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At least 379 records · Page 21

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DOE OSTI2020

A New Process for Carbon Dioxide Conversion to Fuel

In this project, TDA developed a new mixed metal oxide-based sorbent that converts CO 2 (captured from coal fired power plant) to CO, which can then be combined with renewable H 2 generated by water electrolysis to produce different liquid fuels. TDA’s absorbent-based CO 2 conversion process uses a redox process, which splits the reverse water gas shift reaction steps into two stages: CO 2 reduction to CO and H 2 oxidation to H 2 O and eliminates the equilibrium limitations. The CO produced in the two-stage reactor system can then be further reacted with renewable H 2 to produce methanol, naphtha, diesel, or gasoline. We worked with the Gas Technology Institute (GTI) and Advanced Power & Energy Program (APEP) of University of California, Irvine (UCI) to design and develop the liquid fuel synthesis process that is built around this new material. We demonstrated the techno-economic viability of the new sorbent based redox process to convert CO 2 into synthesis gas by: 1) demonstrating continuous carbon dioxide reduction in a prototype test system for over 500 hours while converting up to 0.4 kg CO 2 /day. With the successful completion of the R&D effort, the technology is now ready for a larger pilot-scale demonstration and the technology readiness has been raised from TRL 3 to TRL 5. In collaboration UCI, we also completed a high-fidelity process design and economic analysis. The required selling price (RSP) for methanol (Case 1 H2-MeOH) is $\$$3.06/gal, naphtha and diesel (Case 2 H2-FT) are $\$$6.21/gal and $\$$8.91/gal, and for gasoline (Case 3 H2-MTG) is $\$$6.96/gal on a 2011 dollar basis. To put these costs in perspective, the recent (June 2020) U.S. price for methanol made from natural gas is about $\$$1.19/gal according to Methanex, a major methanol producer in North America. The recent (June 2, 2020) California prices for gasoline and diesel with California’s strict specifications are $\$$3.35/gal and $\$$3.73/gal according to the U.S. Energy Information Agency. On the other hand, it should be noted that the gasoline and diesel produced by the designs of Case 2 and Case 3 would be both nitrogen and sulfur free. These RSPs are based on a cost of imported electricity of $\$$64/MWh based on the low-end current wind generated electricity cost (Genevieve and Ramsden, Wind Electrolysis: Hydrogen Cost Optimization, Technical Report, June 2011, NREL/TP-5600-50408). This cost is by far the largest component of the variable costs used in computing the RSPs. The cost of the imported electricity has to approach zero for the RSP to be competitive for methanol produced in Case 1 and naphtha and diesel produced in Case 2 while the cost of electricity has to be less than $\$$10/MWh for gasoline produced in Case 3.

01 COAL, LIGNITE, AND PEAT↗

DOE OSTI2020

Model-less Source Location for Forced Oscillation based on Synchrophasor and Moving Fast Fourier Transformation

Forced oscillations in power systems occur when the grid is driven by an external and periodic force. To quickly detect and locate the source of the forced oscillation is critical in terms of ensuring the reliability of an interconnected power grid. This paper explores the electromechanical wave propagation theory and the Fast Fourier Transformation to analyze the forced oscillations. It proposes a model-less, adaptive, fast, and accurate source location algorithm. The proposed algorithm is extensively evaluated through simulation data from a 70k-bus U.S. Eastern Interconnection test system and field-collected synchrophasor data from the distribution-level wide-area monitoring system, FNET/GridEye. The evaluation results demonstrate the correctness and effectiveness of the proposed model-less forced oscillation source location algorithm.

Wang, Weikang↗

DOE OSTI2025

Frequency Control and Disturbance Containment Using Grid-Forming Embedded Storage Networks

The paper presents a distributed approach for operating a network of inverter-based energy storage resources embedded in a bulk power system. Departing from their traditional role of steady-state reserves, the storage assets in the network are utilized as frequency-responsive resources shaping system dynamics. The power electronics converter systems interfacing the storage resources are equipped with local controllers designed to respond under transient disturbances. To this end, a safety-constrained distributed control strategy is explored. The paper compares the performance of converter-interfaced grid-forming and grid-following storage networks for fast frequency control and disturbance containment/localization. Sensitivity studies are performed to study the impact of storage size, steady-state dispatch, and controller design on dynamic performance. The findings are presented through case studies with results from the IEEE test systems.

