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Intercell Transformer (ICT) Design Optimization and Interphase Crosstalk Mitigation of a 100-kW SiC Filter-Less Grid-Connected PV String Inverter
Not Available
End-To-End System Level Trade Considerations for Deep Space PV Systems
No abstract available
Lista de Verificacion Antes de la Tormenta: Sistemas Solares Fotovoltaico (PV) de Servicios Publicos Montados en el Suelo
Through funding provided by the U.S. Department of Energy, the National Renewable Energy Laboratory (NREL) has used subject matter experts to compile a set of checklists to help Puerto Rico and other communities prepare for storms. Renewable energy and distributed energy systems have the potential to provide power to neighborhoods, vulnerable residents, and certain facilities within a community, if those systems are designed to provide power during a grid disruption. The storm-hardening checklists provide storm preparation actions that can increase the chances that solar photovoltaic (PV) systems are available when communities need them most. This resource was translated from English to Spanish for greater accessibility.
Too Much of a Good Thing? Global Trends in the Curtailment of Solar PV
Solar photovoltaic (PV) systems generate electricity with no marginal costs or emissions. As a result, PV output is almost always prioritized over other fuel sources and delivered to the electric grid. However, PV curtailment is increasing as PV composes greater shares of grid capacity. In this paper, we present a novel synthesis of curtailment in four key countries: Chile, China, Germany, and the United States. We find that about 6.5 million MWh of PV output was curtailed in these countries in 2018. We find that: Policy and grid planning practices influence where, when, and how much PV is curtailed; Some PV curtailment is attributable to limited transmission capacity connecting remote solar resources to load centers; PV curtailment peaks in the spring and fall, when PV output is relatively high but electricity demand is relatively low. We discuss available measures to reduce PV curtailment as well as increasing PV curtailment in the contexts of evolving grids and energy technologies.
PyPVRPM: Photovoltaic Reliability and Performance Model in Python
The ability to perform accurate techno-economic analysis of solar photovoltaic (PV) systems is essential for bankability and investment purposes. Most energy yield models assume an almost flawless operation (i.e., no failures); however, realistically, components fail and get repaired stochastically. This package, PyPVRPM, is a Python translation and improvement of the Language Kit (LK) based PhotoVoltaic Reliability Performance Model (PVRPM), which was first developed at Sandia National Laboratories in Goldsim software (Granata et al., 2011) (Miller et al., 2012). PyPVRPM allows the user to define a PV system at a specific location and incorporate failure, repair, and detection rates and distributions to calculate energy yield and other financial metrics such as the levelized cost of energy and net present value (Klise, Lavrova, et al., 2017). Our package is a simulation tool that uses NREL’s Python interface for System Advisor Model (SAM) (National Renewable Energy Laboratory, 2020b) (National Renewable Energy Laboratory, 2020a) to evaluate the performance of a PV plant throughout its lifetime by considering component reliability metrics. Besides the numerous benefits from migrating to Python (e.g., speed, libraries, batch analyses), it also expands on the failure and repair processes from the LK version by including the ability to vary monitoring strategies. These failures, repairs, and monitoring processes are based on user-defined distributions and values, enabling a more accurate and realistic representation of cost and availability throughout a PV system’s lifetime.
Rethinking solar PV contracts in a world of increasing curtailment risk
Not Available
Preparacion de Sistemas Solares Fotovoltaicos Contra Tormentas
Through funding provided by the U.S. Department of Energy, the National Renewable Energy Laboratory (NREL) has used subject matter experts to compile a set of checklists to help Puerto Rico and other communities prepare for storms. Renewable energy and distributed energy systems have the potential to provide power to neighborhoods, vulnerable residents, and certain facilities within a community, if those systems are designed to provide power during a grid disruption. The storm-hardening checklists provide storm preparation actions that can increase the chances that solar photovoltaic (PV) systems are available when communities need them most. This resource was translated from English to Spanish for greater acessibility.
Preparing Solar Photovoltaic Systems Against Storms
Through funding provided by the U.S. Department of Energy, the National Renewable Energy Laboratory (NREL) has used subject matter experts to compile a set of checklists to help Puerto Rico and other communities prepare for storms. Renewable energy and distributed energy systems have the potential to provide power to neighborhoods, vulnerable residents, and certain facilities within a community, if those systems are designed to provide power during a grid disruption. The storm-hardening checklists provide storm preparation actions that can increase the chances that solar photovoltaic (PV) systems are available when communities need them most.
