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At least 271 records · Page 15

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DOE OSTI2020

Progress on the National Solar Radiation Data Base (NSRDB): A new DNI computation

This study introduces a new technique to compute direct normal irradiance (DNI) for improving the National Solar Radiation Data Base (NSRDB). A finite-surface integration algorithm is developed to compute solar radiation in differential solid angles and efficiently infer its contribution to a surface perpendicular to the solar direction. A lookup table of cloud bi-directional transmittance distribution function (BTDF) is developed by use of the discrete ordinates radiative transfer (DISORT) model for possible solar and observing directions and various cloud optical and microphysical properties. In each solar incident direction, DNI is given by the cloud BTDFs from approximately 200 differential solid angles. The simulated DNI is calibrated and evaluated using surface observations at the National Renewable Energy Laboratory's (NREL's) Solar Energy Research Laboratory (SRRL) and the Atmospheric Radiation Measurement (ARM) Southern Great Plains (SGP) facility.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2021

The Energizer Bunny: Dual-Use Photovoltaic and Pasture-Raised Rabbit Farms (Final Report)

This case study project lays the groundwork for the broader realization of agrivoltaics by considering the techno-economic, environmental, and social aspects of system development and assessing a novel rabbit-based concept. Research on the social and political barriers to agrivoltaic development is sparse, which emphasizes the importance of this project as it provides key insight into the consequential socio-political challenges that may hinder the diffusion of agrivoltaic technology. Additionally, the rabbit agrivoltaic concept is novel and has not been applied in experimental or commercial applications to date. This project advances our understanding of the viability of this co-location scheme through empirical assessment of integrating grazing rabbits with solar. A total of five manuscripts (3 published in peer-reviewed journals, 2 under review) have resulted from this project. The techno-economic component of the project included a) a pilot test study investigating the feasibility of the rabbit agrivoltaic concept and b) an economic analysis of the advantages available to solar operators who leverage grazing animals for lawn maintenance and a dual-revenue stream. Our calculations indicate that the co-location of solar and rabbit farms is a viable form of agrivoltaics, increasing overall site revenue by 2.5%-24.0% above projected electricity revenue. The environmental component of the project entailed an ISO 14040 and 14044 compliant life cycle assessment to quantify the impacts of the rabbit agrivoltaic concept. The results indicate pasture-based agrivoltaic systems provide a dual synergy that produces 69.3% less emissions and demands 82.9% less fossil energy per functional unit of cumulative MWh output of electricity and cumulative kg of meat compared to non-integrated production. The social component of the project included conducting two separate interview studies with agriculture and solar industry professionals and the distribution of a public survey. The interview findings identify the key socio-political opportunities for agrivoltaics include: the retention of agricultural land and rural interests, and increased local level acceptance of solar development. The key barriers to agrivoltaics include: ensuring long term agricultural productivity is not compromised, and subnational zoning strategies. The survey results indicate that support for local solar projects increase by 10% when an agricultural function is incorporated. Survey respondents prefer agrivoltaic projects that are a) designed to provide economic opportunities for farmers and the local community b) located on private property or existing agricultural land, and c) do not threaten local interests. Cumulatively, this project can inform agrivoltaic decision making, solar development practices, rabbit-based applications, land use management, and policy making in a way that supports the furtherance of the renewable energy transition, conserves arable land, and utilizes innovative solar photovoltaic technologies.

14 SOLAR ENERGY↗

DOE OSTI2022

Molecular-Modified Photocathodes for Applications in Artificial Photosynthesis and Solar-to-Fuel Technologies

Nature offers inspiration for developing technologies that integrate the capture, conversion, and storage of solar energy. In this review article, we highlight principles of natural photosynthesis and artificial photosynthesis, drawing comparisons between solar energy transduction in biology and emerging solar-to-fuel technologies. Key features of the biological approach include use of earth-abundant elements and molecular interfaces for driving photoinduced charge separation reactions that power chemical transformations at global scales. Finally, for the artificial systems described in this review, emphasis is placed on advancements involving hybrid photocathodes that power fuel-forming reactions using molecular catalysts interfaced with visible-light-absorbing semiconductors.