Chatterjee, Kaustav (ORCID:0000000153273860)↗

DOE OSTI2024

A Transactive Approach for Service Restoration Utilizing Customer Load Flexibility and Grid-Edge Resources

This paper develops a transactive energy system model to restore electricity to customers in an isolated distribution system after an outage. The model is developed to engage a variety of customer types - prosumers, flexible loads, critical/noncritical customers, and distributed generators - as active participants in the restoration process. Unlike many existing transactive approaches, the proposed model is developed for service restoration and accounts for various customer types and their autonomy and privacy through an iterative approach to determine the optimal market price, while maintaining systemlevel power flow and voltage constraints. The advantages of the proposed approach are numerically validated on a modified IEEE 123-bus test system.

distributed energy resources↗

DOE OSTI2024

Transient Stability Enhancement via a Scalable RL Method with VSG Parameter Tuning

This paper presents a reinforcement learning (RL)-driven strategy to improve the transient stability of power systems via tuning parameters of multiple virtual synchronous generators (VSGs). We proposed a scalable method to support RL training convergence probability and speed, even when a large number of contingencies are considered. The proposed scalable RL framework first decomposes the large number of contingencies into multiple groups and then conducts parallel training for each group, decreasing the state space and complexity of each training. Additionally, we propose a contingency grouping algorithm to streamline the RL action space and facilitate the training. The proposed method is validated across various standard test systems.

Huang, Xiaoge↗

DOE OSTI2026

Vitrification of inorganic ion exchange media

The primary objective of these tests outlined in the Test Plan for this work [15] and described herein was to demonstrate the vitrification of ion exchange media for cesium removal, either alone or in combination with a representative Hanford HLW stream. This included one formulation with chabazite as the only waste component and two formulations containing direct-feed fully washed AY-102 HLW solids combined with either CST or chabazite. Feed processing characteristics, glass production rate, melter emissions, and feed carryover were determined for each of the three feed compositions. This was accomplished through VGF and DM100 melter system testing.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

DOE OSTI2024

Performance Demonstration of an Occupancy Sensor-enabled Integrated Solution for Commercial Buildings

Traditionally, a single-loop fixed-gain controller is applied to supply fan (SF) and cooling coil (CC) valve controls while a fixed-damper position control is applied to outdoor air (OA) damper control at air handling units (AHUs) in commercial buildings. With the increasing application of occupancy sensors, the information generated by occupancy sensors is applied to not only reduce the electricity loads from lighting and controllable plug loads, but also reset OA intake and minimum supply airflow setpoints. Meanwhile, these intermittent operation actions greatly elevate the dynamics of AHU systems, which may introduce unstable SF and CC valve operations and inaccurate OA flow control at AHUs and consequently degrade maximum energy efficiency gains. With virtual fan and valve flow meter technologies, two advanced controls, including cascade control and gain scheduling control, can be implemented on both the SF and CC valve, and an advanced control using a virtual OA flow meter can be implemented on OA damper integrated with occupancy sensors. The goal of this project is to demonstrate the savings, cost, and performance of an integrated solution that integrates the three advanced HVAC controls with occupancy sensors to allow accurate and stable AHU operations in real buildings. The project objectives are to: 1) develop and validate an advance SF control algorithm; 2) develop and validate an advanced CC valve control algorithm; 3) validate an algorithm to implement a virtual OA flow meter; and 4) demonstrate the savings, cost, and performance of the integrated solution in real buildings. The technical approaches are to: 1) select a test system at the University of Oklahoma; 2) develop and implement the algorithms of advanced SF and CC valve controls and validate the performance; 3) develop and implement the advanced OA control using a virtual OA flow meter and validate the performance; 4) demonstrate the savings, cost, and performance of the proposed integrated solution with and without three advanced HVAC controls; and 5) disseminate the project results through publications and presentations. For the SF control, both the gain scheduling and cascade controls can improve the fan energy performance by reducing the fan power during the transient period and the fan control performance at lower speeds by reducing fan speed variation. Moreover, the gain scheduling control provides a simple and low-cost solution and is recommended. The fan power savings can reach 30% in a transient period. For the CC valve control, the gain scheduling control can considerably reduce the supply air temperature oscillation range and frequency under both higher and lower load conditions and the control valve response is much more stable. As a result, the gain scheduling control is recommended. The projected pump energy consumption can be reduced by 68.5%. With the developed virtual OA flow meter, the OA can be accurately controlled at its setpoint, which is determined based on the actual number of occupants in the building provided by occupancy sensors. The RMSE of the proposed OA control is 15.9 L/s. The energy data shows that the fan power and CC cooling energy were significantly reduced. On the other hand, the energy savings majorly results from the occupancy sensors and the energy savings by the advanced HVAC controls is minimal because that the controllers in the test AHU were tuned with very slow response. An annual technical savings potential is estimated as 0.5 quads in the commercial sector.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2021