Impact of Wildfires on Solar Resource Availability in California in a Changing Climate
Wildfires can emit large amounts of atmospheric particulate matters and influence not only air quality but also availability of photovoltaic (PV) generation due to scattering and absorption of solar radiation. Under anthropogenic changing climate, wildfire activity is projected to increase over western North America due to drier and warmer climate, implying increasing impact on solar resource and larger uncertainty in solar generation especially in regions with faster PV penetration. This study focuses on quantifying the impact of wildfires on aerosol optical depth (AOD) and thus solar resource over California using National Solar Radiation Database (NSRDB), developed by the National Renewable Energy Laboratory (NREL). This assessment includes historical analysis and estimation of solar resource under wildfire scenarios (2020 wildfire and an enhanced wildfire scenario based on 2020 wildfires). Historical analysis for the period of July-October 2019/2020 (low/high fire activity period) shows that the averaged global horizontal irradiance (GHI) and direct normal irradiance (DNI) are reduced by about 30 and 90 W m-2 (5.6 and 15.3%), respectively, during high fire activity period. To create AOD dataset for enhanced fire scenario, 165% increase in burn area (in around 2050) is selected based on comprehensive literature review, which is further applied to the Fire INventory from NCAR (FINN) fire emission. WRF-Chem model with the enhanced FINN emissions is used to simulate and represent a preserving spatial distribution of burned areas and wildfire-emitted aerosols. Our initial analysis suggests that the"enhanced 2020 wildfire" AOD can increase by a factor of 1.3 - 2, which can significantly reduce solar irradiance and increase uncertainty in generation and reliability of power system in extreme wildfire events under a high solar penetration scenario. Overall, this study provides an estimate of the impacts of wildfires on solar resource to make informed decisions on reserve planning, generation scheduling, and reliability investments.
GET-Solar (Generation forecasting and parameter Estimation Tool for Solar) [SWR-20-115]
GET-Solar (Generation forecasting and parameter Estimation Tool for Solar) can be used to estimate behind the meter (BTM) solar generation from limited datasets. Using distributed sets of diverse solar sites, but with close spatial proximity, and/or limited historical PV generation information can be used to generate of solar profiles. This is useful for applications where partial solar generation data is available, and on-site irradiance data is not available. GET-Solar calculates PV technical data parameters and calculates output by modeling shading and cloud cover impacts. Clear sky irradiance profiles are used to calculate base generation profiles on which the local shading and cloud cover layers are added. In order to arrive at clear sky generation data, PV mounting information like panel tilt and and angle is needed. For cases where PV mounting information is missing, panel tilt and azimuth angle can be estimated using a non-linear optimization algorithm. GET-Solar can also be used for forecasting applications where historical PV data is available to estimate local shading at various solar positions. This overall framework can be used for estimation of solar parameters, and assisting in analyzing and modeling diverse sets of DER where solar generation is also present in utility meter data. GET-Solar has been developed in Python and uses the Pyomo optimization language.
AI-Based EMT Dynamic Model of PV Systems
Several electromagnetic transient (EMT) dynamic modeling methods are available to model systems like photovoltaic (PV) plants, wind power plants, variable-speed drives, among others. The methods include: (a) physics-based models and (b) data-driven models. The physics-based dynamic models may include high-fidelity switched system model and average-value model that both require the control algorithms included in the models. However, manufacturers typically prefer to provide black-box models to avoid disclosing proprietary. One of the solutions to prevent disclosing control algorithms is the use of data-driven dynamic EMT models of PV systems. In this paper, data-driven dynamic EMT model based on artificial intelligence (AI) algorithms are presented. The AI algorithms evaluated include convolutional neural networks, recurrent neural networks, and nonlinear auto-regressive exogenous model. Automation in generating data and training these models is also discussed in this paper. The results generated by the best AI algorithms have been observed to be greater than 95 % accurate.
Distribution of tessera terrain on Venus - Prediction for Magellan
Tessera terrain is the dominant tectonic unit in the northern hemisphere of Venus and is characterized by complex sets of intersecting structural trends and distinctive radar properties due to a high degree of meter and sub-meter scale (5 cm to 10 m) roughness. Based on these distinctive radar properties, a prediction of the global distribution of tessera can be made using Pioneer Venus (PV) reflectivity and roughness data. Where available, Benera 15/16 and Arecibo images and PV diffuse scattering data were used to evaluate the prediction. From this assessment, it is concluded that most of the regions with prediction values greater than 0.6 (out of 1) are likely to be tessera, and are almost certain to be techonically deformed.
Upstream Extraction of Tellurium from Copper Concentrates
A major barrier to increasing CdTe PV module production is the availability of tellurium (Te), an element necessary to manufacture CdTe PV cells that currently has a very limited supply. Most Te is obtained from ore extracted for copper mining, but the current processing methods only extract 3-4% of the available Te in this ore, with the rest being discarded during other processing steps. This project aims to increase Te supply by developing an innovative extraction method that will recover more Te from the copper ore earlier in the process. This method will also extract toxic elements like antimony and arsenic, making the copper mining process more environmentally friendly.
