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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 343 records · Page 19
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Simulating Impacts of Extreme Events on Grids with High Penetrations of Wind Power Resources

As extreme weather events become more frequent and intense, the demand for connecting grid operation and infrastructure planning with extreme event models will increase as well. We present a methodology for creating damage contingencies and scenarios for electric transmission grids during a hurricane strike. Included is an example case study: Hurricane Dolly damaging a synthetic 2000 bus test system during its landing in Southern Texas. Using WIND Toolkit meteorological data in conjunction with fragility curves for various electric grid elements, we generate stochastic damage scenarios that can be used for short- and long-term planning problems including emergency asset management. We perform statistical analysis of damages and quantify topological effects on example synthetic grid. Also, we investigate loss-of-load events during two-day economic dispatch experiment. Finally, we point out various shortcomings of our method and suggest how it can be improved.

data-driven forecasting↗
DOE OSTI2022

Simulating Impacts of Extreme Events on Grids with High Penetrations of Wind Power Resources: Preprint

As extreme weather events become more frequent and intense, the demand for connecting grid operation and infrastructure planning with extreme event models will increase as well. We present a methodology for creating damage contingencies and scenarios for electric transmission grids during a hurricane strike. Included is an example case study: Hurricane Dolly damaging a synthetic 2000 bus test system during its landing in Southern Texas. Using WIND Toolkit meteorological data in conjunction with fragility curves for various electric grid elements, we generate stochastic damage scenarios that can be used for short- and long-term planning problems including emergency asset management. We perform statistical analysis of damages and quantify topological effects on example synthetic grid. Also, we investigate loss-of-load events during two-day economic dispatch experiment. Finally, we point out various shortcomings of our method and suggest how it can be improved.

contingencies↗
DOE OSTI2022

Understanding Economic and Deployment Benefits of Wind-PV Hybrid Power Plants

The least-cost approach to decarbonizing the U.S. electricity supply will likely involve a significantly expanded share of variable renewable energy (VRE) generation. Many strategies and approaches have been identified to address integration challenges in a VRE-dominated system, including standalone and coupled battery systems. In this study, we explored the current and future potential of utility-scale hybrid energy systems comprising PV, wind, and lithium-ion battery technologies (PV-wind-battery systems). Analysis results include temporal complementarity of wind and PV resources across the contiguous United States, with an emphasis on metrics that quantify reductions in variability that can be achieved through hybridization. We further use a price-taker model with simulated hourly energy and capacity prices to determine the revenue-maximizing dispatch of a range of PV-wind-battery configurations across Texas, from the present through 2050. We find that coupling PV, wind, and battery technologies allows for more effective utilization of interconnection capacity by increasing capacity factors to 60-80%+ and capacity credits to close to 100%, depending on battery capacity. We also compared the energy and capacity values of PV-wind and PV-wind-battery systems to the corresponding stability coefficient metric, which describes the location-and configuration-specific complementarity of PV and wind resources. Our results show that the stability coefficient effectively predicts the configuration-location combinations in which a smaller battery component can provide comparable economic performance in a PV-wind-battery system (compared to a PV-battery system). These PV-wind-battery hybrids can help integrate more VRE by providing smoother, more predictable generation and greater flexibility. Finally, capacity expansion modeling of PV-wind systems indicates that hybridization can reduce transmission expansion requirements associated with a heavily decarbonized U.S. electricity system.

complementarity↗
DOE OSTI2023

Synthetic Electricity Market Data Generation and HERON Use Case Setup of Advanced Nuclear Reactors Coupled with Thermal Energy Storage Systems

This study evaluates and optimizes advanced nuclear reactors coupled with thermal energy storage (TES) systems in an Integrated Energy System (IES) architecture to enable advanced nuclear power plants (A NPP) to participate in multi-commodity markets, thus enhancing their economic competitiveness. Nuclear-TES coupling scenarios studied herein are designed attenuate the nuclear heat dynamics and defer energy delivery to a later time, enabling the nuclear reactor to continue operating at or near steady-state design conditions as usual while also enabling flexible generation. Three A-NPPs, namely, an advanced light-water reactor (A LWR), a high temperature gas-cooled reactor (HTGR) and a liquid-metal fast reactor (LMFR) were selected as the initial use cases for demonstrating the technoeconomic of thermally balanced energy storage coupling design for thermal power extraction. Each of the reactor technologies were evaluated in two different electricity markets. Stochastic optimization approach was adopted which included the evaluation of price signals from the Pennsylvania-New Jersey-Maryland (PJM) market, and Electric Reliability Council of Texas (ERCOT), using an autoregressive moving average (ARMA) model. Risk Analysis Virtual Environment (RAVEN) tool and its dispatch optimization plugin, the Holistic Energy Resource Optimization Network (HERON), were used to perform dispatch and capacity optimization, using the price data provided by the ARMA models. The results from the Nuclear-TES use cases will be used to design and characterize dynamic integrated system behavior and feedback.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2022

