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At least 739 records · Page 41

The Development of the Corrosion Control Limits for Direct Feed Low-Activity Waste Melter-Off Gas Returns to Hanford Tank Farms - 18196

The Savannah River National Laboratory has been developing a corrosion model to facilitate implementation of Hanford's Direct Feed Low Waste (DFLAW) flowsheet. Laboratory testing and statistical analysis have been used to determine the necessary corrosion controls for returning effluent from the Hanford Waste Treatment and Immobilization Plant's Low Activity Waste Vitrification melter off-gas treatment system to the tank farms. The stream compositions are projected to contain components at relative concentrations that are significantly more corrosive toward carbon steel, specifically halide and sulfate anions, than the current waste compositions in the tank farms. Administrative programs are in place to mitigate potential corrosion mechanisms and thereby maintain the structural and leak integrity functions of these waste tanks throughout their intended service life. Waste chemistry and temperature control are the means by which corrosion degradation of the waste tanks is minimized. The current administrative specification for chemical composition and temperature for the underground carbon steel waste tanks is not designed to control the higher halide or sulfate composition. The content of the DFLAW waste streams will be diverse and depend on several factors, such as the melter feed composition and melter idle time. Other factors, such as effluent management of the off gas water collections, will impact the variability of the return streams even more. The work performed by the Savannah River National Laboratory has confirmed that the halide ions are the most aggressive species in the return stream compositions projected using a flowsheet simulation, and nitrite is the most effective inhibitor at pH 10 and 40 deg. C. This test program has employed statistically designed test matrices to determine the dependent variables and the interaction terms between the variables that are significant for the corrosion model and definition of the corrosion control specifications. The first phase of testing focused on identifying aggressive species in off-gas condensate return compositions that present a propensity for localized corrosion attack, namely pitting corrosion. The second phase of testing focused on developing a corrosion model from the interaction terms that will predict the susceptibility of pitting in the double shell tank system based on waste composition and the required amount of corrosion inhibitor. The data collected from this testing program in conjunction with other testing programs, both at the Savannah River Site and the Hanford Site, along with operations knowledge, has determined the chemistry ranges and chemical species requirements for corrosion control in the Hanford double-shell tank system for the effluents generated in the Hanford Waste Treatment and Immobilization Plant's Low Activity Waste facility during the DFLAW phase of operations. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

California Wave Power Technologies Open Water Demonstration - Budget Period 1 reports

The objective of the project is to advance the Technology Readiness Level (TRL) of the Wave Energy Converter (WEC) developed by CalWave Wave Power Technologies Inc (CalWave) through advanced numerical simulations, dynamic hardware tests, and ultimately a scaled open water demonstration deployment while continuing to exceed DOE's target ACE threshold of 3m/M$. The outcomes of Budget Period 1 will be a detailed design of the scaled demonstration unit and bench testing of the critical hardware components.

16 TIDAL AND WAVE POWER↗

Model Based Validation of Intelligent Powertrain Strategies for Connected and Automated Vehicles

Systems incorporating Vehicle to Everything (V2X) and conventional cellular based communication in vehicles can significantly help improve energy consumption via a combination of intelligent powertrain control strategies, smarter routing algorithms and driving in such a way as to minimize fuel economy and the emission of carbon dioxide, known as "eco-driving." In projects led by the Southwest Research Institute (SwRI), large-scale traffic simulations are created to model real-world scenarios with dynamic behavior that is reactive to imposed changes. Coupled with high fidelity powertrain models, the closed loop framework enables research and development of such Connected and Automated Vehicle (CAV) enabled technologies at scale. This paper will discuss a traffic system simulation environment that was built based on the High Street urban corridor in Columbus, Ohio. Eco-driving strategies were tested at scale on a variety of powertrain platforms – internal combustion engines, hybrid electric and fully electric vehicles. Furthermore, the paper will focus on hybrid electric powertrain modeling along with details on how the powertrain model was leveraged to develop a sophisticated clustering scheme to help down-select speed traces from large scale simulation studies for validation on vehicle dynamometer. Nominal energy consumption improvement around 12% was observed with good match between simulation studies and vehicle testing.

