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70 records · Page 4

Learning-Based Building Flexibility Estimation and Control to Improve Microgrid Economics and Resilience: Preprint

This paper proposes a learning-based building flexibility estimation and control framework to improve system economics and resilience. A data-driven building load flexibility model consisting of weather forecasting and estimating load consumption is proposed to quantify building heating, ventilation, and air conditioning (HVAC) load flexibility. A reinforcement learning-based microgrid controller is proposed to dispatch distributed generators, distributed energy resources, and build HVAC loads while taking flexibility information as one of the inputs. Simulation analysis is conducted on the model of a real microgrid in California. The effectiveness of the proposed learning-based building flexibility estimation and control in reducing microgrid energy costs and improving the sustainability of critical loads is demonstrated.

building load flexibility

First Solar Thermal Energy Planner (STEP 1) and Nationwide Industrial Heat and Power Analysis

The First Solar Thermal Energy Planner (STEP 1) and Nationwide Industrial Heat and Power Analysis (aka the STEP 1 Project or the Project) aimed to (1) developed a brand-new web tool that could provide decision support through free, rapid techno-economic analysis of behind-the-meter solar+storage systems for industrial process heat and (2) conduct high-level analyses of the cost-competitiveness of the same systems across the US in key sectors. The STEP 1 web tool collects key location, land availability, thermal load profile, proccess heat temperature and media, and other key parameters through an easy-to-use user interface (UI). The UI was designed to meet the user at their level of understanding by minimizing the number of required inputs as much as possible while including options for more nuanced inputs if the user desires. STEP 1 advises users on which solar thermal tehcnologies that could fit their needs based on the inputs provided (namely process media and temperature). The tool can model a wide range of solar thermal technologies including flat plate collectors, evacuated tubes, parabolic troughs, linear Fresnel, and molten salt towers all with corresponding thermal energy storage (TES) - solar PV with resistive heating and TES is also included. Once the parameters are collected, a nominal thermal energy production profile for the facility's location is generated using NREL's System Advisory Model (SAM) and then passed to a modified version of NREL's REopt platform to optimize the size (capacity) and dispatch of the solar+storage system to minimize lifecycle costs subject to energy balance, fuel and electricity rates, emission reductions goals, and other constraints. This entire process takes less than 20 minutes, is completely free, requires zero coding skills, and provides the user with a high-level assessment on the techno-economic feasability of deploying solar+storage systems for their energy needs. In addition to the development of the STEP 1 web tool, the project completed two complementary analyses focused on leveraging the backend code of STEP 1, public industrial facility locations and fuel consumption data, and key sector information to assess the economic opportunity of reducing fuel costs at various levels of capacity factor around the US. Both analyses found that there are key markets, locations, industrial sectors (namely food and beverage), and degrees of offset where solar thermal technologies could be cost-effectively deployed, highlighting a key market entry point for these technologies, and assessing deployment potential. In summary, the STEP 1 project improved the opportunities for solar+storage systems to expand into the industrial process heat market through breaking down barriers to assessing these technologies.

14 SOLAR ENERGY

System and Component Development of Particle-Based Pumped Thermal Energy Storage

Reliable power supply from variable renewable resources requires energy storage at various scales to overcome resource intermittency. Long-duration energy storage (LDES, 10-100 hours) can improve dispatchability and grid reliability with increasing levels of renewable power supply. Thermal energy storage (TES) has siting flexibility and the ability to store a large capacity of energy, and thus has the potential to meet the LDES need and provide charging and discharging durations beyond the economic capacity of conventional batteries. TES technology has evolved from concentrating solar thermal power (CSP) generation and is recognized as an economic large-scale energy storage method. A standalone electric-thermal energy storage system supporting renewable integration of wind and solar power without CSP solar field can firm renewable generation and boost overall grid resilience and security.

concentrating solar thermal power

Techno-Economic Analysis and Market Potential of Geological Thermal Energy Storage (GeoTES) Charged With Solar Thermal and Heat Pumps

