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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 865 records · Page 48
All sourcesNASA NTRSDOE OSTI
NASA NTRS1982

Photovoltaic Systems Test Facilities: Existing capabilities compilation

A general description of photovoltaic systems test facilities (PV-STFs) operated under the U.S. Department of Energy's photovoltaics program is given. Descriptions of a number of privately operated facilities having test capabilities appropriate to photovoltaic hardware development are given. A summary of specific, representative test capabilities at the system and subsystem level is presented for each listed facility. The range of system and subsystem test capabilities available to serve the needs of both the photovoltaics program and the private sector photovoltaics industry is given.

Volkmer, K.↗
DOE OSTI2025

Sizing and Location Selection of Medium‐Voltage Back‐to‐Back Converters for DER‐Dominated Distribution Systems

Medium‐voltage back‐to‐back (MVB2B) converters can connect two distribution systems and quantifiably transfer power between them. This function can enable the MVB2B converter to exchange distributed energy resource (DER)‐generated power between two systems and bring significant value to enhancing distribution system DER adoption. Our previous work analysed and demonstrated the value MVB2B converter can bring to DER integration. As continuous work, this paper presents a methodology that helps address the MVB2B converter sizing and location selection problem in distribution systems with high DER penetrations. The proposed methodology aims to address three critical problems for MVB2B converter implementation in the real world: (1) which distribution systems are better to be connected, (2) what converter size is appropriate for connecting the distribution systems, and (3) where the optimal connection points are in the systems for connecting the MVB2B converter. The proposed methodology has been demonstrated by case studies that include various scenarios involving distribution systems with different dominated load types and high photovoltaic penetrations. The results demonstrate that selecting the optimal converter size based on net revenue and time of return considerations leads to a balance between maximizing energy savings and minimizing financial payback periods. Furthermore, feeder pair selection based on load profile standard deviation effectively identifies systems that derive the greatest value from MVB2B integration. Finally, an optimized connection point selection approach using a voltage load sensitivity matrix ensures minimal system impact while facilitating efficient power exchange. These findings provide practical insights for the real‐world deployment of MVB2B converters to enhance DER hosting capacity and improve grid resilience.

14 SOLAR ENERGY↗
DOE OSTI2021

Optimized AC/DC Dual Active Bridge Converter using Monolithic SiC Bidirectional FET (BiDFET) for Solar PV Applications

Grid interface power conversion systems for commercial, industrial and residential solar power generation are becoming ubiquitous due to the competitive cost of solar energy. The AC/DC dual active bridge (DAB) converter is an upcoming topology in industrial PV energy and energy storage applications, providing bidirectional power transfer and galvanic isolation. In this paper, the properties of a DAB-type converter are leveraged to propose a design optimization process. It can optimize the high-frequency RMS current, size of magnetic elements and zero-voltage-switching (ZVS) region of the converter. The resulting design is compared against that derived from a conventional approach. In addition, an algorithm to compute the harmonic currents at the DC and line frequency AC ports of the system is proposed, and the respective filter designs are presented. The optimized design of the AC/DC DAB converter is implemented using the newly developed, 1200 V, 46 mΩ, four quadrant, SiC-based monolithic bidirectional FETs (BiDFET). Experimental results from the 2.3 kW, 400V/277VRMS hardware prototype are finally presented to verify the design process.

Bidirectional isolated AC-DC conversion, solar ene↗
DOE OSTI2024

Evaluating Utility Costs Savings and Resilience: A Case Study in Port Arthur, Texas

This study evaluates the techno-economic feasibility of integrating solar photovoltaics (PV), battery energy storage systems (BESS), and generators to enhance both cost savings and resilience in critical community facilities in Port Arthur, Texas. Using NREL's REopt model, we analyze four facilities: the Golden Triangle Empowerment Center (GTEC), Lamar State College (LSC), Port Arthur Independent School District (PAISD), and Port Arthur Transit (PAT). A key aspect of the analysis is the incorporation of the Value of Lost Load (VoLL) and microgrid upgrade costs to assess the hidden value of resilience during grid outages. While standalone PV scenarios show moderate cost reductions and a 10-15% decrease in CO2 emissions, the inclusion of resilience measures with BESS and generators significantly increases system costs. However, the hidden value of resilience - quantified through avoided outage costs - leads to a substantial improvement in financial outcomes, resulting in positive Net Present Value (NPV) at many sites. The study demonstrates that resilient solar and storage systems offer both economic and resilience benefits, particularly for underserved communities, by balancing energy savings and enhanced operational continuity during outages.

