Developing Process Models and Refining Code Capabilities:Comparing COMSOL and PFLOTRAN.
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EPRI formed a working group of utilities and software vendors called the Distribution Advanced PV Model Working Group (DAWG). The working group has been focused on building consensus regarding the models that represent the reactive power capabilities outlined in Section 5 of IEEE Std 1547™-2018. This report provides an overview of the reactive and active power capabilities specified in IEEE Std 1547™-2018 and outlines a specification of key functions for usage during steady state snapshot and time series power flow analysis. Additionally, it presents a framework for performing tests to verify the correct operation of functions during power flow analysis.
Abstract not provided.
A method for digital image segmentation is provided. The method comprises training a neural network for image segmentation with a labeled training dataset from a first domain, wherein a subset of nodes in the neural net are dropped out during training. The neural network receives image data from a second, different domain. A vector of N values that sum to 1 is calculated for each image element, wherein each value represents an image segmentation class. A label is assigned to each image element according to the class with the highest value in the vector. Multiple inferences are performed with active dropout layers for each image element, and an uncertainty value is generated for each image element. The label of any image element with an uncertainty value above a predefined threshold is replaced with a new label corresponding to the class with the next highest value.
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Integration of renewable generation, which is often intermittent and decentralized, substantially increases the stochasticity and complexity of power grid operations. Future power systems planning will require significant computational capability to evaluate balance between demand and supply under varying conditions, both temporally and spatially. The standard approach for generation unit commitment is to use mixed-integer linear programming to find the optimal generation schedule considering ramping and generator constraints. In the future grid this poses computational scalability challenges because generation and demand are not known with certainty due to stochasticity in weather and complexity of the grid. To address this challenge, we present a data-driven unit commitment approach that can efficiently include stochastic weather impacts and contingency considerations to improve unit commitment. Our approach uses graph-based data analytics techniques on solutions to the security constrained (and possibly stochastic) economic dispatch problem to identify potential improvements to a given unit commitment. Recent breakthroughs in fully-parallel stochastic economic dispatch software allow this approach to be scalably deployed. Simulations on synthetic South Carolina and Texas grids show this method can improve grid reliability with security constraints over a set of contingencies, while also meaningfully lowering total generation cost.
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In the wake of the Fukushima Daiichi nuclear power plant accident in 2011, the accident tolerant fuels (ATF) program was initiated to enhance the safety of light-water reactor fuels, placing significant emphasis on cladding. A crucial step for the broad implementation of ATF in commercial reactors involves irradiation testing of the fuel designs. ATF-2D, the latest experiment in the ATF series, is slated to undergo irradiation in the Advanced Test Reactor (ATR) at Idaho National Laboratory (INL). ATF-2D is a joint effort of the INL with industry partners General Electric Global Research; Framatome; General Atomics; the Japan Atomic Energy Agency; Hitachi-GE Nuclear Energy, Ltd; Global Nuclear Fuel-Japan Co., Ltd; Nippon Nuclear Fuel Development Co., Ltd; and Mitsubishi Heavy Industries, Ltd. The ATF-2D test train design consists of four tiers, each housing six rodlets. The device will be inserted in Loop 2A within the central flux trap of the ATR, and is anticipated to undergo irradiation throughout three 60-day cycles. Typical pressurized water reactor conditions will be emulated during the irradiation. The objective of the work presented here is to dimension neutron-absorbing hafnium (Hf) components surrounding the fuel rodlets, such that the axial power profile is flattened, while simultaneously ensuring that the total fission power output of the entire test train remains below 200 kW.
In the wake of the Fukushima Daiichi nuclear power plant accident in 2011, the accident tolerant fuels (ATF) program was initiated to enhance the safety of light-water reactor fuels, placing significant emphasis on cladding. A crucial step for the broad implementation of ATF in commercial reactors involves irradiation testing of the fuel designs. ATF-2D, the latest experiment in the ATF series, is slated to undergo irradiation in the Advanced Test Reactor (ATR) at Idaho National Laboratory (INL). ATF-2D is a joint effort of the INL with industry partners General Electric Global Research; Framatome; General Atomics; the Japan Atomic Energy Agency; Hitachi-GE Nuclear Energy, Ltd; Global Nuclear Fuel-Japan Co., Ltd; Nippon Nuclear Fuel Development Co., Ltd; and Mitsubishi Heavy Industries, Ltd. The ATF-2D test train design consists of four tiers, each housing six rodlets. The device will be inserted in Loop 2A within the central flux trap of the ATR, and is anticipated to undergo irradiation throughout three 60-day cycles. Typical pressurized water reactor conditions will be emulated during the irradiation. The objective of the work presented here is to dimension neutron-absorbing hafnium (Hf) components surrounding the fuel rodlets, such that the axial power profile is flattened, while simultaneously ensuring that the total fission power output of the entire test train remains below 200 kW.
The Broadband Reflector Experiment for Axion Detection (BREAD) is an ongoing collaboration searching for the conversion of yet undiscovered axion-like dark matter particles to photons in the presence of a magnetic field. InfraBREAD, an experiment of BREAD, uses a superconducting nanowire single photon detector (SNSPD), a high-efficiency and low-noise device, to specifically detect infrared-range photons produced by $\mathcal{O}$(eV) axion-like particles. The unique BREAD reflector setup allows for the focusing of converted signal photons to a 1mm $\times$ 1mm SNSPD. However, when the detector is cooled to cryogenic temperatures during operation, uneven thermal contraction of reflector components may lead to a small shift in the location of the focal spot. A novel calibration method using blackbody radiation is proposed to locate the true focal spot of the detector \textit{in situ}. Through ray tracing simulations done in FRED Optical Engineering Software, this method is demonstrated to locate the focus to within $\SI{50}{\micro\metre}$ in the $z$ dimension.
Work conducted in FY23 identified that RELAP5-3D was capable of reproducing trends in HTTF data during experiment PG-27 but was incapable of reproducing measured values. The primary cause of this discrepancy between RELAP5-3D results and experimental data was hypothesized to be a distortion in power density that was introduced by the radial nodalization of the model. We further hypothesized that a new model would provide better results when compared to the experiments PG-27 and PG-29. Work this FY developed a new model that is better capable of capturing local heat generation rates and contains a representation of each 1/6 azimuthal sector of the core. We used this model to develop a new set of solutions to Exercises 1 and 2 of Problems 2 and 3 in the benchmark. In this report, we present the first comprehensive comparison of the results between the two models. We see that in Exercise 1A, which is common between problems 2 and 3, the results are similar, though the results from the new model show greater detail than those from the legacy model. In Problem 2 Exercise 1B and Problem 3 Exercise 1B, we see that heat removal is slower in the new model than the legacy model. Problem 3 Exercise 1C shows temperatures that are lower in most places in the new model than the legacy model, but the area with active heat generation has higher block temperatures in the new model than the legacy model. Problem 3 Exercise 1D further shows that long-term heat removal is lower in the new model. Problem 2 Exercise 1C demonstrated that the new model observes higher temperatures in the core regions than the legacy model, justifying the need to preserve the power density in HTTF. The validation of PG-27 and PG-29 also demonstrated the improved temperature agreement in the core regions, particularly with a calibrated model that implements an effective thermal conductivity for the core material. Overall, PG-27 models show reasonable to excellent agreement for steady-state temperatures and minimal to reasonable agreement for transients. PG-29 models showed minimal to insufficient agreement with the data.