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Impacts

Read about the impacts of NREL's innovations in computational science.

Processing Big Data for the National Solar Radiation Database

2020

Challenge

Since its creation in the 1990s, the National Solar Radiation Database (NSRDB) has been the leading public source of high-resolution solar resource data in the United States for use in energy modeling, currently having over 55,000 unique users and more than 245,000 pageviews each year. This database represents the state of the art in satellite-based estimation of solar resource information and uses a unique physics-based modeling approach that enables improvements in accuracy with the deployment of the next-generation geostationary satellites. However, the NSRDB is a significant big data processing challenge with massive requirements, needing compute nodes with high speed and memory. 

Achievement

NREL is leveraging Eagle’s HPC capabilities to help process the NSRDB’s big data requirements. Eagle’s impressive data processing speed and memory strengthen the NSRDB’s mission of making the highest quality, state-of-the-art, regularly updated datasets available on a reasonably timely basis for a variety of users. Down the line, this helps reduce the costs of solar deployment by providing accurate information for siting studies and system output prediction, and thereby reduces levelized cost of electricity. Additionally, the NSRDB enables the integration of high amounts of solar on the grid by providing critical information about solar availability and variability that is used to enhance grid reliability and power quality. Given the NSRDB’s high storage requirements, Eagle’s compute capabilities are invaluable to the effort.

Impact

Powered by NREL’s HPC data processing speed and memory capabilities, the NSRDB continues to be the leading public source of solar resource data.

Read more on the National Solar Radiation Database website.

Athena: Wisdom to Guide Energy Transformations at U.S. Ports

2020

Challenge

Airports are complex transportation hubs that coordinate the movement of passengers, goods, and services from the surrounding urban area. They need decision support and actionable insight to reduce uncertainty and mitigate risk for long-term planning. There are significant challenges in adapting complex transportation networks to rapidly evolving technology megatrends—and poor planning or execution may result in increased energy use, costs, and system inefficiencies.

Achievement

Athena is a collaborative effort funded by the U.S. Department of Energy Vehicle Technologies Office and industry and is led by NREL in partnership with Oak Ridge National Laboratory and Dallas-Fort Worth International Airport. NREL and Oak Ridge National Laboratory experts are leveraging the powerful scientific computing capabilities at the labs to develop sophisticated models of current and future behaviors based on expanded mobility choices to and from transportation hubs, increased freight volume, and anticipated dynamics of airport access.

Impact

The Athena team is developing a “digital twin” model of the Dallas-Fort Worth Airport with data from individuals, traffic, freight routes, flight schedules, autonomous vehicles, and other sources. Using data-driven statistical modeling and artificial intelligence, this model can simulate the impacts of future capacity expansion scenarios. It will also identify options that maximize the value of passenger and freight mobility per unit of energy and/or cost. The project aims to inform transportation hubs in integrating transformative technologies and achieving ambitious energy goals.

Read more on the Athena website

Evaluating the Impact of Water Availability on Grid Configurations

2020

Challenge

The U.S. electric power sector relies heavily on cooling water and hydroelectric power for reliable and consistent operation. The impacts of water scarcity on power sector operations can be quantified using a variety of metrics, including total system production costs, regional energy generation, and regional energy prices.

Achievement

NREL is using a power systems model to evaluate the impact of water availability and grid configurations, considering region-wide impacts as well as sub-regional responses to capture regional capacity differences and realistic grid connectivity dynamics. Recently, NREL used Eagle to capture multiple climate-forced water availability scenarios across a range of historical and future years.

HPC is critical for this project because each of the project’s 700 individual-year simulations takes about 2 days to generate. The simulations are completed in 6-month chunks, taking about 24 hours each. With traditional computing, run time could take two months. Eagle allows NREL to parallelize the simulations and complete them in about a day.

Impact

Researchers believe this work represents the largest set of power system simulations under climate-forced water constraints to date. Additionally, this work rapidly quantified the impacts of water scarcity on power sector operations.

See the Environmental Science and Technology journal article Climate-Water Adaptation for Future U.S. Electricity Infrastructure for more information. 

NREL's R&D 100 Award-Winning Tools Help Develop End-Use Load Profiles to Inform Stakeholders

2020

Challenge

End-use building load profiles are critically important to understanding the time-sensitive value of energy efficiency, demand response, and other distributed energy resources. Various stakeholders—including electric utilities, grid operators, manufacturers, government entities and research organizations—require a foundational dataset to reference when making critical decisions about prioritizing research and development, utility resource and distribution system planning, and state and local energy planning and regulation.

Achievement

To provide this dataset, a team comprising NREL researchers and partnering labs is using a hybrid approach that combines the best-available ground-truth data—from submetering studies, statistical disaggregation of whole-building interval meter data, and other emerging data sources—with the reach, cost-effectiveness, and granularity of data-driven and physics-based building stock modeling. The project uses capabilities developed by NREL for the U.S. Department of Energy: ComStock and ResStock. The latter received an R&D 100 Award for its innovative ability to inform stakeholders about which home improvements save the most energy and money.

HPC resources are essential to the success of this project, as a typical analysis at the national scale includes the simulation of 350,000 building energy models. Each of the models on average takes about 5 minutes to simulate. Running a single national-scale simulation in serial on a laptop would take approximately 3.3 years.

Impact

By scaling up building stock simulations of the entire nation, this project provides a solid basis to help stakeholders make critical R&D and planning decisions.

Read more about end-use load profiles for the U.S. building stock.

Understanding Biomass Deconstruction Enzymes for Biofuel Production

2020

Challenge

Cellulase enzymes have the unique ability to deconstruct stubborn cellulose into soluble sugars, making them a biocatalyst of interest for biofuel research and production, Cellobiohydrolases (CBHs) are particularly promising enzymes, capable of freeing a great number of sugar molecules without dissociating from the cellulose substrate. This dissociation is rate limiting, but the molecular mechanism of this step is unknown, having not yet been discussed in literature or directly investigated.

Achievement

Using a combination of molecular simulation, structural biology, and biochemistry, NREL researchers directly compared two previously proposed molecular mechanisms for CBH dissociation. Eagle's scale provided a platform for these simulations, allowing the team to compare competing hypothesized mechanisms for the very first time. In this study, the molecular dynamics engine NAMD provided a detailed dissociation mechanism for the cellulose-degrading enzyme TrCel7A. This study revealed the rate of CHB dissociation via dethreading, in which the process of cellulose processivity is reversed.

Impact

With applications across nascent bioeconomy research, this study provides detailed knowledge that enables rational enzyme engineering for industrial use. These findings may help lower the cost of biomass deconstruction for upgrading to fuels and chemicals.

See the Proceedings of the National Academy of Sciences article The Dissociation Mechanism of
Processive Cellulases for more information.