14 SOLAR ENERGY↗
DOE OSTI2023

Recent and Planned Improvements to the System Advisor Model (SAM)

This talk will focus on recent and planned modeling improvements to the NREL System Advisor ModelTM (SAM), including PV hourly clipping correction, expanded geographic scope of PVWatts including Ukraine, additional options for hybrids, and enhanced PySAM and GUI interoperability. Additional topics will also include: bifacial modeling features including irradiance on the ground for agrivoltaics, PV uncertainty simulation features, and integrations with other NREL and industry tools.

battery↗
DOE OSTI2021

Community-scale interaction of energy efficiency and demand flexibility in residential buildings

Demand-side management (DSM) strategies, including energy efficiency (EE) and demand flexibility (DF), contribute to cost-effective operation of the electricity grid. From a system-level perspective, such programs reduce costs, enhance reliability, and reduce network issues. Similarly, DSM programs help participating customers reduce utility bills while maintaining occupant comfort. Understanding the relationship between EE and DF is key to realizing the full potential of DSM programs. In this study, we modeled an all-electric residential community based on a 498-home community that is planned for construction in Fort Collins, Colorado in the United States. We used this community model to study the relationship between different EE measures, including building envelope upgrades and smart appliances, and DF enabled by a home energy management system (HEMS) responding to a time-varying tariff. Various EE levels in the homes – code-minimum, zero energy ready, and even higher levels of envelope efficiency – were simulated. DF is enabled by the HEMS, which coordinates behind-the-meter resources, including flexible building loads, PV, and home battery systems, to minimize utility bills while maintaining occupant comfort. When comparing to the code-minimum homes, EE upgrades alone reduce HVAC energy use during peak hours by up to 50% and the HVAC utility bill by up to $312/year. With the addition of HEMS, the average daily peak demand can be reduced by up to 0.58 MW or 1.2 kW/home in the higher envelope efficiency homes. The combination of EE upgrades, HEMS, and home battery systems is expected to save homeowners up to $590/year while increasing community load flexibility. However, HEMS and home battery systems are less effective in increasing the DF in the more efficient homes due to the lower load.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2025

Assessing the Impacts of Extreme Weather Events on Photovoltaic Installations Using Remote Sensing Imagery

In this study, we analyze poststorm satellite imagery to assess solar photovoltaic (PV) damage for over 11,300 systems following a catastrophic hailstorm in Austin, TX, in September 2023, which produced softball‐sized hail and for over 1500 systems across Puerto Rico and the US Virgin Islands after Hurricanes Irma and Maria in September 2017. Findings show that approximately 5.5% of identified PV sites were damaged in the hailstorm and approximately 17% of PV installations were damaged after the hurricanes. A weak correlation between hurricane wind gust speed and percent site damage was determined, with installation practices playing a heavy role in site resilience. Additionally, we show that newer module vintages are more susceptible to hail damage than older modules, possibly due to a convergence of larger size modules, decreased frame dimensions, and decreased front glass thickness but more research is needed. For hail sizes of 60 mm or greater, consistent hail damage is sustained by PV installations, regardless of system configuration.

14 SOLAR ENERGY↗
DOE OSTI2021

Secondary Frequency Regulation from Variable Generation through Uncertainty Decomposition: An Economic and Reliability Perspective

The rapid integration of variable generation (VG), such as photovoltaics (PV), necessitates an increase in the secondary frequency regulation (SFR) to handle the system intra-dispatch interval imbalance because of VG's variation. Although PV has the control capability to provide SFR, the main challenge is in guaranteeing the delivery of PV's energy and SFRs capacities in the automatic generation control (AGC) within each dispatch interval considering its uncertainty. This paper proposes a deliverable VG SFR provision model with endogenous VG's power uncertainty decomposition. First, the uncertainty of VG is decomposed using distributionally robust chance constraints through which the deliverable SFR provision is guaranteed. Next, the intra-interval frequency response of PV's SFR is validated with a user defined AGC model including the PV power plant. Finally, the economic benefits and the reliability improvements such as the frequency deviation reduction with PV providing SFRcan be integrated and evaluated. The proposed model is tested in a modified 18-bus system and in the Western Electricity Coordinating Council test system. Results demonstrate that with the deliverable SFR from PV, the system cost and the frequency reliability can be improved simultaneously. PV's SFR performance can be guaranteed with the proposed model.

