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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 19 records
All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Infinite photovoltaic solar arrays: Considering flux of momentum and heat transfer

Large scale solar farms supply an increasing amount of the worlds electricity supply. However, high operation temperatures can strongly reduce efficiency and panel lifetime, negatively affecting the levelized cost of energy. In this work, the convective heat transfer coefficient for a utility-scale solar farm is studied with combined thermal and particle-image-velocimetry measurements in a scaled wind tunnel experiment. The measurements confirm the applicability of the scaled experimental setup to study large solar arrays. The velocity measurements indicate the complex flow structure within the solar array, governed by wakes directed upwards due to the orientation of the solar panels.

14 SOLAR ENERGY↗
DOE OSTI2021

Facilitating Large‐Scale Snow Shedding from In‐Field Solar Arrays using Icephobic Surfaces with Low‐Interfacial Toughness

Abstract Large‐scale accrual of snow and ice on solar arrays in northern latitudes can cause significant power generation losses during winter. Depending on environmental conditions, snow can encompass a wide range in physical characteristics from dry snow (modulus ≈100 kPa and density ≈0.1 g cm −3 ) to bulk ice (modulus ≈8 GPa and density ≈0.9 g cm −3 ). This variation in snow morphology has made the development of a passive, broad‐spectrum, snow and ice‐shedding surface challenging. Here, the authors develop one of the first surfaces that simultaneously possesses both low‐interfacial strength ( τ˄ ice < 50 kPa) and toughness (Γ ice < 0.5 J m −2 ) with ice. These surfaces, fabricated via the addition of mobile polymer chains/oils to a thin polymeric coating, require extremely low detachment forces for ice, enabling its passive shedding at virtually any accretion length scale. Preliminary evidence that the new surfaces can shed different forms of snow and ice from field‐deployed solar arrays, over a range of subzero temperatures for several weeks, leading to significant increases in power generation is provided. The optically transparent surfaces are easily scalable and can be widely deployed by the solar industry in areas that see persistent snow. Other applications include automotive windshields, LIDAR covers for autonomous vehicles, and cold climate optical sensors.

Dhyani, Abhishek↗
DOE OSTI2021

Unsupervised Azimuth Estimation of Solar Arrays in Low-Resolution Satellite Imagery through Semantic Segmentation and Hough Transform

This paper explains the use of a convolutional neural network (CNN) to segment solar panels in a satellite image containing solar arrays, and extract associated metadata from the arrays. A novel unsupervised technique is introduced to estimate the azimuth of each individual solar panel from the predicted mask of the convolutional neural network. This pipeline was developed with the aim of extracting necessary metadata for a solar installation, using only a set of latitude–longitude coordinates. Azimuth prediction results for 669 individual solar installations associated with 387 sites located across the United States are provided. A mean average error and median average error of 21.65 degrees and 1.0 degrees were obtained, respectively, when predicting the azimuth of the solar fleet data set, with about 80% of the results within an error of zero degrees of the ground truth azimuth value and about 85% within an error of 25 degrees. The predicted azimuth was then used to estimate the energy conversion of the solar arrays. Results show a 90.9 and 90.6 R-squared value for estimating alternating current (AC) and direct current (DC) energy, respectively, and a mean absolute percentage error (MAPE) of 1.70% in estimating the alternating current (AC) energy using the fully automated algorithm.

14 SOLAR ENERGY↗
DOE OSTI2022

Panel-Segmentation: A Python Package for Automated Solar Array Metadata Extraction Using Satellite Imagery

The NREL Python Panel-Segmentation package is a toolkit that automates the process of extracting accurate and valuable metadata related to solar array installations, using publicly available Google Maps satellite imagery. Previously published work includes automated azimuth estimation for individual solar installations in satellite images. Our continued research focuses on automated detection and classification of solar installation mounting configuration (tracking or fixed-tilt; rooftop, ground, or carport). Specifically, a Faster-RCNN Resnet-50 feature pyramid network (FPN) model was trained and validated on 862 manually labeled satellite images. This model was used to perform object detection on satellite imagery, locating and classifying individual solar installations' mounting configuration and type. Model results showed a mean average precision score (mAP) of 77.79%, with the model strongest at detecting fixed-tilt ground mount and fixed-tilt carport installations. The object detection model and its outputs have been incorporated into the Panel-Segmentation package's automated metadata extraction pipeline, which returns the mounting configuration and azimuth for individual solar arrays in satellite imagery. The complete image data set with labels has been released on the U.S. Department of Energy (DOE) DuraMAT DataHub, to encourage further research in this area.

