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At least 19 records

Integration of renewable energy generation and storage systems for emissions reduction in an islanded campus microgrid

Microgrid connected building communities are projected to play an integral part in the clean energy transition. These types of systems, when integrated with distributed energy resources (DERs) such as combined heat and power (CHP), district heating and cooling, renewable generation, and energy storage, can provide clean, reliable power to critical facilities and vulnerable communities. The intermittent nature of renewable generation is a challenge when integrating renewables into any grid system, but particularly in islanded microgrids. The University of Texas at Austin (UT) operates an islanded microgrid powered by a CHP plant, while also utilizing district heating and cooling systems and thermal energy storage (TES). High fidelity operating data was used to develop a validated reduced order model of UT’s integrated campus energy systems to serve as a testbed for use in a case study. Hypothetical renewable energy installations on land owned by UT in west Texas were modeled and integrated into the validated campus models along with battery energy storage (BES). Simulations showed that a combination of renewable energy from wind, and optimally controlled 24-hour thermal and battery storage systems could reduce carbon dioxide emissions on campus by 45.4%. The additional retrofit of burner systems to utilize hydrogen natural gas blends resulted in an overall annual emissions reduction of 54.7%. Carbon capture and storage eliminated the majority of the remaining emissions with increased plant energy expenditure. The presented simulations display the practical limitations of a CHP system complemented by renewable generation and short-term storage in eliminating emissions. Furthermore, results highlight the need for further research and development in long duration storage technologies and hydrogen fueled turbines to increase penetration of renewable energy and reduce emissions.

CHP

PNNL-Richland Campus Radionuclide Air Emissions Report for Calendar Year 2024

This report documents radionuclide air emissions that result in the 2024 highest effective dose equivalent (EDE) to an offsite member of the public, referred to as the maximally exposed individual (MEI). The report has been prepared in compliance with the Code of Federal Regulations, Title 40, Protection of the Environment, Part 61, National Emission Standards for Hazardous Air Pollutants, Subpart H, “National Emission Standards for Emissions of Radionuclides Other than Radon from Department of Energy Facilities” and Washington Administrative Code Chapter 246-247, “Radiation Protection–Air Emissions.” The total dose to the MEI from all PNNL-Richland campus radionuclide emissions in 2024, including fugitive emissions and radon, is 1.3E-05 mrem (1.3E-07 mSv) EDE, or 100,000 times less than the federal and state standard of 10 mrem/yr, with which the PNNL Richland campus is in compliance. The dose attributable to radon emissions is 4.1E-10 mrem (4.1E-12 mSv) EDE.

40 CFR 61 Subpart H

PNNL Sequim Campus Radionuclide Air Emissions Report for Calendar Year 2025 : Department of Energy – Office of Science Pacific Northwest National Laboratory

The U.S. Department of Energy Office of Science’s Pacific Northwest Site Office has oversight and stewardship duties associated with the Pacific Northwest National Laboratory Sequim Campus. Facility operations include radiological operations with the potential-to-emit low levels of radioactive materials. This report is prepared to document compliance with the 40 CFR Part 61, National Emission Standards for Hazardous Air Pollutants, Subpart H, “National Emission Standards for Emissions of Radionuclides Other than Radon from Department of Energy Facilities,” and Washington Administrative Code Chapter 246-247, Radiation Protection–Air Emissions. The PNNL Sequim Campus is in compliance with the federal and state 10 mrem/yr standard for 2025 operations.

40 CFR 61 Subpart H

PNNL Richland Campus Radionuclide Air Emissions Report for Calendar Year 2025

This report documents radionuclide air emissions that result in the 2025 highest effective dose equivalent (EDE) to an offsite member of the public, referred to as the maximally exposed individual (MEI). The report has been prepared in compliance with the Code of Federal Regulations, Title 40, Protection of the Environment, Part 61, National Emission Standards for Hazardous Air Pollutants, Subpart H, “National Emission Standards for Emissions of Radionuclides Other than Radon from Department of Energy Facilities” and Washington Administrative Code Chapter 246-247, “Radiation Protection–Air Emissions.” The total dose to the MEI from all PNNL Richland Campus radionuclide emissions in 2025, including fugitive emissions and radon, is 1.8E-05 mrem (1.8E-07 mSv) EDE, or more than 100,000 times less than the federal and state standard of 10 mrem/yr, with which the PNNL Richland Campus is in compliance. The dose attributable to radon emissions is 1.5E-13 mrem (1.5E-15 mSv) EDE.

