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At least 487 records · Page 27

The Heuristic Dynamic Programming Approach in Boost Converters

In this study, a heuristic dynamic programming controller is proposed to control a boost converter. Conventional controllers such as proportional-integral-derivative (PID) or proportional-integral (PI) are designed based on the linearized small-signal model near the operating point. Therefore, the performance of the controller during the start-up, the load change, or the input voltage variation is not optimal since the system model changes by varying the operating point. The heuristic dynamic programming controller optimally controls the boost converter by following the approximate dynamic programming. The advantage of the HDP is that the neural network-based characteristic of the proposed controller enables boost converters to easily cope with large disturbances. An HDP with a well-trained critic and action networks can perform as an optimal controller for the boost converter. To compare the effectiveness of the traditional PI-based and the HDP boost converter, the simulation results are provided.

24 POWER TRANSMISSION AND DISTRIBUTION↗

AmeriFlux FLUXNET-1F US-ICt Imnavait Creek Watershed Tussock Tundra

This is the AmeriFlux Management Project (AMP) created FLUXNET-1F version of the carbon flux data for the site US-ICt Imnavait Creek Watershed Tussock Tundra. This is the FLUXNET version of the carbon flux data for the site US-ICt Imnavait Creek Watershed Tussock Tundra produced by applying the standard ONEFlux (1F) software. Site Description - The Imnavait Creek Watershed Tussock Tundra (Biocomplexity Station) is located near Imnavait Creek in Alaska, north of the Brooks Range in the Kuparuk basin near Lake Toolik and the Toolik Field Station. The Kuparuk River has its headwaters in the Brooks Range and drains through northern Alaska into the Arctic Ocean. Within these headwaters lies the Imnavait basin at an average elevation of 930 m. Water tracks run down the hill in parallel zones with a spacing of approximately 10 m. The Biocomplexity Station was deployed in 2004, and it has been in operation during the melt seasons ever since.

Euskirchen, Eugenie↗

Report on FY 2021 testing in support of integrating Alloy 800H and 2.25Cr-1Mo for EPP analysis

The use of simplified Elastic-Perfectly Plastic (EPP) design methods avoids the complexities and limitations of the elastic analysis approach in evaluating strain limits and creep-fatigue damage for Class A metallic coolant boundary components in ASME Boiler and Pressure Vessel Code, Section III, Division 5, Subsection HB, Subpart B. No stress classification and linearization are required in the EPP methods. Further, the strain limits and creep-fatigue damage evaluation procedures based on elastic analysis results were developed for the reactor operating conditions where uncoupled, rate-independent plasticity and stationary creep can be used to approximate the deformation in the component adequately. But at very high temperatures, the deformation is rate-dependent, and it can only be approximated adequately by unified viscoplastic model. Thus, for example, the elastic analysis approach cannot be used to evaluate strain limits and creep-fatigue damage for Alloy 617 above 650 °C. The EPP methods remove the temperature restriction. They can be used to evaluate strain limits and creep-fatigue damage for the full range of temperatures.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

A Radiation-Shielded, Shallow Underground, Long-Coherence Time Quantum Qubit Concept

Ionizing radiation from ambient radioactivity has been shown to reduce the coherence time of superconducting qubits. Qubit performance can be improved by shielding the system from external radiation: operating the system underground to reduce cosmic rays, and use of lead shielding to reduce ambient gammas. Here we present a design for a lead shield optimized for a dilution refrigerator operating in PNNL's Shallow Underground Laboratory. The shield reduces the ambient gamma flux by approximately 99.8%, so that cosmic ray muons dominate the ionizing radiation input to the qubits.