SIW21-95: Hybridizing Synchronous Condensers with Grid-Forming Battery Energy Storage Systems

One of the main challenges associated with deployment of high shares of inverter-based resources (IBRs) in power grid is not only reduced system inertia but also degrading system strength that may cause severe stability impacts. A minimum level of system strength is needed for the power system to remain stable under normal conditions and to return to a steady state condition following a system disturbance. Significant system strength reduction is expected in almost all planned areas for solar and wind generation deployment. Synchronous condensers (SC) have been considered as one main technology to address the system strength issues for the areas with high levels of IBRs. SCs can help improving reliability and resiliency of power system but they do not provide the full range of services needed by power systems for reliable and economic integration of high shares of inverter-coupled variable generation such as PV generation. Services related to active power controls cannot be provided by SCs due to lack of prime mover. Even for provision of reactive power SCs have certain constraints based on their thermal and stability limits. NREL has been conducting research on a hybridized concept that combines SCs with grid forming (GFM) battery energy storage systems (BESS). This super flexible AC transmission system (SuperFACTS) that combines these two technologies in a single plant under the same controller offers a unique scalable set of services to the power system at all levels (transmission, sub-transmission, distribution, islands and isolated microgrids). Depending on use cases, SuperFACTS can be controlled to provide fully dispatchable and flexible operation using energy storage component, provide a full range of existing and future ancillary and reliability services to the grid (similar or better than conventional sources), maintain adequate levels of grid strength and inertia, and provide fault current for proper operation of protection systems. Therefore, this economic and easy to commercialize solution has potential for significant impacts on certain segments of global energy sector. All types of gird services (market based, reliability and resiliency) can be provided by SuperFACTS plants. GFM BESS can act as a self-black start source for each SuperFACTS module, which in turn can act a black start resource for co-located PV and wind power plants, segments of transmission and distribution networks, for conventional power plants, etc. The issue of in-rush currents during black start is addressed by overcurrent capability of SCs. In this paper we describe the results of modeling for SuperFACTS concept.

grid forming↗
DOE OSTI2024

High-Fidelity and High-Performance Computational Simulations for Rapid Design Optimization of Sulfur Thermal Energy Storage