deep learning↗
DOE OSTI2020

Little Big Horn College Health and Wellness Center 45 kilo-Watt (kW) Solar Array (Final Report)

The report summarizes the activities completed, results, and lessons learned in installing at 45 kW photovoltaic solar array on the roof and as awnings at the 25,000 square foot Health and Wellness Center on the campus of the Little Big Horn College (LBHC) in Crow Agency, Montana. The installation is expected to displace greater than 16% of the current electricity requirements at the Health and Wellness Center and save LBHC more than $6,600 in operating costs annually.

14 SOLAR ENERGY↗
DOE OSTI2022

What you get is not always what you see—pitfalls in solar array assessment using overhead imagery

Effective integration planning for small, distributed solar photovoltaic (PV) arrays into electric power grids requires access to high quality data: the location and power capacity of individual solar PV arrays. Unfortunately, national databases of small-scale solar PV do not exist; those that do are limited in their spatial resolution, typically aggregated up to state or national levels. While several promising approaches for solar PV detection have been published, strategies for evaluating the performance of these models are often highly heterogeneous from study to study. The resulting comparison of these methods for practical applications for energy assessments becomes challenging and may imply that the reported performance evaluations overly optimistic. The heterogeneity comes in many forms, each of which we explore in this work: the degree of diversity of the locations and sensors (e.g. different satellites, aerial photography) from which the training and validation data originate, the validation of ground truth (manual annotation of imagery vs known solar PV locations), the level of spatial aggregation (e.g. array-level vs regional estimates), and inconsistencies in the training and validation datasets (e.g. different datasets are used for each study and those data are not always made accessible). For each, we discuss emerging practices from the literature to address them or suggest directions of future research. As part of our investigation, we evaluate solar PV identification performance in two large regions: the entire state of Connecticut and the city of San Diego, CA. In Connecticut, we also use 33,114 known parcel-level solar PV installations from Berkeley Lab’s Tracking the Sun dataset to evaluate parcel-level performance and evaluate capacity estimates using 169 municipalities. We also make our code (which we call SolarMapper), pre-trained models, training data, and predictions publicly available and provide a web portal for interactively inspecting each prediction that was made. Here our findings suggest that traditional performance evaluation of the automated identification of solar PV from satellite imagery may be optimistic due to common limitations in the validation process. The takeaways from this work are intended to inform and catalyze the large-scale practical application of automated solar PV assessment techniques by energy researchers and professionals.

14 SOLAR ENERGY↗
DOE OSTI2023

Pivotable support structure for cross canal solar array

A cross canal support structure for photovoltaic cells is disclosed. The structure includes a major frame having disconnectable and hinged connections to anchors at its corners, on either side of the canal. The major frame carries a plurality of minor frames, which are inclinable at an angle with respect to the major frame with the use of fixed or adjustable mounting plates. The combination of the major frame's tilt and the minor frame tilt enables fabrication of support structures that hold panels at latitude inclination for various portions of a canal.

42 ENGINEERING↗
DOE OSTI2024

Shading and Energy Impacts for Farmer-Friendly Agrivoltaics Arrays

When designing agrivoltaic solar arrays, farmers’ natural row tilling directions might be reasonable choices for array alignment, especially in cases where the tilling direction helps prevent soil erosion or has other benefits for the farmer’s operations. We examined the light field and energy production effects when installing arrays that have azimuth values that deviate from the typical ideal for three important array types: fixed-tilt, single-axis tracking, and vertical bifacial arrays. On a fractional annual energy production basis, though, all three array types lose very little output when rotated away from their ideal. This offers farmers and solar developers a wider range of system design to possibly align solar array rows with the farmer’s preferred tilling directions.

