensive experimental measurements and computer studies using detailed models of the subject converters. It is demonstrated that all the proposed new models have excellent accuracy over a wide range of operating conditions while being computationally much faster than the corresponding detailed switching models. It is envisioned that the models and methodologies proposed in this dissertation will receive wide acceptance in the research community and simulation software industry, and will enable the next generation of power systems simulation tools.
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Modern power systems, from continent-spanning networks down to isolated microgrids, are experiencing unprecedented technological changes with broader use of direct current (dc) in addition to traditional alternating current (ac). Such integrated ac-dc power systems present notable challenges in all aspects of design, analysis, control, and operation, where extensive computer simulations play the essential and enabling role. Due to the use of diverse types of signal representation and component formulation, state-of-the-art power system simulation tools are limited to their distinct time scales of transient phenomena. This thesis considers the dynamic phasor (DP) type modelling approaches, where two types of DP theories, namely the shifted-frequency analysis (SFA) and the generalized averaging method (GAM), are considered. In DP-type simulations, power systems are modelled using analogous low-pass time-phasor signals, thereby offering flexible selection of time-step sizes and superior combination of numerical accuracy and efficiency.The ultimate goal of this research is to increase the numerical efficiency of DP-type simulations for the integrated ac-dc power systems. This is achieved by proposing several new DP component models with desirable features and improved numerical properties. First, the constant-parameter SFA model of synchronous machines is proposed to avoid numerically-costly recalculations of the time-varying stator-network matrices. This model is then extended to induction machines for modelling in state-variable based (SV-based) simulation tools. Next, we propose a new, highly efficient model of line-commutated rectifiers using a parametric DP formulation, which is demonstrated as valid for various system operating conditions. Moreover, the effect of ac side harmonics is incorporated to improve modelling fidelity. Finally, the interface between SFA- and GAM-type DPs is achieved to interconnect the proposed DP models. Rigorous case studies demonstrate the superior numerical efficiency of the proposed models, and their advantageous accuracy in capturing the desired phenomena of ac-dc power systems. It is envisioned that the proposed models will become highly useful to many researchers and engineers worldwide, and facilitate the development of next-generation power system simulation tools.
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With rapid increase in complexity of modern power systems, there is a strong need for better computational tools to ensure the reliable operation of electrical grids. These tools need to be accurate, computationally efficient, and capable of using advanced measurement devices. In this context, transient stability assessment (TSA) is an important study that determines system’s dynamic security margins following a major disturbance. The TSA consists of a set of differential-algebraic equations (DAEs), which are typically solved using time-domain simulation (TDS) approach. While being very accurate, the TDS requires significant computational resources when applied to practical power systems. This problem becomes more significant in transient stability monitoring (TSM), wherein the computational performance of the TDS is typically the bottleneck. This research is to investigate available challenges in the TSM applications and develop new algorithms to help realizing a practical monitoring tool for transient stability studies. The thesis focuses on three research thrusts: i) dynamic reduction of power system to reduce problem size; ii) advanced computation approaches to expedite the TDS method; iii) integration of PMU measurements into the TSM. Initially, a new adaptive aggregation algorithm for dynamic reduction is proposed, wherein parameters of generators and structure of transmission network are considered to aggregate coherent generators and create a reduced-order system. Also, a new criterion is defined to monitor validity of the constructed reduced system. It is shown that the proposed technique is more accurate than traditional aggregation methods. To expedite the TDS approach, this thesis presents two new integration techniques, which are called Multi-Decomposition Approach (MDA) and Successive Linearization and Integration Technique (SLIT). In these methods, the nonlinear DAEs are decomposed into a series of linear subsystems, which participate in approximating actual solution. It is demonstrated that sequential and parallel versions of the MDA and SLIT are faster than state-of-the-art integration techniques. Finally, a dynamic state estimator based on Extended Kalman Filter is developed to convert the PMU measurements into a set of state variables suitable for transient stability studies. Computer studies show that the proposed framework provides accurate results in highly disturbed power systems with fairly low PMU sampling rates.
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State estimation is the heart of many tools used in operations of distribution and transmission power systems. The quality of distribution systems state estimation (DSSE) typically suffers from a lack of adequate/accurate measurements and has not been fully implemented by many utilities. Recently, as part of many smart grid related initiatives to modernize power systems, electric utilities started to invest in advanced metering infrastructure (AMI) throughout their distribution systems. The main challenge in this area is that AMI measurements are generally not synchronized, and the difference between the measuring times of smart meters can be significant. In generation and transmission systems, the transmission system state estimation (TSSE) is already prevalent in many utilities. However, TSSE typically suffers from four major problems: partial unobservability, numerical ill-conditioning, bad data, and low accuracy. This thesis is based on three contributions. Firstly, an innovative method is developed to incorporate the non-synchronized measurements coming from AMI based on the credibility of each available measurement and appropriately adjusting the statistical property of the measurement signals. To illustrate the effectiveness of the proposed method, it is compared with traditional approach used in DSSE and the results show the improvements in the accuracy of DSSE. Next, based on the interconnection of the transmission system and distribution systems at PQ buses (feeder heads), a novel approach in TSSE method is presented which uses the DSSE results to provide additional measurements at the PQ buses of the transmission system. Comparisons between the traditional TSSE and the proposed TSSE show that significant improvements are achieved. The third contribution is the methodology for identification of electricity theft points in distribution systems without violating privacy of consumers. The proposed approach models theft as bad data and consists of two stages. Firstly, the multiple bad data identification problem is solved using a heuristic optimization method to locate the points of theft which have redundant measurements. In the second stage, regarding identification of theft points which do not have redundant measurements, a method is proposed based on the discrepancies between the measured and estimated voltage magnitudes. Simulations results demonstrate the effectiveness of the proposed approach.
