Online two-section PV array fault diagnosis with optimized voltage sensor locations

Photovoltaic (PV) stations have been widely built in the world to utilize solar energy directly. In order to reduce the capital and operational costs, early fault diagnosis is playing an increasingly important role by enabling the long effective operation of PV arrays. This paper analyzes the terminal characteristics of faulty PV strings and arrays, and it develops a PV array fault diagnosis technique. The terminal current-voltage curve of a faulty PV array is divided into two sections, i.e., high-voltage and low-voltage fault diagnosis sections. The corresponding working points of healthy string modules and of healthy and faulty modules in an unhealthy string are then analyzed for each section. By probing into different working points, a faulty PV module can be located. The fault information is of critical importance for the maximum power point tracking and the array dynamical reconfiguration. Furthermore, the string current sensors can be eliminated, and the number of voltage sensors can be reduced by optimizing voltage sensor locations. Typical fault scenarios including monostring, multistring, and a partial shadow for a 1.6-kW 3 $times$ 3 PV array are presented and experimentally tested to confirm the effectiveness of the proposed fault diagnosis method

Efficiency improvement of non-uniformly-aged PV arrays

The utilization of solar energy by photovoltaic (PV) systems have received much research and development (R&D) attention across the globe. In the past decades, a large number of PV array have been installed. Since the installed PV arrays often operate in harsh environments, non-uniform aging can occur and impact adversely on the performance of PV systems, especially in the middle and late periods of their service life. Due to the high cost of replacing aged PV modules by new modules, it is appealing to improve energy efficiency of aged PV systems. For this purpose, this paper presents a PV module reconfiguration strategy to achieve the maximum power generation from non-uniformly aged PV arrays without significant investment. The proposed reconfiguration strategy is based on the cell-unit structure of PV modules, the operating voltage limit of gird-connected converter, and the resulted bucket-effect of the maximum short circuit current. The objectives are to analyze all the potential reorganization options of the PV modules, find the maximum power point and express it in a proposition. This proposition is further developed into a novel implementable algorithm to calculate the maximum power generation and the corresponding reconfiguration of the PV modules. The immediate benefits from this reconfiguration are the increased total power output and maximum power point voltage information for global maximum power point tracking (MPPT). A PV array simulation model is used to illustrate the proposed method under three different cases. Furthermore, an experimental rig is built to verify the effectiveness of the proposed method. The proposed method will open an effective approach for condition-based maintenance of emerging aging PV arrays

Computational Intelligence for Modeling, Control, Optimization, Forecasting and Diagnostics in Photovoltaic Applications

This book is a Special Issue Reprint edited by Prof. Massimo Vitelli and Dr. Luigi Costanzo. It contains original research articles covering, but not limited to, the following topics: maximum power point tracking techniques; forecasting techniques; sizing and optimization of PV components and systems; PV modeling; reconfiguration algorithms; fault diagnosis; mismatching detection; decision processes for grid operators

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

Modelling, Monitoring, Control and Optimization for Complex Industrial Processes

This reprint includes 22 research papers and an editorial, collected from the Special Issue "Modelling, Monitoring, Control and Optimization for Complex Industrial Processes", highlighting recent research advances and emerging research directions in complex industrial processes. This reprint aims to promote the research field and benefit the readers from both academic communities and industrial sectors

Industrial Applications: New Solutions for the New Era

This book reprints articles from the Special Issue "Industrial Applications: New Solutions for the New Age" published online in the open-access journal Machines (ISSN 2075-1702). This book consists of twelve published articles. This special edition belongs to the "Mechatronic and Intelligent Machines" section

Advanced Operation and Maintenance in Solar Plants, Wind Farms and Microgrids

This reprint presents advances in operation and maintenance in solar plants, wind farms and microgrids. This compendium of scientific articles will help clarify the current advances in this subject, so it is expected that it will please the reader

Analysis and Mitigation of Remote Side-Channel and Fault Attacks on the Electrical Level