42 ENGINEERING↗

SCALE Modeling of the Sodium Cooled Fast-Spectrum Advanced Burner Test Reactor

This report documents the modeling and simulation of a sodium-cooled fast reactor (SFR) as part of a U.S. Nuclear Regulatory Commission–sponsored project to assess the modeling and simulation capabilities for accident progression, source term, and consequence analysis for advanced reactor technologies with the Oak Ridge National Laboratory code SCALE and the Sandia National Laboratories (SNL) code MELCOR. Based on publicly available benchmark specifications, a fully heterogeneous 3D SCALE model of the 250 MWth Advanced Burner Test Reactor (ABTR) was developed to demonstrate SCALE’s capabilities for full-core reactivity analysis, fuel inventory prediction, and decay heat analysis of an SFR. The benchmark specifications contain modeling details for the ABTR core at the beginning of equilibrium cycle (BOEC) at operating conditions; they were derived from a 2006 preconceptual design report produced by Argonne National Laboratory. The ABTR was designed to demonstrate reactor-based transmutation of transuranics, that is, to “burn” transuranics recovered from light-water reactor (LWR) spent fuel. The ABTR’s fuel is designed to operate in 4 month cycles using uranium/transuranic (U/TRU) metallic fuel, with a TRU content of approximately 20%, at a conversion ratio of approximately 0.6. Various reactivity calculations were performed with SCALE for the ABTR and, where possible, compared with results available in the open literature. Additionally, SCALE was used to perform a full-core depletion calculation over the 4 month cycle to obtain the nuclide inventory at the end of equilibrium cycle (EOEC). These nuclide inventories, decay heat, power profiles, and reactivity feedback coefficients at EOEC represent the initial conditions for analyzing severe accident scenarios with MELCOR.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

Self-Sustainable IoT-Based Remote Sensing Powered by Energy Harvesting Using Stacked Piezoelectric Transducer and Thermoelectric Generator

We propose a self-powered remote multi-sensing system for traffic sensing which is powered by the collective energy harvested from the mechanical vibration of the road caused by the passing vehicles and from the temperature gradient between the asphalt of the road and the soil underneath. A stacked piezoelectric transducer converts mechanical vibrations into electrical energy and a thermoelectric generator harvests the thermal energy from the thermal gradient. Electrical energy signals from the stacked piezoelectric transducer and the thermoelectric generators are converted into usable DC power to recharge the battery using AC-DC and DC-DC converters working simultaneously. The multi-sensing system comprises an embedded system with a microcontroller that acquires data from the sensors and sends the sensory data to an IoT transceiver which transmits the data as RF packets to an ethernet gateway. The gateway converts the RF packets into Internet Protocol (IP) packets and sends them to a remote server. Laboratory and road-testing results showed over 98% sensory data accuracy with the system functioning solely powered by the energy harvested from the alternative energy sources. The successful maximum transmission distance obtained between the IoT, and the gateway was approximately 1 mile, which is a considerable transmission distance achieved in an urban environment. Successful operation of the self-powered multi-sensing system under both laboratory and road conditions contributes considerably to the fields of energy harvesting and self-powered remote sensing systems. The energy flow chart and efficiency for the steps in the system were found to be mechanical power from vehicles to the energy harvester of 0.25%, stacked PZT transducer efficiency was found to be 37%, and for the TEGs the efficiency is 11%. AC-to-DC and DC-to-DC converters’ efficiencies were found to be 90% and 11%. The wireless communication RF transceiver efficiency was found to be 62.5%.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Need for advanced research reactors for the next-generation reactor physics, analysis tools, and technology