An investigation into the effects of cyclic strain rate on the high cycle and very high cycle fatigue behaviors of wrought and additively manufactured Inconel 718

Additive Manufacturing (AM) has increasingly been used to fabricate parts in aerospace applications, which may require service lives beyond ten-million cycles due to the imposed high loading frequencies. Understanding the very high cycle fatigue (VHCF) behavior of these additive manufactured (AM) parts is an important step towards their design and qualification processes. This study focuses on the high cycle fatigue (HCF) and VHCF behaviors of both wrought and laser beam-powder bed fusion (LB-PBF) fabricated Inconel 718 in machined/polished surface condition, emphasizing on the influence of test frequency (i.e., cyclic strain rate). Uniaxial, fully-reversed force- and stress-controlled fatigue tests were conducted utilizing a servo-hydraulic and an ultrasonic test system operating at 5 Hz and 20 kHz, respectively, on wrought as well as LB-PBF vertically and diagonally built specimens. Fatigue cracks in the majority of the specimens were found to initiate from intra-granular slip bands near or at the surface, which gives rise to strong anisotropy in fatigue resistance in LB-PBF specimens due to the presence of columnar grains along the build directions. Longer fatigue lives were obtained at 20 kHz, which was ascribed to possibly lower-than-intended stresses applied in the ultrasonic tests. The corrected stress-life fatigue data at 20 kHz were found to converge to the one obtained from conventional testing at 5 Hz, implying no effect of cyclic strain rate on the fatigue behavior of Inconel 718 regardless of the fabrication process. The findings of this work confirm the use of ultrasonic fatigue testing to expedite generation of AM materials data to keep up with the current demand; however, the applied stress may need to be corrected.

36 MATERIALS SCIENCE↗

DOE OSTI2022

Impact of Storage Dispatch Assumptions on Resource Adequacy and Capacity Credit

Representing energy-limited resources in power system probabilistic resource adequacy assessment introduces new considerations that invalidate classical modeling assumptions. In particular, such resources have multi-period operating objectives and constraints that in real systems are addressed via a sequence of rolling intertemporal optimizations. Ideally, adequacy models would develop dispatch decisions by solving a similar sequence of problems, but this approach has historically been too computationally intensive for practical use in Monte Carlo simulations, with studies making use of simplifying approximations instead. These simplifications have the potential to distort the assessed value of energy-limited resources on the system.This work describes three classes of storage dispatch assumptions in current use and discusses their theoretical differences. It then provides an empirical analysis of their differences on test systems with different levels of storage, assessing the potential for a study's modeling assumptions to influence the perceived contribution of energy-limited resources.

capacity credit↗

DOE OSTI2024

Sparse Linear Solvers for Large-scale Electromagnetic Transient Simulations

Linear solvers form the basis for electromagnetic transient (EMT) simulations. There is a need to speed up EMT simulations as larger regions are analyzed using EMT simulations. For the same, the performance of linear solvers plays an important role. Exploiting the sparsity of the matrices generated in EMT simulations could assist with speed-up. Scalability is also crucial as power grids expand, demanding solutions capable of accommodating the increasing system size. Recent studies from the North American Electric Reliability Corporation (NERC) increasingly emphasize that EMT simulation models of the power grid will grow larger with the inclusion of power electronics components. Parallelisms in sparsity patterns exploit modern central processing units (CPUs), multi-core CPUs, and graphics processing units (GPUs) architectures in sparse solver designs. Therefore, this paper explores publicly available existing linear solvers and investigates their efficiency in large-scale power grid simulations. A large-scale power grid is developed by increasing the size of the IEEE 39 bus test system to up to 39000 bus systems.

