Publications

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Increasing the penetration of distributed renewable sources, including photovoltaic (PV) sources, poses technical challenges for grid management. The grid has been optimized over decades to rely upon large centralized power plants with well-established feedback controls, but now non-dispatchable, renewable sources are displacing these controllable generators. By programming autonomous functionality into distributed energy resources-in particular, PV inverters-the aggregated PV resources can act collectively to mitigate grid disturbances. This paper focuses on the problem of frequency regulation. Specifically, the use of existing IEC 61850-90-7 grid support functions to improve grid frequency response using a frequency-watt function was investigated. The proposed approach dampens frequency disturbances associated with variable irradiance conditions as well as contingency events without incorporating expensive energy storage systems or supplemental generation, but it does require some curtailment of power to enable headroom for control action. Thus, this study includes a determination of the trade-offs between reduced energy delivery and dynamic performance. This paper includes simulation results for an island grid and hardware results for a testbed that includes a load, a 225 kW diesel generator, and a 24 kW inverter.

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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.

The increasing pressure for network operators to meet distribution network power quality standards with increasing peak loads, renewable energy targets, and advances in automated distributed power electronics and communications is forcing policy-makers to understand new means to distribute costs and benefits within electricity markets. Discussions surrounding how distributed generation (DG) exhibits active voltage regulation and power factor/reactive power control and other power quality capabilities are complicated by uncertainties of baseline local distribution network power quality and to whom and how costs and benefits of improved electricity infrastructure will be allocated. DG providing ancillary services that dynamically respond to the network characteristics could lead to major network improvements. With proper market structures renewable energy systems could greatly improve power quality on distribution systems with nearly no additional cost to the grid operators. Renewable DG does have variability challenges, though this issue can be overcome with energy storage, forecasting, and advanced inverter functionality. This paper presents real data from a large-scale grid-connected PV array with large-scale storage and explores effective mitigation measures for PV system variability. As a result, we discuss useful inverter technical knowledge for policy-makers to mitigate ongoing inflation of electricity network tariff components by new DG interconnection requirements or electricity markets which value power quality and control.

Presently, approximately 20 GW or 2% of the nation's generating capacity comes from solar, and solar penetration is increasing. However, for this trend to continue without adversely affecting electrical power system (EPS) performance, the photovoltaic inverters must participate in voltage- and frequency-regulation requirements. EPS support capabilities under development are the low-/high-voltage and low/high-frequency ride through, volt-VAr, frequency-watt, watt-power factor, commanded power factor, commanded power functions, and others. Each of the functions have parameter set points, and most have ramp rates for implementation of the functions as defined in the International Electrotechnical Commission Technical Report 61850-90-7. This paper focuses on methods to quantify EPS support functions for DER certification. Sandia National Laboratories and Underwriters Laboratories, in collaboration with industry stakeholders, have developed a draft test protocol that efficiently and effectively evaluates support-function capabilities. This paper describes the functions, their intended use, and results of EPS support functions in a controlled laboratory environment.

PV faults have caused rooftop fires in the U.S., Europe, and elsewhere in the world. One prominent cause of past electrical fires was the ground fault detection blind spot in fuse-based protection systems uncovered by the Solar America Board for Codes and Standards (SolarABCs) steering committee in 2011. Fortunately, a number of alternatives to ground fault fuses have been identified, but there has been limited adoption and historical use of these technologies in the United States. This paper investigates the efficacy of one of these devices known as isolation monitoring (or isolation resistance monitoring, Riso) in small (∼3kW) and large (∼700 kW) arrays. Unfaulted and faulted PV arrays were monitored with Riso technology and compared to SPICE simulations to recommend appropriate thresholds to the maximize the range of ground faults which could be detected while minimizing unwanted tripping. Based on analytical and computational models, it is impossible to determine a trip threshold that provides fire safety and negates unwanted tripping issues. This paper mathematically demonstrates that appropriate Riso trip thresholds must be determined on an arrayby- array basis with sufficient leeway by system operators to adjust trip threshold settings for their particular usage cases.

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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.

Increasing the penetration of distributed renewable sources, including photovoltaic (PV) sources, poses technical challenges for grid management. The grid has been optimized over decades to rely upon large centralized power plants with well-established feedback controls, but now non-dispatchable, renewable sources are displacing these controllable generators. This one-year study was funded by the Department of Energy (DOE) SunShot program and is intended to better utilize those variable resources by providing electric utilities with the tools to implement frequency regulation and primary frequency reserves using aggregated renewable resources, known as a virtual power plant. The goal is to eventually enable the integration of 100s of Gigawatts into US power systems.

Increasing the penetration of distributed renewable sources, including photovoltaic (PV) generators, poses technical challenges for grid management. The grid has been optimized over decades to rely on large centralized power plants with well-established feedback controls. Conventional generators provide relatively constant dispatchable power and help to regulate both voltage and frequency. In contrast, photovoltaic (PV) power is variable, is only as predictable as the weather, and provides no control action. Thus, as conventional generation is displaced by PV power, utility operation stake holders are concerned about managing fluctuations in grid voltage and frequency. Furthermore, since the operation of these distributed resources are bound by certain rules that require they stop delivering power when measured voltage or frequency deviate from the nominal operating point, there are also concerns that a single grid event may cause a large fraction of generation to turn off, triggering a black out or break-up of an electric power system.