14 SOLAR ENERGY↗
DOE OSTI2022

Physics-Based Method for Generating Fully Synthetic IV Curve Training Datasets for Machine Learning Classification of PV Failures

Classification machine learning models require high-quality labeled datasets for training. Among the most useful datasets for photovoltaic array fault detection and diagnosis are module or string current-voltage (IV) curves. Unfortunately, such datasets are rarely collected due to the cost of high fidelity monitoring, and the data that is available is generally not ideal, often consisting of unbalanced classes, noisy data due to environmental conditions, and few samples. In this paper, we propose an alternate approach that utilizes physics-based simulations of string-level IV curves as a fully synthetic training corpus that is independent of the test dataset. In our example, the training corpus consists of baseline (no fault), partial soiling, and cell crack system modes. The training corpus is used to train a 1D convolutional neural network (CNN) for failure classification. The approach is validated by comparing the model’s ability to classify failures detected on a real, measured IV curve testing corpus obtained from laboratory and field experiments. Results obtained using a fully synthetic training dataset achieve identical accuracy to those obtained with use of a measured training dataset. When evaluating the measured data’s test split, a 100% accuracy was found both when using simulations or measured data as the training corpus. When evaluating all of the measured data, a 96% accuracy was found when using a fully synthetic training dataset. The use of physics-based modeling results as a training corpus for failure detection and classification has many advantages for implementation as each PV system is configured differently, and it would be nearly impossible to train using labeled measured data.

Hopwood, Michael W. (ORCID:0000000161901767)↗
NASA NTRS1984

Investigation of test methods, material properties, and processes for solar cell encapsulants

Photovoltaic (PV) modules consist of a string of electrically interconnected silicon solar cells capable of producing practical quantities of electrical power when exposed to sunlight. To insure high reliability and long term performance, the functional components of the solar cell module must be adequately protected from the environment by some encapsulation technique. The encapsulation system must provide mechanical support for the cells and corrosion protection for the electrical components. The goal of the program is to identify and develop encapsulation systems consistent with the PV module operating requirements of 30 year life and a target cost of $0.70 per peak watt ($70 per square meter) (1980 dollars). Assuming a module efficiency of ten percent, which is equivalent to a power output of 100 watts per square meter in midday sunlight, the capital cost of the modules may be calculated to be $70.00 per square meter. Out of this cost goal, only 20 percent is available for encapsulation due to the high cost of the cells, interconnects, and other related components. The encapsulation cost allocation may then be stated as $14.00 per square meter, included all coatings, pottant and mechanical supports for the cells.

Source record↗
DOE OSTI2020

System-level performance and degradation of 21 GWDC of utility-scale PV plants in the United States

We assess the performance of a fleet of 411 utility-scale (i.e., >5 MWAC and ground-mounted) photovoltaic (PV) projects totaling 21.1 GWDC (16.3 GWAC) of capacity, which achieved commercial operations in the United States from 2007 to 2016. This fleet of projects contributed more than 50% of all solar electricity generated in the United States in 2017. Using detailed information on individual project characteristics, in conjunction with modeled irradiance data, we assess the extent to which actual first-year performance has lived up to both modeled and stated expectations. We then analyze system-level performance degradation in subsequent years by employing a “fixed effects” regression model to statistically isolate the impact of age on system performance. We find that this fleet of utility-scale PV projects has generally lived up to ex ante expectations for first-year performance but that subsequent system-level degradation—found to be −1.3%/year (±0.2%)—has, on average, been worse than both ex ante expectations (commonly −0.5%/year) and results from past studies (ranging from −0.8%/year to −1.0%/year). We emphasize that −1.3%/year is a system-level estimate that captures more than just module degradation (e.g., including soiling, balance of plant degradation, and downtime for maintenance and/or other events). A side analysis of a variety of project characteristics suggests that system-level degradation rates tend to be of lower magnitude among newer projects and larger projects and at sites with lower long-term average temperatures.