In this project, we developed a techno-economic analysis (TEA) model that can be used to evaluate the viability of a proposed Geological Thermal Energy Storage (GeoTES) design. This MATLAB-based model integrates distinct subsystem models for the reservoir, wells, power cycle, and solar field to capture their distinct characteristics. It applies this approach in simulating GeoTES storage and dispatch operations for durations ranging from hourly to seasonal. Using cases studies based on GeoTES designs provided by industry partners - Premier Resource Management (PRM) and EarthBridge Energy - we validated the TEA model estimations of system performance and costs (such as thermal and electrical power/energy inflow and outflow, capital costs, and levelized costs of energy and storage) for both concentrating solar thermal (CST) and Carnot Battery (CB) pairings with GeoTES (CST-GeoTES and CB-GeoTES). For the CST-GeoTES case, the model was validated against the proposed system designed by PRM. It showed good agreement with PRM's estimations when well and pump costs derived from PRM's estimations were used. When GETEM-based costs were used, there was a slight overprediction due to GETEM's project/site agnostic assumption of these costs. From a sensitivity analysis perspective, the levelized cost of electricity (LCOE) of the CST-GeoTES case was most sensitive to well flow rate and the charging temperature. An optimal design scenario resulted in an LCOE of 0.11 $\$$/kWhe. CST-GeoTES can also provide a source of heat to meet seasonal demands. With 12-hour and 24-hour levelized cost of heat (LCOH) of 0.018 $\$$/kWhth and 0.022 $\$$/kWhth, respectively, CST-GeoTES could be competitive in the California market with an average industrial price of natural gas in California between 0.041-0.047 $\$$/kWhth. The levelized cost of storage (LCOS) for CST-GeoTES depends on the energy storage duration. Although the LCOS is relatively higher for shorter durations (e.g., ~0.50 $\$$/kWhe for 1 hour of storage), it is an order of magnitude lower (0.06 $\$$/kWhe) for longer storage durations and competitive with lithium-ion batteries (beyond 12 hours of storage) and molten-salt thermal energy storage (beyond 32 hours). Energy. Three options were explored and applied to the EarthBridge case study: (1) A Carnot Battery design using R125 working fluid with both hot and cold storage; (2) A Carnot Battery design using R125 working fluid with only hot storage; (3) A Carnot Battery using a commercially available heat pump with carbon dioxide (CO2) working fluid and hot storage only. The CB-GeoTES with cold storage only had a slight (round-trip) efficiency advantage over the system without (43.4% vs. 42.8%). This is because the cold storage is limited by the freezing point of water, so the cold storage is not much colder than the environment. The system using commercially available technologies was the least efficient - partly because different cycles were used in the heat pump (CO2) and heat engine (binary cycle) which leads to some inefficiencies. Using the commercially available design, the levelized cost of energy (LCOS) from the model (0.10 $\$$/kWhe) was higher than that estimated by EarthBridge (0.068 $\$$/kWhe). This is because of the low round-trip (38.7%) efficiency of the commercially available design. Sensitivity analysis reveals that the model is most sensitive to electricity price. Including electricity price in the TEA for CB-GeoTES leads to an increase in LCOS from the base value to 0.25 $\$$/kWhe. To determine storage sites suitable for GeoTES, we gathered and analyzed geological, petrophysical, and geophysical data of oil and gas reservoir and aquifers in California and Texas. We down-selected possible sites based on cut-off values for site characteristics (e.g., reservoir temperature, formation thickness, permeability, porosity, depth, and brine salinity) and preliminary costs. Using this approach, the Carrizo-Wilcox, Yegua-Jackson, and Dockum brackish aquifers in Texas were identified as having the highest suitability. Similarly, in the central California region, the White Wolf, Belridge South Tulare, and Belridge South Reef Ridge were the most suitable. Going further, we assessed the storage potential in the selected sites. To do this we developed distributions of reservoir characteristic data and applied a Monte Carlo-based analysis to account for intrinsic uncertainty in the acquired data. The analysis revealed that the Carrizo-Wilcox aquifer had the highest storage potential with a mean capacity of 554 TWhth (i.e., 63 TWhe). The estimated capacity serves as an upper limit of storage potential given that not all fields in the basin will be developed. We participated in multiple outreach activities including conference presentations, panel session discussions, and the facilitation of a GeoTES workshop at the NREL Golden campus.