Industrial process heating (IPH) accounts for approximately 70% of US manufacturing energy use and is primarily produced by fossil fuel combustion. Approximately 1500 TWht (approximately 60%) of IPH demand is in the temperature range of 100-300. Industrial applications in this temperature range include drying, hydrothermal processing, thermal enhanced oil recovery, food and beverage, bioethanol production, etc. Cost-effective thermal energy storage (TES) that increases the utilization of waste and renewable heat (solar, geothermal, etc.) could provide significant energy savings and reliable heat sources, decrease emissions, and increase US manufacturing competitiveness through reductions in fuel consumption. TES development has historically been dominated by technologies suitable for deployment with concentrating solar power (CSP). State-of-the-art thermal storage deployed commercially with power tower CSP plants uses a 60%/40% NaNO3/KNO3 molten salt and operates between temperatures of approximately 280 degrees Celsius and 570 degrees Celsius using a two-tank configuration. However, these nitrate salts are unsuitable for operation outside of this temperature range due to a high freezing point of approximately 220 degrees Celsius, and limits on high-temperature salt stability and corrosion resistance of containment alloys. Other materials being investigated for TES include those based on: (1) sensible energy storage (various molten salt compositions, inert solid particles, rocks or pebble beds, sulfur, water, concrete, graphite, etc.), (2) latent energy storage in materials that undergo solid-liquid phase change at relevant temperatures (organic materials for low-temperature applications, inorganic salts and/or metals for high-temperature applications), or (3) thermochemical energy storage (hydrides, hydroxides, carbonates, metal oxides, etc.). The application temperature and challenges pertaining to storage material and/or containment cost, energy density, long-term thermal and cyclic stability, and charge/discharge heat transfer effectiveness drive material selection for a given IPH or electricity generation application. Sulfur is a cheap commodity at $80/ton compared to $1100 - 1300/ton for conventional salts. When using a metric of storage cost per kWh, sulfur costs around 2-3 $/kWh. Previous sulfur TES development focused on high temperature (>600 degrees) concentrated solar power applications with sulfur encapsulated in pipes and flow of gaseous HTF (air) in the shell side. However, for lower-temperature IPH applications in the range of approximately 100-300 degrees Celsius Element 16 adopted a compact and scalable TES design with molten sulfur in the shell and HTF pipes submerged in the molten sulfur bath. The low-cost molten sulfur TES for dispatchable IPH has deployment potential for broad applications. The spatial and temporal evolution of the HTF and sulfur temperature is critical to the TES system performance, and thus detailed modeling can improve understanding of the performance and facilitate design improvements. Using high performance computing and computational fluid dynamics (CFD) a low-cost molten sulfur thermal energy storage (TES) system for industrial process heating (IPH) applications was developed. The unique challenges in CFD modeling of sulfur TES are the sharp property changes of sulfur relevant to the working temperatures. Above 159, liquid sulfur undergoes polymerization, and the viscosity of sulfur rapidly increases by several orders of magnitude between 159 degrees Celsius and 188 degrees Celsius, followed by a decrease in viscosity beyond 188 degrees Celsius due to thermal bound dissociation. In addition, various concentrations of H2S impurities can also modify sulfur viscosity. This numerical challenge is especially relevant to transient simulation of the sulfur TES charging and discharging processes as the extreme property variations limit the applicability of traditional heat transfer correlations. Transient CFD simulations including the temperature-dependent sulfur properties and geometric complexity of the TES design were used to predict the effect of natural convection during charging and discharging on the heat transfer process, sulfur temperature uniformity, charge/discharge rates, and performance of the storage devices. The CFD model was validated with experimental results for a full charge and discharge cycle. The work will show 3D and 2D simulation comparisons aimed to facilitate rapid design iterations and a machine learning based design optimization approach.

CFD↗
DOE OSTI2025

Practical Implementation of GPU-based Computing at the Grid Edge for Resilience Scenarios

This paper presents a practical implementation of GPU-accelerated computing at the grid edge to enhance power system resilience through next-generation smart meters. Advanced Metering Infrastructure (AMI) systems rely predominantly on centralized processing architectures, which limit real-time response capabilities during grid disturbances. This work proposes the integration of GPU-enabled computational platforms directly within smart meter to enable local execution support for power system analytics, fault detection algorithms, and optimization routines. The proposed framework uses the Julia programming language to leverage highperformance parallel computing capabilities while maintaining code portability and development efficiency. We use two experimental scenarios to benchmark the computational feasibility of this approach: sparse linear system solutions representative of power flow analyses, and multi-stage production cost simulations incorporating unit commitment and economic dispatch operations. Results demonstrate that computationally intensive power system algorithms, such as those supporting resilience scenario calculations, can be effectively executed at the distribution edge using commercially available embedded GPU hardware. Keywords—GPU acceleration, edge computing, smart meters, grid resilience, AMI, resilience.

De Souza, Reubun [School of Electrical Engineering↗
DOE OSTI2025

Digital Real-Time Simulation and Power Quality Analysis of a Hydrogen-Generating Nuclear-Renewable Integrated Energy System