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Extensive computer simulations are necessary to operate power systems in a stable, secure, and optimal manner. This thesis considers electromagnetic transients (EMT) simulators, which are widely used to study modern power systems of which rotating machines are essential components. In EMT simulations, induction and synchronous machines are usually represented by general-purpose lumped-parameter models, which can be formulated using different sets of coordinates and state variables. While algebraically equivalent, these models’ numerical properties can differ greatly, which in turn can significantly affect the numerical accuracy and efficiency of entire EMT simulations. The ultimate goal of this thesis is to increase the numerical efficiency of EMT simulators without degrading their numerical accuracy and stability. This is achieved by proposing several new machine models with improved numerical properties. Models are presented for both families of EMT simulators, namely nodal-analysis-based (EMTP-type) and state-variable-based (SVB) programs. Moreover, we incorporate the effect of saturation to improve modeling fidelity. This thesis makes several important contributions to the state of the art. As a first step, the implicit flux correction (FC) method frequently used in SVB programs is reformulated to achieve explicit qd models with main flux saturation. Next, we propose new highly efficient saturable SVB voltage-behind-reactance (VBR) machine models with constant-parameter interfacing circuits. A new and accurate EMTP-type VBR induction machine model with a saturation-independent interfacing circuit is then proposed, thereby avoiding numerically costly re-factorizations of the network’s conductance matrix. Finally, the numerical efficiency of this VBR model is further improved by using multirate techniques. Numerous case studies demonstrate the superior combination of numerical accuracy and efficiency of the proposed models, and their beneficial impact on the speed of EMT simulations. It is envisioned that the proposed models will eventually be included in commercial EMT programs, extending their reach to thousands of engineers worldwide.
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Transient simulation programs are used extensively for modeling and simulation of various electrical power and energy systems that include rotating alternating current machines as generators and motors. In simulation programs, traditionally, the machine models are expressed in qd-coordinates (rotational reference frame) and transformed variables, and the power networks are modeled in abc-phase coordinates (physical variables), which represents an interfacing problem. It has been shown in the literature that the method of interfacing machine models and the electric network models plays an important role in numerical accuracy and computational performance of the overall simulation. This research considers the state-variable-based simulation programs and proposes a unified constant-parameter decoupled RL-branch circuit in abc-phase coordinates (with optional zero-sequence). The proposed circuits are based on voltage-behind-reactance (VBR) formulation and can be used for interfacing both induction and synchronous machine models. The new models achieve a direct and explicit interface with arbitrary external electrical networks, which results in many computational advantages. Extensive computer studies are presented to verify the proposed models and to demonstrate their implementation in several commonly-used simulation programs. The new models are shown to offer significant improvements in accuracy and numerical efficiency over the existing state-of-the-art models due to their direct interface. It is further envisioned that the proposed models will receive a wide acceptance in research community and simulation software industry, and may enable the next generation of power systems simulation tools.
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High power switching converters such as line-commutated converters (LCC) and high voltage direct current (HVDC) systems are widely used in modern energy grids for interconnection of industrial loads, large motor drives, as well as electronically-interfaced renewable/alternative/distributed energy resources (DER) and storage systems. For design and analysis of systems with power-electronic-based DERs and loads, accurate and efficient computer models are essential. This thesis is focused on dynamic average-value models (AVM) that neglect switching of converter circuits and are established by averaging the variables (currents and voltages) over a prototypical switching interval. The AVMs are continuous (free of switching), allow using larger integration time steps, and typically run much faster than the conventional detailed switching models, which makes them particularly useful for the system-level studies. This thesis considers the parametric AVM framework, and extends this approach to the thyristor-controlled LCCs operating in inverter mode with current source or voltage source control. The proposed modeling methodology is demonstrated on various topologies including the HVDC CIGRE benchmark system. The research is further extended to incorporate the ac side harmonics into the AVM using the multiple reference frame theory. Traditionally, the AVMs are developed using state-variable-based approach. This thesis also presents a new parametric AVM for direct interfacing in nodal-analysis-based electromagnetic transient programs (EMTP), e.g., PSCAD/EMTDC, EMTP-RV, and MicroTran. It is expected that the proposed models and interfacing approaches will find their application in widely used transient simulation tools and will be appreciated by many researchers and practicing engineers worldwide.
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Power electronic converters are used in a wide range of applications as well as being the enabling technology for interfacing the alternative energy resources and many loads in modern power systems. The methodology of developing the so-called dynamic average-value models (AVMs) for such converters is based on averaging the variables (currents and voltages) within a switching interval resulting in numerically efficient models that are much more suitable than the detailed switching models for system-level studies as well as numerical linearization and the respective small-signal analysis. However, the AVMs available in the literature for line-commutated converters have several limitations such as neglecting the effects of losses, being only valid in certain operational modes and under balanced excitation, as well as employing a simplified representation of the multi-phase transformer in high-pulse-count converters. Moreover, a unified AVM methodology for high-pulse-count converters has not yet been established.In this thesis, a generalized AVM methodology is developed for voltage-source- and rotating-machine-fed multi-pulse line-commutated converters for both classes of transient simulation software packages, i.e., state-variable-based and nodal-analysis-based electromagnetic transient program (EMTP) type. The previously-developed AVM approaches, i.e., analytical and parametric, are extended to the EMTP-type programs, and the indirect and direct methods of interfacing the models with external circuit-network are introduced and compared. For the machine-converter systems, the effects of machine and bridge losses are taken into account in the new AVM. Finally, a generalized dynamic AVM methodology is developed for high-pulse-count converters based on the parametric approach. An effective multi-phase transformer model is developed in transformed (qd0) and phase (abc) variables. An efficient transformer model is also developed, which accurately represents the multi-phase transformer using an equivalent three-phase formulation. The proposed generalized AVM remains valid for all operational modes under balanced and unbalanced excitation. This model is employed for AVM implementation in state-variable-based and EMTP-type programs. Extensive simulation and experimental studies are carried out on several example systems in order to compare the developed AVMs against the detailed and previously-developed average models in time- and frequency-domains. The results demonstrate the great accuracy of the proposed AVMs and a significant improvement compared to the previously-developed models.
