Between Two Zones: Balancing the Maritime Security Zone and Emergency Planning Zone for Floating Nuclear Power Plants
Explore the source record for details and available documents.
Karcz, Jason↗
SEARCH · Engineering Papers
Results for “power balancing”
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.
Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.
Impact of Non-Steady State Operation on Cooling Water Consumption at Coal- and Natural Gas-Fired Power Plants
Increased renewable energy penetration in the electricity grid in coming decades will result in more frequent cycling at thermal power plants. Simultaneously, thermal power plants may face water scarcity with declining availability of cooling water. Therefore, to enhance thermal power plants’ resiliency to water shortages it is important to understand how non-steady conditions due to cycling will impact cooling water consumption and withdrawal intensity. Non-steady operation at power plants has been previously shown to decrease power plant thermal efficiency. Energy balance models have also demonstrated that a decrease in thermal efficiency is expected to increase cooling water consumption intensity. Furthermore, past work has used operating hours data to show idling and cycling gaps where cooling systems operate more than corresponding generators. As a result, an increase in cycling behavior may impact cooling water consumption and withdrawal intensity. This study uses data from the Energy Information Administration (EIA) and Environmental Protection Agency (EPA) to quantify the impact of cycling cooling water consumption intensity for recirculating cooling systems and withdrawal intensity for once-through cooling systems using energy balance and statistical approaches. In a novel application of a fixed effects model to study the effect of temperature on cooling water consumption and withdrawal intensity, this study finds temperature was consistently expected to increase consumption intensity and withdrawal intensity. Non-steady state conditions do not increase cooling water consumption intensity with statistical significance across unit types. However, additional validation of cooling water data is required to confirm these observed trends due to the sensitivity of these findings to model form and concerns with data quality of the dependent variables, cooling water consumption and withdrawal.
20 FOSSIL-FUELED POWER PLANTS↗
IM3 GO WEST Parameter Search Dataset
GO WEST is an open-source power grid modeling framework for U.S. Western Interconnection, which allows users to tailor the model depending on their research study and science questions. It is developed to address weather and water dynamics, and associated vulnerabilities in this bulk power system. It covers 28 balancing authorities (BA) and 12 states in U.S. Western Interconnection. GO WEST allows users to select different number of nodes and come up with a simplified network by utilizing 10,000 nodal topology of U.S. Western Interconnection created by Texas A&M University. Users can try and select different number of nodes, mathematical formulations (linear programming vs. mixed-integer linear programming), transmission line limit scaling factors, and hurdle rate scaling factors. GO WEST offers a unit commitment and economic dispatch (UC/ED) module to simulate grid operations on an hourly scale. In this sense, users can calibrate and validate their model versions by comparing model outputs to historical datasets. Therefore, GO WEST can help researchers to strike a balance between model fidelity (i.e. accuracy) and computational complexity (i.e. runtime). This dataset includes model inputs and outputs from 600 model versions for each 2019, 2020, and 2021. The folder naming convention is as follows: Exp{Number of Nodes}_{Mathematical Formulation}_{Transmission Line Limit Scaling Factor in MW}_{Hurdle Rate Scaling Factor in %}_{Year}. Linear programming is designated with "simple" label whereas mixed-integer linear programming is designated with "coal" label. For example, "Exp100_simple_1000_50_2019" folder contains inputs and outputs from 2019 model version with 100 nodes, linear programming, +1000 MW transmission line limit scaling factor, and +50% hurdle rate scaling factor. GO WEST GitHub repository hosts all raw datasets, processing scripts, and model scripts. Please refer to the README file for a detailed description of the included files.