33 ADVANCED PROPULSION SYSTEMS↗

Recent results from a testbed for the reliability of the digital instrumentation and control systems and cybersecurity in nuclear power plants - 392

Transition from analog to digital instrumentation and control systems requires a systematic study of the modifications, and assessment of their reliability. Such studies are often carried out on a test bed. The test bed developed earlier includes a commercially available triple modular redundant (TMR) programmable logic controller (PLC) for testing not only the reliability of the digital I and C but also the cyber-security of the system during plant operation. This paper reports results of our preliminary analyses carried out using the test bed following the injection of faults mimicking faulty sensors. The fault injection tool generates faulty signals in single or multiple sensors located in the primary loop. These scenarios studied under steady-state operation conditions simulate a bad sensor, a cut wire, noise, etc. The faults injected can lead to information being displayed in the main control room (MCR) to not match the conditions in the plant. In addition to a fault injection module, a result analyzer module is also a part of this testbed. Operator actions can be based on information displayed in the MCR, or they can be informed by the result analyzer. Potential operator actions following these single- or multiple faulty signals are assessed. It is concluded that the result analyzer in some cases can be helpful in guiding operators to make the right decisions. (authors)

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Approach to Quality Assurance for Complex Environmental Modeling - 20407

A strong Quality Assurance (QA) program for complex environmental modeling is essential for regulatory and public acceptance and trust, but it does not have to be onerous. Neptune and Company, Inc. (Neptune) has developed a strong QA program that improves transparency, traceability, reproducibility, and therefore, defensibility and trust. Neptune's QA program has evolved over the past 27 years, transitioning from an ad hoc QA program, to a program that is currently Nuclear Quality Assurance-1 (NQA-1) compliant, and will soon be NQA-1/DOE approved for DOE EM modeling work. In addition, Neptune is a qualified laboratory assessor and qualified auditor for reference materials, a proficiency testing provider, and fully complies with the Environmental Protection Agency (EPA) QA program. Neptune's President and CEO, Kelly Black, was recently named the Chairperson of the International Organization for Standardization (ISO) Technical Committee 69, Application of Statistical Methods. A strong QA program has been developed for Neptune's radiological performance assessment (PA) program. Although pieces of their QA program are currently in development, their current program includes document control using Subversion, issue tracking and work flow tracking using JIRA, and transparency and traceability via a system of 'calc sheets' for documentation of all data analysis and modeling combined with 'check print' documentation of QA checking, and rigorous model testing and configuration control. All work is reviewed by an independent subject matter expert who is not associated with the collection and assembly of information, for an internal peer review. The program is enforced with a handful of Standard Operation Procedures (SOPs), Work Instructions, QA Project Plans (QAPPs), and Quality Management Plans (QMPs) that are updated frequently, with required annual training and acknowledgment. In addition, effective communication of modeling approaches and results to clients and stakeholders are integral to their QA program. Many of their models are built using the GoldSim modeling platform, for which their models are well-known for their level of transparency, documentation, and QA traceability. This level of QA is also applied to their process-level models. Neptune has taken some lessons learned from the extremely rigorous QA program required for the Yucca Mountain Project (YMP), and imposed the YMP requirements of complete traceability, transparency, and reproducibility, but avoided the inflexibility of a QA program that likely contributed to the suspect e-mails in 2005 that resulted in loss of trust in the YMP, and in nuclear waste disposal (and nuclear power) in general. There are far too many examples of loss of public trust due to poor QA that could have been easily avoided with a simple and straight-forward QA program combined with stakeholder engagement. The purpose of this paper is to share features of Neptune's Radiological Performance Assessment program QA program, and some of their QA related lessons learned over the past 27 years of QA for complex environmental modeling. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

PhenoCurve: capturing dynamic phenotype-environment relationships using phenomics data

MOTIVATION: Phenomics is significant for understanding the mechanisms that regulate or influence growth, fitness, and development. Techniques have been developed to conduct high-throughput large-scale phenotyping on animals, plants and humans, aiming to bridge the gap between genomics, gene functions and traits. Although new developments in phenotyping techniques are exciting, we are limited by the tools to analyze fully the massive phenotype data, especially the dynamic relationships between phenotypes and environments. RESULTS: We present a new algorithm called PhenoCurve, a knowledge-based curve fitting algorithm, aiming to identify the complex relationships between phenotypes and environments, thus studying both values and trends of phenomics data. The findings on both real and simulated data showed that PhenoCurve has the best performance among all the six tested methods. Its application to photosynthesis hysteresis pattern identification reveals new functions of core genes that control photosynthetic efficiency in response to varying environmental conditions, which are critical for understanding plant energy storage and improving crop productivity.