Full text of publication follows. There is an urgent need for design and deployment of advanced research and test reactors in support of design, licensing and operation of advanced power reactors and education of next generation nuclear workforce. Existing research reactors mostly were designed and constructed decades ago with the main objectives of training operators, performing reactor physics experiments, and educating nuclear engineers and scientists. There are already gaps and significant concern about future capabilities for the existing research reactor facilities to address modern instrumentation and/or flexible environments for: performing reactor physics studies for advanced designs which have significantly different core materials forms and compositions, reactor shapes and size; validation of advanced high-fidelity software; development of machine learning algorithms for enhancement of human-machine collaboration in support of reactor monitoring, operation and safeguards; and, effective education of the next-generation workforce. The authors will focus on the need for advanced research reactors to improve and validate fast and accurate simulation tools for high-fidelity modeling and analysis of nuclear reactors in support of their design, optimization, licensing, operation, and monitoring. In the past, simulation tools were limited to relatively coarse models using approximate methodologies that benefited from two main factors: i) allowance for large margins and tolerances; ii) ability to construct prototype (e.g., zero power) reactors for adjustment of approximate methodologies. The next generation reactors have to be designed mainly by using novel high-fidelity computational tools that are accurate and fast, and therefore can be used for parametric studies and uncertainty quantification. To sufficiently demonstrate the accuracy of these tools, advanced research reactors are needed. The authors argue the need for new computational paradigms such as the MRT (Multistage, Response- function Transport) methodology which has resulted in the development of the novel high-fidelity RAPID (Real-time Analysis for Particle-transport and In-situ Detection) code system. Such code systems have to be robust in modeling any complex system, and should be fast and accurate, henceforth their uncertainties can be quantified at reasonable costs. Again, advanced research reactors are needed for the validation of the fidelity and accuracy of new computational tools. (authors)

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

Assessing the Performance and Impact of PV Technologies on Storage in Hybrid Renewable Systems

Traditional monofacial photovoltaic (mPV) systems are commonly adopted and well-documented because of their lower upfront costs in comparison to bifacial photovoltaic (bPV) systems. This study investigates how PV technologies impact energy storage in grid-scale hybrid renewable systems, focusing on optimizing and assessing the performance of mPV and bPV technologies integrated with pumped storage hydropower. Using Ludington City, Michigan as a case study and analyzing real-world data such as solar irradiance, ambient temperature, and utility-scale load profiles, the research highlights the operational and economic benefits of bPV systems. The results reveal that bPV systems can pump approximately 10.38% more water annually to the upper reservoir while achieving a lower levelized cost of energy ($0.0578/kWh for bPV vs. $0.0672/kWh for mPV). This study underscores the outstanding potential of bPV systems in enhancing energy storage and management strategies, contributing to a more sustainable and resilient renewable energy future.

13 HYDRO ENERGY↗

Improved Architectures and Training Algorithms for Deep Operator Networks

Operator learning techniques have recently emerged as a powerful tool for learning maps between infinite-dimensional Banach spaces. Trained under appropriate constraints, they can also be effective in learning the solution operator of partial differential equations (PDEs) in an entirely self-supervised manner. In this work we analyze the training dynamics of deep operator networks (DeepONets) through the lens of Neural Tangent Kernel theory, and reveal a bias that favors the approximation of functions with larger magnitudes. To correct this bias we propose to adaptively re-weight the importance of each training example, and demonstrate how this procedure can effectively balance the magnitude of back-propagated gradients during training via gradient descent. We also propose a novel network architecture that is more resilient to vanishing gradient pathologies. Taken together, our developments provide new insights into the training of DeepONets and consistently improve their predictive accuracy by a factor of 10-50x, demonstrated in the challenging setting of learning PDE solution operators in the absence of paired input-output observations.

97 MATHEMATICS AND COMPUTING↗

A New Era of Nuclear Criticality Experiments: The First 10 Years of Godiva IV Operations at NCERC

The work presented in this paper focuses on the first 10 years (2011–2020) of Godiva IV operations at the National Criticality Experiments Research Center (NCERC). Godiva IV is a fast burst critical assembly constructed of approximately 65 kg of highly enriched uranium fuel alloyed with 1.5% molybdenum for strength. Godiva is one of the last such critical assemblies in the United States and can be used for studies of super-prompt-critical behavior as well as irradiations and demonstrations. An overview of the startup of Godiva IV at NCERC is given followed by a summary of the experiments performed utilizing Godiva IV over the first 10 years of operation at NCERC.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Data-driven reduced-order models for port-Hamiltonian systems with operator inference