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Modeling of electrical machines for power system’s electromagnetic transient programs (EMTP) has been an active area of research since the late 1970s. Most machine models are based on the qd reference frame. The phase-domain (PD) model was also proposed wherein the direct interface with the external network is achieved at a price of increased the computational cost. This thesis focuses on improving the numerical efficiency and accuracy of machine models for power systems transient simulation. The modeling approach developed in this thesis is based on the so-called voltage-behind-reactance (VBR) formulation. The new VBR models of synchronous and induction machines are proposed for EMTP-type solution. It is shown that the proposed VBR models significantly improve the overall numerical accuracy and efficiency, compared with the traditional qd and PD models, due to the direct machine-network interface and better-scaled eigenvalues. The proposed model implementations require as little as 240 flops for synchronous and 108 flops for induction machines, per time-step, respectively. This amounts to 3.75 microseconds and 1.6 microseconds (per time-step) of the CPU time on a modest personal computer and represents a significant improvement over existing EMTP machine models. Magnetic saturation has been incorporated into the VBR models for EMTP-type solution. Computer studies demonstrate that the proposed saturable VBR model in addition of being very efficient also preserves good numerical accuracy and stability even at very large time step. A new full-order VBR induction machine model is also proposed for state-variable simulation languages. Computer studies demonstrate that the proposed models achieve a 740% improvement in computational efficiency as compared with the coupled-circuit models used in state-variable simulation languages. Finally, an approximate VBR induction machine model is proposed for the discretized EMTP solution wherein a constant equivalent conductance matrix is achieved. This further improves the efficiency of the machine-network solution since it avoids the re-factorization of the network conductance matrix at every time step. It is envisioned by the author that due to structural and numerical advantages, the proposed VBR models will find wide application in simulation packages and tools widely used in the power industry.
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Master's Student Supervision
Theses completed in 2010 or later are listed below. Please note that there is a 6-12 month delay to add the latest theses.
In today’s wider adaptation of renewable energy resources, computer simulations and power system transient studies play a vital and enabling role. For conducting the power system studies, the nodal-analysis-based electromagnetic transient program (EMT or EMTP)-type simulators have been widely accepted and used by researchers and engineers as the industry standard tools, wherein the synchronous machines are commonly represented by the general-purpose lumped-parameter models. The traditional machine models are expressed in qd0 coordinates, which represents a challenge when interfacing with external networks that are represented in abc physical variables and coordinates, often making the machine models the computational bottleneck of computer simulations. This thesis advances the state-of-the-art and develops computationally-efficient and accurate models of synchronous machines for EMTP-type solutions. To enhance the modelling fidelity, the main flux magnetic saturation is considered. Two groups of models are proposed based on voltage-behind-reactance (VBR) and phase-domain (PD) methodologies, respectively. The previously established models of this type possess rotor-position- and saturation-dependent interfacing circuit, which requires costly refactorization of the entire network conductance matrix at each time step. The new VBR and PD models are proposed that have a constant interfacing conductance matrix. Extensive computer studies demonstrate the superiority of the proposed models in terms of computational efficiency compared to other state-of-the-art models. It is envisioned that the new models will become adopted by many standard offline and real-time EMTP simulators.
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This research focuses on two promising control strategies for integrating power-electronic-based renewable energy generation into power grids. The first strategy involves controlling the power-electronic converters as virtual synchronous generators (VSGs) to emulate the classic synchronous generators (SGs) with their droop characteristic, inertia and damping to regulate dynamic response. The second strategy is the virtual oscillator (VO) based controller, which governs power-electronic converters to mimic the conventional droop characteristic while automatically synchronizing with the grid without a traditional phase-locked loop (PLL). In both control schemes, the droop characteristic refers to the output power of the converter responding to frequency disturbances on the grid. However, most converter-interfaced renewable energy resources typically operate in maximum power point tracking (MPPT) mode for economic reasons. Thus, new control strategies with external control loops that allow the energy resource to smoothly restore its power dispatch level after a frequency disturbance are proposed for the VSG- and the VO-based distributed energy resources (DERs). The proposed modified droop controller for VSGs can regulate the converter frequency after disturbances for maximum power harnessing. For VO-based DERs, two modified controllers are proposed: one with an external power-control loop to regulate the commanded power reference; and the other with an outer frequency-control loop to update the natural frequency of the VO. The proposed methods are evaluated through simulation studies in MATLAB/Simulink. It is demonstrated that the proposed controllers improve the capability of the VSGs and VOs and enable a smooth transition between the droop behaviour and the MPPT mode after a frequency disturbance in the grid. This research highlights the potential of proposed control strategies for integrating renewable energy generation into power grids.
