As a result of the increase in penetration of inverter-based generation such as wind and solar, the dynamics of the grid are being modified. These modifications may threaten the stability of the power system since the dynamics of these devices are completely different from those of rotating generators. Protection schemes need to evolve with the changes in the grid to successfully deliver their objectives of maintaining safe and reliable grid operations. This paper explores the theory of traveling waves and how they can be used to enable fast protection mechanisms. It surveys a list of signal processing methods to extract information on power system signals following a disturbance. The paper also presents a literature review of traveling wave-based protection methods at the transmission and distribution levels of the grid and for AC and DC configurations. The paper then discusses simulations tools to help design and implement protection schemes. A discussion of the anticipated evolution of protection mechanisms with the challenges facing the grid is also presented.
In order to study the relative degradation between co-located PV modules and microinverters in an ACPV configuration, four 260 Watt PV modules and four 250 W microinverters purchased on the open market have been co-located in a thermal chamber set at a static temperature (69°C). Instantaneous electrical/thermal measurements have been taken on the microinverters with periodic dark IV measurements on the modules. After over 10,000 hours of testing, no failures or observable degradation have been seen in either the module or microinverter. Using average measured field-temperature data with Military Handbook analysis, this indicates an approximate field use of 44 years of operation lifetime for PV modules, and 13 years of operation for microinverters with reliability of 66.87% with a lower one-sided confidence level of 80%.
To determine risk of an electric shock to firefighter personnel due to contact with live parts of a damaged PV system, simulated PV arrays were constructed with multiple 'modules' connected to a central inverter. The results of this analysis demonstrate that ungrounded arrays are significantly safer than grounded arrays for reasonable module isolation resistances. Ungrounded arrays provide current hazards to personnel up to three orders of magnitude smaller than for a grounded array counterpart. While the size of the array does not affect the current hazard in grounded arrays for body resistances above 100,Ω, in ungrounded arrays, increased array size yields increased current hazards- considering that the overall fault current level is still significantly smaller than for grounded arrays. In both grounded and ungrounded arrays, the current hazard has a direct correlation to array voltage. Since the level of fault current in a grounded array can be significant, this work shows that the non- linearity of the array IV curve must be taken into account for body resistances below 600 Ω and array voltages above 1000V for accurate fault current determination. Although module and array isolation resistance is not a factor that modulates fault current in a grounded array, this resistance, Riso, has a significant effect on current hazard to the firefighter for ungrounded arrays.
2018 IEEE 7th World Conference on Photovoltaic Energy Conversion, WCPEC 2018 - A Joint Conference of 45th IEEE PVSC, 28th PVSEC and 34th EU PVSEC
Jones, C.B.; Hamzavy, Babak; Hobbs, William B.; Libby, Cara; Lavrova, Olga A.
Accelerated testing has been recognized as a valuable tool for identifying modules that are prone to early-life failures or excessive degradation. Yet, it is unclear how many of the tests, including IEC 61215, match with reality. The present work performed indoor aging tests based on the IEC standard and compared the current and voltage (I-V) curve results with fielded modules. The in-field modules were installed in a subtropical dessert climate about five years ago. The modules were recently outfitted with in situ I-V curve tracing devices that measured its characteristics at various environmental conditions. The IEC tests tended to decrease current, but the voltage increased, which caused power output to not change. The in-filed modules, on the other hand, experienced a drop in power that was greater than 5% over a 5 year period.
This project explored coupling modeling and analysis methods from multiple domains to address complex hybrid (cyber and physical) attacks on mission critical infrastructure. Robust methods to integrate these complex systems are necessary to enable large trade-space exploration including dynamic and evolving cyber threats and mitigations. Reinforcement learning employing deep neural networks, as in the AlphaGo Zero solution, was used to identify "best" (or approximately optimal) resilience strategies for operation of a cyber/physical grid model. A prototype platform was developed and the machine learning (ML) algorithm was made to play itself in a game of 'Hurt the Grid'. This proof of concept shows that machine learning optimization can help us understand and control complex, multi-dimensional grid space. A simple, yet high-fidelity model proves that the data have spatial correlation which is necessary for any optimization or control. Our prototype analysis showed that the reinforcement learning successfully improved adversary and defender knowledge to manipulate the grid. When expanded to more representative models, this exact type of machine learning will inform grid operations and defense - supporting mitigation development to defend the grid from complex cyber attacks! This same research can be expanded to similar complex domains.
The key objectives of this project were to increase meaningful stakeholder engagement in photovoltaic performance modeling and reliability areas. We did this by hosting six workshop over the past three years, giving conference and workshop presentations and contributing to technical standards committees. Our efforts have made positive contributions by increasing the sharing of information and best practices and by creating and sustaining a technical community in PV Performance Modeling. This community has worked together over the past three years and has improved its practice and decreased performance modeling uncertainties.