Hamiltonian operator inference has been developed in Sharma et al. (2022) to learn structure-preserving reduced-order models (ROMs) for Hamiltonian systems. The method constructs a low-dimensional model using only data and knowledge of the functional form of the Hamiltonian. The resulting ROMs preserve the intrinsic structure of the system, ensuring that the mechanical and physical properties of the system are maintained. In this work, we extend this approach to port-Hamiltonian systems, which generalize Hamiltonian systems by including energy dissipation, external input, and output. Based on snapshots of the system’s state and output, together with the information about the functional form of the Hamiltonian, reduced operators are inferred through optimization and are then used to construct data-driven ROMs. To further alleviate the complexity of evaluating nonlinear terms in the ROMs, a hyper-reduction method via discrete empirical interpolation is applied. Accordingly, we derive error estimates for the ROM approximations of the state and output. Lastly, we demonstrate the structure preservation, as well as the accuracy of the proposed port-Hamiltonian operator inference framework, through numerical experiments on a linear mass–spring-damper problem and a nonlinear Toda lattice problem.

97 MATHEMATICS AND COMPUTING↗

A New Hybrid Quantum-Classical Algorithm for Solving the Unit Commitment Problem

Solving problems related to planning and operations of large-scale power systems is challenging on classical computers due to their inherent nature as mixed-integer and nonlinear problems. Quantum computing provides new avenues to approach these problems. We develop a hybrid quantum-classical algorithm for the Unit Commitment (UC) problem in power systems which aims at minimizing the total cost while optimally allocating generating units to meet the hourly demand of the power loads. The hybrid algorithm combines a variational quantum algorithm (VQA) with a classical Benders-type heuristic. The resulting algorithm computes approximate solutions to UC in three stages: i) a collection of UC vectors capable meeting the power demand with lowest possible operating costs is generated based on VQA; ii) a classical sequential least squares programming (SLSQP) routine is leveraged to find the optimal power level corresponding to a predetermined number of candidate vectors; iii) in the last stage, the approximate solution of UC along with generating units power level combination is given. To demonstrate the effectiveness of the presented method, three different systems with 3 generating units, 10 generating units, and 26 generating units were tested for different time periods. In addition, convergence of the hybrid quantum-classical algorithm for select time periods is proven out on IonQ's Forte system.

Aboumrad, Willie [IonQ, Inc]↗

Unraveling the conundrum of electronic leakage in protonic ceramic cells: Operation-specific insights and rational design strategies

Electronic conduction through proton-conducting electrolytes significantly impairs the efficiency of protonic ceramic cells (PCCs). Here, in this study, we explore the electron and ion mixed transport properties of four common protonic ceramics, BaZr 0.8 Y 0.2 O 3-δ (BZY82), BaZr 0.7 Ce 0.2 Y 0.1 O 3-δ (BZCY721), BaZr 04 Ce 0.4 Y 0.1 Yb 0.1 O 3-δ (BZCYYb4411), and BaZr 0.1 Ce 0.7 Y 0.1 Yb 0.1 O 3-δ (BZCYYb1711). It marks the first instance of investigating these properties under operation-specific scenarios: fuel side of electrolysis cell, air side of electrolysis cell, fuel side of fuel cell, and air side of the fuel cell. BZCYYb1711 exhibits the highest ionic conductivity, but two to three times higher electronic leakage when exposed to oxygen-containing environments than the others. BZY82 exhibits approximately two times higher electronic leakage in a hydrogen-containing environment. BZCY721 demonstrates excellent ion transport numbers (~0.95) across these four operating conditions. BZCYYb4411 behaves quite similarly to BZCY721. The most challenging operating environment for all candidates is the air side of fuel cell mode. This mode leads to a high initial electronic leakage, followed by a significant increase with polarization. The probable cause for this behavior is a H 2 -free, polarization-induced reduction that leads to the formation of V$^•_O$. The electron small polaron associated with V$^•_O$ is released by the electrical field due to the Poole-Frenkel effect. ZnO and NiO sintering aids are found to be detrimental to the ionic conductivity of the electrolytes. In particular, NiO substantially lowers the ion transport number. The correlation of the operation-specific electronic leakage to full cells is discussed. It is suggested that a rational PCC design should synergistically couple BZCYYb1711 at fuel side with BZCY4411 at air side to deliver a well-balanced performance and faradaic efficiency simultaneously, and the high temperature sintering process with a NiO fuel electrode should be shortened or replaced by ultra-fast sintering techniques or using a fuel electrode scaffold-infiltration fabrication strategy.