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Variable frequency drives (VFDs) of low- and high-power levels are widely utilized in many commercial, industrial, vehicular, and propulsion applications, wherein typically, a squirrel-cage induction motor is fed from an inverter through a cable. To design and tune such systems, it is essential to develop efficient, accurate models of induction machines for studying the motor-converter interactions and low-to-high frequency phenomena. Depending on the required fidelity level, study objectives, and frequency range of interest, several classes of models of induction machines have been proposed in the literature, which can be generally classified into low-frequency and high-frequency models. Moreover, the motor-converter systems are typically the computational bottleneck in electromagnetic transient (EMT) simulators that are used in the power industry. It is desirable to have an induction machine model capable of capturing all transient phenomena in the range from dc to 10 MHz and can be effectively used for the analysis of VFD systems. This thesis is focused on advancing the state-of-the-art induction machine and VFD modelling in state-variable-based (SVB) EMT programs. Specifically, this thesis presents an efficient modelling approach for system-level studies of VFDs, a reconfigurable star-delta CPVBR model for studying star-delta starting transients in motors, and a wideband decoupled constant-parameter VBR model capable of studying motor-converter interactions in the range from dc to 10 MHz. Computer simulations and experimental studies of the VFD systems demonstrate that the proposed models represent advantages over existing/conventional models. It is also envisioned that proposed models will become a valuable asset for offline and real-time EMT simulators that are used for transient studies of machine-converter interactions in marine power systems, mining and oil drilling sites, and other applications with VFD systems.
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Hall-sensor-controlled brushless dc (BLDC) motors are widely used in many electromechanical applications due to their simplicity, low cost, and good torque-speed characteristics. The conventional commutation methods include the 120-degree and 180-degree switching logics. For these commutation methods, the maximum torque per Ampere (MTPA) and maximum torque per Voltage (MTPV) control schemes are often considered to achieve the optimal properties. Previously, many analytical and numerical implementations of MTPA and MTPV have been developed and widely applied. However, the common limitations such as deviation from the optimal operation due to machine parameters and high computational cost of controllers necessitate further research and improvements. In this thesis, three simple and novel control schemes have been proposed. Firstly, a hybrid MTPA/MTPV method is proposed based on the equations of 180-degree operation to combine the advantages of both methods. This hybrid method is shown to achieve high efficiency in steady state and fast response during electromechanical transients. Secondly, a numerical implementation of the MTPA and MTPV strategies has been developed for BLDC motors with 120-degree commutation to achieve better torque-speed characteristics compared with the conventional implementations. Thirdly, the switching logic has been extended to cover any conduction angle between 120 and 180 degrees while maintaining the MTPA optimal property. This proposed method is demonstrated to achieve up to 10% higher maximum achievable phase voltage than the conventional 120-degree operation from the same dc source voltage. Since the new methods are simple and computationally efficient, it is envisioned that they may be easily adopted in many applications utilizing Hall-sensor controlled BLDC motors where higher efficiency and faster transient response are desirable.
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Microgrids are envisioned as building blocks of evolving power systems, where they have a potential for improved resiliency, higher energy efficiency, and integration of renewable resources on a smaller scale. At the same time, the increased complexity of integrating new and distributed energy resources (DERs) presents several control-related challenges for the safe and optimal operation of AC microgrids. The new challenges also include the increasing number of power-electronically interfaced loads and sources that behave as constant power loads (CPLs) or constant power sources (CPS), and are known to have destabilizing effect on the system. All of this necessitates research for better analysis tools, control schemes, and technological solutions that ensure proper coordination of all components within a microgrid. To improve the operation of envisioned AC microgrids, this thesis proposes an economical hierarchical control scheme that incorporates control levels with different dynamics. This scheme not only ensures proper voltage and frequency regulation and power sharing among different resources, but it also minimizes the operational costs considering the price of available energy resources. At the next level, this thesis investigates dynamic interactions between the DERs and CPLs within a microgrid. A recently proposed virtual oscillator controlled source (VOS) is investigated and compared against the traditional/generic control used with DERs. It is demonstrated that impedance-based analysis can accurately predict the instability and sideband oscillations resulted from the interaction with the CPL, as well as used to tune the controllers. It is also shown that while the VOS has a faster dynamic response, its stability boundaries may actually be smaller. It is envisioned that the presented research will contribute to the development of AC microgrids with high penetration of renewables, energy storage systems, as well as various types of electronic loads.
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An essential component in modern DC systems is the bus-forming boost converter. However, voltage regulation of the boost converter in continuous conduction mode using traditional linear technique is not an easy task due to the system’s inherent right-half-plane zero, which often forces designers to settle with a controller that has narrow bandwidth and poor dynamic response in exchange for adequate stability margin. The effectiveness of linear controllers is further undermined by the nonlinearities of the system. To address these limitations, sliding-mode control, which is a nonlinear control method well-known for its intrinsic stability, robustness and fast response, has gained increased attention in its application to DC–DC boost converters.This thesis focuses on the theoretical analysis as well as the practical implementation of sliding-mode control for boost converters supplying constant impedance and constant power loads. The first part of this thesis reviews the conventional sliding-mode controller for boost converters with simple resistive load and identifies its drawback, whereupon an observer-based fixed-frequency sliding-mode controller is proposed to improve output response while keeping sensor count low. The second part of this thesis extends the basic framework of sliding-mode control to boost converters supplying both constant impedance and constant power loads. The nonlinear mixed-load system is analyzed rigorously, and an accurate closed-loop small-signal model is derived, giving insight into system dynamics and stability. The third part of this thesis utilizes the results from the analysis of the mixed-load system and proposes a new adaptive sliding-mode controller to improve system performance while guaranteeing stability. Simulation studies and experimental results are included to support the analysis and validate the proposed control strategies. The analytical approach presented here is sufficiently general that it may be applied to other converter typologies. The proposed control strategies provide new and beneficial alternatives for power electronic design engineers who are seeking fast, stable and robust control solutions.
