Publications

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Environmental stress can degrade photovoltiac (PV) modules. We perform a literature search to identify models that estimate the damage caused by exposure to various environmental stressors, including temperature, radiation, and humidity. The weather-related variables, including ambient temperature, irradiance and humidity are calculated using the Global Land Data Assimilation System (GLDAS). The analysis also calculated degradation-model stressors, module temperature, plane of array irradiance, and relative humidity and compared these PV-specific variables to identify correlations and the translation required to represent the stressor accurately. The results show that global horizontal (GHI) irradiance can be used instead of plane-of-array irradiance to represent radiation dose. However, module temperature can be significantly different from ambient temperatures and specific humidity is significantly different from relative humidity.

In this paper, we present a new, light-weight approach for extracting the five single diode parameters (IL, Io, RS, RSH, and nNsVt) for advanced, in-field monitoring of in situ current and voltage (I-V) tracing devices. The proposed procedure uses individual I-V curves, and does not require the irradiance or module temperature measurement to calculate the parameters. It is suitable for operation on a small, single board computer at the point of I-V curve measurement. This allows for analysis to occur in the field, and eliminates the need to transfer large amounts of data to centralized databases. Observers can receive alerts directly from the in-field devices based on the extraction, and analysis of the commonly used single diode equivalent model parameters. This paper defines the approach and evaluates its accuracy by subjecting it to I-V curves with known parameters. Its performance is defined using actual I-V curves generated from an in situ scanning devices installed within an actual photovoltaic production field. The algorithm is able to operate at a high accuracy for multiple module types and performed well on actual curves extracted in the field.

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In this paper, we present a new, light-weight approach for extracting the five single diode parameters (IL, Io, RS, RSH, and nNsVt) for advanced, in-field monitoring of in situ current and voltage (I-V) tracing devices. The proposed procedure uses individual I-V curves, and does not require the irradiance or module temperature measurement to calculate the parameters. It is suitable for operation on a small, single board computer at the point of I-V curve measurement. This allows for analysis to occur in the field, and eliminates the need to transfer large amounts of data to centralized databases. Observers can receive alerts directly from the in-field devices based on the extraction, and analysis of the commonly used single diode equivalent model parameters. This paper defines the approach and evaluates its accuracy by subjecting it to I-V curves with known parameters. Its performance is defined using actual I-V curves generated from an in situ scanning devices installed within an actual photovoltaic production field. The algorithm is able to operate at a high accuracy for multiple module types and performed well on actual curves extracted in the field.

The IEC 61215 and Qualification Plus indoor aging tests are recognized as valuable assessment procedures for identifying photovoltaic (PV) modules that are prone to early-life failures or excessive degradation. However, it is unclear how well the tests match with reality, and if they can predict in-field performance. Therefore, the present work performed indoor-aging thermal cycling tests on pristine-condition modules and evaluated, using in-field current and voltage (I-V) curve scans, modules of the same make and model exposed to the actual environment within a production field. The experiment included the estimate of the overall exposure to thermal cycling in both indoor and outdoor environments, the extraction of the series resistance from the I-V curves, the development of a model based on the indoor results, and finally the testing of the model on outdoor exposure amounts to predict actual changes in resistance. Index Terms - photovoltaic, accelerated aging, series resistance.

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The integration of communication-enabled grid-support functions in distributed energy resources (DER) and other smart grid features will increase the U.S. power grid's exposure to cyber-physical attacks. Unwanted changes in DER system data and control signals can damage electrical infrastructure and lead to outages. To protect against these threats, intrusion detection systems (IDSs) can be deployed, but their implementation presents a unique set of challenges in industrial control systems (ICSs), New approaches need to be developed that not only sense cyber anomalies, but also detect undesired physical system behaviors. For DER systems, a combination of cyber security data and power system and control information should be collected by the IDS to provide insight into the nature of an anomalous event. This allows joint forensic analysis to be conducted to reveal any relationships between the observed cyber and physical events. In this paper, we propose a hybrid IDS approach that monitors and evaluates both physical and cyber network data in DER systems, and present a series of scenarios to demonstrate how our approach enables the cyber-physical IDS to achieve more robust identification and mitigation of malicious events on the DER system.

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Adoption of plug-in electric vehicles (PEVs) has expanded over the last few years, yet introduction of PEV smart charging has been stalled due to barriers in communication, controls, and an unclear method for determining the value PEVs will bring to the grid. This project will consider the grid impact of a variety of future scenarios, including adoption of different vehicle types, proliferation of extreme fast charging (xFC), expanded adoption of distributed energy resources (DER), and multiple smart charge management approaches. This project will determine how PEV charging at scale should be managed to avoid negative grid impacts, allow for critical strategies and technologies to be developed, and increase the value for PEV owners, building managers, charge network operators, grid services aggregators, and utilities.

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The U.S. DOE Regional Test Center for Solar Technologies program was established to validate photovoltaic (PV) technologies installed in a range of different climates. The program is funded by the Energy Department's SunShot Initiative. The initiative seeks to make solar energy cost competitive with other forms of electricity by the end of the decade. Sandia National Laboratory currently manages four different sites across the country. The National Renewable Energy Laboratory manages a fifth site in Colorado. The entire PV portfolio currently includes 20 industry partners and almost 500 kW of installed systems. The program follows a defined process that outlines tasks, milestones, agreements, and deliverables. The process is broken out into four main parts: 1) planning and design, 2) installation, 3) operations, and 4) decommissioning. This operations manual defines the various elements of each part.

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