42 ENGINEERING↗

AGR-5/6/7 Irradiation Test Final As-run Report

This document presents the as-run analysis of the Advanced Gas Reactor (AGR)-5/6/7 irradiation experiment. AGR-5/6/7 is the last of a series of experiments conducted in the Advanced Test Reactor (ATR) at Idaho National Laboratory in support of the development and qualification of tri-structural isotropic low-enriched fuel for use in high-temperature gas-cooled reactors. The test train contained five separate capsules that were independently controlled and monitored. Each capsule contained multiple 24.91-mm-long and 12.25-mm-dimeter compacts filled with low-enriched uranium carbide/oxide tri-structural isotropic fuel particles. The objectives of the AGR-5/6/7 experiment were to: • Irradiate reference-design fuel particles to support fuel qualification. • Establish operating margins for the fuel, beyond normal operating conditions. • Provide irradiated-fuel performance data and irradiated-fuel samples for post-irradiation examination and safety testing. The primary objective of the AGR-5/6 test (Capsules 1, 2, 4, and 5) was to verify the successful performance of the reference-design fuel under normal operating conditions. The AGR-7 test (Capsule 3) was designed to explore fuel performance at higher temperatures. Its primary objective was to demonstrate the capability of the fuel to withstand conditions beyond normal operating conditions, in support of plant design and licensing. AGR-5/6/7 will also provide irradiated-fuel performance data based on the fission gas release from particles during irradiation. To achieve the test objectives, the AGR-5/6/7 experiment was irradiated in the northeast flux trap of the ATR with a planned duration of 500 effective full-power days. The northeast flux trap was selected because its larger diameter provided greater flexibility for test-train design compared to the Large B positions used for the AGR-1 and AGR-2 irradiations, significantly enhancing test capabilities for the combined irradiation campaigns. Due to delays in the ATR schedule, the AGR-5/6/7 irradiation was significantly shorter than the originally planned 13-cycle schedule. Irradiation began on February 16, 2018 and ended on July 22, 2020, spanning nine ATR cycles (162B–168A) over two and a half years. Thus, the AGR-5/6/7 fuel compacts were irradiated for a total of approximately 360.9 effective full-power days. Final burnup values, on a per-compact basis, ranged from 5.66 to 15.26% fissions per initial heavy metal atom, while fast fluence values ranged from 1.62 to 5.55 × 1025 n/m2 (E >0.18 MeV). Time-averaged volume-averaged fuel temperatures on a capsule basis at the end of irradiation ranged from 756°C in Capsule 5 to 1313°C in Capsule 3 excluding days with significantly lower temperature during the two short powered axial locator mechanism cycles, 163A and 167A. By the end of irradiation, 48 out of 54 installed thermocouples had failed (the bottom three capsules lost all thermocouples). During the first five cycles (162B – 165A), the fission-gas isotope release-rate-to-birthrate (R/B) ratios were stable in the 10-8–10-6 range, and no in-pile particle failures were observed based on the gross gamma counts. During this time, the high exposed kernel fraction and high fuel particle temperatures in Capsule 1 led to a maximum R/B value of around 2 ? 10-6 for Kr-85m. The fission gas release in all capsules started to increase from the second half of Cycle 166A, when a large number of in-pile particle failures occurred in Capsule 1 and a gas line problem in this capsule caused fission gas leakage at various degrees into the other four capsules. This gas line problem also prevented a fission gas release measurement for Capsule 1 during the last three cycles due to gas flow isolation. By the end of irradiation, it is estimated that approximately 15 particles failed in Capsule 3, which was considered possible because the experiment was designed to operate beyond the high-temperature gas-cooled reactor normal operating temperature range. A few hundred in-pile particle failures were estimated for Capsule 1 by the end of Cycle 166A, but the total number of failures is unknown due to the lack of fission gas release data in the later cycles. Additionally, four potential in-pile failures were identified for Capsule 2 during the last cycle, Cycle 168A. In contrast, no in-pile failures were identified in the top two capsules (4 and 5) based on the absence of the typical spikes in gross gamma counts and low failure estimates using the AGR-3/4 R/B per exposed kernel model.