Economics↗
Impact of Geothermal District Heating System on Flexibility of Microgrid in Tuttle, Oklahoma
Flexibility is the capability of the power grid to maintain a balance between electricity generation and variable demand. This study presents preliminary results evaluating the impact of geothermal district heating systems on the flexibility of microgrid in Tuttle, Oklahoma. Heating demand profiles were modeled using EnergyPlus for the district that includes two schools and 250 single-family houses. Then, geothermal energy production was modeled using GEOPHIRES to estimate how much heating demand in the district can be supplied by five different geothermal system scenarios. The results indicated that geothermal energy production varied depending on the resource temperature at different depths, system configurations, and flow rates. For the grid flexibility analysis, electricity consumptions in the five geothermal systems were estimated for pump operations to circulate water from the wells to radiators, while electricity consumption by air-source heat pump in the base case was estimated to supply the same heating load. Electricity consumption in the geothermal systems was significantly lower than those in base cases. The electricity saved by the geothermal system was then incorporated into the microgrid electrical load profiles where variable renewable electricity generation is significantly high. The results visually showed that geothermal district heating system can improve grid flexibility as a baseload during the winter season. The results also highlighted potential opportunities to save energy costs that will be further analyzed in future study.
Cambium↗
Feedback on the Electric Emergency Incident and Disturbance Report, OE-417
The US Department of Energy (DOE) Office of Electricity (OE) mandates requirements for reporting electric emergencies and disruptions in the United States. Specific electric power industry organizations (such as balancing authorities, reliability coordinators, some generating entities, and electric utilities) report this information through the OE-417 Electric Emergency Incident and Disturbance Report via Form OE-417. Entities are required to submit Form OE-417 when at least one of the qualifying 26 criteria is met pursuant to Section 13(b) of the Federal Energy Administration Act of 1974 (Public Law 93-275). Entities are required to report, within 6 hours of the incident, loss of electric service to 50,000 customers or more for 1 hour or longer. The deadline for submitting Form OE-417 depends on the nature of the incident. An updated Form OE-417 Schedule 1 and all of Schedule 2 are both due within 72 hours of the incident to provide complete disruption information. Additionally, a Final Report must be filed within 72 hours of the incident, unless an interim update has been provided. If the incident meets specific criteria, the form must be filed within one hour, six hours, or by the later of 24 hours after the recognition of the incident or by the end of the next business day.1 The ability of DOE to respond quickly to energy emergencies that could affect the nation’s infrastructure and help alleviate or prevent further disruptions depends on the industry’s prompt and complete submission of information. This report summarizes current issues with Form OE-417 and the reporting process and presents recommendations for improvements.
24 POWER TRANSMISSION AND DISTRIBUTION↗
Floating platform effects on power generation in spar and semisubmersible wind turbines
The design and financing of commercial-scale floating offshore wind projects require a better understanding of how power generation differs between newer floating turbines and well-established fixed-bottom turbines. In floating turbines, platform mobility causes additional rotor motion that can change the time-averaged power generation. In this work, OpenFAST simulations examine the power generated by the National Renewable Energy Laboratory's 5-MW reference turbine mounted on the OC3-UMaine spar and OC4-DeepCWind semisubmersible floating platforms, subjected to extreme irregular waves and below-rated turbulent inflow wind from large-eddy simulations of a neutral atmospheric boundary layer. For these below-rated conditions, average power generation in floating turbines is most affected by two types of turbine displacements: an average rotor pitch angle that reduces power, caused by platform pitch; and rotor motion upwind-downwind that increases power, caused by platform surge and pitch. The relative balance between these two effects determines whether a floating platform causes power gains or losses compared to a fixed-bottom turbine; for example, the spar creates modest (3.1%–4.5%) power gains, whereas the semisubmersible creates insignificant (0.1%–0.2%) power gains for the simulated conditions. Furthermore, platform surge and pitch motions must be analyzed concurrently to fully capture power generation in floating turbines, which is not yet universal practice. Finally, a simple analytical model for predicting average power in floating turbines under below-rated wind speeds is proposed, incorporating effects from both the time-averaged pitch displacement and the dynamic upwind-downwind displacements.
17 WIND ENERGY↗
Hardware-in-the-Loop Evaluation of Grid-Edge DER Chip Integration Into Next-Generation Smart Meters
To facilitate the implementation of distributed energy resource management systems (DERMS), we propose to insert a grid-edge distributed energy resource (DER) chip hosting a DERMS algorithm into the next generation of smart meters. This will create a pathway for the wide adoption of DERMS technology because many utilities plan to invest in advanced metering infrastructure in the near future. This will also bridge the gap between an electrical power utility and DERs behind the meter. The DER chip is designed to follow power direction signals from the DERMS coordinator while balancing its local objectives. We tested the chip using a controller- and power-hardware-in-the-loop evaluation under three scenarios that a DERMS could face in the real world. The DER chip was capable of and effective at directing four heterogeneous DERs to respond to a DERMS coordinator for grid services (e.g., voltage regulation and a virtual power plant).