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Many electronic loads in fast-developing power systems behave as constant-power loads (CPLs) which are known to exhibit negative incremental impedance and have a destabilizing effect in the system. To improve the stability of modern power systems with CPLs, research efforts have been focused on impedance-based and small-gain stability criterion, the design of advanced controllers, and passive or active damping solutions. Some disadvantages for most of the existing solutions include unnecessary energy losses in their passive elements, requirements of beforehand knowledge of the system characteristics, and inadaptability to the change in system operating conditions.This thesis presents new methods for stabilizing power systems with CPLs using tunable active damping based on an auxiliary converter circuit. Therein, the load bus voltage is monitored and an active damper is used to stabilize the system once an instability is detected. The methodologies are first developed in DC power systems and later extended for three-phase AC power systems as well. The proposed methodologies are less conservative than traditional methods and its damping characteristics are established “on-the-fly” in real-time to achieve effective stabilization under various CPLs and different operating conditions that may be unknown a priori. The proposed methodologies are verified under three different power systems: a simplified version of an aircraft power system with two sources, a 48/24 VDC telecom system consisting commercially available converters, and a three-phase AC power system. It has been shown that the proposed methodologies can detect instability and damp the unstable oscillations in all three systems when the CPL power level becomes high.
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Adaptive control is widely used in modern control systems to maintain optimal system performance when the plant parameters are unknown and/or varying with time. Various system identification methods have been developed to estimate the system parameters in real time, which allows a parameter-related adaptive controller to be accordingly calibrated under parameter variation conditions. In this thesis, two practical applications of online parameters estimation are introduced: one the online source impedance identification for self-stabilizing controller design in dc distribution systems; and the adaptive controller design in interior permanent magnet synchronous motor (IPMSM) drive systems. In dc distribution systems, the parameters of source impedances are crucial for load controller design to guarantee the stability of source-load interface. Since the source impedance may vary when the system configuration changes, the online impedance estimation is necessary for designing advanced self-stabilizing controllers with “plug-n-play” functionality. In this thesis, an innovative technique is proposed for parametric estimation of source impedance using the recursive extended least-squares (RELS) method in conjunction with impulse and pseudo-random binary sequence (PRBS) injections. Rigorous simulation studies demonstrate that the proposed technique yields direct results while providing advantages over traditional ac sweep and commonly used discrete Fourier transform (DFT) techniques. To further verify the feasibility of the proposed method in the real-time environment, the proposed online parameters estimator is implemented and validated on the Typhoon and Opal-RT hardware-in-the-loop (HIL) platform. Moreover, the proposed methodology is extended to parameter-estimation-based adaptive control to mitigate the impact of parameter variations on the maximum torque per ampere (MTPA) operation of IPMSM drive systems. Specifically, a parameter estimator that exploits the RELS algorithm is established to accurately estimate the main parameters of the machine in real time, which enables calibration of the optimal current vector angle that is critical in the MTPA operation of IPMSMs. Extensive simulation studies have been carried out to verify the effectiveness and robustness of the proposed strategy.
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Modelling and transient simulation of electric power systems and their components is enabling field of research much needed for planning, design, and operation of present and future evolving electrical grids and systems. The line-commutated-rectifiers (LCRs) are commonly used in integrated AC-DC energy conversion systems, where they are also known as the source of harmonics. Recently, a full-order parametric dynamic phasor (PDP) modelling methodology has been proposed in the literature for efficient transient simulation of the LCR systems including harmonics. Although this modelling approach is able to capture any desired number of harmonics, this increased accuracy also comes at an additional computational cost. The main objective of this thesis is to improve the numerical efficiency of transient simulation of the LCR systems with harmonics using the parametric dynamic phasor (PDP) modelling methodology. In this thesis, a reduced-order PDP model is proposed to reduce the computational cost and enable faster simulations. The fundamental DPs are represented by differential equations, while high-order DPs are represented by algebraic equations. Moreover, the harmonic ripples that may exist in the DC subsystem have also been incorporated to increase the modelling fidelity of the new approach. The superior performance of the new technique is validated on several examples of integrated AC/DC power systems (including three-phase transformer and synchronous machine). Rigorous case studies demonstrate that the reduced-order PDP model of integrated AC/DC systems is capable of accurately tracking the steady-state and transient responses, while providing higher numerical efficiency compared to the conventional detailed model and the prior established full-order PDP models.
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Common solutions to mitigating harmonics and improving power quality of power systems would include installing dedicated passive or active harmonic filters at the point of common coupling (PCC). However, as the complexity of energy systems increases with integration of renewables and storage systems on the one side, and the number of electronic loads increases rapidly on the other, the centralized compensation of harmonics may not be cost effective. At the same time, many modern loads and energy sources have high–bandwidth front–end power converters that present an opportunity for alternative solutions to improve power quality. This thesis presents a new methodology to compensate harmonics. Utilizing widely deployed smart meters, the measured information of harmonics can be transmitted in real time through the internet to smart electronic loads, where the loads can inject out–of–phase harmonics for compensation in a distributed fashion. First, this thesis investigates the feasibility of using smart meter measurements in the Fred Kaiser Building on the University of British Columbia (UBC) Vancouver campus, which are then used to demonstrate potential harmonic compensation using installed grid–tied converters. Next, since many modern single–phase electronic loads include a power factor correction (PFC) stage, this thesis develops a PFC controller algorithm to inject typical harmonics (i.e. 3rd, 5th, and 7th) at different levels and phase angles for compensation. This concept is further extended to smart LED drivers that also have a PFC stage, which are envisioned to have advanced power quality features. Such smart electronic loads and LED drivers can be integrated into future distribution systems of residential/commercial buildings, microgrids, etc., with distributed controls and communications through Internet of Things (IoT)/advanced user interfaces.