This paper investigates the challenges and solutions associated with integrating a hydrogen-generating nuclear-renewable integrated energy system (NR-IES) under a transactive energy framework. The proposed system directs excess nuclear power to hydrogen production during periods of low grid demand while utilizing renewables to maintain grid stability. Using digital real-time simulation (DRTS) in the Typhoon HIL 404 model, the dynamic interactions between nuclear power plants, electrolyzers, and power grids are analyzed to mitigate issues such as harmonic distortion, power quality degradation, and low power factor caused by large non-linear loads. A three-phase power conversion system is modeled using the Typhoon HIL 404 model and includes a generator, a variable load, an electrolyzer, and power filters. Active harmonic filters (AHFs) and hybrid active power filters (HAPFs) are implemented to address harmonic mitigation and reactive power compensation. The results reveal that the HAPF topology effectively balances cost efficiency and performance and significantly reduces active filter current requirements compared to AHF-only systems. During maximum electrolyzer operation at 4 MW, the grid frequency dropped below 59.3 Hz without filtering; however, the implementation of power filters successfully restored the frequency to 59.9 Hz, demonstrating its effectiveness in maintaining grid stability. Future work will focus on integrating a deep reinforcement learning (DRL) framework with real-time simulation and optimizing real-time power dispatch, thus enabling a scalable, efficient NR-IES for sustainable energy markets.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2022

Fast simultaneous feasibility testing and applications for electrical power grids

Fast simultaneous feasibility testing (SFT) for management of an electrical power grid is achieved through various innovations. The computation problem relates to evaluation of candidate solutions for external power flows into a power grid, with respect to predetermined constraints and contingencies. Storage and computations are reduced by formulating the problem in terms of transactional nodes (e.g. third party connections for generators and loads) instead of the larger number of bus nodes. Further advantages are achieved by precomputing matrices that can be reused across multiple SFT invocations, organizing matrices and operations to reduce storage and computation, and eliminating branches that have no contingency violations. The fast SFT further enables new applications for integrating SFT with a Security-Constrained Unit Commitment (SCUC) optimizer for efficient single pass solutions; operating SFT as a service to multiple SCUC solvers; or integration with Security-Constrained Economic Dispatch (SCED) optimization.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2022

Introducing the 9500 Node Distribution Test System to Support Advanced Power Applications: An Operations-Focused Approach

The 9500 Node Test System is a representative section of distribution power system model developed as a part of the GridAPPS-D™ project, an effort funded by DOE as a part of the Grid Modernization Lab Consortium (GMLC) program. The test system was developed to fulfill a growing need to represent the rapidly evolving state of electric distribution systems by combining elements of legacy infrastructure systems, modern feeder topologies, and an anticipated future with smart grid technologies. It also provides a network model capable of supporting the simulation of operational scenarios such as the ones in a utility distribution control center. This test system allows the evaluation of the performance of advanced power applications in real-time, such as one that simulates the operations of an Advanced Distribution Management Systems (ADMS), Distributed Energy Resource Management Systems (DERMS), etc. in a Distribution control center. This model is an extension of the widely used IEEE 8500 Node Test Feeder and is currently being validated to become an IEEE test case to help increase adoption and widespread usage among both academia and industry. It is a full-size model representative of a section of a utility’s distribution system with multiple feeders fed from different substations. The model includes multiple distribution circuits, a sub-transmission system, multiple substations, behind the meter customer rooftop photovoltaics (PV), and multiple utility-scale distributed energy resources. To enable accurate simulations of operational scenarios, the 9500 Node Test System is designed to support procedure-based operations, with the ability to realistically demonstrate switching operations, feeder reconfiguration, adjustment of volt-var control equipment, dispatch of distributed generation, and response to planned and unplanned outages. The 9500 Node Test System includes three radial distribution feeders with 12.3 MVA of average load, consisting of both medium voltage and low voltage equipment each supplied by a different distribution substation. The three distribution feeders are connected to each other through Normally-Open switches which can be closed when needed to simulate restoration scenarios due to a fault. One feeder represents today’s grid with low penetration of customer-side renewables. The second represents a potential future grid with microgrids and 100% renewable penetration. The third has no customer generation resources, a district steam plant, and a utility-scale solar farm. The three diverse circuits were created to allow the simulation of both today’s situation as well as potential future scenarios. All three feeders have customers connected by low-voltage secondary triplex lines. This test system meets all requirements outlined in the report for creating a simulation environment that would enable discussion between key technical stakeholders as well as having the potential to accelerate operational application development and their subsequent testing and integration. The new model is a possible representation of what we believe the distribution grid may look like in the future: a high penetration of renewables, reconfigurable radial and mesh topology, numerous DERs, islanded microgrids, and significantly increased data and measurement density. The system supports both the solution of existing and newer algorithms but also enables the evaluation of applications in a realistic operational environment defined by task oriented procedural steps that represent the interaction between the control center operator and field personnel.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2025