distributed energy resource management system↗
Hardware-in-the-Loop Evaluation of Grid-Edge DER Chip Integration Into Next-Generation Smart Meters: Preprint
To facilitate the implementation of distributed energy resource management systems (DERMS), we propose to insert a grid-edge distributed energy resource (DER) chip hosting a DERMS algorithm into the next generation of smart meters. This will create a pathway for the wide adoption of DERMS technology because many utilities plan to invest in advanced metering infrastructure in the near future. This will also bridge the gap between an electrical power utility and DERs behind the meter. The DER chip is designed to follow power direction signals from the DERMS coordinator while balancing its local objectives. We tested the chip using a controller- and power-hardware-in-the-loop evaluation under three scenarios that a DERMS could face in the real world. The DER chip was capable of and effective at directing four heterogeneous DERs to respond to a DERMS coordinator for grid services (e.g., voltage regulation and a virtual power plant).
distributed energy resource management system↗
Optimization-based control using input convex neural networks
Input convex neural networks (ICNNs) are a family of deep learning models where the outputs are constructed to be convex functions of the inputs. By parameterizing system models using ICNNs, optimization-based control problems can be solved as convex optimization problems, leading to improved performance and robustness. This work proposes a novel framework where the control objective function and constraints are modelled using ICNNs. A case study of optimization-based control with output constraints is conducted on a process with input multiplicity and nonminimum phase behavior. The simulation results demonstrate improved economic yield compared with normal neural networks. Additionally, the input convexity formulation is compared with simple regularization techniques, and unique benefits such as improved data efficiency and robustness of the proposed formulation are shown. Finally, by explicitly incorporating prior knowledge about convexity, this framework provides a good balance between the universal approximation power of deep learning and computational feasibility required by control.
42 ENGINEERING↗
Self-consistent integrated modeling of combined hybrid discharge-laser produced plasma devices for extreme ultraviolet metrology
Discharge- and laser-produced plasma (DLPP) devices are being used as light sources for extreme ultraviolet (EUV) generation. A key challenge for both, DPP and LPP, is achieving sufficient brightness to support the throughput requirements of nanometrology tools. To simulate the environment of a hybrid DLPP device and optimize the EUV output, we have developed an integrated HEIGHTS-DLPP computer simulation package. The package integrates simulation of two evolving plasmas (DPP and LPP) and includes modeling of a set of integrated self-consistent processes: external power source and plasma energy balance, plasma resistive magnetohydrodynamics, plasma heat conduction, detailed radiation transport (RT), and laser absorption and refraction. We simulated and optimized DLPP devices using Xe gas as a target material. We synchronized the external circuit parameters, chamber gas parameters, and laser beam temporal and spatial profiles to achieve maximum EUV output. The full 3D Monte Carlo scheme was integrated for detailed RT and EUV output calculations in Xe using more than 3600 spectral groups. The modeling results are in good agreement with Julich Forschungszentrum experimental data. Theoretical models, developed and integrated into the HEIGHTS package, showed wide capabilities and flexibility. In conclusion, the models and package can be used for optimization of the experimental parameters and settings, investigation of DLPP devices with complex design, analyzing the impact of integrated spatial effects and working timeline arrangement on the final EUV output, and EUV source size, shape, and angular distribution.
70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
Design and Analysis of a 200 kW Dynamic Wireless Charging System for Electric Vehicles
Dynamic wireless charging of electric vehicles can significantly alleviate or eliminate range anxiety while reducing the required on-board battery capacity. To achieve an electric vehicle charging balance with minimal infrastructure costs, power transfer levels around 200 kW are required. In this paper, a system architecture with a modularized power electronics and optimized power transfer couplers was adopted to enable efficient power transfer. A DC/DC converter was used for secondary-side charging control of the battery. The system performance was validated in an experimental setup at 120 kW with 91.31% efficiency from the DC input on the primary side to the vehicle battery.
