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Results for “control simulation testing”

Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 1,135 records · Page 63

All sources NASA NTRS DOE OSTI

DOE OSTI2016

Evaluation and Field Assessment of Bifacial Photovoltaic Module Power Rating Methodologies

1-sun power ratings for bifacial modules are currently undefined. This is partly because there is no standard definition of rear irradiance given 1000 Wm-2 on the front. Using field measurements and simulations, we evaluate multiple deployment scenarios for bifacial modules and provide details on the amount of irradiance that could be expected. A simplified case that represents a single module deployed under conditions consistent with existing 1-sun irradiance standards leads to a bifacial reference condition of 1000 Wm-2 Gfront and 130-140 Wm-2 Grear. For fielded systems of bifacial modules, Grear magnitude and spatial uniformity will be affected by self-shade from adjacent modules, varied ground cover, and ground-clearance height. A standard measurement procedure for bifacial modules is also currently undefined. A proposed international standard is under development, which provides the motivation for this work. Here, we compare outdoor field measurements of bifacial modules with irradiance on both sides with proposed indoor test methods where irradiance is only applied to one side at a time. The indoor method has multiple advantages, including controlled and repeatable irradiance and thermal environment, along with allowing the use of conventional single-sided flash test equipment. The comparison results are promising, showing that the indoor and outdoor methods agree within 1%-2% for multiple rear-irradiance conditions and bifacial module types.

14 SOLAR ENERGY↗

DOE OSTI2018

A generic microgrid controller: Concept, testing, and insights

Microgrids have garnered attention in recent years as a way to increase the reliability of the grid, increase the reliability of electricity service to customers, adapt to an increasing percentage of intermittent renewable generation, and serve both customer critical loads and the needs of adjacent communities in the case of emergencies such as natural disasters. One barrier to microgrids is the historic cost and lack of standardization associated with microgrid controllers. To reduce this cost and address standardization, specifications for a Generic Microgrid Controller (GMC) were developed with the goal to facilitate the design and ease of adaptation of microgrid controllers to various microgrids of different sizes and with different resources. A GMC must address two core functions, Transition and Dispatch, as well as several optional higher level functions such as economic dispatch, and renewable and load forecasting. The GMC specifications were demonstrated and evaluated using a commercial simulation platform for two different microgrids, a 20MW-Class community microgrid and a 10MW-Class medical center microgrid. For each microgrid, the GMC was tested in hardware-in-the-loop (HIL) using an OPAL-RT real-time digital simulator, and the two core functions were assessed. The results established that (1) the GMC is successful in seamlessly transitioning the microgrids to and from an islanded mode, (2) a load/generation mismatch at the time of separation depends on the microgrid configuration and must be lower than a specific value determined by simulation testing, and (3) the GMC Dispatch Function response is acceptable in maintaining, in the islanded mode, 60Hz for a range of load changes.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2025

Benchmarking the performance of a high-Q cavity qudit using random unitaries

High-coherence cavity resonators are excellent resources for encoding quantum information in higher-dimensional Hilbert spaces, moving beyond traditional qubit-based platforms. A natural strategy is to use the Fock basis to encode information in qudits. One can perform quantum operations on the cavity mode qudit by coupling the system to a non-linear ancillary transmon qubit. However, the performance of the cavity-transmon device is limited by the noisy transmons. It is, therefore, important to develop practical benchmarking tools for these qudit systems in an algorithm-agnostic manner. We gauge the performance of these qudit platforms using sampling tests such as the heavy output generation test as well as the linear cross-entropy benchmark, by way of simulations of such a system subject to realistic dominant noise channels. We use selective number-dependent arbitrary phase and unconditional displacement gates as our universal gateset. Our results show that contemporary transmons comfortably enable controlling a few tens of Fock levels of a cavity mode. This framework allows benchmarking even higher dimensional qudits as those become accessible with improved transmons.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