In der fortlaufenden Miniaturisierung von integrierten Schaltungen werden physikalische Grenzen erreicht, wobei beispielsweise Einzelatomtransistoren eine mögliche untere Grenze für Strukturgrößen darstellen. Zudem ist die Herstellung der neuesten Generationen von Mikrochips heutzutage finanziell nur noch von großen, multinationalen Unternehmen zu stemmen. Aufgrund dieser Entwicklung ist Miniaturisierung nicht länger die treibende Kraft um die Leistung von elektronischen Komponenten weiter zu erhöhen. Stattdessen werden klassische Computerarchitekturen mit generischen Prozessoren weiterentwickelt zu heterogenen Systemen mit hoher Parallelität und speziellen Beschleunigern. Allerdings wird in diesen heterogenen Systemen auch der Schutz von privaten Daten gegen Angreifer zunehmend schwieriger. Neue Arten von Hardware-Komponenten, neue Arten von Anwendungen und eine allgemein erhöhte Komplexität sind einige der Faktoren, die die Sicherheit in solchen Systemen zur Herausforderung machen. Kryptografische Algorithmen sind oftmals nur unter bestimmten Annahmen über den Angreifer wirklich sicher. Es wird zum Beispiel oft angenommen, dass der Angreifer nur auf Eingaben und Ausgaben eines Moduls zugreifen kann, während interne Signale und Zwischenwerte verborgen sind. In echten Implementierungen zeigen jedoch Angriffe über Seitenkanäle und Faults die Grenzen dieses sogenannten Black-Box-Modells auf. Während bei Seitenkanalangriffen der Angreifer datenabhängige Messgrößen wie Stromverbrauch oder elektromagnetische Strahlung ausnutzt, wird bei Fault Angriffen aktiv in die Berechnungen eingegriffen, und die falschen Ausgabewerte zum Finden der geheimen Daten verwendet. Diese Art von Angriffen auf Implementierungen wurde ursprünglich nur im Kontext eines lokalen Angreifers mit Zugriff auf das Zielgerät behandelt. Jedoch haben bereits Angriffe, die auf der Messung der Zeit für bestimmte Speicherzugriffe basieren, gezeigt, dass die Bedrohung auch durch Angreifer mit Fernzugriff besteht. In dieser Arbeit wird die Bedrohung durch Seitenkanal- und Fault-Angriffe über Fernzugriff behandelt, welche eng mit der Entwicklung zu mehr heterogenen Systemen verknüpft sind. Ein Beispiel für neuartige Hardware im heterogenen Rechnen sind Field-Programmable Gate Arrays (FPGAs), mit welchen sich fast beliebige Schaltungen in programmierbarer Logik realisieren lassen. Diese Logik-Chips werden bereits jetzt als Beschleuniger sowohl in der Cloud als auch in Endgeräten eingesetzt. Allerdings wurde gezeigt, wie die Flexibilität dieser Beschleuniger zur Implementierung von Sensoren zur Abschätzung der Versorgungsspannung ausgenutzt werden kann. Zudem können durch eine spezielle Art der Aktivierung von großen Mengen an Logik Berechnungen in anderen Schaltungen für Fault Angriffe gestört werden. Diese Bedrohung wird hier beispielsweise durch die Erweiterung bestehender Angriffe weiter analysiert und es werden Strategien zur Absicherung dagegen entwickelt

Energy Harvesting and Energy Storage Systems

This book discuss the recent developments in energy harvesting and energy storage systems. Sustainable development systems are based on three pillars: economic development, environmental stewardship, and social equity. One of the guiding principles for finding the balance between these pillars is to limit the use of non-renewable energy sources

A review for solar panel fire accident prevention in large-scale PV applications

Due to the wide applications of solar photovoltaic (PV) technology, safe operation and maintenance of the installed solar panels become more critical as there are potential menaces such as hot spot effects and DC arcs, which may cause fire accidents to the solar panels. In order to minimize the risks of fire accidents in large scale applications of solar panels, this review focuses on the latest techniques for reducing hot spot effects and DC arcs. The risk mitigation solutions mainly focus on two aspects: structure reconfiguration and faulty diagnosis algorithm. The first is to reduce the hot spot effect by adjusting the space between two PV modules in a PV array or relocate some PV modules. The second is to detect the DC arc fault before it causes fire. There are three types of arc detection techniques, including physical analysis, neural network analysis, and wavelet detection analysis. Through these detection methods, the faulty PV cells can be found in a timely manner thereby reducing the risk of PV fire. Based on the review, some precautions to prevent solar panel related fire accidents in large-scale solar PV plants that are located adjacent to residential and commercial areas