Doctor of Philosophy

dissertationThree major catastrophic failures in photovoltaic (PV) arrays are ground-faults, line-to-line faults, and arc faults. Although the number of such failures is few, recent fire events on April 5, 2009, in Bakersfield, California, and April 16, 2011, in Mount Holly, North Carolina suggest the need for improvements in present fault detection and mitigation techniques, as well as amendments to existing codes and standards to avoid such accidents. A fault prediction and detection technique for PV arrays based on spread spectrum time domain reflectometry (SSTDR) has been proposed and was successfully implemented. Unlike other conventional techniques, SSTDR does not depend on the amplitude of the fault-current. Therefore, SSTDR can be used in the absence of solar irradiation as well. However, wide variation in impedance throughout different materials and interconnections makes fault locating more challenging than prediction/detection of faults. Another application of SSTDR in PV systems is the measurement of characteristic impedance of power components for condition monitoring purposes. Any characteristic variations in one component will simultaneously alter the operating conditions of other components in a closed-loop system, resulting in a shift in overall reliability profile. This interdependence makes the reliability of a converter a complex function of time and operating conditions. Details of this failure mode, mechanism, and effect analysis (FMMEA) have been developed. By knowing the present state of health and the remaining useful life (RUL) of a power converter, it is possible to reduce the maintenance cost for expensive high-power converters by facilitating a reliability centered maintenance (RCM) scheme. This research is a step forward toward power converter reliability analysis since the cumulative effect of multiple degraded components has been considered here for the first time in order to estimate reliability of a power converter

Fault Diagnosis and Condition Monitoring of Power Electronic Components Using Spread Spectrum Time Domain Reflectometry (SSTDR) and the Concept of Dynamic Safe Operating Area (SOA)

Title from PDF of title page viewed April 1, 2021Dissertation advisors: Faisal Khan and Yong ZengVitaIncludes bibliographical references ( page 117-132)Thesis (Ph.D.)--School of Computing and Engineering and Department of Mathematics and Statistics. University of Missouri--Kansas City, 2021Fault diagnosis and condition monitoring (CM) of power electronic components with a goal of improving system reliability and availability have been one of the major focus areas in the power electronics field in the last decades. Power semiconductor devices such as metal oxide semiconductor field-effect transistor (MOSFET) and insulated-gate bipolar transistor (IGBT) are considered to be the most fragile element of the power electronic systems and their reliability degrades with time due to mechanical and thermo-electrical stresses, which ultimately leads to a complete failure of the overall power conversion systems. Therefore, it is important to know the present state of health (SOH) of the power devices and the remaining useful life (RUL) of a power converter in order to perform preventive scheduled maintenance, which will eventually lead to increased system availability and reduced cost. In conventional practice, device aging and lifetime prediction techniques rely on the estimation of the meantime to failure (MTTF), a value that represents the expected lifespan of a device. MTTF predicts expected lifespan, but cannot adequately predict failures attributed to unusual circumstances or continuous overstress and premature degradation. This inability is due in large part to the fact that it considers the device safe operating area (SOA) or voltage and current ride-through capability to be independent of SOH. However, we experimentally proved that SOA of any semiconductor device goes down with the increased level of aging, and therefore, the probability of occurrence of over-voltage/current situation increases. As a result, the MTTF of the device as well as the overall converter reliability reduces with aging. That said, device degradation can be estimated by accomplishing an accurate online degradation monitoring tool that will determine the dynamic SOA. The correlation between aging and dynamic SOA gives us the useful remaining life of the device or the availability of a circuit. For this monitoring tool, spread spectrum time domain reflectometry (SSTDR) has been proposed and was successfully implemented in live power converters. In SSTDR, a high-frequency sine-modulated pseudo-noise sequence (SMPNS) is sent through the system, and reflections from age-related impedance discontinuities return to the test end where they are analyzed. In the past, SSTDR has been successfully used for device degradation detection in power converters while running at static conditions. However, the rapid variation in impedance throughout the entire live converter circuit caused by the fast-switching operation makes CM more challenging while using SSTDR. The algorithms and techniques developed in this project have overcome this challenge and demonstrated that the SSTDR test data are consistent with the aging of the power devices and do not affect the switching performance of the modulation process even the test signal is applied across the gate-source interface of the power MOSFET. This implies that the SSTDR technique can be integrated with the gate driver module, thereby creating a new platform for an intelligent gate-driver architecture (IGDA) that enables real-time health monitoring of power devices while performing features offered by a commercially available driver. Another application of SSTDR in power electronic systems is the ground fault prediction and detection technique for PV arrays. Protecting PV arrays from ground faults that lead to fire hazards and power loss is imperative to maintaining safe and effective solar power operations. Unlike many standard detection methods, SSTDR does not depend on fault current, therefore, can be implemented for testing ground faults at night or low illumination. However, wide variation in impedance throughout different materials and interconnections makes fault location more challenging than fault detection. This barrier was surmounted by the SSTDR-based fault detection algorithm developed in this project. The proposed algorithm was accounted for any variation in the number of strings, fault resistance, and the number of faults. In addition to its general utility for fault detection, the proposed algorithm can identify the location of multiple faults using only a single measurement point, thereby working as a preventative measure to protect the entire system at a reduced cost. Within the scope of the research work on SSTDR-based fault diagnosis and CM of power electronic components, a cell-level SOH measurement tool has been proposed that utilizes SSTDR to detect the location and aging of individual degraded cells in a large series-parallel connected Li-ion battery pack. This information of cell level SOH along with the respective cell location is critical to calculating the SOH of a battery pack and its remaining useful lifetime since the initial SOH of Li-ion cells varies under different manufacturing processes and operating conditions, causing them to perform inconsistently and thereby affect the performance of the entire battery pack in real-life applications. Unfortunately, today’s BMS considers the SOH of the entire battery pack/cell string as a single SOH and therefore, cannot monitor the SOH at the cell level. A healthy battery string has a specific impedance between the two terminals, and any aged cell in that string will change the impedance value. Since SSTDR can characterize the impedance change in its propagation path along with its location, it can successfully locate the degraded cell in a large battery pack and thereby, can prevent premature failure and catastrophic danger by performing scheduled maintenance.Introduction -- Background study and literature review -- Fundamentals of Spread Spectrum Time Domain Reflectometry (SSTDR): A new method for testing electronics live -- Accelerated aging test bench: design and implementation -- Condition monitoring of power switching in live power switching devices in live power electronic converters using SSTDR -- An irradiance-independent, robust ground-fault detection scheme for PV arrays based on SSTDR -- Detection of degraded/aged cell in a LI-Ion battery pack using SSTDR -- Dynamiv safe operating area (SOA) of power semiconductor devices -- Conclusion and future researc