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Power system engineers use transient stability computer simulation programs tomodel the power grid’s behaviour when large disruptions cause the grid to deviatefrom its 60-Hz operating frequency. These programs must be able to capture thesefrequency dynamics around 60 Hz while being computationally efficient, as an extensive number of simulations are typically run for a given scenario. In the traditionalpower grid, the large mechanical inertia of the synchronous generators stabilizes thenetwork during disturbances and maintains the system frequency close to the 60 Hzoperating frequency. In the modern grid, however, the increase of renewable energysources lowers the grid’s inertia and larger frequency deviations can occur. Thephasor solution method employed in the traditional programs solves the networkassuming a constant 60-Hz frequency. When deviations from 60 Hz are prominent,the Electromagnetic Transients Program (EMTP) is used as an alternative to thephasor solution to capture these fluctuations. The EMTP models the electricalnetwork based on the differential equations of the network components, which allows the tracing of the network waveforms. However, this discretization requiressmall time-steps, which makes the solution method computationally expensive. TheShifted Frequency Analysis (SFA) method discussed in this work is an alternativeto the traditional phasor solution and to the EMTP solution. In this work, a generalized SFA-based program is written and used for transient stability analysis. SFAis a discrete-time solution method, like the EMTP, but uses a frequency-shiftingtransformation to bring the solution domain down to 0 Hz. Because of this transformation, SFA can capture network dynamics around 60 Hz using large time-steps,making it suitable for transient stability analysis studies.
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The wind power penetration has been increasing significantly, and this trend is likely to continue. As wind power penetration levels increase, interconnecting large-scale wind power plants (WPPs) into the existing power system has become a critical issue. Therefore, appropriate wind turbine generator models are required to conduct transient stability (TS) studies. While it is possible to construct detailed and accurate models of manufacturer-specific wind turbine generators in electromagnetic transient (EMT) simulators, such models are not suitable for large-scale transient stability studies due to their high computational complexity. The Western Electricity Coordinating Council (WECC) Renewable Energy Modeling Task Force (REMTF) is working towards developing generic wind turbine generator models that would be applicable for a range of general purpose system-level studies. However, such the generic models are typically over-simplified and not able to predict some of the phenomena, e.g. the unbalanced disturbance which is easily captured by the EMT simulations.In this research, a numerically-efficient model for the doubly-fed induction generator (DFIG) is developed that can predict steady state, balanced and unbalanced disturbances, and is sufficiently generic. The new DFIG model is based on the dynamic-phasor (DP) based machine models, which have been recently developed for the EMT simulators and can work with fairly large time-steps (up to several milliseconds) approaching that of the TS program solution. The WPP models have been implemented in MATLAB/Simulink® to assess the improved accuracy and computational efficiency. The new DP-based DFIG model is tested in a single machine infinite bus case and a two-area four-machine network to validate the model’s responses to balanced and unbalanced conditions of the grid. The accuracy of new DFIG model is shown to be significantly better compared to traditional TS models, which is achieved at a slightly increased computational cost.The result of this research will provide more accurate dynamic phasor based models of WPP for TS analysis. Since TS programs are widely used by utilities over the world, the new DP-based DFIG model will contribute to more reliable and accurate studies. This, in turn, will enable more reliable integration of large-scale WPPs into the existing and expanding power grids.
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The portion of high-bandwidth power converters in modern DC distribution systems has been increasing and is projected to dominate over time. These devices having fast response act as constant power loads (CPLs) and possess the so-called negative incremental input impedance characteristics at the input terminals, which may ultimately cause dynamic interactions and instability at certain interfaces in the system. Most existing approaches that address this problem use passive or active damping to reshape the source/load impedances so that stability may be achieved. The drawbacks of most existing methods include energy losses in passive components and/or requirement of changing the internal controls in existing loads.This thesis presents a new active damping methodology using an auxiliary converter circuit to stabilize DC distribution systems with CPLs. A simplified single frequency criterion is proposed for identifying the damping parameters. The proposed auxiliary converter circuit exchanges the energy between very strong power bus and a potentially unstable bus with CPLs, which requires very small injected damping current and achieves lossless damping (conserves the energy during transients). The methodology may operate by emulating fixed or operating-point-depended virtual RC values of the equivalent damping, with the latter having potential advantages of achieving faster damping.To verify and demonstrate the proposed concept, the auxiliary converter circuit has been designed and built with innovative compensated average current control mode. The experimental studies have been carried out on a reduced scale subsystem of a DC microgrid installed by Alpha Technologies Ltd., in Kaiser building at UBC. It is envisioned that the proposed active damping methodology using low-power auxiliary converter circuit may be very cost-effective and practical solution for the future DC systems with modular design and multiple sources/loads being constructed by different vendors with limited knowledge of their parameters and access to their internal controls.