Xue, Lincoln↗
Grid-Integrated Production of Fischer-Tropsch Synfuels from Nuclear Power
Idaho National Laboratory (INL) investigates the relative economic profitability of an integrated energy system (IES) coupling an NPP with a synfuel production process at selected case study locations across the United States. In the synfuel IES, a high-temperature steam electrolysis (HTSE) plant is thermally and electrically coupled with an NPP to produce zero-carbon hydrogen. The synthetic fuel is produced from this H 2 combined with a CO 2 supply using the reverse water gas shift process followed by the Fischer-Tropsch (FT) reaction. This analysis considers a system in which the CO 2 is sourced from regional CO 2 emitters via the construction and operation of pipeline-based CO 2 supply networks. Locating the FT plant at the same site as the NPP and HTSE plants enables the NPP to provide zero-carbon heat and power to the HTSE plant and zero-carbon power to the FT plant as well as avoid the requirement for long-distance H 2 product transport from the HTSE plant to the FT plant. Hydrogen storage is used to enable the NPP to dispatch power to the electrical grid (instead of the HTSE plant) when grid demand increases, thus enabling the FT plant to continue to operate in a steady-state production mode. The ability to cease hydrogen production for several hours within each day enables the NPP to provide power to the grid to balance the electricity market during peak periods and maximize revenues for the nuclear synfuel IES. The FT process design considered has a 99% carbon conversion efficiency. The use of nuclear energy and nuclear energy-derived hydrogen enables synfuel production to achieve this high level of carbon utilization. Additionally, the life-cycle carbon emissions of the nuclear-based synfuel production process are very low, with WTW emissions of approximately 25 gCO 2 e/MJ, including steam credits (generated from FT process excess heat), and approximately 7 gCO 2 e/MJ, if steam credits are excluded. This compares favorably with the WTW emissions of 90.5 gCO 2 e/MJ for a compression-ignition, direct injection (CIDI) vehicle with a fuel economy of 31.6 miles per gallon gasoline equivalent (MPGGE), using low-sulfur diesel produced using conventional petroleum production and refining processes. Several NPPs in various regions of the U.S. are considered as case study analyses. Supply locations and transportation via pipeline of the CO 2 feedstock to the NPP site are analyzed through the National Energy Technology Laboratory (NETL) CO 2 Transport Cost model. The team finds that the amount of CO 2 generated by different sectors is sufficient for the synfuel production process at all locations considered. The CO 2 transportation costs are functions of the distance of the source to the NPP location, the CO 2 capture cost at the source, and the quantity of CO 2 transported. Historical electricity prices for the NPP case study locations are collected and analyzed. Monthly average prices, price range, and duration of negative-price periods vary among these locations. For each location, an auto-regressive moving average (ARMA) model is trained on historical electricity price data. ARMA validation is done to ensure the synthetic price distributions represent one of historical prices with high fidelity. Synthetic time series from these ARMA models are used in a coupled dispatch and system optimization in the Holistic Energy Resource Optimization Network (HERON) to compute the differential net present value (NPV) of the IES. The team finds that this econometric is positive, ranging from $14M–1.3bn (2020) depending on the location. The optimal synfuel IES configuration to obtain this increase in NPV often maximizes the size of the synfuel production process with regards to the size of the NPP. However, the team shows that the NPP still plays a stabilizing role for the grid: In periods of high prices and high loads, more electricity from the NPP is sent to the grid. A high variability of electricity prices and extreme maximum prices tend to drive up electricity production. While it requires significant investment, the synfuel IES could increase the economic profitability for the existing fleet of LWRs across the country while still maintaining the grid stabilizer role of NPPs. During its lifetime, the main costs for the nuclear synfuel IES are the carbon feedstock transportation costs, followed by the capital expenses (CAPEX) and operation and maintenance (O&M) costs while the revenue comes first from the IRA H 2 production tax credit (PTC) and then from the sales of synfuel products. The profitability of the synfuel IES is most sensitive to the value of the hydrogen PTC and the synfuel products as well as the cost of the carbon feedstock, highlighting the importance of governmental incentives regarding hydrogen, carbon emissions, and synfuel in driving the deployment of future nuclear synfuel IESs.