A comprehensive review and performance evaluation in solar (PV) systems fault classification and fault detection techniques

The renewable energy industry is growing faster than ever before and in particular solar systems have significantly expanded. Abnormal conditions lead to a reduction in the maximum available power from solar (photovoltaic) systems. Thus, it is necessary to identification, detection, and monitoring of various faults in the PV system that they are the key factors to increase the efficiency, reliability, and lifetime of these systems. Up to now, faults on PV components and systems have been identified; some of them have physical damage on PV systems and some of them are electrical faults that occur on the DC side or AC side of the PV system. Here, the faults will be divided into groups based on their location of occurrence. This paper provides a comprehensive review of almost all PV system faults and fault detection techniques of PV system proposed in recent literature

Failure analysis informing intelligent asset management

With increasing demands on the UK’s power grid it has become increasingly important to reform the methods of asset management used to maintain it. The science of Prognostics and Health Management (PHM) presents interesting possibilities by allowing the online diagnosis of faults in a component and the dynamic trending of its remaining useful life (RUL). Before a PHM system can be developed an extensive failure analysis must be conducted on the asset in question to determine the mechanisms of failure and their associated data precursors that precede them. In order to gain experience in the development of prognostic systems we have conducted a study of commercial power relays, using a data capture regime that revealed precursors to relay failure. We were able to determine important failure precursors for both stuck open failures caused by contact erosion and stuck closed failures caused by material transfer and are in a position to develop a more detailed prognostic system from this base. This research when expanded and applied to a system such as the power grid, presents an opportunity for more efficient asset management when compared to maintenance based upon time to replacement or purely on condition

Decision-Making for Utility Scale Photovoltaic Systems: Probabilistic Risk Assessment Models for Corrosion of Structural Elements and a Material Selection Approach for Polymeric Components

abstract: The solar energy sector has been growing rapidly over the past decade. Growth in renewable electricity generation using photovoltaic (PV) systems is accompanied by an increased awareness of the fault conditions developing during the operational lifetime of these systems. While the annual energy losses caused by faults in PV systems could reach up to 18.9% of their total capacity, emerging technologies and models are driving for greater efficiency to assure the reliability of a product under its actual application. The objectives of this dissertation consist of (1) reviewing the state of the art and practice of prognostics and health management for the Direct Current (DC) side of photovoltaic systems; (2) assessing the corrosion of the driven posts supporting PV structures in utility scale plants; and (3) assessing the probabilistic risk associated with the failure of polymeric materials that are used in tracker and fixed tilt systems. As photovoltaic systems age under relatively harsh and changing environmental conditions, several potential fault conditions can develop during the operational lifetime including corrosion of supporting structures and failures of polymeric materials. The ability to accurately predict the remaining useful life of photovoltaic systems is critical for plants ‘continuous operation. This research contributes to the body of knowledge of PV systems reliability by: (1) developing a meta-model of the expected service life of mounting structures; (2) creating decision frameworks and tools to support practitioners in mitigating risks; (3) and supporting material selection for fielded and future photovoltaic systems. The newly developed frameworks were validated by a global solar company.Dissertation/ThesisDoctoral Dissertation Civil and Environmental Engineering 201