Hsu, Kuan-Chieh↗

DOE OSTI2020

A Flexible Operation of Distributed Generation in Distribution Networks With Dynamic Boundaries

Distributed generators performing black start to form isolated microgrids offer a flexible and resilient solution to service restoration in distribution systems. Employing the dynamic microgrid concept, distributed generators can form isolated microgrids by changing their physical boundaries through smart switches and conventional circuit breakers. However, the flexibility of distributed generators has not been thoroughly investigated and utilised in existing works. To address this issue, this letter presents a new model to the reconfiguration formulation in active distribution networks considering different operation modes of distributed generators. Compared with the existing models, this study provides a new formulation supporting different DGs' operation modes and fully making use of their flexibility. Illustrative results on IEEE 34-test systems verify the effectiveness of the proposed model.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2020

A Model-Predictive Hierarchical-Control Framework for Aggregating Residential DERs to Provide Grid Regulation Services: Preprint

This paper develops a hierarchical control fram-ework to aggregate and control behind-the-meter distributed energy resources (DERs), which will be ubiquitous in future distribution systems. Even though the increasing penetration of DERs will strain the power networks in terms of voltage regul-ation and coordination issues with existing transmission-level conventional generators, the distribution-level DERs can also be utilized to help provide flexibility to the power network while providing cost savings to the DER owners. Therefore, this paper develops a model-predictive control strategy to determine the available power flexibility, and to utilize the flexibility in an aggregated form to provide grid regulation services. Numerical simulations performed on the IEEE 37-bus test system demonstrate the efficacy of the proposed approach.

14 SOLAR ENERGY↗

DOE OSTI2021

Distribution System State Estimation With High Penetration of Demand Response Enabled Loads

Demand-side operations incentivize utility customers to take part in various grid services. A demand response enabled load (DREL) is a flexible grid asset that schedules electricity consumption in response to a time-of-use (TOU) energy price. Consequently, its energy profile differs from that of a conventional load that is insensitive to price. This difference may cause new challenges for distribution system state estimation (DSSE). It is well known that DSSE often needs to use pseudo-measurements based on historic load profiles to increase system observability. However, historic profiles of conventional loads are not representative of DREL behaviors. Additionally, the inaccuracy impacts DSSE results and other DSSE-dependent operations. In this paper, we propose an online pseudo-measurement generation approach for DSSE with DRELs. We formulate an optimization model to represent DRELs self-adjusting actions. Sampling-based stochastic optimization techniques are proposed to account for uncertainties in DRELs. A set of representative DREL behavior data corresponding to the samples are used to characterize DREL pseudo-measurements. Case studies with modified IEEE 123-bus test system verify the validity of the proposed work.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2021

Examining the Economic Optimality of Automatic Generation Control

The automatic generation control (AGC) system is temporally situated between economic dispatch and synchronous generator dynamics, and its primary role is to regulate frequency within and tie-line flows between control areas. Given appropriate choice of participation factors (feed-forward controller gains that govern the disaggregation of the area-level power requirement to individual generators), the AGC can be engineered to nudge system dynamics toward a steady-state operating point corresponding to economic optimality. This paper establishes necessary and sufficient conditions under which a widely accepted choice of participation factors guarantees the alignment of steady-state synchronous generator outputs with a global minimum of a prototypical economic dispatch problem. In so doing, it resolves several ambiguities and formalizes technical assumptions governing the role of the standard AGC architecture in the context of economic dispatch and steady-state operation. Numerical case studies tailored to a modified version of the New England 39-bus 10-machine test system validate the theoretical results.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