08 HYDROGEN↗
Record Efficiency InGaAs Thermophotovoltaic Cells For Energy Storage Applications
Utility-scale energy storage is a significant technical challenge and a key barrier to widespread adoption of renewable energy. An efficient, modular, and scalable solution can be achieved by storing energy in the form of high-temperature heat and then extracting energy, on demand, using thermophotovoltaic (TPV) cells to convert the heat back to electricity. The ideal thermal emitter temperature is determined by balancing the desire for higher power densities, high-temperature compliant materials, and efficient, cost-effective thermophotovoltaic cells, among other considerations. 0.74-eV InGaAs lattice-matched to InP is a good choice for a cell absorber, and here we describe our development of InGaAs TPV cells with efficiencies of 38.8% from an ~1850 degrees celsius source temperature. This is the highest efficiency yet measured and reported for a single-junction TPV device. This efficiency was achieved by carefully quantifying and then reducing the parasitic absorption in the semiconductor layers, and by significantly reducing the series resistance to minimize the power loss.
ENERGY STORAGE,ENGINEERING,SOLAR ENERGY↗
Impact of Geothermal District Heating System on Flexibility of Microgrid in Tuttle, Oklahoma: Preprint
Flexibility is the capability of the power grid to maintain a balance between electricity generation and variable demand. This study presents preliminary results evaluating the impact of geothermal district heating systems on the flexibility of a conceptual microgrid in Tuttle, Oklahoma. Heating demand profiles were modeled using EnergyPlus for the district that includes two schools and 250 single-family houses. Then, geothermal energy production was modeled using GEOPHIRES to estimate how much heating demand in the district can be supplied by five different geothermal system scenarios. The results indicated that geothermal energy production varied depending on the resource temperature at different depths, system configurations, and flow rates. For the grid flexibility analysis, electricity consumptions in the five geothermal systems were estimated for pump operations to circulate water from the wells to radiators, while electricity consumption by air-source heat pump in the base case was estimated to supply the same heating load. Electricity consumption in the geothermal systems was significantly lower than those in base cases. The electricity saved by the geothermal system was then incorporated into the microgrid electrical load profiles where variable renewable electricity generation is significantly high. The results visually showed that geothermal district heating system can improve grid flexibility as a baseload during the winter season. The results also highlighted potential opportunities to save energy costs that will be further analyzed in future study.
Cambium↗
A Short-Term Solar Forecasting Platform Using a Physics-Based Smart Persistence Model and Data Imputation Method
Electrical energy plays vital role in our socio-economic activity and therefore ensuring the reliability of the electric grid, from the generation, transmission and distribution level is critical. In order to maintain the power system parameter viz., frequency, voltage, etc., optimally, balancing of generation and consumption is very much essential. However, solar energy is infirm power by nature this is due to cloud cover / other local phenomena. Hence, Photovoltaic (PV) power generation brings a significant challenge to the grid operator due to the variability of the solar energy. The complexity of this challenge in terms of planning and dispatch ability of PV resources, aggravates with the high penetration of solar energy into the electric grid. In this setting, reliable solar radiation forecasting models based on accurate and quality input data become essential. In order to develop a suitable model for predicting solar radiation, quality historical / real time measurement is also needed. Under this study NIWE and NREL jointly developed / tested short-term solar forecasting frameworks using a smart persistence and physics-based smart persistence models for intra-hour forecasting of solar radiation (PSPI) and benchmarked 9 different data imputation techniques in 15 Solar Radiation Resource Assessment (SRRA) stations, located at different parts of India. During any measurement campaign, due to various technical reasons, we may miss few observations. However, the missing observation often reduce the performance of any forecasting model. Therefore, suitable data imputation method would assist us to obtain continuous observation of solar radiation. A station-by-station and method-by-method analysis was carried out to understand the performance of each model. Based on our analysis, among all the data imputation methods, the Kalman data imputation method is better for Indian Weather condition. In addition, Kalman StructTS, Linear, Stine and Arima methods yield slightly inferior accuracy compared to Kalman, but outperform the other methods. The extended solar radiation data are used by solar forecasting models to provide the prediction of solar radiation at 15 SRRA stations. As far as short term forecasting model is concerned, the PSPI model outperforms the Smart Persistence model. However, the forecast error is increases with the forecasting horizon.