40 CFR 61 Subpart H

Spokane Eco-District Campus Performance Under Alternative Electricity Rates: Benefits for virtual power plant participants and suppliers

Here, the respective benefits for virtual power plant participants and suppliers are revealed and compared under alternative electricity rate structures, including conventional large commercial electricity rates, large commercial electricity rates with special rates for demand-side generation, and dynamic hourly transactive prices. These three scenarios were explored using the capabilities of the Eco-District campus, a virtual power plant in Spokane, Washington, that is supplied electricity by Avista Utilities. The Eco-District Campus was modeled to host solar power generation, battery energy storage, and thermal energy resources that must be coordinated with building heating and cooling needs. First, the electricity supplier’s costs for energy, infrastructure, and energy losses were modeled. Then, the virtual power plant’s performance was modeled while presuming that its manager would minimize its costs under its electricity rate structure. The demand charges of conventional commercial electricity rates managed monthly peak, as would be expected, but hourly dynamic transactive pricing resulted in a striking alignment between the costs incurred by the supplier and the virtual power plant’s energy costs.

Electricity rates

Techno-Economic Analysis for the Addition of Thermal Energy Storage to a Campus With Existing Battery Storage

Rising global temperatures and increasing energy demands pose significant challenges for energy management, particularly in institutional and commercial settings. As cooling needs grow, campuses must balance operational efficiency, cost control, and grid stability. Energy storage solutions, such as thermal energy storage (TES) systems, offer a promising approach to shifting energy consumption from peak to off-peak periods, alleviating peak demand, reducing utility costs, and enhancing grid resilience. When integrated with existing battery energy storage systems (BESS), TES can further optimize load management and improve energy savings, especially in buildings with diverse energy needs. This article presents a techno-economic analysis of integrating a chilled water TES system into the central plant at California State University, Dominguez Hills, which already operates a BESS. We assess three TES sizing strategies—full storage, load leveling, and peak demand limiting—by modeling and simulations based on historical energy loads. Our findings show that we can control TES systems to complement BESS operation, with campus-level load leveling providing the greatest cost savings by reducing peak demands. Furthermore, the study also evaluates the long-term economic viability of TES, considering installation costs, energy savings, and payback periods under varying tariffs. This research offers practical guidance for institutions seeking to enhance energy resilience and reduce operational costs through energy storage solutions.

25 ENERGY STORAGE

Integration and commissioning plan of Full Flow Purifier at Muon Campus

The Full Flow Purifier for Fermilab’s Muon Campus uses a charcoal bed surrounded by a liquid nitrogen jacket to purify up to 240 g/s of helium gas. Fabrication by Ability Engineering Technology Inc. has been completed and the purifier delivered to Fermilab. It is the largest purifier to be used at Fermilab based on both capacity and size. A previous paper discussed the design of purifier for various operational conditions and horizontal shipping. The purifier is designed to withstand 5g force in vertical and 2g force in lateral and longitudinal directions. Transportation experience from vendor to Fermilab and within site is discussed. Integration of the purifier involved design and fabrication of a liquid nitrogen transfer line, regeneration system, and helium piping to connect it to Muon Campus cryogenic system. It also involved establishing electrical, instrumentation and controls connections to the system. Integration of the purifier is discussed in detail. The purifier is to be commissioned using up to 4 MYCOM helium compressors to supply helium and liquid nitrogen supplied by a 15,000 -gallon tank. Actual effectiveness of the 3-stream heat exchanger is to be estimated based on measured temperatures and flow rate. Impurity levels shall be monitored at inlet and outlet of the purifier. Theoretical adsorption capacity of the purifier is calculated based on the measured temperatures and flowrates and is compared to actual adsorption capacity over time.