14 SOLAR ENERGY↗
DOE OSTI2022

Supervised Learning for Distribution Secondary Systems Modeling: Improving Solar Interconnection Processes

The current interconnection process and hosting capacity analysis for distributed energy resources (DERs), such as photovoltaics (PV) and battery energy storage systems, are based on analyzing grid network constraints (voltage and thermal) using only medium-voltage distribution network models. This is because most utilities do not have secondary low-voltage system models that connect service transformers and residential customers. This is important because in many cases the main impact of interconnecting DERs could occur on the low-voltage distribution systems. This paper proposes a supervised learning method to approximate local secondary models to improve the interconnection process. The proposed supervised learning method includes a decision tree model that predicts the secondary topology and a logistic regression model that predicts conductor types. The case studies demonstrate the benefits of including secondary low-voltage circuits in the interconnection process. We report the proposed modeling methodology is readily scalable and thus can reduce the cost and effort of PV interconnection for the industry and stakeholders.

14 SOLAR ENERGY↗
DOE OSTI2021

Fall 2021 Solar Industry Update

Each quarter, the National Renewable Energy Laboratory (NREL) conducts the Quarterly Solar Industry Update, a presentation of technical trends within the solar industry, to the solar office staff. Each presentation focuses on global and U.S. supply and demand, module and system price, investment trends and business models, and updates on U.S. government programs supporting the solar industry.

component↗
DOE OSTI2021

Deep Reinforcement Scheduling of Energy Storage Systems for Real-time Voltage Regulation in Unbalanced LV Networks with High PV Penetration

The ever-growing higher penetration of distributed energy resources (DERs) in low-voltage (LV) distribution systems brings both opportunities and challenges to voltage support and regulation. This paper proposes a deep reinforcement learning (DRL)-based scheduling scheme of energy storage systems (ESSs) to mitigate system voltage deviations in unbalanced LV distribution networks. The ESS-based voltage regulation problem is formulated as a multi-stage quadratic stochastic program, with the objective of minimizing the expected total daily voltage regulation cost while satisfying operational constraints. While existing voltage regulation methods are mostly focused on onetime- step control, this paper explores a day-horizon systemwide voltage regulation problem. In other words, the size of action and state spaces are extremely high-dimensional and need to be delicately handled. Furthermore, in order to overcome the difficulty of modeling uncertainties and develop a realtime solution, a learn-to-schedule feedback control framework is proposed by adapting the problem to a model-free DRL setting. The proposed algorithm is tested on a customized 6-bus system and a modified IEEE 34-bus system. Simulation results validate the effectiveness and near-optimality of voltage regulation by ESS in comparison with a deterministic quadratic program solution.

Wang, Shengyi↗
DOE OSTI2020

Off-design performance of molten salt-driven Rankine cycles and its impact on the optimal dispatch of concentrating solar power systems

This paper presents a model for improving off-design performance predictions for molten salt-driven Rankine power cycles, such as in concentrating solar power tower applications. The model predicts cycle off-design performance under various boundary conditions, including molten salt inlet temperature, mass flow rate, and ambient temperature. The model is validated using industry performance data and benchmarked with results from the literature. A complete concentrating solar power plant, inclusive of solar heliostat field and receiver, is then considered, by implementing the Rankine cycle off-design performance results into the National Renewable Energy Laboratory’s System Advisor Model software, which includes a tool that determines optimal power production schedules. The work improves upon the current System Advisor Model by updating off-design performance characteristics. A case study demonstrates the impact of cycle off-design behavior on annual performance for a stand-alone concentrating solar power system and a concentrating solar power-photovoltaic hybrid system. In addition, we demonstrate how cycle off-design performance influences optimal operator dispatch decisions and, thereby, overall system design and economics. We conclude that off-design cycle performance impacts “optimal” sub-system sizing, especially for a concentrating solar power-photovoltaic hybrid configuration in which concentrating solar power must dispatch in conjunction with photovoltaic generation.

14 SOLAR ENERGY↗