A novel faulted section location technique for future active distribution networks

Distribution Network Operators (DNOs) face increasingly higher challenges to preserve quality and continuity of supply due to the widespread penetration of Distributed Energy Resources (DER) [1–8]. In parallel, more advanced technologies are being introduced into secondary substations for better observability and controllability. These features provided via instrumented substation assets and Information Communication Technologies (ICT) present opportunities for the development and implementation of new functions aiming to the effective operation and monitoring of active distribution networks [9–14]. This thesis focuses on one of these functionalities – that is, leveraging the ability of Low Voltage (LV) sensors to locate 11 kV unsymmetrical faults by monitoring and processing the network voltage profile during fault conditions. In particular, a novel technique has been developed which identifies the Faulted Section (FS) of the Medium Voltage (MV) feeder after a fault has occurred. The proposed algorithm, of which the successful operation depends solely on distributed LV voltage monitoring devices, represents the main contribution of the research work. A key characteristic is that, although the LV sensors connected at the secondary side of MV/LV step-down transformers require communication to transmit the data to a central point, they do not require time synchronisation. The technique facilitates the fault location procedure, which is of major importance as it accelerates restoration, reduces the system downtime, minimises repair cost, and hence, increases the overall availability and reliability of the distribution network. Moreover, the thesis deals with the challenges related to the complexity of modern distribution networks, taking into account ring topologies, MV lateral connections, pre-fault load unbalance and the presence of DERs. In this sense, the empirical characterisation of grid connection stability and fault response of small scale commercially available LV PV inverters was realised. The purpose was twofold: 1) highlight the diversity among the inverters’ responses as observed during the testing and indicate the risk of loss of PV generation during typical MV and HV level faults and 2) develop a dynamic model representing the behaviour of a real inverter under the applied physical testing conditions. The particular model was deployed in the power system studies conducted, aiding the evaluation of the FS location technique. Laboratory investigation was also carried out at the facilities of the Power Networks Demonstration Centre (PNDC) to further examine the performance of the developed faulted section location algorithm. The tests were performed in both MV radial and ring PNDC network configurations and measurements were acquired from various LV test-bays. It was demonstrated that the scheme can reliably identify the faulted section of the line while consistently maintaining high accuracy across a wide range of fault scenarios. Further sensitivity analysis demonstrates that the proposed scheme is robust against partial loss of communications and noise interference. The thesis concludes with an overview of future work that is required to further advance the concepts demonstrated.Distribution Network Operators (DNOs) face increasingly higher challenges to preserve quality and continuity of supply due to the widespread penetration of Distributed Energy Resources (DER) [1–8]. In parallel, more advanced technologies are being introduced into secondary substations for better observability and controllability. These features provided via instrumented substation assets and Information Communication Technologies (ICT) present opportunities for the development and implementation of new functions aiming to the effective operation and monitoring of active distribution networks [9–14]. This thesis focuses on one of these functionalities – that is, leveraging the ability of Low Voltage (LV) sensors to locate 11 kV unsymmetrical faults by monitoring and processing the network voltage profile during fault conditions. In particular, a novel technique has been developed which identifies the Faulted Section (FS) of the Medium Voltage (MV) feeder after a fault has occurred. The proposed algorithm, of which the successful operation depends solely on distributed LV voltage monitoring devices, represents the main contribution of the research work. A key characteristic is that, although the LV sensors connected at the secondary side of MV/LV step-down transformers require communication to transmit the data to a central point, they do not require time synchronisation. The technique facilitates the fault location procedure, which is of major importance as it accelerates restoration, reduces the system downtime, minimises repair cost, and hence, increases the overall availability and reliability of the distribution network. Moreover, the thesis deals with the challenges related to the complexity of modern distribution networks, taking into account ring topologies, MV lateral connections, pre-fault load unbalance and the presence of DERs. In this sense, the empirical characterisation of grid connection stability and fault response of small scale commercially available LV PV inverters was realised. The purpose was twofold: 1) highlight the diversity among the inverters’ responses as observed during the testing and indicate the risk of loss of PV generation during typical MV and HV level faults and 2) develop a dynamic model representing the behaviour of a real inverter under the applied physical testing conditions. The particular model was deployed in the power system studies conducted, aiding the evaluation of the FS location technique. Laboratory investigation was also carried out at the facilities of the Power Networks Demonstration Centre (PNDC) to further examine the performance of the developed faulted section location algorithm. The tests were performed in both MV radial and ring PNDC network configurations and measurements were acquired from various LV test-bays. It was demonstrated that the scheme can reliably identify the faulted section of the line while consistently maintaining high accuracy across a wide range of fault scenarios. Further sensitivity analysis demonstrates that the proposed scheme is robust against partial loss of communications and noise interference. The thesis concludes with an overview of future work that is required to further advance the concepts demonstrated