DOE OSTI2023

Modelling galaxy cluster triaxiality in stacked cluster weak lensing analyses

Counts of galaxy clusters offer a high-precision probe of cosmology, but control of systematic errors will determine the accuracy of this measurement. Using Buzzard simulations, we quantify one such systematic, the triaxiality distribution of clusters identified with the redMaPPer optical cluster finding algorithm, which was used in the Dark Energy Survey Year-1 (DES Y1) cluster cosmology analysis. We test whether redMaPPer selection biases the clusters’ shape and orientation and find that it only biases orientation, preferentially selecting clusters with their major axes oriented along the line of sight. Modelling the richness–mass relation as log-linear, we find that the log-richness amplitude ln (A) is boosted from the lowest to highest orientation bin with a significance of 14σ, while the orientation dependence of the richness-mass slope and intrinsic scatter is minimal. We also find that the weak lensing shear-profile ratios of cluster-associated dark haloes in different orientation bins resemble a ‘bottleneck’ shape that can be quantified with a Cauchy function. We test the correlation of orientation with two other leading systematics in cluster cosmology – miscentering and projection – and find a null correlation. The resulting mass bias predicted from our templates confirms the DES Y1 finding that triaxiality is a leading source of bias in cluster cosmology. However, the richness-dependence of the bias confirms that triaxiality does not fully resolve the tension at low-richness between DES Y1 cluster cosmology and other probes. Our model can be used for quantifying the impact of triaxiality bias on cosmological constraints for upcoming weak lensing surveys of galaxy clusters.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2024

Impacts of Control, Penetration, and Distribution of Embedded Storage Network in Bulk Power System

The current shift in generation mix from fossil fuel plants towards variable and intermittent renewable energy sources is poised to create a future grid with reduced physical inertia and mismatch between generation and demand. Embedded storage, which is a concept of a coordinated network of storage units sited at the interface between the transmission and distribution system, is proposed as a mechanism to provide a buffer between generation and demand. This paper proposes an automated framework to model and integrate embedded storage in large-scale power systems with industry-grade grid-following (GFL) and grid-forming (GFM) control technologies. More importantly, the developed framework is used to explore the impacts of embedded storage control, penetration, location, and capacity in providing fast frequency response to the grid under contingency events such as generator trips and faults. The framework and study are conducted using the transient-stability simulation tool PSS/E and a realistic model of the Puerto Rico grid as a chosen test system. The simulation results show that GFL and GFM embedded storage, distributed throughout the system, with sufficient penetration and capacity, can effectively improve primary frequency response of the system under the studied contingency events.

Battery Energy Storage, embedded storage, grid-for↗

DOE OSTI2018

EPA and Idaho National Laboratory create first of its scale

Advancing the science and engineering of decontaminating water distribution systems and safely disposing of high-volumes of contaminated water are high priorities for the EPA. To help address these science gaps, EPA homeland security researchers have developed the first-of-its-scale Water Security Test Bed (WSTB). Water is an important component of everyday life. We rely on safe, clean water for our health and the health of the environment. Protecting this vital resource is critical to living safely and securely. The U.S. Environmental Protection Agency is responsible for working with water utilities to protect water systems from contamination and to clean up systems that become contaminated. Purposeful or inadvertent distribution system contamination can result in large amounts of infrastructure and water that must be cleaned. Water distribution systems contamination can be caused by, for example, natural disasters such as Superstorm Sandy or by individuals hoping to cause harm. The WSTB, constructed at the Department of Energy’s (DOE) Idaho National Laboratory, replicates a section of a typical municipal drinking water system including a piping system with roughly 445 feet of pipe and two fire hydrants laid out in an “L” shape using 40-year-old, eight-inch cement mortar lined, ductile iron pipes, excavated after twenty years of use for water conveyance. Researchers built the WSTB above ground for easy access during experiments, and to facilitate fast leak detection. Over the next several years, EPA and partner researchers will conduct experiments using simulants of various biological, chemical, and radioactive materials that simulate high toxic versions of these agents. At this “full” sized system, researchers will demonstrate approaches to contamination detection, sensor and model testing, infrastructure decontamination, water treatment and cyber testing developed at lab and pilot scale. Researchers are also able to verify if laboratory results that were effective in controlled conditions are as effective in full-scale testing. Having the ability to conduct bench scale studies in a real world setting can help address specific research gaps, and help water researchers understand conditions in which real world drinking water systems operate.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2015