14 SOLAR ENERGY↗
DOE OSTI2020

Montana Community-Scale Solar Strategy Project (Final Technical Report)

Grid-tied solar photovoltaic (PV) development began gradually in Montana, initially taking root in the early 2000s, largely in the form of small residential systems, rarely larger than two kilowatts. Utility support for solar technology through public benefit funding triggered the installation of the state’s first solar PV installations on community-owned facilities including schools, libraries, fire stations and local government buildings in the mid-2000s. By 2016, solar PV installations totaled approximately 28 megawatts of installed capacity, generating less than 0.05% of electricity sold in Montana. Montana’s solar fleet in 2016 included 17 megawatts of utility-scale solar farms, and three shared solar projects developed by rural electric cooperatives that ranged from 25 to 50 kilowatts in size. However, with only 3,000 households utilizing solar PV, either through an on-site installation or participation in a shared solar project, the potential benefits and reach of solar technology was limited. The Montana Solar Community Project (MSCP) was developed by the Montana Energy Office (MEO) at the Department of Environmental Quality in order to implement a “community-scale” solar energy strategy for the state that would cost-effectively expand Montanans’ access to solar PV. This project defines three types of community-scale solar projects: shared solar, community-sited solar, and group purchasing programs. The MSCP project conducted research and stakeholder engagement that helped to inform and develop model community-scale initiatives and an overarching community-scale solar strategy for Montana. Specifically, the project included a solar market assessment, stakeholder meetings across Montana, development of a menu of community-scale solar options, a study of solar potential on schools, community solar market research, and community-scale project implementation support. MSCP activities were successful in implementing solar projects and supporting solar development in communities across Montana. Project activities realized 280 kW of newly installed solar from two solarize programs, a shared solar array at a rural electric cooperative, and a solar array atop a Bozeman high school. The community-scale project implementation support and Solar on Schools components of the project resulted directly in the analysis and design of nearly 2 MW of distributed solar systems across the state. The Solar on Schools analysis alone produced solar designs for 25 schools, representing 920.8 kW of solar potential. Many of the deliverables from this project provide guidance on future development of community-scale solar in Montana, and resulted in a number of important conclusions about community-scale solar in Montana. There is strong interest in community-scale solar in Montana, as noted during stakeholder meetings, in response to solar market research surveys, and as seen by applications for implementation support grants provided by MEO. Project activities also suggest that Montanans demonstrated a desire and need for more information about solar energy technology, solar financing options, and the state’s policy and regulatory framework. Additionally, the project found that schools will be key partners for future community-scale solar programs. In addition to being excellent hosts for solar arrays, schools have the opportunity to use the installation of a solar array to develop educational materials and curricula to educate Montana’s future leaders about these technologies, which can be shared and replicated across the state. Project activities laid a clear path forward for solar energy in Montana. Certain activities have concrete next steps. For example, numerous solar arrays were designed for schools and other public buildings around the state. Many of those designs will be used as soon as funding becomes available. Other activities have less developed next steps, though lay the foundation for future work. The solar market assessment, solar market research, and community stakeholder meetings are good examples. These documents can be used as stepping stones to increase renewable energy education, increase stakeholder outreach, and support communities as they seek to develop community-scale solar projects.

14 SOLAR ENERGY↗
DOE OSTI2023

Solar Farm Development Impacts on Eastern Box Turtle ( Terrapene carolina ) Home Ranges

Eastern Box Turtle (Terrapene carolina) populations have declined drastically since 1970 because of continued destruction and fragmentation of their habitat. Although they are known to shift their home ranges because of environmental degradation, it is unknown how solar arrays impact Eastern Box Turtles. From 2011–2018, we collected data on Eastern Box Turtle movement and occupancy in a 79-ha solar farm. The solar farm is divided into six fenced areas, each containing wildlife openings for movement of terrestrial fauna every 23 m around the fenced solar arrays. For this work, we hypothesized that the solar arrays changed the home range sizes of turtles that interacted with the field. We fitted 41 Eastern Box Turtles with radio transmitters and tracked their locations twice per week in June–August from 2011–2018. Seventeen turtles had home ranges that overlapped with the solar arrays whereas 24 turtles had home ranges that never interacted with the solar arrays. We calculated home range sizes and tested for differences between overlapping and nonoverlapping groups. We further considered if the number of observations within the solar farm impacted home range size and displacement. We found that Eastern Box Turtles that used the solar farm exhibited 55–83% larger home ranges on average than turtles in natural habitats, but there was no significant association of home range size with the amount of time observed within the solar farm. Finally, we discuss strategies to mitigate negative impacts of solar farm development on turtles.