Subedi, Jeewan [Fermilab]

Integration and commissioning plan of Full Flow Purifier at Muon Campus

The Full Flow Purifier for Fermilab's Muon Campus uses a charcoal bed surrounded by a liquid nitrogen jacket to purify up to 240 g/s of helium gas. Fabrication by Ability Engineering Technology Inc. has been completed and the purifier delivered to Fermilab. It is the largest purifier to be used at Fermilab based on both capacity and size. A previous paper discussed the design of purifier for various operational conditions and horizontal shipping. The purifier is designed to withstand 5g force in vertical and 2g force in lateral and longitudinal directions. Transportation experience from vendor to Fermilab and within site is discussed. Integration of the purifier involved design and fabrication of a liquid nitrogen transfer line, regeneration system, and helium piping to connect it to Muon Campus cryogenic system. It also involved establishing electrical, instrumentation and controls connections to the system. Integration of the purifier is discussed in detail. The purifier is to be commissioned using up to 4 MYCOM helium compressors to supply helium and liquid nitrogen supplied by a 60,000-liter tank. Actual effectiveness of the 3-stream heat exchanger is to be estimated based on measured temperatures and flow rate. Impurity levels will be monitored at inlet and outlet of the purifier. Theoretical adsorption capacity of the purifier is calculated based on the measured temperatures and flowrates and is compared to actual adsorption capacity over time.

Subedi, J. [Fermilab] (ORCID:0009000185837576)

PNNL-Sequim Campus Radionuclide Air Emissions Report for Calendar Year 2024

The U.S. Department of Energy Office of Science’s Pacific Northwest Site Office has oversight and stewardship duties associated with the Pacific Northwest National Laboratory (PNNL) Sequim campus. Facility operations include radiological operations with the potential to emit low levels of radioactive materials.

54 ENVIRONMENTAL SCIENCES

Seven soil endospore forming bacteria from campus woodland fragments

We isolated 7 endospore forming bacteria from campus woodland and sequenced their genomes using Illumina NextSeq. We share the draft genome assemblies for strains Bacillus wiedmanii_SC129, Bacillus pseudomycoides_SC131, Bacillus pumilis_SC133, Peribacillus butanolivorans_SC135, Bacillus thuringiensis_SC136, Priestia megaterium_SC138, and Bacillus wiedmanii_SC141. Draft genomes are between 3645032-5969865 bp and 34.8-41.2 % GC.

59 BASIC BIOLOGICAL SCIENCES

Entanglement-based quantum digital signatures over a deployed campus network: erratum

We correct a minor error in Table 1 and a related minor error in the simulations of the improved system. These revisions result in minor changes to Fig. 6 and Table 1 in [ Opt. Express 32 , 7521 ( 2024 ) 10.1364/OE.510787 ]. These changes do not affect the experimental measurements or the conclusions of the work.

Chapman, Joseph C. (ORCID:0000000233460914)

Mixing Zone Dilution Study for the Pacific Northwest National Laboratory Sequim Campus

In summary, we conducted a plume modeling study to determine the dilutions at regulatory mixing zones for outfall 008 located at MRCL, Sequim. This included an analysis of diffuser and effluent characteristics together with ambient conditions around the outfall. Table 5, summarized the main results for dilution numbers estimated in our study, showing the minimum dilution for acute criteria is 29.8 that occurred for July conditions and the minimum dilution for chronic criteria is 1713.58 under December conditions.