Hydropower and environmental flow management: System-level trade-offs at Glen Canyon Dam

The research focuses on the Colorado River Basin, specifically examining the Glen Canyon Dam (GCD) and its influence on surrounding aquatic ecosystems. This area is crucial due to its role in hydropower production and its impact on downstream environments, including the Grand Canyon National Park. This study explores the integration of environmental factors into hydro dispatch modeling at GCD to tackle ecological challenges posed by the invasive smallmouth bass (SMB). Utilizing the GTMax SL and SERM models, the research assesses the effects of SMB control experiments on hydropower generation, economic value, and grid stability. The study examines the financial and economic impacts of bypass flows designed to release colder water to prevent SMB spawning, which can significantly reduce hydropower output and increase costs. The research identifies that declining reservoir levels and rising water temperatures in Lake Powell have facilitated SMB spawning, posing a threat to native fish populations like the endangered humpback chub. The findings highlight the importance of adaptive management strategies to balance ecological preservation with hydropower generation amid long-term weather-related challenges. The study underscores the need for comprehensive assessments of flow options to prevent SMB establishment below GCD, considering the broader implications for sediment dynamics and ecological interactions.

Ecological impact assessment↗
DOE OSTI2020

Economic Dispatch With Distributed Energy Resources: Co-Optimization of Transmission and Distribution Systems

The increasing penetration of distributed energy resources (DERs) in the distribution networks has turned the conventionally passive load buses into active buses that can provide grid services for the transmission system. To take advantage of the DERs in the distribution networks, this letter formulates a transmission-and-distribution (T&D) systems co-optimization problem that achieves economic dispatch at the transmission level and optimal voltage regulation at the distribution level by leveraging large generators and DERs. A primal-dual gradient algorithm is proposed to solve this optimization problem jointly for T&D systems, and a distributed market-based equivalent of the gradient algorithm is used for practical implementation. Finally, the results are corroborated by numerical examples with the IEEE 39-Bus system connected with 7 different distribution networks.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2022

Market-Integrated Optimization of Wind-Battery-Hydrogen Hybrids for Peaking Capacity via Storage

As Integrated Energy Systems (IES) combine multiple energy and storage technologies to provide potentially more value and less risk via resource diversification, complementary overbuild, increased flexibility, and revenue-stacking, IES value is dependent on electricity market dispatch and grid interactions should play an important role in IES design and operation. This study hybridizes and retrofits wind and combustion turbine plants to study the impacts of replacing gas generation capacity with wind, battery, PEM electrolysis, hydrogen tanks and hydrogen turbines. The optimized design is co-simulated in a production cost model with different bidding strategies in order to compare performance and highlight the importance of grid-interactions. We analyze the revenue and dispatch changes as well as the price and cost implications of wind-battery-hydrogen IESs.

electrolysis↗
DOE OSTI2026

Stakeholder-guided holistic, Adaptive Framework for enhancing community Energy Resilience (SAFER) (Final Technical Report)

The Stakeholder-guided holistic, Adaptive Framework for enhancing community Energy Resilience (SAFER) project advances resilience science and engineering by addressing challenges in rural Kansas communities where aging infrastructure, extreme weather, and socioeconomic disparities heighten vulnerability to energy disruptions. Traditional approaches often focus on technical performance while overlooking community concerns and priorities. SAFER responds by integrating community perspectives with advanced analytical frameworks to create a holistic model for measuring and improving resilience. Project objectives included developing novel resilience metrics, advancing modeling frameworks that capture interdependencies across infrastructures, and embedding community-centric indicators directly into planning processes for distributed energy resources. The key technical innovations included the creation of self-organizing map (SOM)-based indices for objective resilience quantification, hetero-functional graph theory (HFGT) models linking power, water, transportation, and community assets, and graph neural network (GNN) tools for identifying critical nodes in complex systems. Community-centric energy planning was demonstrated through optimal siting and sizing of (photovoltaic) PV and battery storage, ensuring resilience enhancements also addressed energy burden and energy insecurity. SAFER engaged community partners in Dodge City and Ford County through surveys, focus groups, and workshops, generating more than 600 responses that established baseline measures of energy burden, financial insecurity, and willingness-to-pay to avoid outages. This data, organized in terms of a community capitals framework, informed the development of weighted reliability indices that better reflect community costs than traditional utility metrics. SAFER’s GNN-based critical node identification framework identified expert-labelled critical nodes with over 99% accuracy, while also uncovering additional functionalities essential for proactive resilience planning. The project’s models demonstrated that optimal PV and storage deployment could improve resilience indices by over 11 percent, with dispatch strategies further enhancing outcomes, confirming both the technical effectiveness and economic feasibility of these approaches. Through its combined emphasis on rigorous modeling, community-focused planning, and community engagement, SAFER advances the state of resilience research while delivering direct benefits to rural communities. The project provides tools, guidelines, and resilience heatmaps that help utilities, local governments, and residents better anticipate disruptions, prioritize investments, and strengthen the capacity to withstand and recover from energy-related hazards. Furthermore, the developed HFG and GNN frameworks are designed for transferability, allowing them to be adapted for resilience planning in other communities with minimal retraining. This inductive learning capability provides a scalable pathway to extend the SAFER project’s impact. Thus, creating a foundation for a nationally applicable model of infrastructure resilience. Additionally, the HFG can also be extended to include other FEMA community lifelines.