Yang, Yifan↗

Real-Time Optimized Load Recovery Considering Frequency Constraints

A self-healing power grid can mitigate the impact of power outages and recover the affected area swiftly. To properly size the optimal amount and location of de-energized loads in the presence of both conventional and renewable sources, a precise optimization-based load recovery tool is proposed herein. The steady-state and transient behaviors of loads have been taken into account. The proposed tool contains three separate problems that interact with each other during the restoration period. The first-level problem determines the dispatching of generation units. The second-level problem comprises the non-linear algebraic equations, whose task is to provide the initial conditions for the third-level problem. Finally, the third-level problem intends to determine the optimal location and amount of load pickup through modeling the governor of generators as well as loads' dynamic behaviors. To examine the effectiveness of the proposed tool, a modified IEEE 39-system under a partial blackout condition has been tested. The results are verified by a commercial time-domain simulation software (PSS/E) to demonstrate the accuracy of the proposed approach. Ultimately, the impact of wind turbine frequency control on the load recovery process has been studied under different penetration levels.

24 POWER TRANSMISSION AND DISTRIBUTION↗

SU-E-T-103: Development and Implementation of Web Based Quality Control Software

Purpose: Historically many radiation medicine programs have maintained their Quality Control (QC) test results in paper records or Microsoft Excel worksheets. Both these approaches represent significant logistical challenges, and are not predisposed to data review and approval. It has been our group's aim to develop and implement web based software designed not just to record and store QC data in a centralized database, but to provide scheduling and data review tools to help manage a radiation therapy clinics Equipment Quality control program. Methods: The software was written in the Python programming language using the Django web framework. In order to promote collaboration and validation from other centres the code was made open source and is freely available to the public via an online source code repository. The code was written to provide a common user interface for data entry, formalize the review and approval process, and offer automated data trending and process control analysis of test results. Results: As of February 2014, our installation of QAtrack+ has 180 tests defined in its database and has collected ∼22 000 test results, all of which have been reviewed and approved by a physicist via QATrack+'s review tools. These results include records for quality control of Elekta accelerators, CT simulators, our brachytherapy programme, TomoTherapy and Cyberknife units. Currently at least 5 other centres are known to be running QAtrack+ clinically, forming the start of an international user community. Conclusion: QAtrack+ has proven to be an effective tool for collecting radiation therapy QC data, allowing for rapid review and trending of data for a wide variety of treatment units. As free and open source software, all source code, documentation and a bug tracker are available to the public at https://bitbucket.org/tohccmedphys/qatrackplus/.

07 ISOTOPE AND RADIATION SOURCES↗

funnel v0.0.1

fcompare is a software package that applies for comparing two curves generated from datasets in csv format. A funnel is generated around the reference curve and the other curve is checked to verify if it is inside the funnel. The funnel can be reshaped by setting a tolerance. One potential application is to verify the development of building HVAC control sequence, in which it compares data curves from real operation with data curves from simulation using developed control sequences, to verify if the developed control sequences have been implemented correctly. In addition, it can be used for Modelica library developer to do the unit test that verifies new model developments.

Wetter, Michael↗

Study the Cyclic Plasticity Behavior of 508 LAS under Constant, Variable and Grid-Load-Following Loading Cycles for Fatigue Evaluation of PWR Components

This report provides an update of an earlier assessment of environmentally assisted fatigue for components in light water reactors. This report is a deliverable in September 2016 under the work package for environmentally assisted fatigue under DOE’s Light Water Reactor Sustainability program. In an April 2016 report, we presented a detailed thermal-mechanical stress analysis model for simulating the stress-strain state of a reactor pressure vessel and its nozzles under grid-load-following conditions. In this report, we provide stress-controlled fatigue test data for 508 LAS base metal alloy under different loading amplitudes (constant, variable, and random grid-load-following) and environmental conditions (in air or pressurized water reactor coolant water at 300°C). Also presented is a cyclic plasticity-based analytical model that can simultaneously capture the amplitude and time dependency of the component behavior under fatigue loading. Results related to both amplitude-dependent and amplitude-independent parameters are presented. The validation results for the analytical/mechanistic model are discussed. This report provides guidance for estimating time-dependent, amplitude-independent parameters related to material behavior under different service conditions. The developed mechanistic models and the reported material parameters can be used to conduct more accurate fatigue and ratcheting evaluation of reactor components.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