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IEEE Standard 1547-2003 [1] conformance of several interconnected microinverters was performed by Sandia National Laboratories (SNL) to determine if there were emergent adverse behaviors of co-located aggregated distributed energy resources. Experiments demonstrated the certification tests could be expanded for multi- manufacturer microinverter interoperability. Evaluations determined the microinverters' response to abnormal conditions in voltage and frequency, interruption in grid service, and cumulative power quality. No issues were identified to be caused by the interconnection of multiple devices.

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Arc faults are a significant reliability and safety concern for photovoltaic (PV) systems and can cause intermittent operation, system failure, electrical shock hazard, and even fire. Further, arc faults in deployed systems are seemingly random and challenging to faithfully create experimentally in the laboratory, which makes the study of arc fault signature detection difficult. While it may seem trivial to simply record arcing signatures from real-world system, an obstacle in capturing these arc signals is that arc faults in the PV systems do not happen predictably, and depending on the location of the sensors relative to the arc location, may contribute a negligible portion to the magnitude of the sensed current or voltage waveform. The high-frequency content of the arc requires fast sampling, long memory, and fast processing to acquire, store, and analyze the waveforms; this adds substantial balance-of-system cost when considering widespread deployment of arc fault detectors in PV applications. In this paper, we study the performance of the fast Fourier transform arc detection method compared to the wavelet decomposition method by using synthetic waveforms. These waveforms are created by combining measured waveforms of normal background noise from inverters in DC PV arrays along with waveforms of arcing events. Using this technique allows the ratio of amplitudes are varied. Combining these separate waveforms in various amplitude proportions enables creation of test signals for the study of detection algorithm efficacy. It will be shown that the wavelet transformation technique produce more easily recognized detection results and can perform this detection using a much lower sampling rate than what is required for the fast Fourier transform

Many methods have been proposed to detect arc faults within photovoltaic systems. However, because of the dearth of data surrounding arcs that actually occur in commercial or residential PV systems, a sound method is necessary to systematically check for the effectiveness of algorithms claiming the ability to detect PV arc faults. This method should include data representing actual background PV system noise and seek to quantify the limits of the detection capability for the algorithms of interest.

While arc-faults are rare in photovoltaic installations, more than a dozen documented arc-faults have led to fires and resulted in significant damage to the PV system and surrounding structures. In the United States, National Electrical Code® (NEC) 690.11 requires a listed arc fault protection device on new PV systems. In order to list new arc-fault circuit interrupters (AFCIs), Underwriters Laboratories created the certification outline of investigation UL 1699B. The outline only requires AFCI devices to be tested at arc powers between 300-900 W; however, arcs of much less power are capable of creating fires in PV systems. In this work we investigate the characteristics of low power (100-300 W) arc-faults to determine the potential for fires, appropriate AFCI trip times, and the characteristics of the pyrolyzation process. This analysis was performed with experimental tests of arc-faults in close proximity to three polymer materials common in PV systems, e.g., polycarbonate, PET, and nylon 6,6. Two polymer geometries were tested to vary the presence of oxygen in the DC arc plasma. The samples were also exposed to arcs generated with different material geometries, arc power levels, and discharge times to identify ignition times. To better understand the burn characteristics of different polymers in PV systems, thermal decomposition of the sheath materials was performed using infrared spectra analysis. Overall a trip time of less than 2 seconds is recommended for the suppression of fire ignition during arc-fault events.

Many photovoltaic (PV) direct current (DC) arc-fault detectors use the frequency content of the PV system to detect arcs. The spectral content is influenced by the duration and power of the arc, surrounding insulation material geometry and chemistry, and electrode geometry. A parametric analysis was conducted in order to inform the Underwriters Laboratories (UL) 1699B ('Photovoltaic DC Arc-Fault Circuit Protection') Standards Technical Panel (STP) of improvements to arc-fault generation methods in the certification standard. These recommendations are designed to reduce the complexity of the experimental setup, improve testing repeatability, and quantify the uncertainty of the arc-fault radio frequency (RF) noise generated by different PV arcs in the field. In this investigation, we (a) discuss the differences in establishing and sustaining arc-faults for a number of different test configurations and (b) compare the variability in arc-fault spectral content for each respective test, and analyze the evolution of the RF signature over the duration of the fault; with the ultimate goal of determining the most repeatable, 'worst case' tests for adoption by UL.

This work investigates balance of systems (BOS) connector reliability from the perspective of arc fault risk. Accelerated tests were performed on connectors for future development of a reliability model. Thousands of hours of damp heat and atmospheric corrosion tests found BOS connectors to be resilient to corrosion-related degradation. A procedure was also developed to evaluate new and aged connectors for arc fault risk. The measurements show that arc fault risk is dependent on a combination of materials composition as well as design geometry. Thermal measurements as well as optical emission spectroscopy were also performed to further characterize the arc plasma. Together, the degradation model, arc fault risk assessment technique, and characterization methods can provide operators of photovoltaic installations information necessary to develop a data-driven plan for BOS connector maintenance as well as identify opportunities for arc fault prognostics.

Data from of a highly instrumented residential feeder in Ota City, Japan was used to determine 1 second load variability for the aggregation of 50, 100, 250, and 500 homes. The load variability is categorized by binning the data into seasons, weekdays vs. weekends, and time of day to create artificial sub-15-minute variability estimates for modeling dynamic load profiles. An autoregressive, AR(1) function along with a high pass filter was used to simulate the high resolution variability. The simulated data were validated against the original 1-second measured data.

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