14 SOLAR ENERGY↗

DOE OSTI2021

Transparent MgO for Back-Contact Passivation of CdTe-Based Solar Cells

The passivating effects of MgO have been studied by integrating into an existing superstrate CdTe thin film solar cell device architecture. When implemented as an emitter to replace the typical MZO, the device performance was below par, but improved PL and TRPL was detected with significant carrier lifetimes in comparison to the MZO devices. However, when integrated at the back, the PL signal was detected upon the illumination of excitation laser from the back. This has opened the possibility of probing the back of the CdTe thin film solar cells with transparent back contact with improved back passivation and a bifacial device structure. Further, the TRPL measurements suggests that the MgO shows passivating effects to a CdTe surface irrespective of method of deposition implemented.

bifacial↗

DOE OSTI2021

RAVIS: Resource Forecast and Ramp Visualization for Situational Awareness - An Introduction to the Open-Source Tool and Use Cases

The Resource Forecast and Ramp Visualization for Situational Awareness (RAVIS) is an open-source tool for visualizing variable renewable resource forecasts and ramp alerts for significant up/down ramps in renewable resource and the consequent net-load. The modular dashboard of RAVIS contains configurable panes for viewing- probabilistic time series forecasts, ramp event alerts on the look-ahead timeline, spatially resolved resource sites and forecasts, and system simulation and market clearing data such as transmission lines utilization, nodal prices and available generation flexibility. RAVIS uses a technology suite that is assembled to provide optimum visualization facility while maintaining a wide pool of potential deployment and client environments. The tool is designed to take advantage of web application technologies, open source visualization libraries and tooling. Utilizing this technology will enable deployment in any environment, using any operating system, and is scalable to much higher spatial and temporal scales of visualization. As a prototype of the tool and demonstrating a use case of variable renewable integration, RAVIS currently integrates site-specific solar power forecasts in the California Independent System Operator (CAISO) and Mid-continent ISO (MISO) footprint from the IBM WattSun forecasting platform, and also superimposes market simulation data for CAISO footprint from as in-house NREL market clearing tool. The tool has the ability to alert the viewer for excessive up or down ramps for both individual solar sites as well as regionally aggregated net-load ramps, and alerts can also be qualified with respect to available flexible generation. This report will provide an introduction to the RAVIS tool, and summarize the above mentioned capabilities, typical use cases and possible extensions of the tool. The RAVIS development team believes there are likely to be high economic and reliability benefits of integrating probabilistic forecasts of variable renewables into control center visualizations and improved ramp events situational awareness for system operators and forecasting teams in the ISOs and electric utilities in comparison with their business as usual practices.

96 KNOWLEDGE MANAGEMENT AND PRESERVATION↗

DOE OSTI2022

Flexible organic integrated electronics for self-powered multiplexed ocular monitoring

Smart contact lens has drawn extensive research interests due to the noninvasive real-time detection of the human body to provide biomedical information for health management. However, it has been difficult to accurately measure the physiological signals in tears, and the use of external power source has also hindered the future applications. Here, we demonstrated an organic electrochemical transistor based multiplexed sensors self-powered by the organic solar cells (OSCs). The integrated device was fabricated via simple process including solution blade-coating and thermal evaporation. OSCs were optimized to provide optimal operation voltage for the sensors that exhibit semilog-linear response to the glucose and calcium ions in tear fluids without any peripheral circuits. The sensing signals can be transmitted to the laptop wirelessly through a near filed communication unit. This integrated self-powered multiplexed sensing device will provide real-time monitoring of the biomarkers in tears, prospected to be installed on the smart contact lens for the early detection and diagnosis of diabetes.

36 MATERIALS SCIENCE↗

DOE OSTI2022

Enhanced Control, Optimization, and Integration of Distributed Energy Applications (ECO-IDEA)

With support from the U.S. Department of Energy Solar Energy Technologies Office, the National Renewable Energy Laboratory (NREL) partnered with Xcel Energy, Schneider Electric, Varentec, and Electric Power Research Institute (EPRI) to meet the goals of the Enabling Extreme Real-Time Grid Integration of Solar Energy (ENERGISE) program. This project developed and validated an innovative data-enhanced hierarchical control architecture that enables the efficient, reliable, resilient, and secure operation of future distribution systems with a high penetration of distributed energy resources like solar energy. The architecture enables a hybrid control approach where a centralized control layer is complemented by distributed control algorithms for solar inverters and autonomous control of grid edge devices. It is fully interoperable and includes all the cybersecurity aspects necessary for reliable and secure system operation. The hybrid approach can seamlessly integrate multiple voltage-regulation technologies, both at central and grid-edge levels, which enables reliable and efficient system operation in the face of unpredictable conditions. The overarching goal of the Eco-Idea project is to develop, validate, and deploy a unique and innovative Data-Enhanced Hierarchical Control (DEHC) architecture that comprehensively addresses the formidable challenges associated with proliferation of high penetration of distributed PV such as reverse power flows, transients from variability of PV systems, feeder load balancing, and voltage stability. These issues are exposing the weaknesses of existing grid operations and controls - including, but not limited to, lack of grid situational awareness, heuristic and slow-acting control actions, latency of control for emergency situations, and points of failure in communications. The proposed architecture will comprehensively resolve the deficiencies of current operational settings - where monitoring and control solutions proposed across industry and academia may not be interoperable and may not coexist in the same system - and will enable an efficient, reliable, resilient, and secure operation of future distribution systems with penetration of solar energy well beyond current limits. The DEHC architecture was developed and validated rigorously through hardware-in-loop simulations in the laboratory environment and deployed on the field.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2021