Photovoltaic Analysis and Response Support (PARS) Platform for Solar Situational Awareness and Resiliency Services

The project's primary objective is to develop a digital-twin based Photovoltaic (PV) Analysis and Response Support (PARS) platform, which aims to provide real-time situational awareness and optimal response plans. This platform is designed to enhance the performance of hybrid PV systems, making them competitive with or even superior to conventional generation resources. The PARS platform enabled the project team to develop and evaluate an extensive suite of grid support functionalities for the hybrid PV systems to enhance grid performance, across key areas including visibility, dispatchability, security, resilience, and reliability. Given the global push toward achieving 100% clean energy by 2035, there is a significant increase in the integration of inverter-based resources (IBRs) throughout the energy grid. Effectively managing the inherent variability and uncertainty associated with IBRs is crucial for ensuring cost-effectiveness, reliability, and security in both the main grid and islanded microgrids. Constrained to a limited array of IEEE test systems or standard feeder models, traditional IBR modeling struggles to assimilate new field data, accurately reflect system dynamics, and adapt to the evolving energy landscape. In our project, we embraced a Digital Twin (DT) strategy for crafting the PARS platform. A digital twin acts as a precise virtual counterpart of a physical system, built on historical data and continuously honed with real-time insights. This enables the high-fidelity DT to accurately mirror current system operations and forecast future scenarios. Consequently, the PARS platform becomes an ideal environment for testing and refining monitoring, control, power, and energy management algorithms designed to boost hybrid PV system performance. The defining feature of the PARS platform, distinguishing it from other advanced simulation tools, is its exceptional adaptability. This is achieved by employing actual network topologies and utilizing real-time field data for fine-tuning and calibration, ensuring a close emulation of real-world conditions. The project deliverables include: 1) High-fidelity IBR models and tools for real-time parameterization, utilizing real-time field measurements to refine IBR models for enhanced accuracy and performance; 2) Grid-forming and Grid-following capabilities to deliver resilience services, including blackstart, voltage and frequency support, cold-load pick-up, power reserves, and three-phase load balancing across grid-connected and microgrid settings; 3) Machine learning-based forecasting tools and methods for generating synthetic data and topologies, creating diverse and realistic simulation environments for evaluating varied operational scenarios; 4) Advanced microgrid power and energy management algorithms for optimizing the integration and operation of PV, storage, and demand response resources within both feeder and community scales. The power grid data sets are provided by four utility companies in North Carolina and the New York Power Administration. Acting as industry advisors, our industry partners communicated stakeholder needs and regulatory standards to the research teams, aiding technology transfer by incorporating the developed methodologies into their daily operations. This collaboration ensures that the PARS platform, functioning as a power system digital twin, enhances our understanding of IBR dynamic behaviors and enables the development and evaluation of IBR control functions that match or exceed the capabilities of conventional synchronous generators.

14 SOLAR ENERGY↗

Multiphysics Modeling of Microreactors with NEAMS codes, and Validation Based on KRUSTY Reactivity Insertion