Simplified predictive models for CO 2 sequestration performance assessment

CO2 sequestration in deep saline formations is increasingly being considered as a viable strategy for the mitigation of greenhouse gas emissions from anthropogenic sources. In this context, detailed numerical simulation based models are routinely used to understand key processes and parameters affecting pressure propagation and buoyant plume migration following CO2 injection into the subsurface. As these models are data and computation intensive, the development of computationally-efficient alternatives to conventional numerical simulators has become an active area of research. Such simplified models can be valuable assets during preliminary CO2 injection project screening, serve as a key element of probabilistic system assessment modeling tools, and assist regulators in quickly evaluating geological storage projects. We present three strategies for the development and validation of simplified modeling approaches for CO2 sequestration in deep saline formations: (1) simplified physics-based modeling, (2) statisticallearning based modeling, and (3) reduced-order method based modeling. In the first category, a set of full-physics compositional simulations is used to develop correlations for dimensionless injectivity as a function of the slope of the CO2 fractional-flow curve, variance of layer permeability values, and the nature of vertical permeability arrangement. The same variables, along with a modified gravity number, can be used to develop a correlation for the total storage efficiency within the CO2 plume footprint. Furthermore, the dimensionless average pressure buildup after the onset of boundary effects can be correlated to dimensionless time, CO2 plume footprint, and storativity contrast between the reservoir and caprock. In the second category, statistical “proxy models” are developed using the simulation domain described previously with two approaches: (a) classical Box-Behnken experimental design with a quadratic response surface, and (b) maximin Latin Hypercube sampling (LHS) based design with a multidimensional kriging metamodel fit. For roughly the same number of simulations, the LHS-based metamodel yields a more robust predictive model, as verified by a k-fold cross-validation approach (with data split into training and test sets) as well by validation with an independent dataset. In the third category, a reduced-order modeling procedure is utilized that combines proper orthogonal decomposition (POD) for reducing problem dimensionality with trajectory-piecewise linearization (TPWL) in order to represent system response at new control settings from a limited number of training runs. Significant savings in computational time are observed with reasonable accuracy from the PODTPWL reduced-order model for both vertical and horizontal well problems – which could be important in the context of history matching, uncertainty quantification and optimization problems. The simplified physics and statistical learning based models are also validated using an uncertainty analysis framework. Reference cumulative distribution functions of key model outcomes (i.e., plume radius and reservoir pressure buildup) generated using a 97-run full-physics simulation are successfully validated against the CDF from 10,000 sample probabilistic simulations using the simplified models. The main contribution of this research project is the development and validation of a portfolio of simplified modeling approaches that will enable rapid feasibility and risk assessment for CO2 sequestration in deep saline formations.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2020

RELAP5-3D Modeling of High Temperature Test Facility (HTTF) Test PG-26

The High Temperature Test Facility (HTTF) at Oregon State University (OSU) is a scaled integral effects experiment designed to investigate transient behavior in high-temperature gas-cooled nuclear reactors with prismatic fuel and reflector blocks. Several tests have been completed, and more are still planned to at the HTTF, including depressurized conduction cooldown (DCC) and pressurized conduction cooldown (PCC) transients. This report analyses test PG-26, a progression of the Double Ended Inlet-Outlet Crossover Duct Break transient that is referred to as a DCC. PG-26 has been performed at the HTTF between May 30 and June 30, 2019. Core initial conditions (i.e., before the DCC started) have been met using low power (<100 kW) and two of ten available electric heaters. The DCC transient was initiated during the 50 th hour of the test. The break valves were opened, and hot helium from the core and cold helium from the reactor cavity simulation tank (RCST) started mixing. The gases flowed in a countercurrent fashion, where the top half of the hot duct contained hot helium that flowed in one direction and cold helium that flowed in the other direction in the bottom half of the duct. After the pressure and density reached equilibrium, the event entered a diffusion mode. The onset of a reverse natural circulation was not observed during the DCC period of the test. Version 4.4.2ie of the RELAP5-3D computer code has been used to model the HTTF PG-26 test, and results have been compared to available high-quality measured data. The model used in this study is the quality-controlled HTTF RELAP5-3D model (HTTF base 2018-04-19 QA), originally developed by P. Bayless. The report includes RELAP5-3D results of the “base calculations” as well as some sensitivities to important uncertain model inputs, such as primary helium mass flow rate, core ceramic thermal properties, as well as heat evacuation and loop friction models. Using the base RELAP5-3D model predicts a countercurrent helium flow in the hot duct observed at the beginning of the DCC, but instead of going into a molecular diffusion mode, the model predicts the onset of natural convection. Increasing friction in the core and hot duct prevents the natural convection from happening in some of the simulations. Although some temperatures are well predicted (and even overpredicted), the general tendency is to underpredict the ceramic and helium temperatures and heat removal rates during the DCC, resulting in many of the assessment findings being in minimal or insufficient agreement with the data. It is worth noting that the described discrepancies between measured data and RELAP5-3D predictions are not RELAP5-3D code limitations. More so, they reflect limitations in boundary condition and thermal property knowledge. While the RELAP5-3D calculations of the test provide some insights into what happens during the transient, and point to missing or potentially uncertain data to which the experimenters can direct their attention, the principal conclusion is that the PG-26 test data are insufficient for a system code assessment.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