North American Renewables Integration Study (NARIS): Cooperative Research and Development Final Report, CRADA Number CRD-16-00633

The goal of the study is to help inform and assist power system planning entities, electricity system operators, government energy agencies, legislators and regulators to better understand the planning, engineering, operational, and economic implications of integrating large amounts of wind, solar and hydro energy into the Canadian, US and Mexican electrical systems.

14 SOLAR ENERGY↗

DOE OSTI2020

Sustainability, Feasibility, and Economics of a Fuel Cell-Powered Data Center

Data centers, used for cloud computing or data storage, consume huge amounts of power and are increasing rapidly in number, and consequently, this increase in power consumption has raised concerns with green and sustainable energy supplies to minimize carbon emissions. Significant renewable power can be a carbon-free energy source to reduce the carbon footprint of a data center; however, direct integration of wind and solar power with data center causes concern of the power quality for uninterrupted power supply to computer servers. The reliable power supply can be accomplished by using power produced from fuel cells fueled by hydrogen. If fed with hydrogen derived from renewable sources, fuel cells will realize carbon-free data centers. This presentation shows various renewable-integration scenarios to meet reliable and sustainable power requirements for a data center.

25 ENERGY STORAGE↗

DOE OSTI2020

An improved method for direct incident solar radiation calculation from hourly solar insolation data in building energy simulation

Solar radiation considerably influences the energy consumption of buildings and the power production of building integrated photovoltaic (BIPV) systems. Hourly solar insolation (Wh/m 2 ), represented as the amount of solar irradiance collected on the ground during a 1-h period, is the most common solar radiation data available and widely used in weather files applied in building energy modeling programs (BEMPs). Because the solar beam and position vary over time, the use of hourly insolation data as the input might result in errors in the estimation of the direct incident solar radiation on a particular surface. In this study, methods used in BEMPs for direct incident solar radiation calculations are first analyzed, and an improved method adopting a new algorithm for estimating the solar irradiance is proposed. Furthermore, the algorithm assumes that the solar irradiance changes linearly within a 1-h period and can be estimated based on the solar irradiance at the half clock and slope. The collected direct normal solar irradiance data of 2016 from eight solar radiation stations in China were used to demonstrate the proposed method and evaluate its performance by comparing the results with those from three conventional methods used in BEMPs along with the ground truth measurements. In addition, in this study, factors affecting the accuracy of the calculation results are explored. The results of the estimated direct incident solar radiation show that the proposed method achieves the best accuracy, followed by the methods used in DOE-2, EnergyPlus, and DeST. The proposed method guarantees that the hourly direct solar insolation will remain the same and reflects the variation in the direct solar irradiance across a 1-h time frame. The proposed method can be adopted in BEMPs to improve the accuracy of the solar radiation calculation, thereby improving the accuracy of the simulated building performance and the BIPV production.

14 SOLAR ENERGY↗

DOE OSTI2020

Optimal Heliostat Assignment Strategy for Multiple-Receiver Systems

Next-generation concentrating solar power concepts currently being developed under the U.S. Department of Energy's Gen3 program include several novel heliostat field and receiver arrangements. Among these concepts are solar fields utilizing multiple receivers or several distinct receiver flux control zones, and each of which has particular power or peak flux constraints. In this paper, we present a linear program that identifies optimal heliostat-to-receiver assignment strategies for multi-receiver or multi-zone solar fields based on detailed calculations made by an optics modeling package. Two distinct problems are addressed: namely, (1) a design problem that chooses the optimal set of heliostats to include in a final layout given receiver constraints and performance, and (2) an operations problem that assigns existing heliostats to a receiver, maximizing field power output while maintaining receiver power constraints. The optimization methodology is integrated into the concentrating solar power tower modeling package SolarPILOTTM, and results are presented showing that heliostat assignment strategies can impact both initial heliostat field layout characteristics and the cost of thermal energy produced by the field. The methodology succeeds in maintaining power requirements but at the expense of producing different flux profiles on each receiver surface. Consequently, the paper also discusses additional measures that are applied to ensure that desirable flux distribution properties are maintained, reducing local flux mean-absolute-deviation values from a baseline of 17% or greater to less than 5% compared to a desired reference flux profile.