14 SOLAR ENERGY↗
DOE OSTI2021

ARENA: Asynchronous Reconfigurable Accelerator Ring to Enable Data-Centric Parallel Computing

The next generation HPC and data centers are likely to be reconfigurable and data-centric due to the trend of hardware specialization and the emergence of data-driven applications. In this work, we propose ARENA – an asynchronous reconfigurable accelerator ring architecture as a potential scenario on how the future HPC and data centers will be like. Despite using the coarse-grained reconfigurable arrays (CGRAs) as the substrate platform, our key contribution is not only the CGRA-cluster design itself, but also the ensemble of a new architecture and programming model that enables asynchronous tasking across a cluster of reconfigurable nodes, so as to bring specialized computation to the data rather than the reverse. We presume distributed data storage without asserting any prior knowledge on the data distribution. Hardware specialization occurs at runtime when a task finds the majority of data it requires are available at the present node. In other words, we dynamically generate specialized CGRA accelerators where the data reside. The asynchronous tasking for bringing computation to data is achieved by circulating the task token, which describes the dataflow graphs to be executed for a task, among the CGRA cluster connected by a fast ring network. Evaluations on a set of HPC and data-driven applications across different domains show that ARENA can provide better parallel scalability with reduced data movement (53.9 percent). Compared with contemporary compute-centric parallel models, ARENA can bring on average 4.37× speedup. The synthesized CGRAs and their task-dispatchers only occupy 2.93mm 2 chip area under 45nm process technology and can run at 800MHz with on average 759.8mW power consumption. ARENA also supports the concurrent execution of multi-applications, offering ideal architectural support for future high-performance parallel computing and data analytics systems.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

Tri-Level Scheduling Model Considering Residential Demand Flexibility of Aggregated HVACs and EVs Under Distribution LMP

Residential loads, especially heating, ventilation and air conditioners (HVACs) and electric vehicles (EVs), have great potentials to provide demand flexibility which is an attribute of grid-interactive efficient buildings (GEB). Under this new paradigm, first, EV and HVAC aggregator models are developed in this paper to represent the fleet of GEBs, in which the aggregated parameters are obtained based on a new approach of data generation and least squares parameter estimation (DG-LSPE), which can deal with heterogeneous HVACs. Then, a tri-level bidding and dispatching framework is established based on competitive distribution operation with distribution locational marginal price (DLMP). Furthermore, the first two levels form a bilevel model to optimize the aggregators’ payment and to represent the interdependency between load aggregators and the distribution system operator (DSO) using DLMP, and the third level is to dispatch the optimal load aggregation to all residents by the proposed priority list-based demand dispatching algorithm. Finally, case studies on a modified IEEE 33-Bus system illustrate three main technical reasons of payment reduction due to demand flexibility: load shift, DLMP step changes, and power losses. They can be used as general guidelines for better decision-making for future planning and operation of demand response programs.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2023

Flexible Fully-Decoupled Nuclear Plants with Thermal Energy Storage - Technoeconomic Optimization