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Detailed switching models are commonly used for analysis of power electronic converters, whereas the average-value modeling (AVM) provides an efficient way to study the power electronic systems in large and small signal sense. This thesis considers a dual-active-bridge (DAB) DC-DC converter, as this topology is very common in applications that require bi-directional power flow and galvanic isolation between the input (primary) and output (secondary) sides. Although this type of converter is very common, the available state-of-the-art models often relay on many assumptions and neglect the losses, which make such models inaccurate for studies where the converter efficiency and small- and large-signal responses must be predicted with high fidelity in system-level studies. We first present an improved detailed model of the DAB DC-DC converter by including the conduction loss, switching loss and core loss, which are derived based on the conventional phase shift modulation approach while considering the energy conservation principle. According to the proposed methodology, the equivalent resistances representing switching loss and core loss have been appropriately derived and added to the final simplified circuit model. The proposed approach is simple to use for modeling DAB converters when considering non-ideal circuit components. The new detailed model increases the accuracy in efficiency predictions over wide range of converter operating conditions.Furthermore, this thesis presents a new reduced-order AVM that includes the parasitic resistance and input/output filters. Based on the large-signal AVM, the small-signal model and control-to-output transfer function are also derived. The proposed AVM is compared with full-order generalized average model and the detailed model in predicting large-signal transients in time domain and small-signal analysis in frequency domain. Experimental prototype of a 150W, 24/48 VDC DAB converter has been designed and built to validate the proposed modeling methodologies. The experimental results confirm that the proposed detailed and average-value models yield high accuracy in predicting the power losses and time-domain responses, which represents an improvement over the existing state-of-the-art models.
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Multiple-input multiple-output (MIMO) converters have been identified as a cost-effective approach for energy harvesting and dispatching in hybrid power systems such as those envisioned in future smart homes and DC microgrids. Compared with relatively complex set-up of single-input single-output (SISO) converters linked at a common DC bus to exchange power, the MIMO converters possess promising features of fewer components, higher power density, and centralized control. This thesis addresses various issues regarding the development of MIMO converters. Both non-isolated and isolated MIMO converter topologies are proposed. Steady-state analysis and dynamic modeling of MIMO non-inverting buck–boost and flyback converters are introduced and presented in detail. Specific switching strategies are proposed and appropriate control algorithms are presented to enable power budgeting between diverse sources and loads in addition to regulating output voltages. Furthermore, a simple method is put forward for deriving the non-isolated MIMO converters with DC-link inductor (DLI) and DC-link capacitor (DLC). Based on a basic structure, a set of rules is listed for the synthesis of MIMO converters. Using the time-sharing concept, multiple sources provide energy in one period, and multiple loads draw energy in the subsequent period. In the end, general techniques are introduced for extending the SISO converters to their MIMO versions, where parts of the conventional SISO converters are replaced with multiport structures. It is envisioned that MIMO converters presented in this thesis will find their acceptance in the future in various applications with DC distribution, which are becoming increasingly accepted by industry.
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Modeling and analysis of basic DC-DC converters is essential for enabling power-electronic solutions for the future energy systems and applications. Average-value modeling (AVM) provides a time-efficient tool for studying power electronic systems, including DC/DC converters. Many AVM techniques including the analytical and numerical state-space averaging and circuit averaging have been developed over the years and available in the literature. Average-value modeling of ideal PWM converters neglects parasitics (losses) to simplify the derivations and modeling procedures, and the resulting models may not be sufficiently accurate for practical converters. In this work, first we consider a second-order Flyback converter, which has transformer isolation and additional parasitics such as conduction losses that have not been accurately included in the prior literature. We propose three new AVMs using the analytical state-space averaging, circuit averaging, and parametric AVM approaches, respectively. By taking into account conduction losses, the accuracy of the proposed average-value models is significantly improved. The derived (corrected) models show noticeable improvement over the traditional (un-corrected) models. Next, we consider the Flyback converter including the snubbers and leakage inductances in the full-order model. Snubbers reduce electromagnetic interfaces (EMI) during transients and protect switching devices from high voltage, and therefore are necessary in many practical converter circuits. Including snubbers into the model improves accuracy in predicting the circuit variables during the time-domain transients as well as predicting the converter efficiency. It is shown that conventional analytical/numerical methods of averaging do not result in accurate AVM for the full-order Flyback converter. A new formulation for the state-space averaging methodology is proposed that is functional for higher-order converters with parasitics and result in highly accurate AVM. The new approach is justified mathematically and verified experimentally using hardware prototype and measurements. The new model is demonstrated to achieve accurate results in large signal time-domain transients, and small-signal frequency-domain analysis in continuous conduction mode (CCM) and discontinuous conduction mode (DCM), which represents advancement to the state-of-the-art in this field.
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For large and small signal analysis of electromechanical systems with power electronic devices such as Brushless DC (BLDC) motor-inverter drives, average-value models (AVMs) are indisputable. Average-value models are typically orders of magnitude faster than the corresponding detailed models. This advantage makes AVMs ideal for representing motor-drive components in system level studies. Derivation of accurate dynamic average-value model of BLDC motor-drive system is generally challenging and requires careful averaging of the stator phase voltages and currents over a prototypical switching interval (SI) to find the corresponding average-value relationships for the state variables and the resulting electromagnetic torque.The so-called 120° voltage source inverter (VSI) driven brushless dc (BLDC) motors are very common in many commercial and industrial applications. This thesis extends the previous work and presents a new and improved dynamic average-value model (AVM) for such BLDC motor-drive systems. The new model is explicit and uses a proper model of the permanent magnet synchronous machine with non-sinusoidal rotor flux. The model utilizes multiple reference frame theory to properly include the back EMF harmonics as well as commutation and conduction intervals into the averaged voltage and torque relationships. The commutation angle is readily obtained from the detailed simulation. The proposed model is then demonstrated on two typical industrial BLDC motors with differently-shaped back EMF waveforms (i.e. trapezoidal and close to sinusoidal). The results of studies are compared with experimental measurements as well as previously established state-of-the-art models, whereas the new model is shown to provide appreciable improvement especially for machines with pronounced trapezoidal back EMF.