Premathilake, Lakshitha

IM3 Open Source Data Center Atlas

IM3 Open Source Data Center Atlas Description This dataset contains locations of existing data center facilities in the United States. Data center locations were derived from OpenStreetMap (OSM), a crowd-sourced database. Data points from OSM are processed in various ways to determine additional variables provided in the data including: facility area (square feet), associated US county, and US state. This dataset can be used to identify areas of concentrated data center development and inform government and private sector planning strategies for future buildout of data centers and the infrastructure necessary to support it. Usage Notes Validation of OSM-derived data center locations is an ongoing development under the IM3 project, and the database will be updated as new information becomes available. In some instances, both the data center area (e.g., campus) and individual data center buildings are included as overlapping areas in the database. Both values are retained. Data center points, buildings, and campus areas are provided as separate layers in the downloadable data package. Note that data items are not necessarily complete across layers. That is, a specific data center may only be present as a single point geometry in the "point" layer while other data centers are represented in both the campus and building layers. In some cases, data center campuses and/or buildings straddle a county boundary line. Mappings to both counties are retained in the database as separate rows. These data rows will have the same data center id information, but each will have different county information. Crowd-sourced data, by nature, relies on individuals and communities to provide information. As a result, some data may be missing where it has not yet been reported. As we collect information on additional data center locations and as OSM receives additional contributions, the database will be updated to capture additional data points not yet shown. Technical Information Data is available for download under the following formats: GeoPackage (GPKG) CSV Geospatial data is provided in the WGS84 (EPSG:4326) coordinate reference system. The GeoPackage download contains the following layers. See usage notes for more information. "point" "building" "campus" The "point" layer includes all data from OSM that had POINT geometry type (i.e., individual coordinates). The "building" layer includes all OSM data that did not have POINT geometry and where the building tag in the OSM export was neither equal to "no" or null. Data that did not meet the "point" or "building" qualification was assumed to be a facility campus and included in the "campus" layer. The dataset contains the following parameters. Variables provided by OSM are labeled with (OSM-provided). id - unique identification number (OSM-provided with prefix of "node/", "relation/" and similar attributes removed) state - name of US state state_abb - two letter US state abbreviation state_id - state ID number county - name of US county county_id - county ID number ref - reference numbers or codes (OSM-provided) operator - the name of the company, corporation, or person in charge facility (OSM-provided) name - name of facility (OSM-provided) sqft - surface area of facility polygon, measured in square feet. Only available for "building" and "campus" layers lat - latitude of data centroid point lon - longitude of data centroid point type – represented spatial information. One of "point", "building", or "campus". geometry – POLYGON geometry of area footprint (in "campus" and "building" layers) or POINT geometry of locations (in "point" layer). This parameter is not included in the csv download. Attribution Data center locations were derived from OpenStreetMap, which is made available at openstreetmap.org under the Open Database License (ODbL). US state and county boundary information was collected from the US Census Bureau for the year 2024, which is made publicly available at https://www.census.gov/geographies/mapping-files.html Acknowledgment IM3 is a multi-institutional effort led by Pacific Northwest National Laboratory and supported by the U.S. Department of Energy's Office of Science as part of research in MultiSector Dynamics, Earth and Environmental Systems Modeling Program. License The IM3 Open Source Data Center Atlas is made available under the Open Database License: http://opendatacommons.org/licenses/odbl/1.0/. Disclaimer This material was prepared as an account of work sponsored by an agency of the United States Government. Neither the United States Government nor the United States Department of Energy, nor the Contractor, nor any or their employees, nor any jurisdiction or organization that has cooperated in the development of these materials, makes any warranty, express or implied, or assumes any legal liability or responsibility for the accuracy, completeness, or usefulness or any information, apparatus, product, software, or process disclosed, or represents that its use would not infringe privately owned rights. Reference herein to any specific commercial product, process, or service by trade name, trademark, manufacturer, or otherwise does not necessarily constitute or imply its endorsement, recommendation, or favoring by the United States Government or any agency thereof, or Battelle Memorial Institute. The views and opinions of authors expressed herein do not necessarily state or reflect those of the United States Government or any agency thereof. PACIFIC NORTHWEST NATIONAL LABORATORYoperated byBATTELLEfor theUNITED STATES DEPARTMENT OF ENERGYunder Contract DE-AC05-76RL01830