DOE OSTI2020

Thermal Management for FPGA Nodes in HPC Systems

The integration of FPGAs into large-scale computing systems is gaining attention. In these systems, real-time data handling for networking, tasks for scientific computing, and machine learning can be executed with customized datapaths on reconfigurable fabric within heterogeneous compute nodes. At the same time, thermal management, particularly battling the cooling cost and guaranteeing the reliability, is a continuing concern. The introduction of new heterogeneous components into HPC nodes only adds further complexities to thermal modeling and management. The thermal behavior of multi-FPGA systems deployed within large compute clusters is less explored. Here, we first show that the thermal behaviors of different FPGAs of the same generation can vary due to their physical locations in a rack and process variation, even though they are running the same tasks. We present a machine learning–based model to capture the thermal behavior of each individual FPGA in the cluster. We then propose two thermal management strategies guided by our thermal model. First, we mitigate thermal variation and hotspots across the cluster by proactive thermal-aware task placement. Under the tested system and benchmarks, we achieve up to 26.4° C and on average 13.3° C system temperature reduction with no performance penalty. Second, we utilize this thermal model to guide HLS parameter tuning at the task design stage to achieve improved thermal response after deployment.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2020

A Model-Predictive Hierarchical-Control Framework for Aggregating Residential DERs to Provide Grid Regulation Services

This paper develops a hierarchical control frame-work to aggregate and to manage behind-the-meter distributed energy resources (DERs), which will be ubiquitous in future distribution systems. In the proposed framework, firstly, each controller in the hierarchy determines the flexibility of the DERs such that the obtained flexibility is feasible with respect to its operational purview. For example, the operational purview of a home energy management system may only consider consumer comfort preferences, while that for an aggregator or a grid controller may consider network voltage management as well. Based on the feasible flexibility, optimal setpoints for the DERs is then determined by the hierarchical controllers to help the distribution power network in voltage regulation, coordination issues with existing transmission-level conventional generators, etc. Therefore, the proposed strategy, which is based on model-predictive control, can be effectively utilized by the distribution network to coordinate several DERs to provide grid regulation services. Numerical simulations performed on the IEEE 37-bus test system demonstrate the efficacy of the proposed approach.

behind-the-meter↗

DOE OSTI2020

A Model-Predictive Hierarchical-Control Framework for Aggregating Residential DERs to Provide Grid Regulation Services

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2024

IMAGINE BioSecurity: Mesocosm-Based Methods to Evaluate Biocontainment Strategies and Impact of Industrial Microbes Upon Native Ecosystems

Project Goals: The Integrative Modeling and Genome-scale Engineering for Biosystems Security (IMAGINE BioSecurity) SFA project seeks to establish an understanding of the behavior of engineered microbes in controlled versus environmental conditions to predictively devise new strategies for responding to biological escape. To this end, the IMAGINE Team has established a plant-soil mesocosm platform to track and quantify the fate of industrial microbes in environmental systems and assess the efficacy of biocontainment constraints upon genetically engineered microbe escape frequency and the impact of industrial microbes upon native ecological microbiomes. Abstract Text: Genetically modified industrial production microbes and their associated bioproducts have emerged as an integral component of a sustainable bioeconomy. However, the rapid development of these innovative technologies raises biosecurity concerns, namely, the risk of environmental escape. Thus, the realization of a bioeconomy hinges not only on the development and deployment of microbial production hosts, but also on the development of secure biosystems and biocontainment designs. Current laboratory-based biocontainment testing systems do not accurately reflect complexities found in natural environments, necessitating an environmentally relevant analysis pipeline that allows for the detection of rare escapees, the effect of associated bio-products, and the impact on native ecologies. To this end, we have developed an approach that utilizes soil mesocosms and integrated systems analyses to evaluate the efficacy of novel biocontainment strategies and to assess the impact of production systems upon terrestrial microbiome dynamics. We demonstrate the utility of this approach by modeling a contamination with industrial microbial chasses versus their biocontained counterparts. Here we demonstrate the broad utility of this system by highlighting findings from both strains of Saccharomyces cerevisiae that are contained with an inducible toxin anti-toxin system, and stains of Escherichia coli that are contained via genomic recoding. The resultant data demonstrate that this system has broad utility across diverse microbial chassis and biocontainment strategies, enables us to track the fate of our contaminating microbe with high sensitivity in the soil, as well as monitor broader impacts of the perturbation on the underlying soil system. The findings presented here support the use of this mesocosm-based approach to assess the environmental impact of industrial microbes and to validate biocontainment strategies.

BASIC BIOLOGICAL SCIENCES,INORGANIC, ORGANIC, PHYS↗