Operation and Maintenance of PV Systems: Data Science, Analysis, and Standards
This effort improves the effectiveness and reduce uncertainty in O&M cost through four primary objectives/tasks: 1) institutionalize standards for reliability and availability reporting for large PV power plants; 2) bridge systemic O&M knowledge gaps around important topics affecting O&M; 3) characterize systemic failure modes and patterns and accelerate O&M experiential learning cycles using field data; and 4) establish a baseline understanding of UPVS O&M cost drivers. Key results of this effort include publication of IEC standards, published topical papers on O&M topics, training, and characterize field data for climate- and service-related patterns (additional details below). Integrating these results serves to reduce performance risk and facilitate improvement in the way solar projects are operated and maintained. Results are well received and two publications are among the most successful SETO publications at NREL ("Model of Operation and Maintenance Costs for Photovoltaic Systems with over 40,000 downloads and "Best Practices in Operation and Maintenance of PV Systems, 3rd Ed." with over 90,000 downloads).
Solar dynamic power for space station freedom
The Space Station Freedom Program is presently planned to consist of two phases. At the completion of Phase 1, Freedom's manned base will consist of a transverse boom with attached manned modules and 75 kW of available electric power supplied by photovoltaic (PV) power sources. In Phase 2, electric power available to the manned base will be increased to 125 kW by the addition of two solar dynamic (SD) power modules, one at each end of the transverse boom. Power for manned base growth beyond Phase 2 will be supplied by additional SD modules. Studies show that SD power for the growth eras will result in life cycle cost savings of $3 to $4 billion when compared to PV-supplied power. In the SD power modules for Space Station Freedom, an offset parabolic concentrator collects and focuses solar energy into a heat receiver. To allow full power operation over the entire orbit, the receiver includes integral thermal energy storage by means of the heat of fusion of a salt mixture. Thermal energy is removed from the receiver and converted to electrical energy by a power conversion unit (PCU) which includes a closed brayton cycle (CBC) heat engine and an alternator. The receiver/PCU/radiator combination will be completely assembled and charged with gas and cooling fluid on Earth before launch to orbit. The concentrator subassemblies will be pre-aligned and stowed in the orbiter bay before launch. On orbit, the receiver/PCU/radiator assembly will be installed as a unit. The pre-aligned concentrator panels will then be latched together and the total concentrator attached to the receiver/PCU/radiator by the astronauts. After final electric connections are made and checkout is complete, the SD power module will be ready for operation.
Solar dynamic power for Space Station Freedom
The Space Station Freedom Program is presently planned to consist of two phases. At the completion of Phase 1, Freedom's manned base will consist of a transverse boom with attached manned modules and 75 kW of available electric power supplied by photovoltaic (PV) power sources. In Phase 2, electric power available to the manned base will be increased to 125 kW by the addition of two solar dynamic (SD) power modules, one at each end of the transverse boom. Power for manned base growth beyond Phase 2 will be supplied by additional SD modules. Studies show that SD power for the growth eras will result in life cycle cost savings of $3 to $4 billion when compared to PV-supplied power. In the SD power modules for Space Station Freedom, an offset parabolic concentrator collects and focuses solar energy into a heat receiver. To allow full power operation over the entire orbit, the receiver includes integral thermal energy storage by means of the heat of fusion of a salt mixture. Thermal energy is removed from the receiver and converted to electrical energy by a power conversion unit (PCU) which includes a closed brayton cycle (CBC) heat engine and an alternator. The receiver/PCU/radiator combination will be completely assembled and charged with gas and cooling fluid on earth before launch to orbit. The concentrator subassemblies will be pre-aligned and stowed in the orbiter bay before launch. On orbit, the receiver/PCU/radiator assembly will be installed as a unit. The pre-aligned concentrator panels will then be latched together and the total concentrator attached to the receiver/PCU/radiator by the astronauts. After final electric connections are made and checkout is complete, the SD power module will be ready for operation.
Grid-Tied PV Inverter with Oversized Power Module to Increase its Low-Voltage Ride Through (LVRT) Capabilities and VAR Support
This paper proposes a novel design for grid-tied 3-ph Photovoltaic (PV) inverter to improve its low-voltage ride through (LVRT) response while significantly increasing its voltampere reactive (VAR) support during voltage sags. The literature available on LVRT for PV inverters can be grouped in solutions that dissipate the excess energy and those that temporary stores this energy. This paper proposes a third solution; oversizing inverter hardware components to safely transferring all the energy excess back to while maintaining the semiconductor under the maximum temperature limits. The advantages of the proposed approach are: 1) Improved LVRT capabilities and stable dc-link voltage control at MPP during sags. 2) Increased VAR support during voltage sags. 3) Increased use of renewable energy as all active power is injected back to the grid during voltage sags. Finally, the proposed solution is more cost effective compared with solutions that incorporate energy storage because only a few inverter components are required to be oversized. This paper also presents a detailed power loss analysis, which determined that that oversizing the power semiconductors has minimal impact in the inverter losses while significatively reducing the diode and IGBT conduction losses during both normal operation and grid fault conditions.