New nuclear power plants may be one of the technologies for future zero carbon electricity production. These future systems will however also need significant flexibility to cope with fluctuating demand and large share of intermittent renewable supply, rather than running in conventional baseload generation. The present work explores the use of thermal energy storage (TES) as a buffer between the reactor heat and its conversion to electricity, enabling flexible operation of nuclear plants. The focus is on maximizing flexibility, ideally as full decoupling of the nuclear and power cycle islands, as well as on system efficiency in various modes. A system design presented for a high temperature gas cooled reactor (HTGR) presents a slightly complex solution, as separate high- and low-temperature TES systems are required in order to cover the extended temperature range. Although this configuration imposes certain limitations on the discharge system configuration, it also presents the opportunity to design a more efficient system. For this case in particular, a steam reheat cycle is advantageous. Dynamic models were developed for the decoupled system in order to generate insights into aspects of off design operation and system control. A technoeconomic analysis, furthermore, provides sizing and costing of the component, followed by size and dispatch economic optimization considering energy arbitrage. This optimization shows that in all explored markets, the addition of TES system with the proposed configuration results in positive impact on project net present value. Further sensitivity analyses show impact of multiple inputs and possible technical limitations.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗
DOE OSTI2020

Geothermal Deep Direct Use for Turbine Inlet Cooling in East Texas

The National Renewable Energy Laboratory (NREL), the Southern Methodist University Geothermal Laboratory (SMU), Eastman Chemical (Longview, TX), and TAS (Houston, TX) evaluated the feasibility of using geothermal heat to improve the performance of a natural-gas power plant in East Texas. The area of interest is the Eastman Chemical plant in Longview, Texas, which is on the northwestern margin of a geologic region known as the Sabine Uplift. The feasibility study focused on determining the potential for accessing a subsurface hot-water geothermal resource within a 10-km radius of the site to provide thermal energy for absorption chillers. Wells within a 20-km radius are included for broader geological comparison to determine the heat flow, temperature-at-depth, field porosity and permeability. The lithologies of most interest are the Lower Cretaceous Trinity Group and Upper Jurassic Cotton Valley Group. The deeper Cotton Valley formations are hotter (averaging 117 to 130°C), yet permeability and porosity are low. The shallower Trinity Group contains more variability in permeability and porosity and lower temperatures averaging about 98 to 117°C. The shallower formations are considered despite the lower temperature because of increased ability to produce larger volumes of water and extract enough heat before reinjection. The complete SMU analysis is available in the National Geothermal Data System (NGDS). Tapping such deep geothermal sources for direct heating (as opposed to power generation) is known as geothermal deep direct use (DDU). Geothermal DDU has potential across a wide swath of the United States but is underutilized due to challenging project economics associated with developing a deep geothermal resource for what are typically small-scale, variable-demand projects. This project examines the feasibility of geothermal energy integration in a natural-gas combined cycle power station in East Texas. The DDU resource is tapped to drive absorption chillers (24/7) for production of chilled water at 5-10°C (41-50°F). This chilled water is stored until needed, which allows for continuous operation with a relatively small-capacity geothermal/absorption chiller system. When conditions are favorable, the chilled water is dispatched to cool the air entering the compressor stage of a gas combustion turbine. This process, known as turbine inlet cooling (TIC), boosts power production during periods of high temperature and high-power demand. Such systems can enhance grid reliability and reduce the cost for peak-demand power. A simulation model of the power plant was developed in IPSEpro software and validated against operational data from the plant. This model allowed the team to estimate the additional power that could be produced by applying TIC under different operating and ambient conditions. Absorption chiller performance was estimated from vendor sources to determine the production rate of chilled water from the geothermal resource. Geothermal drilling and development costs were estimated using NREL's GEOPHIRES 2.0. The expected lower drilling costs in this region led to an estimated cost of geothermal heat of about $4/MMBtu (1.4 cents/kWh t ). The estimated cost for the absorption chillers and TIC hardware were obtained from literature sources and project partners. Hourly data were obtained for weather, natural gas and electricity prices, and plant operating state for 2017, which served as a representative year. NREL estimated the capital cost, operating cost, and additional electricity production and revenue for different combinations of geothermal capacity, chiller capacity, and water storage-tank size. The analysis drove toward smaller geothermal and chiller systems to reduce equipment cost. A relatively low-cost water storage tank accumulated the near-continuous chilled water output for later use when TIC was most valued.

15 GEOTHERMAL ENERGY↗