This report describes data collection and analysis of solar photovoltaic (PV) equipment events, which consist of faults and fa ilures that occur during the normal operation of a distributed PV system or PV power plant. We present summary statistics from locations w here maintenance data is being collected at various intervals, as well as reliability statistics gathered from that da ta, consisting of fault/failure distributions and repair distributions for a wide range of PV equipment types.
A hierarchical control algorithm was developed to utilize photovoltaic system advanced inverter volt-VAr functions to provide distribution system voltage regulation and to mitigate 10-minute average voltages outside of ANSI Range A (0.95-1.05 pu). As with any hierarchical control strategy, the success of the control requires a sufficiently fast and reliable communication infrastructure. The communication requirements for voltage regulation were tested by varying the interval at which the controller monitors and dispatches commands and evaluating the effectiveness to mitigate distribution system over-voltages. The control strategy was demonstrated to perform well for communication intervals equal to the 10-minute ANSI metric definition or faster. The communication reliability impacted the controller performance at levels of 99% and below, depending on the communication interval, where an 8-minute communication interval could be unsuccessful with an 80% reliability. The communication delay, up to 20 seconds, was too small to have an impact on the effectiveness of the communication-based hierarchical voltage control.
This paper describes efforts made by Sandia National Laboratories (SNL) and the National Renewable Energy Laboratory (NREL) to validate the SNL developed PV Reliability Performance Model (PV - RPM) algorithm as implemented in the NREL System Advisor Model (SAM). The PV - RPM model is a library of functions that estimates component failure and repair in a photovoltaic system over a desired simulation period. The failure and repair distributions in this paper are probabilistic representations of component failure and repair based on data collected by SNL for a PV power plant operating in Arizona. The validation effort focuses on whether the failure and repair dist ributions used in the SAM implementation result in estimated failures that match the expected failures developed in the proof - of - concept implementation. Results indicate that the SAM implementation of PV - RPM provides the same results as the proof - of - concep t implementation, indicating the algorithms were reproduced successfully.
While arc-faults are rare in electrical installations, many documented events have led to fires that resulted in significant damage to energy-generation, commercial and residential systems, as well as surrounding structures, in both the United States and abroad. Arc-plasma discharges arise over time due to a variety of reliability issues related to cable material degradation, electrical and mechanical stresses or acute conductive wiring dislocations. These may lead to discontinuity between energized conductors, facilitating arcing events and fires. Arc-flash events rapidly release significant energy in a localized volume, where the electric arc experiences a reduction in resistance. This facilitates a reduction in electrical resistance as the arc temperature and pressure can increase rapidly. Strong pressure waves, electromagnetic interference (EMI), and intense light from an arc pose a threat to electrical worker safety and system equipment. This arc-fault primer provides basic fundamental insight into arc-fault plasma discharges, and an overview of direct current (DC) and alternating current (AC) arc-fault phenomena. This primer also covers pressure waves and EMI arc-fault hazard analyses related to incident energy prediction and potential damage analysis. Mitigation strategies are also discussed related to engineering design and employment of protective devices including arc-fault circuit interrupters (AFCIs). Best practices related to worker safety are also covered, especially as they pertain to electrical codes and standards, particularly Institute of Electrical and Electronics Engineers (IEEE) 1584 and National Fire Protection Agency (NFPA) 70E. Throughout the primer various modelling and test capabilities at Sandia National Laboratories are also covered, especially as they relate to novel methods of arc-fault/arc-flash characterization and mitigation approaches. Herein, this work describes methods for producing and characterizing controlled, sustained arcs at atmospheric pressures as well as methods for mitigation with novel materials.
Current-voltage (I-V) curve traces of photovoltaic (PV) systems can provide detailed information for diagnosing fault conditions. The present work implemented an in situ, automatic I-V curve tracer system coupled with Support Vector Machine and a Gaussian Process algorithms to classify and estimate abnormal and normal PV performance. The approach successfully identified normal and fault conditions. In addition, the Gaussian Process regression algorithm was used to estimate ideal I-V curves based on a given irradiance and temperature condition. The estimation results were then used to calculate the lost power due to the fault condition.