41 EE - Solar Energy Technologies Office (EE-4S)↗

DOE OSTI2022

IMoFi - Intelligent Model Fidelity: Physics-Based Data-Driven Grid Modeling to Accelerate Accurate PV Integration (Final Report)

This report summarizes the work performed under a project funded by U.S. DOE Solar Energy Technologies Office (SETO) to use grid edge measurements to calibrate distribution system models for improved planning and grid integration of solar PV. Several physics-based data-driven algorithms are developed to identify inaccuracies in models and to bring increased visibility into distribution system planning. This includes phase identification, secondary system topology and parameter estimation, meter-to-transformer pairing, medium-voltage reconfiguration detection, determination of regulator and capacitor settings, PV system detection, PV parameter and setting estimation, PV dynamic models, and improved load modeling. Each of the algorithms is tested using simulation data and demonstrated on real feeders with our utility partners. The final algorithms demonstrate the potential for future planning and operations of the electric power grid to be more automated and data-driven, with more granularity, higher accuracy, and more comprehensive visibility into the system.

14 SOLAR ENERGY↗

DOE OSTI2023

Compilation of a Solar Mirror Materials Database and an Analysis of Natural and Accelerated Mirror Exposure and Degradation

The National Renewable Energy Laboratory (NREL) has been conducting exposure experiments on solar reflectors for over four decades. Thousands of mirror samples from over one hundred suppliers have been exposed to and monitored in a range of relevant environments. These test conditions include outdoor test settings and several controlled laboratory environments. These samples have been rigorously individually characterized using a series of reflectance measurements, visual inspections, and in some cases, in-depth composition analysis to identify degradation modes, reflectance losses, and other mirror properties integral to understanding the solar reflector's life cycle. Here, this paper compiles the decades of measurement data into a concise statistical analysis. It includes exposure and degradation data for numerous reflector types, including secondary-surface reflector permutations of polymer and glass superstrates with silver and aluminum reflectors as well as front-surface reflectors. The results herein are intended to analyze environmental stressors and degradation trends among various historical and state-of-the-art solar reflectors. It may be used to support solar reflector design, effective testing methodology, and inform manufacturing decisions moving forward. Presented are the results of the compiled database and an initial analysis for degradation rate modeling using full-spectrum and wavelength-dependent approaches. The database is a growing resource hosted on a live, publicly accessible website. In conjunction with the analysis presented here, it provides a valuable resource to the solar reflector manufacturing and testing industry.

14 SOLAR ENERGY↗

DOE OSTI2020

Renewable Integration in Hybrid ac-dc Systems using Multi-port Autonomous Reconfigurable Solar power plant (MARS)

To increase inertia and improve primary frequency response of future grids, grid-forming inverters connecting PV to grid and energy storage systems (ESSs) are likely to play an important role. Moreover, high-voltage direct current (HVdc) links will also be an enabler to transfer remote PV generation and for improved grid stability. That is, with increased penetration of PV, discrete development of PV and ESS connecting to transmission ac grid and HVdc links is one of the solutions for stable operation of grid. Here, an integrated concept for integration of PV and ESS to transmission ac grid and HVdc links is proposed that is named as multi-port autonomous reconfigurable solar power plant (MARS). The proposed integrated development reduces the cost associated with respect to discrete development of PV-ESS systems connecting to transmission ac grid and HVdc links. The integrated development incorporates advanced control methods to provide inertial and primary frequency response, reactive power support, and transient stability to manage PV and ESS resources. In this paper, high-fidelity switched system model of the integrated system and grids are developed and detailed simulation results are provided to showcase the stable operation of the integrated system and provision of grid support functions.