DOE OSTI2014

Subtask – CO 2 storage and enhanced bakken recovery research program

Small improvements in productivity could increase technically recoverable oil in the Bakken Petroleum System by billions of barrels. The use of CO 2 for enhanced oil recovery (EOR) in tight oil reservoirs is a relatively new concept. The large-scale injection of CO 2 into the Bakken would also result in the geological storage of significant amounts of CO 2 . The Energy & Environmental Research Center (EERC) has conducted laboratory and modeling activities to examine the potential for CO 2 storage and EOR in the Bakken. Specific activities included the characterization and subsequent modeling of North Dakota study areas as well as dynamic predictive simulations of possible CO 2 injection schemes to predict the potential CO 2 storage and EOR in those areas. Laboratory studies to evaluate the ability of CO 2 to remove hydrocarbons from Bakken rocks and determine minimum miscibility pressures for Bakken oil samples were conducted. Data from a CO 2 injection test conducted in the Elm Coulee area of Montana in 2009 were evaluated with an eye toward the possible application of knowledge gained to future injection tests in other areas. A first-order estimation of potential CO 2 storage capacity in the Bakken Formation in North Dakota was also conducted. Key findings of the program are as follows. The results of the research activities suggest that CO 2 may be effective in enhancing the productivity of oil from the Bakken and that the Bakken may hold the ability to geologically store between 120 Mt and 3.2 Gt of CO 2 . However, there are no clear-cut answers regarding the most effective approach for using CO 2 to improve oil productivity or the storage capacity of the Bakken. The results underscore the notion that an unconventional resource will likely require unconventional methods of both assessment and implementation when it comes to the injection of CO 2 . In particular, a better understanding of the fundamental mechanisms controlling the interactions between CO 2 , oil, and other reservoir fluids in these unique formations is necessary to develop accurate assessments of potential CO 2 storage and EOR in the Bakken. In addition, existing modeling and simulation software packages do not adequately address or incorporate the unique properties of these tight, unconventional reservoirs in terms of their impact on CO 2 behavior. These knowledge gaps can be filled by conducting scaled-up laboratory activities integrated with improved modeling and simulation techniques, the results of which will provide a robust foundation for pilot-scale field injection tests. Finally, field-based data on injection, fluid production, and long-term monitoring from pilot-scale CO 2 injection tests in the Bakken are necessary to verify and validate the findings of the laboratory- and modeling-based research efforts. This subtask was funded through the EERC–U.S. Department of Energy (DOE) Joint Program on Research and Development for Fossil Energy-Related Resources Cooperative Agreement No. DE-FC26-08NT43291. Nonfederal funding was provided by the North Dakota Industrial Commission, Marathon Oil Corporation, Continental Resources Inc., and TAQA North, Ltd.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2014

Subtask1.10 – CO 2 storage and enhanced bakken recovery research program

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2023

Understanding and control of Zener pinning via phase field and ensemble learning

Zener pinning refers to the dispersion of fine particles which influences grain size distribution via movement of grain boundaries in a polycrystalline material. Grain size distribution in polycrystals has a significant impact on their properties including physical, chemical, mechanical, and optical to name a few. We explore the use of Phase-field modeling and machine-learning techniques to understand and improve the control of grain size distribution via Zener pinning in polycrystalline materials. We develop a machine learning model that determines the relative importance of various parameters to exercise microstructure control via Zener pinning. Our workflow combines high-throughput phase-field simulations and machine learning to address the computational bottlenecks associated with large-scale simulations as well as identify features necessary for microstructure control in polycrystals. A random forest (RF) regression model was developed to predict grain sizes based on five Phase-field model parameters, achieving an average prediction error of 0.72 nm for the training data and 1.44 nm for the test data. The importance of the input parameters is analyzed using the SHapley Additive exPlanations (SHAP) approach which reveals that diffusivity, volume fraction, and particle diameter are the most important parameters in determining the final grain size. These findings will allow us to select the best second-phase particles, optimize grain size distributions and thus design microstructures with the desired properties. The developed method is a highly versatile and generalizable approach that can be used to assess the combined effects of individual features in the presence of multiple variables.