29 ENERGY PLANNING, POLICY, AND ECONOMY↗
MEITNER Resource Team Modeling and Simulation Support to Holos-Quad Reactor Development (Final CRADA Report)
The main objective of this CRADA is to provide Argonne National Laboratory (ANL)’s modeling and simulation capabilities via ARPA-E's MEITNER (Modeling-Enhanced Innovations Trailblazing Nuclear Energy Reinvigoration) Resource Team (RT) arrangement to support the demonstration of the viability of HolosGen’s Holos-Quad reactor design. The Holos-Quad reactor design is an advanced reactor concept that incorporates many new design features, such as the neutron-coupled Subcritical Power Modules (SPMs) in its core design, elimination of balance of plant (BOP) by direct integration of a helium Brayton cycle power conversion system with each SPM, among many other innovative features. The demonstration of the viability of such an innovative reactor design warrants iterations of modeling and simulation and testing. The purpose of this project is to utilize ANL’s modeling and simulation capabilities in nuclear reactor analysis and power conversion system analysis to inform HolosGen and the Design Team (DT) in the design and optimization of the Holos-Quad concept. The major work scopes of this project include: to investigate conceptual designs and materials for radiation shielding to protect personnel and internal components such as turbomachinery; Assess the the helium Brayton cycle power conversion system performance in both nominal and load following conditions; Investigate power conversion components and overall system performance; Identify control strategies to enable load following; Perform simulations of HolosGen’s subscale simulator and using available test data for code validation/benchmark purpose; Perform core thermal-hydraulics, safety analysis, and structural analysis.
21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
Extrapolation Domains for Aggregating Environmental Outcomes from Local to Regional Levels
Billions of dollars are invested every year to run field experiments to quantify the response of crops to new technologies and associated environmental outcomes. Given the diversity of environments where crop production occurs, conducting these research studies without a robust framework for research site selection and upscaling results to larger spatial scales is inefficient. In this project, researchers from the University of Nebraska-Lincoln used their unique Technology Extrapolation Domains framework (TED) as a tool to guide the selection of experimental sites and as basis for aggregating and validating environmental outcomes from local to regional levels. In the present project, we first used the TED framework to evaluate the current distribution and area coverage of the current SMARTFARM sites. The purpose was to showcase how it is possible to use the TED framework to guide site selection and extrapolate results over space. Additionally, the original TED framework was expanded to account for other factors influencing environmental outcomes by inclusion of three additional variables: soil organic matter, soil texture, and topographic wetness index. The resulting expanded framework (TED-E) was validated using nitrogen (N) losses from corn in the United States as a case study. To do so, we used N balance as a proxy to N losses and we evaluated the capacity of the framework to explain variation in N balance across fields and across countries. We found that the TED-E has substantially higher predictive power than the original TED framework to explain spatial variation in N balance. However, improvements in predictive power with the TED-E tool come at the expense of a higher number of TEDs needed to achieve a given crop area coverage compared with the original TED framework. We conclude that the new TED-E framework can help aggregate and extrapolate environmental outcomes from research sites to regional levels and improve the visualization of their spatial patterns across the United States. An online version of the framework is available at: https://www.toolted.org/
54 ENVIRONMENTAL SCIENCES↗
An Analysis of System Balance and Architectural Trends Based on Top500 Supercomputers
Supercomputer design is a complex, multi-dimensional optimization process, wherein several subsystems need to be reconciled to meet a desired figure of merit performance for a portfolio of applications and a budget constraint. However, overall, the HPC community has been gravitating towards ever more FLOPS, at the expense of many other subsystems. To draw attention to overall system balance, in this paper, we analyze balance ratios and architectural trends in the world's most powerful supercomputers. Specifically, we have collected performance characteristics of systems between1993 and 2018 based on the Top500 lists, and then analyzed their architectures from diverse system design perspectives. Notably, our analysis studies the performance balance of the machines, across a variety of subsystems such as compute, memory, I/O, interconnect, intra-node connectivity and power. Our analysis reveals that balance ratios of the various subsystems need to be considered carefully alongside the application workload portfolio to provision the subsystem capacity and bandwidth specifications, which can help achieve optimal performance.
97 MATHEMATICS AND COMPUTING↗