14 SOLAR ENERGY↗

DOE OSTI2024

Improving the National Solar Radiation Database (NSRDB) Using a Physics-Based Direct Normal Irradiance (DNI) Model: Preprint

The National Solar Radiation Database (NSRDB) is a widely used resource providing satellite-derived solar data across the United States and globally. While the NSRDB employs a physical model for computing global horizontal irradiance (GHI), its current method for estimating cloudy-sky direct normal irradiance (DNI) relies on surface observations and empirical models. Recently, a novel physics-based approach, the Fast All-Sky Radiation Model for Solar applications with DNI (FARMS-DNI), was developed to enhance the DNI forecasting. FARMS-DNI incorporates both direct and scattered solar radiation within the circumsolar region, resulting in improved day-ahead DNI predictions when integrated into the Weather Research and Forecasting model with Solar extensions (WRF-Solar). This study integrates FARMS-DNI into the NSRDB algorithm to generate high-resolution DNI data from satellite resources. Our findings reveal that FARMS-DNI effectively mitigates the substantial DNI overestimation present in the conventional NSRDB across surface sites, particularly in conditions categorized as cloudy overcast. Consequently, this innovative model substantially enhances the overall accuracy of the NSRDB.

DNI↗

DOE OSTI2024

A country-scale green energy-water-hydrogen nexus: Jordan as a case study

Many developing countries suffer from a shortage of clean energy-water production, causing significant dependency on imported fossil fuel to meet the local energy and freshwater demands. Furthermore, when planning a 100 % renewable energy system (RES) to match the energy demand on an hourly basis, the RES is usually oversized. Hence, unavoidable large amounts of excess energy would be generated during hours of high production, low demand, and fully charged energy storage systems (ESSs). Hence, using Jordan as a case study, this work proposes a novel integrated system of wind, solar photovoltaic (PV), and lithium-ion ESS to match 100 % of the country's energy demand while using the excess generated power to drive reverse osmosis water desalination plants to match the demand of freshwater as well. Furthermore, the remaining excess energy is used for producing green hydrogen. A techno-economic optimizer was developed to show that this concept is indeed feasible. Here, the model was used to scan Jordan for the fitting sites of the highest demand-supply matching and the lowest levelized cost of electricity (LCOE), simultaneously. Three different integration scenarios are presented, namely PV-ESS, wind-ESS, and hybrid PV-wind-ESS RESs. The hybrid system showed the best performance, especially compared to the wind-ESS RES, in terms of total installed capacity (33.37 GW), LCOE (0.0492 USD/kWh), specific water cost (0.3629 USD/m 3 ), and energy and water demand-supply fractions (99.47 and 96.16 %, respectively). Storing desalinated water in natural aquifers was found to be a favorable option to enhance the performance of the three systems, where stored water by the end of the year was sufficient to cover the freshwater requirements for several following years. Finally, the remaining excess energy is used to produce green hydrogen with an annual production of up to 1.37 million tons and a specific cost down to 1.08 USD/kg.

14 SOLAR ENERGY↗

DOE OSTI2024

Improving the National Solar Radiation Database (NSRDB) Using a Physics-Based Direct Normal Irradiance (DNI) Model

Xie, Yu↗

DOE OSTI2026

Refractory-based thermal energy storage for industrial process heat: one-dimensional modeling, control, and optimization

The variable and weather-dependent output of wind and solar power plants present a substantial challenge for planning and operating electricity-systems, particularly in the absence of cost-effective and dispatchable energy storage technologies. This study investigates a high-temperature, electrically heated, refractory-based thermal energy storage (RTES) system that stores electrical energy as sensible heat in dense ceramic bricks over the 950–1800 °C range. The stored heat can be discharged as a controlled hot-gas stream for industrial heating, fuel substitution in high-temperature processes, or electricity generation. The main novelty is a comprehensive modelling, control, mapping, and optimization framework that integrates one-dimensional transient gas–solid heat transfer, fan-assisted discharge, bypass-flow regulation, reheating logic, fan-power evaluation, insulation-loss assessment, and genetic-algorithm-based design optimization. The model uses feedback from outlet temperature and delivered power to regulate discharge, while a two-stage genetic algorithm optimizes brick-channel geometry, gas-flow operation, and multilayer insulation thicknesses. Storage capacities below 50 MWh and discharge powers of 5–30 MW are analyzed to evaluate hold time, thermal delivery, fan-power penalty, heat loss, state-of-charge evolution, and indicative capital cost. Results demonstrate that optimized and well-insulated refractory-based thermal energy storage units can provide stable, efficient, and repeatable heat delivery over multiple discharge cycles. The generated performance and cost maps support modular refractory thermal energy storage as a practical option for large-scale integration of wind and solar generation and for high-temperature industrial process heat.

25 ENERGY STORAGE↗