36 MATERIALS SCIENCE↗

DOE OSTI2015

Maximizing semi-active vibration isolation utilizing a magnetorheological damper with an inner bypass configuration

A single-degree-of-freedom (SDOF) semi-active vibration control system based on a magnetorheological (MR) damper with an inner bypass is investigated in this paper. The MR damper employing a pair of concentric tubes, between which the key structure, i.e., the inner bypass, is formed and MR fluids are energized, is designed to provide large dynamic range (i.e., ratio of field-on damping force to field-off damping force) and damping force range. The damping force performance of the MR damper is modeled using phenomenological model and verified by the experimental tests. In order to assess its feasibility and capability in vibration control systems, the mathematical model of a SDOF semi-active vibration control system based on the MR damper and skyhook control strategy is established. Using an MTS 244 hydraulic vibration exciter system and a dSPACE DS1103 real-time simulation system, experimental study for the SDOF semi-active vibration control system is also conducted. Simulation results are compared to experimental measurements.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗

DOE OSTI2019

Real-time capable modeling of neutral beam injection on NSTX-U using neural networks

A new model of heating, current drive, torque and other effects of neutral beam injection on NSTX-U that uses neural networks has been developed. The model has been trained and tested on the results of the Monte Carlo code NUBEAM for the database of experimental discharges taken during the first operational campaign of NSTX-U. By projecting flux surface quantities onto empirically derived basis functions, the model is able to efficiently and accurately reproduce the behavior of both scalars, like the total neutron rate and shine through, and profiles, like beam current drive and heating. With this being said, the model has been tested on the NSTX-U real-time computer, demonstrating a rapid execution time orders of magnitude faster than the Monte Carlo code that is well suited for the iterative calculations needed to interpret experimental results, optimization during scenario development activities, and real-time plasma control applications. Simulation results of a proposed design for a nonlinear observer that embeds the neural network calculations to estimate the poloidal flux profile evolution, as well as Z eff and fast ion diffusivity, are presented.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2019

Real-time capable modeling of neutral beam injection on NSTX-U using neural networks

A new model of heating, current drive, torque and other effects of neutral beam injection on NSTX-U that uses neural networks has been developed. The model has been trained and tested on the results of the Monte Carlo code NUBEAM for the database of experimental discharges taken during the first operational campaign of NSTX-U. By projecting flux surface quantities onto empirically derived basis functions, the model is able to efficiently and accurately reproduce the behavior of both scalars, like the total neutron rate and shine through, and profiles, like beam current drive and heating. The model has been tested on the NSTX-U real-time computer, demonstrating a rapid execution time orders of magnitude faster than the Monte Carlo code that is well suited for the iterative calculations needed to interpret experimental results, optimization during scenario development activities, and real-time plasma control applications. Simulation results of a proposed design for a nonlinear observer that embeds the neural network calculations to estimate the poloidal flux profile evolution, as well as effective charge and fast ion diffusivity, are presented.

Neural networks↗

DOE OSTI2018

Integrated Boosting and Hybridization for Extreme Fuel Economy and Downsizing

The objective of this project was to develop, demonstrate, and evaluate commercialization of a highly efficient downsized engine by electrification of the air delivery and waste heat recovery system and optimizing energy usage to achieve significant fuel economy improvement at a commercially viable cost. The system consists of an Electrically Assisted Variable speed Supercharger (EAVS), driven by an electric motor and the engine through a planetary gear train, that provides engine boost pressure and provides the mild hybrid functions of engine start/stop, torque assist, and brake energy recovery. In the exhaust path of the engine is the electric Waste Heat Recovery (eWHR) system, a roots-based expander driven by another electric motor, that enables exhaust gas energy recovery along with controlled back pressure on the engine. The two electric motors are powered by a 48V rechargeable lithium-ion battery. Further, the EAVS system coupled to an EGR valve enables very precise high exhaust recirculation rates to control the NOx emissions. Through two budget periods, the project team of Eaton, Isuzu, Southwest Research Institute and AVL designed and developed the EAVS and eWHR systems, integrated with an Isuzu diesel engine, and validated the target fuel economy performance and emissions by engine dynamometer testing and vehicle level simulations. GT Power model-based analyses results were used to size the EAVS and eWHR systems for the 1.9L Isuzu Spark engine. The two systems were built and the functional testing was carried out to verify the boosting performance of the superchargers. Following the baseline engine dynamometer testing, the two systems were integrated with the engine and the fuel economy performance and emissions were determined by combined steady state and transient testing over three drive cycles, namely, FTP75, NEDC and HWFET. The EAVS/eWHR system demonstrated 4% improvement in fuel economy for the NEDC cycle in engine dyno testing, correlating well with vehicle simulation results (5.3%). The simulation results indicated that the combination of hybrid functions and drivetrain optimization, fuel economy improvement of more than 20% was feasible with the system. The commercialization study to evaluate the cost of the system and the scalability for different engine/vehicle classes was planned for the final budget period but not completed as the project was closed at the end of budget period two.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2021