High Granularity approaches for effective energy delivery from Photovoltaic Sources

Silicon solar cell technology is a fully mature technology but the need to compete with traditional and other renewable energy sources urges to improve the overall efficiency of a photovoltaic (PV) system by a significant amount. Regardless of the solar panel efficiency, the difference between the nominal performance of a PV system and the energy actually produced is quite high, and it can be quantified in the order of 20%. A loss term, often underestimated, depends on possible failure of the Maximum Power Point Tracking (MPPT) algorithms in the presence of multiple maximum power points in power-voltage characteristic, arising in mismatch conditions. This work proposes High Granularity (HG) approaches in order to improve the PV energy yield: a monitoring strategy, a modeling and a power flux control of the whole PV system, all performed at level of single elementary source (i.e., PV cell or PV panel). An innovative HG sensor infrastructure was developed, and the measurements were exploited to perform an automatic PV system reconfiguration, and to design an information based MPPT. Moreover, the data validated a circuit HG model describing the PV system at single cell level, which also accounts for the electrothermal effect. The model was exploited in an automatic tool which translates an AutoCAD project of a PV plant in an equivalent circuit netlist. Finally, the results were employed to investigate the effectiveness of distributed power conversion – in particular the efficiency of the multilevel cascaded H bridge converter controlled by means of an innovative strategy, which overcomes some issues related to the need of performing a distributed MPPT, was assessed

Laboratory Directed Research and Development Program FY 2007 Annual Report

The Oak Ridge National Laboratory (ORNL) Laboratory Directed Research and Development (LDRD) program reports its status to the U.S. Department of Energy (DOE) in March of each year. The program operates under the authority of DOE Order 413.2B, 'Laboratory Directed Research and Development' (April 19, 2006), which establishes DOE's requirements for the program while providing the Laboratory Director broad flexibility for program implementation. LDRD funds are obtained through a charge to all Laboratory programs. This report includes summaries for all ORNL LDRD research activities supported during FY 2007. The associated FY 2007 ORNL LDRD Self-Assessment (ORNL/PPA-2008/2) provides financial data and an internal evaluation of the program's management process. ORNL is a DOE multiprogram science, technology, and energy laboratory with distinctive capabilities in materials science and engineering, neutron science and technology, energy production and end-use technologies, biological and environmental science, and scientific computing. With these capabilities ORNL conducts basic and applied research and development (R&D) to support DOE's overarching mission to advance the national, economic, and energy security of the United States and promote scientific and technological innovation in support of that mission. As a national resource, the Laboratory also applies its capabilities and skills to specific needs of other federal agencies and customers through the DOE Work for Others (WFO) program. Information about the Laboratory and its programs is available on the Internet at http://www.ornl.gov/. LDRD is a relatively small but vital DOE program that allows ORNL, as well as other DOE laboratories, to select a limited number of R&D projects for the purpose of: (1) maintaining the scientific and technical vitality of the Laboratory; (2) enhancing the Laboratory's ability to address future DOE missions; (3) fostering creativity and stimulating exploration of forefront science and technology; (4) serving as a proving ground for new research; and (5) supporting high-risk, potentially high-value R&D. Through LDRD the Laboratory is able to improve its distinctive capabilities and enhance its ability to conduct cutting-edge R&D for its DOE and WFO sponsors. To meet the LDRD objectives and fulfill the particular needs of the Laboratory, ORNL has established a program with two components: the Director's R&D Fund and the Seed Money Fund. As outlined in Table 1, these two funds are complementary. The Director's R&D Fund develops new capabilities in support of the Laboratory initiatives, while the Seed Money Fund is open to all innovative ideas that have the potential for enhancing the Laboratory's core scientific and technical competencies. Provision for multiple routes of access to ORNL LDRD funds maximizes the likelihood that novel ideas with scientific and technological merit will be recognized and supported