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ARPA-E PERFORM datasets

Time-coincident load, wind, and solar data including actual and probabilistic forecast datasets at 5-min resolution for ERCOT, MISO, NYISO, and SPP. Wind and solar profiles are supplied for existing sites as well as planned sites based on interconnection queue projects as of 2021. For ERCOT actuals are provided for 2017 and 2018 and forecasts for 2018, and for the remaining ISOs actuals are provided for 2018 and 2019 and forecasts for 2019. There datasets were produced by NREL as part of the ARPA-E PERFORM project, an ARPA-E funded program that aim to use time-coincident power and load seeks to develop innovative management systems that represent the relative delivery risk of each asset and balance the collective risk of all assets across the grid. For more information on the datasets and methods used to generate them see https://github.com/PERFORM-Forecasts/documentation.

5-min data↗

Solar, Wind, and Load Forecasting Dataset for MISO, NYISO, and SPP Balancing Areas

The Performance-based Energy Resource Feedback, Optimization, and Risk Management (PERFORM) program is an initiative intended to foster "a fundamental shift in grid management rooted in an understanding of asset risk and system risk" (ARPA-E 2020). Launched by the Advanced Research Projects Agency-Energy (ARPA-E), the program supports efforts to incorporate uncertainty in electric power decision making. In support of PERFORM, the National Renewable Energy Laboratory (NREL) has produced a set of time-coincident forecasts of solar, wind, and load profiles. As part of Phase I of the PERFORM effort, NREL created a dataset that consists of one year of time-coincident load, wind, and solar actuals and probabilistic forecasts based on data from the Electric Reliability Council of Texas (ERCOT) (Bryce et al. 2023). In Phase II, NREL developed similar datasets for three other U.S. Independent System Operators (ISO): the Midcontinent Independent System Operator (MISO), the New York Independent System Operator (NYISO), and the Southwest Power Pool (SPP).

24 POWER TRANSMISSION AND DISTRIBUTION↗

Solar PV, Wind Generation, and Load Forecasting Dataset for ERCOT 2018: Performance-Based Energy Resource Feedback, Optimization, and Risk Management (P.E.R.F.O.R.M.)

This report describes the Advanced Research Projects Agency-Energy Performance-Based Energy Resource Feedback, Optimization, and Risk Management (PERFORM) Electric Reliability Council of Texas (ERCOT) dataset consisting of load, solar, and wind deterministic and probabilistic forecasts at three timescales. This dataset consists of 1 year of time-coincident load, wind, and solar actuals and probabilistic forecasts for a region similar to ERCOT. All the data are stored in Hierarchical Data Format 5 (HDF5) files and have been uploaded to an Amazon Web Services repository. The ERCOT data set has 2 years (2017, 2018) of actuals and 1 year (2018) of probabilistic forecasts. These data are provided at various spatial (i.e., site-level, zone-level, and system-level) and temporal scales (i.e., day-ahead, intraday, and intra-hour). Specifically, data are provided for 125 existing wind sites, 22 existing solar sites, 139 proposed wind sites, and 204 proposed solar sites.

14 SOLAR ENERGY↗

A Cryogenic Muon Tagging System Integrated with a Superconducting Qubit Device for Radiation-Induced Error Mitigation

Superconducting qubits are highly sensitive to ionizing radiation, which can induce correlated errors and limit scalable fault-tolerant quantum computing. In particular, cosmic-ray muons can deposit energy in the substrate, generating phonon bursts that break Cooper pairs and produce quasiparticles, leading to correlated decoherence events across multiple qubits. We present the development of a cryogenic muon tagging system based on Kinetic Inductance Detectors (KIDs) and its integration with superconducting quantum hardware. Originally developed within the ACE-SuperQ project and validated as a standalone detector, the system demonstrated a muon tagging efficiency of approximately 90% and excellent agreement with Monte Carlo simulations. Building on this validation, the tagging system has been integrated with a multi-qubit superconducting chip operated in a dilution refrigerator. The detector configuration consists of a multi-layer KID stack arranged above and below the quantum device, enabling time-coincident identification of muon-induced events within the same cryogenic environment. The integrated setup has been successfully commissioned, enabling simultaneous operation of the qubit chip and the muon tagging system. A first measurement campaign has been carried out, and preliminary data show time-correlated events between the muon tagging detectors and the qubit readout. A quantitative analysis of radiation-induced effects on qubit performance is currently ongoing. This work represents a step toward the implementation of event-level radiation tagging as a tool for characterizing and potentially mitigating correlated errors in superconducting quantum processors, while establishing a modular platform for future studies at the interface between particle physics and quantum information science.

Roy, Tanay [Fermilab] (ORCID:000000019442862X)↗

A Search for Correlated Low-energy Electron Antineutrinos in KamLAND with Gamma-Ray Bursts

We present the results of a time-coincident event search for low-energy electron antineutrinos in the KamLAND detector with gamma-ray bursts (GRBs) from the Gamma-ray Coordinates Network and Fermi Gamma-ray Burst Monitor. Using a variable coincidence time window of ±500 s plus the duration of each GRB, no statistically significant excess above the background is observed. We place the world’s most stringent 90% confidence level upper limit on the electron antineutrino fluence below 17.5 MeV. Assuming a Fermi–Dirac neutrino energy spectrum from the GRB source, we use the available redshift data to constrain the electron antineutrino luminosity and effective temperature.

79 ASTRONOMY AND ASTROPHYSICS↗

New Experiments for Detecting Emissions from Fission

Ensuring that nuclear science and technology is used solely for peaceful purposes is one of the most pressing challenges facing our society. The Consortium for Monitoring, Technology, and Verification (MTV) mission is to help meet this challenge by providing advanced technology and trained talent for careers in nuclear security and nonproliferation. The study of nuclear fission is one area of interest in the MTV. We are performing new experiments for the characterization of neutron and gamma ray emissions from fission fragments. These emissions are signatures for the detection and characterization of nuclear materials. To perform these experiments, we have developed Fission Sphere (FS-3), an array of forty organic stilbene detectors operated in time-coincidence. The FS-3 is used to measure the prompt emissions of neutrons and gamma rays from Cf-252 spontaneous fission. These new data will be used to validate physics-based prediction codes, including CGMF and FREYA, and will be useful in future ENDF and ENSDF evaluations. This paper will present results from the first experiments using FS-3 and a Cf-252 spontaneous fission source. It will compare the experimental results with predictions from theory and Monte Carlo simulation. Specifically, we will describe the correlations among energy, multiplicity, and angles of emitted particles. We will also discuss the application of these correlations in multiplicity counting techniques, which are widely used in nuclear safeguards.

Pozzi, S. A.↗