Continued Investigations of Respirable Release Fractions for Stress Corrosion Crack-Like Geometries

The formation of a stress corrosion crack (SCC) in the canister wall of a dry cask storage system (DCSS) has been identified as a potential issue for the long-term storage of spent nuclear fuel. The presence of an SCC in a storage system could represent a through-wall flow path from the canister interior to the environment. Modern, vertical DCSSs are of particular interest due to the commercial practice of using relatively high backfill pressures (up to approximately 800 kPa) in the canister to enhance internal natural convection. This pressure differential offers a comparatively high driving potential for blowdown of any particulates that might be present in the canister. In this study, the rates of gas flow and aerosol transmission of a spent fuel surrogate through an engineered microchannel with dimensions representative of an SCC were evaluated experimentally using coupled mass flow and aerosol analyzers. The microchannel was formed by mating two gage blocks with a linearly tapering slot orifice nominally 13 μm (0.005 in.) tall on the upstream side and 25 μm (0.0010 in.) tall on the downstream side. The orifice is 12.7 mm (0.500 in.) wide by 8.89 mm (0.350 in.) long (flow length). Surrogate aerosols of cerium oxide, CeO 2 , were seeded and mixed with either helium or air inside a pressurized tank. The aerosol characteristics were measured immediately upstream and downstream of the simulated SCC at elevated and ambient pressures, respectively. These data sets are intended to demonstrate a new capability to characterize SCCs under well-controlled boundary conditions. Modeling efforts were also initiated that evaluate the depletion of aerosols in a commercial dry storage canister. These preliminary modeling and ongoing testing efforts are focused on understanding the evolution in both size and quantity of a hypothetical release of aerosolized spent fuel particles from failed fuel to the canister interior and ultimately through an SCC.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

DOE OSTI2023

ActiveBAS: A Low-cost, Scalable Control Solution for Grid-Interactive Small and Medium Sized Commercial Buildings

This project aims to develop and enhance a low-cost, highly scalable control solution for Small and Medium-Sized Commercial Buildings (SMCB), assess the business potential at multiple sites, and perform commercialization efforts. The technology can be applied to any buildings served by multiple units, with the benefits being greatest for open-spaced buildings, such as banks, retail stores, restaurants, and factories. This project aims to develop an affordable control solution for: 1) SMCB grid responsiveness, 2) reduction of GHG by changing unit operations, 3) greater reduction in utility costs, and 4) rapid adoption in the marketplace. The proposed technology will be built on a previously developed and demonstrated MPC solution. The minimal sensor requirement and less need of control expertise are the unique feature of the algorithm that leads to low capital and maintenance costs, and short installation and implementation time. These attributes contribute to low capital and maintenance costs, as well as a short installation and implementation time. However, these advantages come with a trade-off: increased difficulties and unreliability when applying traditional modeling and MPC control approaches due to limited information. This final report describes the modeling approaches developed and tested to overcome these challenges. It begins by outlining the modeling challenge posed by minimal sensor requirements, then delves into the proposed modeling approaches, which primarily involve system identification. Finally, preliminary test results for a simulation case study are presented.

24 POWER TRANSMISSION AND DISTRIBUTION↗

DOE OSTI2018

EGS Collab Project Experiment 1 Overview and Progress

Enhanced Geothermal Systems (EGS) offer the potential to extract and use large quantities of clean energy, but questions remain on reservoir creation and sustainability. The EGS Collab project, supported by the US Department of Energy’s Geothermal Technologies Office, is establishing a suite of highly monitored and well-characterized intermediate-scale (~10-20 m) field test beds along with fracture stimulation and interwell flow tests to better understand processes that control formation of effective subsurface heat exchangers. EGS Collab tests will provide a means of testing tools and concepts that could later be employed under geothermal reservoir conditions at DOE’s Frontier Observatory for Research in Geothermal Energy (FORGE) or enhanced geothermal systems. Key to the project is using numerical simulations in the experiment design and interpretation of results. Our first set of experiments is underway at the Sanford Underground Research Facility (SURF) in South Dakota. To date, stepwise stimulations have been performed at two locations, with the final stimulation connecting our injection and production wells. Numerous data have been collected and are currently being analyzed.

Enhanced Geothermal Systems, EGS Collab, Stimulati↗