The NEAMS Multiphysics Applications team continues to assess code usability and functionality for microreactor design and safety analyses, while demonstrating that NEAMS tools capture both steady-state and transient behavior across distinct microreactor concepts. In FY2025, the team advanced full-core, high-fidelity, multiphysics models that solve more complex problems and strengthen verification/validation for several microreactor systems: heat-pipe microreactor (HPMR), gas-cooled microreactor (GCMR), and the KRUSTY experiment. These models employ the MOOSE MultiApp/Transfers architecture with Griffin for neutronics, BISON for heat conduction/thermomechanics, Sockeye for heat pipes, SAM/THM for coolant channels and loops, and SWIFT for hydride behavior, with meshes generated via the MOOSE Reactor Module. The graphite models available in the Grizzly code were also investigated for future analyses. For the HPMR, a Na-HPMR variant was constructed to align with recently validated heat-pipe experiments and Sockeye’s LCVF capability, enabling mechanistic heat-pipe transients and startup modeling. The Na-HPMR will serve as the primary model for HPMR investigations in upcoming tasks. The load-following and single heat-pipe failure scenarios (Griffin/BISON/Sockeye), which were previously modeled for the K-HPMR, were replicated for the Na-HPMR, showing strong negative temperature feedback and highly localized thermal effects, respectively, while the startup case captured vapor-front progression and heat-removal activation. Solid mechanics was added to the previously built K-HPMR full-core model in BISON, showing minimal impact on steady-state reactivity yet enabling stress-field predictions that prepare the path for full-core TRISO performance analyses. For the GCMR, automated steady-state and four transient scenarios were executed using Griffin/BISON/SAM/SWIFT. Results confirm robust inherent safety: power collapses promptly in loss-of-cooling events, the inlet-temperature drop settles to a new equilibrium, and a single-channel blockage yields only a ~30 K local fuel-temperature rise with <0.4% power decrease. SWIFT-predicted hydrogen redistribution affects reactivity during both steady-state and transient conditions, underscoring its importance. A Brayton-cycle balance of plant (BOP) model in SAM/THM demonstrated stable startup behavior, and xenon-driven reactivity during load following was analyzed. To improve TRISO-compact temperature fidelity, a fast multiscale Heat Source Decomposition (HSD) treatment was implemented. Against heterogeneous benchmarks, HSD reduces underprediction of kernel temperatures and lowers predicted peak powers in reactivity-insertion transients compared to previous homogenized models. KRUSTY warm-critical validation progressed from FY2024 baselines: the 15Ȼ insertion shows excellent agreement in peak power (~2% high) and temperature trends, and the 30Ȼ case was automated via a feedback controller that maintained power near 3 kW for ~150 s with close agreement to data. The successful modeling of the warm critical tests has laid a strong foundation for simulating more complex nuclear system tests in the years ahead. Throughout FY2025, developer feedback was provided (e.g., MOOSE batch mesh generation, distributed pre-split meshes, Griffin sweeper on displaced meshes), several new models were contributed to the Virtual Test Bed, and an OECD-NEA WPRS multiphysics benchmark based on the HPMR was initiated to enable broader cross-comparison and best-practice development with the nuclear community at large.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Power Hardware-in-the-Loop (PHIL) Testing Facility for Distributed Energy Storage (Poster)

The growing deployment of distributed, variable generation and evolving end-user load profiles presents a unique set of challenges to grid operators responsible for providing reliable and high quality electrical service. Mass deployment of distributed energy storage systems (DESS) has the potential to solve many of the associated integration issues while offering reliability and energy security benefits other solutions cannot. However, tools to develop, optimize, and validate DESS control strategies and hardware are in short supply. To fill this gap, NREL has constructed a power hardware-in-the-loop (PHIL) test facility that connects DESS, grid simulator, and load bank hardware to a distribution feeder simulation.

25 ENERGY STORAGE↗

CEEP (Cyber-Energy Emulation Platform) [SWR-20-102]

NREL's Cyber-Energy Emulation Platform (CEEP) provides the capability to realize cyber-energy security and resilience through automation and orchestration of virtualized systems and software defined networks for the electric grid. CEEP enables testing and validation of grid-security and -control methodologies as the grid evolves to include smart technologies/systems, such as virtualization and containerization of grid components, software defined networking, simulation and co-simulation frameworks, and hardware in the loop. CEEP is a modular system that can be distributed and deployed across different hardware infrastructure sizes and network architectures. For example, CEEP can visualize, emulate, and/or coordinate the Smart-Grid Network Visualization, Intrusion Detection, and Network Healing system. Using CEEP, intrusion-detection and network-self-healing solutions can be deployed at grid control centers, within secure private clouds, and in cyber-energy appliances.

Vaughan, Evan↗

Cyber Energy Emulation Platform (CEEP) [SWR-20-102]

NREL's Cyber-Energy Emulation Platform (CEEP) provides the capability to realize cyber-energy security and resilience through automation and orchestration of virtualized systems and software defined networks for the electric grid. CEEP enables testing and validation of grid-security and -control methodologies as the grid evolves to include smart technologies/systems, such as virtualization and containerization of grid components, software defined networking, simulation and co-simulation frameworks, and hardware in the loop. CEEP is a modular system that can be distributed and deployed across different hardware infrastructure sizes and network architectures. For example, CEEP can visualize, emulate, and/or coordinate the Smart-Grid Network Visualization, Intrusion Detection, and Network Healing system. Using CEEP, intrusion-detection and network-self-healing solutions can be deployed at grid control centers, within secure private clouds, and in cyber-energy appliances.