11 - NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Expert and operator perspectives on barriers to energy efficiency in data centers

Abstract It was last estimated in 2016 that data centers (DCs) comprise approximately 2% of total US electricity consumption. However, this estimate is currently being updated to account for the massive increase in computing needs due to streaming, cryptocurrency, and artificial intelligence (AI). To prevent energy consumption that tracks with increasing computing needs, it is imperative we identify energy efficiency strategies and investments beyond the low-hanging fruit solutions. In a two-phased research approach, we ask: What non-technical barriers still impede energy efficiency (EE) practices and investments in the data center sector, and what can be done to overcome these barriers? In particular, we are focused on social and organizational barriers to EE. In Phase I, we performed a literature review and found that technical solutions are abundant in the literature, but fail to address the top-down cultural shifts that need to take place in order to adapt new energy efficiency strategies. In Phase II, reported here, we interviewed 16 data center operators/experts to ground-truth our literature findings. Our interview protocols focus on three aspects of DC decision-making: procurement practices, metrics and monitoring, and perceived barriers to energy efficiency. We find that vendors are the key drivers of procurement decisions, advanced efficiency metrics are facility-specific, and there is convergence in the design of advanced facilities due to the heat density of parallelized infrastructure. Our ultimate goals for our research are to design DC decarbonization policies that target organizational structure, empower individual staff, and foster a supportive external market.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Oxidation of Glycolate in the Defense Waste Processing Facility (DWPF) Recycle Collection Tank - 20305

The Savannah River Site's Defense Waste Processing Facility (DWPF) operations are being upgraded with the introduction of the Nitric-Glycolic Flowsheet. Glycolic acid has been shown superior to formic acid as the reducing acid used during chemical processing. The new flowsheet improves or maintains necessary parameters such as 1) reduction of mercury, 2) adjustment of feed rheology and 3) adjustment of melter oxidation/reduction potential. Further, the potential for catalytic hydrogen generation in DWPF processing is virtually eliminated. DWPF process condensates are collected and returned to the SRS Concentration, Storage and Transfer Facilities (CSTF). The Recycle Collection Tank (RCT) collects off-gas condensate during chemical processing, vitrification, and other unit operations performed in DWPF and is the singular return vessel delivering recycle effluent back to CSTF. Each batch of recycle may contain a small amount of glycolate from chemical processing and melter off-gas condensates. To avoid potential flammability issues due to thermolysis of glycolate in the CSTF, chemical oxidation within the RCT has been investigated as an option for mitigating the transfer of glycolate. Sodium permanganate has been down-selected as the best option for oxidation of glycolate. Testing was performed using both 2-L and 22-L reactors (16,800:1 and 1,530:1 scale by volume) with non-radioactive waste simulants to approximate the expected RCT compositions. RCT simulants were evaluated at various process pH and temperature conditions. Also, RCT operations, namely the sequence of addition of corrosion inhibitors (NaOH and NaNO{sub 2}) versus a permanganate strike, were evaluated. Glycolate was introduced via a sludge simulant to mimic both expected entrainment and abnormal process foam-over conditions - the range being between 68 and 5100 mg/kg glycolate. Glycolate destruction was monitored by ion chromatography (IC). The corresponding manganese behavior was monitored in real-time using in situ ultraviolet-visible (UV-Vis) spectroscopy. RCT glycolate content can be reduced to below the IC detection limit within 90 minutes for all concentrations investigated. Ion Chromatography analysis revealed that under alkaline conditions, glycolate is primarily oxidized to oxalate with no significant formation of CO{sub 2} or carbonate, and nitrite is not oxidized to nitrate. Initially, complete oxidation of organics species and nitrite was assumed. Determination of the mechanistic chemical reaction has allowed the required amount of permanganate to be more accurately predicted and the total addition to be significantly reduced. UV-Vis measurements reveal that permanganate (Mn{sup 7+}) is reduced to manganate (Mn{sup 6+}) in the RCT. The oxidant stoichiometry is defined by using the initial permanganate to glycolate (P/G) molar ratio. At low initial glycolate concentration (68 and 140 mg/kg), the minimum required initial permanganate to glycolate (P/G) molar ratio was found to be 5-6. With high initial glycolate concentrations (5100 mg/kg) a lower (P/G) molar ratio of ∼2.5 was needed. The final portion of this effort supporting the nitric/glycolic flowsheet will be to test actual (fully radioactive) RCT samples as per the above simulant tests. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