Radio telemetry↗
DOE OSTI2025

Energy Improvements of Fire Station 71

Since 2018, the City of Shawnee, Kansas has completed two phases of the State of Kansas Facility Conservation Improvement Program (FCIP), an initiative that guarantees operational cost and energy savings through targeted construction improvements on City facilities and infrastructure. The City is currently in the third phase of this FCIP, where one of the projects included an investment in energy improvements for Fire Station 71 (FS 71). The City partnered with Navitas, an Energy Service Company (ESCO), to implement a Photovoltaic Solar Array on FS71. The purpose of this project was to invest in sustainable building improvements with Energy Conservation Measures (ECM) to bring cost savings to the City and to provide sustainable benefits to the residents of Shawnee. In the first task of the project, Navitas collaborated with the City of Shawnee and the Community Development Department to determine the optimal layout and schedule for the installation of the solar array on FS 71. In the second task of the project, Navitas installed the 99.8 kW DC Photovoltaic solar array system. This system installation comprised of racking, inverters, optimizers, load center, and disconnect, which were all installed at a total ECM price of $\$$247,948. The third task focused on start-up and commissioning of the array. Navitas installed a real-time data analytics information management system integrated with utility meters, which evaluates the operations of the utility system and verifies operation of equipment and ensures optimum operation for energy efficiency. In the final task of this project, this analytics system was used for monitoring and verification, which will continue to be used to evaluate the success of the project for the coming years. The primary goal of the project was to install the 99.8 kW DC PV solar array at FS 71 to demonstrate the viability of solar energy systems in essential municipal facilities. Fire stations are energy demanding structures, as they require a constant intake of power and have a high baseline energy usage. The success of solar arrays on a fire station exemplifies their energy efficiency and effectiveness and displays their potential for application on other city facilities. By installing a solar array at such a facility, the City sought not only to offset electricity usage but also to serve as a model for ECMs in other municipal facilities and infrastructure projects. From an economic standpoint, this project demonstrates the feasibility of renewable energy at the municipal level. The total project cost of $\$$247,948 was split evenly between city funds and award funding, minimizing financial risk while ensuring guaranteed long-term savings. Any excess savings that are beyond the guaranteed minimums remain with the city, which enables future investment in sustainable energy initiatives. This project provides many benefits to the public. In addition to reducing the environmental footprint of city operations, it lowers taxpayer-funded utility spending and improves the energy security of a critical facility. The knowledge gained from this implementation motivates the City to focus on similar efforts across other public facilities in future FCIP phases and other City projects.

14 SOLAR ENERGY↗
DOE OSTI2024

Solar Energy Extension Project

The town of Stratford plans to develop and own a 6 kilowatt (kW) solar array on the roof of a municipal-owned public pavilion on the town green. A SolarEdge level 2 EV charging station will be installed at the pavilion to be used by the public. The charging station will have one charging port. The town will install 3 air source heat pumps in the library located adjacent to the pavilion to reduce the use of propane to heat the library. The town will install 4 air source heat pumps in the Town Hall to reduce the use of #2 heating oil to heat the facility. The 6 kW solar array will provide electricity to the library to offset electricity usage, and when an EV plugs into the charging station the solar will provide electricity to the charging station. There is no ground disturbance or ground trenching associated with this project. The 6 kW solar array on the roof of the pavilion will include 20 (390) watt all black panels. A SolarEdge level 2 EV charger will be installed at the pavilion with the 240 V inverter. The solar array will provide electricity to the library and when a vehicle plugs into the EV charger the solar array will switch to power the charger. Any excess electricity that is generated by the array and not used by the library or the EV charger will be fed onto the grid and the town will receive a net metering credit applied towards future consumption. There is no ground disturbance associated with the EV charger or solar array, and the town will install signage to direct the public to the charger. The library will install 2 (18,000) BTU ductless air source heat pumps and 1 (24,000) BTU unit. This will significantly reduce the amount of propane required to heat the library. The Town Hall will install 2 (36,000) BTU ductless air source heat pumps and 2 (9,000) BTU units to reduce the amount of #2 heating oil required to heat the building.

14 SOLAR ENERGY↗