Rivera, Joshua↗

Equation-based languages – A new paradigm for building energy modeling, simulation and optimization

Most of the state-of-the-art building simulation programs implement models in imperative programming languages. This complicates modeling and excludes the use of certain efficient methods for simulation and optimization. In contrast, equation-based modeling languages declare relations among variables, thereby allowing the use of computer algebra to enable much simpler schematic modeling and to generate efficient code for simulation and optimization. We contrast the two approaches in this paper. We explain how such manipulations support new use cases. In the first of two examples, we couple models of the electrical grid, multiple buildings, HVAC systems and controllers to test a controller that adjusts building room temperatures and PV inverter reactive power to maintain power quality. In the second example, we contrast the computing time for solving an optimal control problem for a room-level model predictive controller with and without symbolic manipulations. As a result, exploiting the equation-based language led to 2, 200 times faster solution

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Findings on Subtask 3.1 - Bakken Rich Gas Enhanced Oil Recovery Project

Total in-place oil for the Bakken petroleum system (BPS) (which includes the Bakken and Three Forks Formations) has been estimated to be 600 billion barrels (bbl). However, BPS wells have decline rates as high as 85% over the first 3 years of their lives, and primary recovery factors typically range from 3% to 10% of original oil in place. Given the low initial recovery rates, even small incremental productivity improvements could dramatically increase technically recoverable oil in the BPS. One potential solution is enhanced oil recovery (EOR) using gas injection, such as carbon dioxide (CO2) or hydrocarbon (HC) gases. While commonly used in conventional reservoirs, CO2 EOR in unconventional tight oil reservoirs has been limited to pilot tests. EOR using rich gas (mixture of methane, ethane, and propane) has also been employed in numerous pilots in several unconventional plays and has recently been successfully applied in the Eagle Ford play. If successful, large-scale gas-based EOR in the BPS could dramatically increase oil productivity and recovery factors and extend the life of the play for decades. While CO2 may be a technically suitable working fluid for EOR in the BPS, supplies are limited and costs for using CO2 in EOR pilots are prohibitively high. Meanwhile, produced gas flaring has presented challenges for BPS operators in North Dakota. Analysis conducted by the North Dakota Pipeline Authority indicates that the current gas-gathering infrastructure in North Dakota is insufficient to accommodate all of the associated gas that is produced from the BPS. The geographically isolated location of North Dakota relative to large natural gas markets, combined with suppressed natural gas prices, has made it economically challenging for industry to invest capital in expanding gas-gathering infrastructure in the state. These circumstances led to a research program conducted by the Energy & Environmental Research Center (EERC) in partnership with Liberty Resources Management Company LLC (LR) to examine the potential to use rich gas injection for EOR and mitigate flaring. A rich gas EOR pilot test was designed and executed by LR at its Stomping Horse development area in Williams County, North Dakota. From July 2018 through May 2019, a total of 160 million standard cubic feet (MMscf) of rich produced gas was injected into the BPS using five different wells in a sequential injection strategy. LR’s Leon–Gohrick drill spacing unit (DSU) was used as the test site. Regulatory oversight was provided by the North Dakota Industrial Commission (NDIC). Technical support was provided by the EERC through a series of laboratory, modeling, and field-based activities, and additional post-pilot research activities incorporated learnings from the test, developed new laboratory data, improved fracture modeling methods, and developed machine learning and big data analytics. The results from the Stomping Horse rich gas EOR pilot activities indicate that developing an effective, economical EOR approach for the BPS will require more field tests. Another key lesson learned from the Stomping Horse tests is that detailed pre- and posttest data on reservoir conditions and fluids production are essential. Robust reservoir characterization provides information that is crucial to creating realistic geomodels and conducting valid dynamic simulations of potential EOR scenarios. A detailed understanding of the completions and production history of offset wells is also necessary for valid test result interpretations. This knowledge is essential to designing the operational parameters of injectivity tests and interpreting the results. A conformance control strategy is also essential to success. Laboratory-based examinations of rich gas interactions with reservoir fluids and rocks were conducted, with an emphasis on determining the ability to mobilize oil in the tight reservoir rocks and shales of the BPS. Injection fluid composition was shown to have a positive impact on reducing reservoir oil minimum miscibility pressure (MMP), reducing interfacial tension (IFT), and altering wettability. IFT and contact angle measurements demonstrated that wettability can be altered in the presence of rich gas, suggesting the potential to improve oil recovery. Iterative modeling of surface infrastructure and reservoir performance using data generated by the various project activities was conducted. A geologic model of the Stomping Horse area was built; history-matched oil, gas, and water production was used in simulations of various EOR scenarios. Early programmatic modeling results were used to support LR’s design and operation of the EOR pilot and to provide insight regarding optimization of future commercial-scale BPS EOR design and operations. Post-pilot modeling focused on alternative methods of understanding complex fracture networks and accelerating simulation time. These led to improved simulation run times and provide excellent history-matching results. Several of these iterative models were used as the bases for developing algorithms into machine learning and big data analytics. History matching in reservoir simulation is time-consuming and computer processing-intensive. Machine learning algorithms were created, and an automated history-matching tool was developed. A large set of synthetic reservoir simulations were created to generate well responses (oil, gas, and water production, well bottomhole pressure [BHP], and tracer or propane breakthrough) for a set of EOR operating parameters that included offset well status (open or closed), injectate (rich gas or propane), injection rate, and injection well BHP. A user interface was developed to provide real-time visualization. Machine learning-based models were developed to provide rapid forecasting of well performance given a set of user-defined EOR operating parameters. These predictive models allow the user to modify the offset well status, injection rate, and injection well BHP and rapidly forecast future production performance. The combination of real-time visualization tools with real-time forecasting tools provides a framework for real-time control—operational changes that the EOR site operator can enact (e.g., changing gas injection rates) to affect the observed performance and potentially improve the EOR outcome. There is great reason to be optimistic about the future of EOR in the Bakken. The results of the laboratory studies suggest significant potential for high rates of oil mobilization using produced field gas injection under the right conditions. The results of the lab studies, combined with rigorous statistical analysis of well production data and associated modeling efforts, confirm the notion that fluid mobility within the reservoir is controlled by fractures. As more knowledge is gained about the nature and distribution of fracture networks in the Bakken, the industry will be in a better position to predict and, ultimately, influence fluid mobility. New field tests are necessary to develop a more complete understanding of those conditions. Thoughtful and creatively engineered field tests within a well-characterized geologic setting will yield the fundamental knowledge needed to take Bakken oil production to the next level. This subtask was cofunded through the EERC–U.S. Department of Energy Joint Program on Research and Development for Fossil Energy-Related Resources Cooperative Agreement No. DE-FE0024233. Nonfederal funding was provided by the North Dakota Industrial Commission’s Oil and Gas Research Program and Computer Modelling Group.