Mongird, Kendall [Pacific Northwest National Labor

IM3 Open Source Data Center Atlas

IM3 Open Source Data Center Atlas Description This dataset contains locations of existing data center facilities in the United States. Data center locations were derived from OpenStreetMap (OSM), a crowd-sourced database. Data points from OSM are processed in various ways to determine additional variables provided in the data including: facility area (square feet), associated US county, and US state. This dataset can be used to identify areas of concentrated data center development and inform government and private sector planning strategies for future buildout of data centers and the infrastructure necessary to support it. Usage Notes Validation of OSM-derived data center locations is an ongoing development under the IM3 project, and the database will be updated as new information becomes available. In some instances, both the data center area (e.g., campus) and individual data center buildings are included as overlapping areas in the database. Both values are retained. Data center points, buildings, and campus areas are provided as separate layers in the downloadable data package. Note that data items are not necessarily complete across layers. That is, a specific data center may only be present as a single point geometry in the "point" layer while other data centers are represented in both the campus and building layers. In some cases, data center campuses and/or buildings straddle a county boundary line. Mappings to both counties are retained in the database as separate rows. These data rows will have the same data center id information, but each will have different county information. Crowd-sourced data, by nature, relies on individuals and communities to provide information. As a result, some data may be missing where it has not yet been reported. As we collect information on additional data center locations and as OSM receives additional contributions, the database will be updated to capture additional data points not yet shown. Data items will occasionally be removed from OSM if they are misidentified, if they no longer exist, if they are duplicates of another item, or similar. For that reason, updated versions of this database may not contain all data center locations included in previous versions. Technical Information Data is available for download under the following formats: GeoPackage (GPKG) CSV Geospatial data is provided in the WGS84 (EPSG:4326) coordinate reference system. The GeoPackage download contains the following layers. See usage notes for more information. "point" "building" "campus" The "point" layer includes all data from OSM that had POINT geometry type (i.e., individual coordinates). The "building" layer includes all OSM data that did not have POINT geometry and where the building tag in the OSM export was neither equal to "no" or null. Data that did not meet the "point" or "building" qualification was assumed to be a facility campus and included in the "campus" layer. The dataset contains the following parameters. Variables provided by OSM are labeled with (OSM-provided). id - unique identification number (OSM-provided with prefix of "node/", "relation/" and similar attributes removed) state - name of US state state_abb - two letter US state abbreviation state_id - state ID number county - name of US county county_id - county ID number ref - reference numbers or codes (OSM-provided) operator - the name of the company, corporation, or person in charge facility (OSM-provided) name - name of facility (OSM-provided) sqft - surface area of facility polygon, measured in square feet. Only available for "building" and "campus" layers lat - latitude of data centroid point lon - longitude of data centroid point type – represented spatial information. One of "point", "building", or "campus". geometry – POLYGON geometry of area footprint (in "campus" and "building" layers) or POINT geometry of locations (in "point" layer). This parameter is not included in the csv download. Attribution Data center locations were derived from OpenStreetMap, which is made available at openstreetmap.org under the Open Database License (ODbL). US state and county boundary information was collected from the US Census Bureau for the year 2024, which is made publicly available at https://www.census.gov/geographies/mapping-files.html Acknowledgment IM3 is a multi-institutional effort led by Pacific Northwest National Laboratory and supported by the U.S. Department of Energy's Office of Science as part of research in MultiSector Dynamics, Earth and Environmental Systems Modeling Program. License The IM3 Open Source Data Center Atlas is made available under the Open Database License: http://opendatacommons.org/licenses/odbl/1.0/. Disclaimer This material was prepared as an account of work sponsored by an agency of the United States Government. Neither the United States Government nor the United States Department of Energy, nor the Contractor, nor any or their employees, nor any jurisdiction or organization that has cooperated in the development of these materials, makes any warranty, express or implied, or assumes any legal liability or responsibility for the accuracy, completeness, or usefulness or any information, apparatus, product, software, or process disclosed, or represents that its use would not infringe privately owned rights. Reference herein to any specific commercial product, process, or service by trade name, trademark, manufacturer, or otherwise does not necessarily constitute or imply its endorsement, recommendation, or favoring by the United States Government or any agency thereof, or Battelle Memorial Institute. The views and opinions of authors expressed herein do not necessarily state or reflect those of the United States Government or any agency thereof. PACIFIC NORTHWEST NATIONAL LABORATORYoperated byBATTELLEfor theUNITED STATES DEPARTMENT OF ENERGYunder Contract DE-AC05-76RL01830

Mongird, Kendall [Pacific Northwest National Labor