Cycle-by-cycle Delay Estimation at Signalized Intersections by using Machine Learning and Simulated Video Detection Data

Accurate estimation of delay is crucial for efficient traffic signal operations. Estimation of delay in the real-time manner using traditional loop detectors requires advanced detectors (in addition to stop-bar detection). In cases when this detection layout is not in place, delay estimates are approximated with a lower accuracy. Video detection is one of the most frequently deployed detection systems at signalized intersections in recent years. In most cases video detection operates in the same way as traditional inductive loops. However, when coupled with computer vision algorithms, video detection systems could be used to retrieve additional information (e.g., vehicular arrivals and departures) that cannot be taken out from the conventional systems (e.g., long stop-bar loop detectors). Although present for several decades, video detection data were not frequently examined for delay estimation purposes. In this study, we proposed a novel delay estimation model which can be developed with only data from stop-bar video detectors. Relevant data were collected from a simulation model of 11 signalized intersections at downtown Chattanooga, TN and processed to create needed inputs for model development. With the use of multigene genetic programming the authors developed a delay model that outperforms accuracy of multi regression model. Furthermore, authors evaluated the developed model by comparison with the other benchmark delay models, such as HCM and approach delay model. It was found that the developed MGGP delay model outperforms benchmark models for a wide range of traffic and signal operation conditions.

Erdagi, Ismet Goksad↗

Tri-Sectional Approximation of the Shortest Path to Long-Term Voltage Stability Boundary with Distributed Energy Resources

Ensuring long-term voltage stability is critical for reliable operations of power grids. High share of distributed energy resources (DERs) can create complicated system operation modes that may invalidate the traditional long-term voltage stability analysis based on typical operation modes. To address this challenge, this paper investigates how to compute the shortest path to the voltage stability boundary in the DER aggregated load space with large dispersion. Instead of working in the Euclidean space, we establish the analysis and computations on the algebraic power flow manifold to better capture the curvature change of the shortest path along the direction of losing stability. A modified optimal control framework is presented for obtaining the ground-truth of the smooth shortest path on the manifold. To efficiently and accurately solve for the shortest path, we further leverage the geometric features of the power flow manifold and propose a tri-sectional approximation model that is scalable for large-scale systems. Several numerical examples, up to the 1354-bus system, with different DER penetration levels and high dimensional renewable power injection variations are evaluated. The simulation results demonstrate that the tri-sectional approximation achieves high accuracy and efficiency to approximate the shortest path to the voltage stability boundary.

24 POWER TRANSMISSION AND DISTRIBUTION↗