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It is generally known that stability of vehicles under certain driving conditions may be improved by forcing the wheels to turn at the same speed and angle regardless of the available traction under individual wheels. For conventional all-terrain vehicles or sport-utility vehicles, this function can be achieved by locking the mechanical differential system. In this thesis, we propose an innovative approach for locking the electrical differential system (EDS) of electric vehicles (EV) with independent brushless DC (BLDC) machine-based wheel drives. The proposed method locks the active wheels of the vehicle as if they were operating on a common “virtual” shaft. The locking algorithm is implemented by processing the Hall sensor signals of the considered motors and driving them with a single set of “averaged” Hall signals, thereby operating the motors at the same speed and angle. A detailed switch-level model of EDS embedded with the proposed Sync-Lock Control (SLC) along with the BLDC propulsion motors has been developed and compared against measurements for the considered BLDC propulsion motors. The proposed technique is shown to achieve better results compared to a conventional speed control loop as the considered motors are locked directly through the corresponding magnetic fields. An efficient realization of the proposed controller is presented that makes it possible to be potentially programmed inside existing motor controllers or implemented in a stand-alone microcontroller which can be packaged into a dongle circuit. The proposed SLC is implemented digitally using a programmable integrated circuit microcontroller. First, the Hall signals undergo a layer of filtering to mitigate the errors that are common due to Hall sensor misalignment in low-cost BLDC motors. Then, the locking algorithm is implemented by averaging the filtered Hall sensor signals. The SLC prototype is implemented in form of a standalone dongle-circuit that can be easily placed between the original Hall-sensors and the BLDC motor driver. Operation of typical industrial BLDC motors with the proposed controller is shown to outperform conventional controllers and lock both speed and angle of the motors.
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Modeling of switched-mode DC-DC converters has been receiving significant interest due to their widespread applications. Averaged modeling is the most common approach (and tool) that has been used to analyze dynamic performance of converter circuits. Specifically, state-space averaged models are widely used because of their simplicity and generality. However, as has been shown in the literature, the challenges of directly applying this approach to predict the discontinuous variables (states) and include the parasitics and losses have limited application of this approach to a wider range of converter circuits. The recently introduced parametric average value models (PAVM) has a potential to overcome this problem. In this Thesis, first of all a second-order flyback converter has been investigated. An analytical solution of state-apace averaging and small-signal analysis of the flyback converter in continuous conduction mode (CCM) and discontinuous conduction mode (DCM) is given without and with parasitics. The PAVM methodology has been applied to the second-order model to overcome the problem of discontinuous state during the DCM.The snubber circuits in flyback converter have also been investigated. Appearance of snubbers in the model introduces a problem on the output voltage besides improving the efficiency prediction. It is shown that with the snubbers the conventional state-space averaging cannot predict the output voltage correctly in CCM and DCM. To solve this problem the model is partitioned into two different sub-circuits: i) switching sub-circuit circuit; and ii) non-switching sub-circuit. Thereafter it becomes possible apply the averaging on the switching sub-circuit only.Finally, a full-order flyback converter with two RC snubber circuits and all the basic parasitics is considered. The PAVM methodology has been extended to this class of switching converter for the first time. It is shown that including the snubbers and parasitics significantly improves the model accuracy in terms of predicting converter efficiency, which represents an appreciable improvement over all previously existing average models. The proposed model has been verified with detailed simulations and hardware measurements.
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Hall-sensor-based Brushless dc (BLDC) motors are becoming very popular in wide range of applications, mainly due to their low cost, high efficiency, and reliable operation as compared to the conventional brushed motors. These machines have been extensively researched in the literature mainly under two common assumptions: each Hall-sensor produce square-wave signal of exactly 180 electrical degrees; and that the signals from the three Hall-sensors are exactly 120 electrical degrees apart. These assumptions are not necessarily the case, particularly for low to medium cost motors. A recently published manuscript investigated operation of motors with unbalanced Hall-sensor signals and introduced inaccurate positioning of the sensors as the cause of the unbalance. There, solutions have been proposed to mitigate the adverse effects of sensor positioning errors on performance of the motor. This thesis builds upon this recent publication by identifying another source of error in the Hall-sensor signals. Here, it is shown that inaccurate positioning of the Hall sensors and uneven magnetization of the tablet with which the Hall sensors react are the major factors contributing to the distortion of Hall sensor signals. It is shown here that errors in the Hall sensor signals result in unsymmetrical operation of the inverter which in turn leads to low-frequency harmonics in the electromagnetic torque; increases torque ripple and acoustic noise; and degrade overall dynamic performance of the drive. A control-level approach is proposed to mitigate the adverse effects of the errors in the Hall-sensor signals. In this approach a multi-stage digital filtering block is added to remove the errors in the original Hall-sensor signals. Each stage of the filter is designed to cancel the undesirable harmonics due to one of the error sources, the unevenly magnetized reaction tablet and the misaligned Hall sensors. An efficient realization of the proposed filter is presented that makes it possible to be potentially programmed inside existing motor controllers or implemented in a stand-alone microcontroller which can be packaged into a dongle circuit. The operation of typical low-precision industrial BLDC motors with the proposed filtering approach is shown to approach the performance of the motors with ideal Hall sensors.
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