04 OIL SHALES AND TAR SANDS↗

Real-Time Testbed for Smart Grid Recloser Controller

The growing need for a low voltage recloser has become apparent due to the rise in requirements for a smart grid. This includes more detailed management of power flow forward (towards load) and backward (towards generation), source synchronization in real time, more indepth fault responses, and the use of green energy. The SEL-651R-2 relay is a device that can manage these needs, especially in fault response and synchronization, and is commonly used in systems called microgrids. Microgrids are distribution level systems that are able to operate separated from the main grid, are typically installed much closer to the load(s), and are fed by distributed energy resources (DERs), such as wind, solar or diesel generators. The SEL-651R-2 is normally used in the field with presets operative settings, but the Western Michigan University (WMU) Center for Interdisciplinary Research on Secure, Efficient and Sustainable Energy Technology (WMU InterEnergy Center) wished to test this device in its range of capabilities for microgrid application. A Hardware-In-the-Loop (HIL) testbed was implemented and used through the Real Time Digital Simulator (RTDS) using the RSCAD software to test the SEL-651R-2's use cases and functions. The testbed includes a microgrid with interconnection to a larger main grid, and the relay is meant to control the recloser at the point of common coupling (PCC) between the main grid and microgrid. The testbed shows how basic protections, reclosing, and synchronization checks function when handling faults that affect both the microgrid and the main grid.

24 POWER TRANSMISSION AND DISTRIBUTION↗