The goal of this effort was to assess the effect of high penetration solar deployment on the small signal stability of the western North American power system (wNAPS). Small signal stability is concerned with the system response to small disturbances, where the system is operating in a linear region. The study area consisted of the region governed by the Western Electricity Coordinating Council (WECC). General Electric's Positive Sequence Load Flow software (PSLF®) was employed to simulate the power system. A resistive brake insertion was employed to stimulate the system. The data was then analyzed in MATLAB® using subspace methods (Eigensystem Realization Algorithm). Two different WECC base cases were analyzed: 2022 light spring and 2016 heavy summer. Each base case was also modified to increase the percentage of wind and solar. In order to keep power flows the same, the modified cases replaced conventional generation with renewable generation. The replacements were performed on a regional basis so that solar and wind were placed in suitable locations. The main finding was that increased renewable penetration increases the frequency of inter-area modes, with minimal impact on damping. The slight increase in mode frequency was consistent with the loss of inertia as conventional generation is replaced with wind and solar. Then, distributed control of renewable generation was assessed as a potential mitigation, along with an analysis of the impact of communications latency on the distributed control algorithms.
A central control algorithm was developed to utilize photovoltaic system advanced inverter functions, specifically fixed power factor and constant reactive power, to provide distribution system voltage regulation and to mitigate voltage regulator tap operations by using voltage measurements at the regulator. As with any centralized control strategy, the capabilities of the control require a reliable and fast communication infrastructure. These communication requirements were evaluated by varying the interval at which the controller sends dispatch commands and evaluating the effectiveness to mitigate tap operations. The control strategy was demonstrated to perform well for communication intervals faster than the delay on the voltage regulator (30 seconds). The communication reliability, latency, and bandwidth requirements were also evaluated.
We have examined ground faults in PhotoVoltaic (PV) arrays and the efficacy of fuse, current detection (RCD), current sense monitoring/relays (CSM), isolation/insulation (Riso) monitoring, and Ground Fault Detection and Isolation (GFID) using simulations based on a Simulation Program with Integrated Circuit Emphasis SPICE ground fault circuit model, experimental ground faults installed on real arrays, and theoretical equations.
Three balance of systems (BOS) connector designs common to industry were investigated as a means of assessing reliability from the perspective of arc fault risk. These connectors were aged in field and laboratory environments and performance data captured for future development of a reliability model. Comparison of connector resistance measured during damp heat, mixed flowing gas and field exposure in a light industrial environment indicated disparities in performance across the three designs. Performance was, in part, linked to materials of construction. A procedure was developed to evaluate new and aged connectors for arc fault risk and tested for one of the designs. Those connectors exposed to mixed flowing gas corrosion exhibited considerable Joule heating that may enhance arcing behavior, suggesting temperature monitoring as a potential method for arc fault prognostics. These findings, together with further characterization of connector aging, can provide operators of photovoltaic installations the information necessary to develop a data-driven approach to BOS connector maintenance as well as opportunities for arc fault prognostics.
The continued exponential growth of photovoltaic technologies paves a path to a solar-powered world, but requires continued progress toward low-cost, high-reliability, high-performance photovoltaic (PV) systems. High reliability is an essential element in achieving low-cost solar electricity by reducing operation and maintenance (O&M) costs and extending system lifetime and availability, but these attributes are difficult to verify at the time of installation. Utilities, financiers, homeowners, and planners are demanding this information in order to evaluate their financial risk as a prerequisite to large investments. Reliability research and development (R&D) is needed to build market confidence by improving product reliability and by improving predictions of system availability, O&M cost, and lifetime. This project is focused on understanding, predicting, and improving the reliability of PV systems. The two areas being pursued include PV arc-fault and ground fault issues, and inverter reliability.
An integrated hybrid photovoltaic-thermoelectric system has been developed using multiple layers of organic photosensitizers on inorganic semiconductors in order to efficiently convert UV-visible and IR energy into electricity. The hot anode of n-type ZnO nanowires was fabricated using a thermal process on pre-seeded layer and results to be crystalline with a transmittance up to 92 % and a bandgap of 3.32 eV. The visible-UV light-active organic layer was deposited between the anode and cathode at room temperature using a layer-by-layer deposition onto ITO and ZnO and Bi2Te3 nanowires from aqueous solution. The organic layer, a cooperative binary ionic (CBI) solid is composed of oppositely charged porphyrin metal (Zn(II) and Sn(IV)(OH–)2) derivatives that are separately water soluble, but when combined form a virtually insoluble solid. The electron donor/acceptor properties (energy levels, band gaps) of the solid can be controlled by the choice of metals and the nature of the peripheral substituent groups of the porphyrin ring. The highly thermoelectric structure, which acts as a cold cathode, is composed of p-type Bi2Te3 nanowires with a thermoelectric efficiency (ZT) between ~0.7 to 1, values that are twice that expected for bulk Bi2Te3. Lastly, efficiency of the integrated device, was found to be 35 at 0.2 suns illumination and thermoelectric properties are enhanced by the charge transfer between the CBI and the Bi2Te3 is presented in terms of photo- and thermogenerated current and advantages of the low cost fabrication process is discussed.