15 GEOTHERMAL ENERGY

A hierarchical framework for aggregating grid-interactive buildings with thermal and battery energy storage

The behind-the-meter (BTM) thermal and battery energy storage can help improve energy efficiency, reduce energy costs, and enhance energy resilience, particularly in rural areas and for disadvantaged communities. Aggregating numerous BTM energy storage systems can act as a price influencer with a significant source of load shifting and peak demand reduction. An integrated and scalable control mechanism is required to effectively utilize energy storage systems and flexible building loads to maximize the economic benefits, considering various distribution system constraints. Here, this paper presents an innovative hierarchical coordination framework for energy storage and flexible load in buildings, considering various factors such as electricity prices, thermal comfort, and distribution system modeling and constraints. At the upper level, a distribution system operator optimizes the power flow to minimize its power procurement costs from the electricity wholesale market, while at the lower level, aggregators determine the optimal dispatch of battery and thermal energy storage systems in multiple buildings on behalf of end-users to minimize operating costs according to the power prices. These problems are solved using a game-theoretic approach through negotiations between the distribution system operator and aggregators as a bi-level decision model. Simulation case studies have been performed for a test distribution network with a number of building end-users using energy storage systems to quantify the performance of aggregators. The results demonstrate that the proposed strategy can reduce peak load for a reliable electricity distribution network while saving electricity bills for customers.

25 ENERGY STORAGE

Solar and Storage Integration in the Southeastern United States: Economics, Reliability, and Operations

Solar energy has the potential to be a core energy resource for the southeastern United States. To better understand the implications of higher levels of solar PV (27%-43% of total generation capacity) and electricity storage (13%-49% of peak load) would affect electricity system reliability, costs, and operations in the U.S. Southeast, this study sought to address two main questions. First, how would higher levels of solar PV and electricity storage impact the costs, reliability, and operations of electricity systems in the Southeast in 2035? Second, at different levels of solar PV and electricity storage, what are the benefits of operational coordination among utilities in the Southeast, through more efficient regional dispatch and sharing operating reserves? To answer these questions, the study used detailed capacity expansion and dispatch modeling to develop and examine 15 scenarios with different levels of solar PV, electricity storage, and operational coordination, focusing on the year 2035. The study also evaluates the benefits of operational coordination among utilities through more efficient regional dispatch and reserve sharing, at different levels of solar and storage. The study focuses on five balancing regions that cover Alabama, Georgia, Kentucky, North Carolina, South Carolina, Tennessee, and parts of Mississippi and Missouri.

14 SOLAR ENERGY

Solar and Storage Integration in the Southeastern United States: Economics, Reliability, and Operations

Solar energy has the potential to be a core energy resource for the southeastern United States. To better understand the implications of higher levels of solar PV (27%-43% of total generation capacity) and electricity storage (13%-49% of peak load) would affect electricity system reliability, costs, and operations in the U.S. Southeast, this study sought to address two main questions. First, how would higher levels of solar PV and electricity storage impact the costs, reliability, and operations of electricity systems in the Southeast in 2035? Second, at different levels of solar PV and electricity storage, what are the benefits of operational coordination among utilities in the Southeast, through more efficient regional dispatch and sharing operating reserves? To answer these questions, the study used detailed capacity expansion and dispatch modeling to develop and examine 15 scenarios with different levels of solar PV, electricity storage, and operational coordination, focusing on the year 2035. The study also evaluates the benefits of operational coordination among utilities through more efficient regional dispatch and reserve sharing, at different levels of solar and storage. The study focuses on five balancing regions that cover Alabama, Georgia, Kentucky, North Carolina, South Carolina, Tennessee, and parts of Mississippi and Missouri.

14 SOLAR ENERGY

Low-Cost Sulfur Thermal Storage for Solar Industrial Process Heat Applications

Industrial process heat (IPH) is one of the largest energy demands in U.S., representing about 10% of all domestic energy consumption. Fuel costs to generate this industrial process heat are generally a top three cost for industry, a major component in American manufacturing competitiveness. Roughly 60% of US IPH demand (about 6,500 TBtu annually) falls in the medium-temperature range of 100–250 °C. While concentrated solar thermal (CST) technologies can provide a cost-effective source of heat in this temperature range, solar intermittency limits their adoption in industries that operate 24/7. Element 16 Technologies, Inc. developed a low-cost sulfur thermal energy storage (TES) technology to bridge this gap by capturing excess solar heat during the day and dispatching it reliably during non-solar hours. The core innovation is the use of sulfur, an abundant, industrial waste byproduct that costs ten times less than molten salt used in commercial TES systems. The overall goal of the project was to advance the design and development of molten sulfur TES to a manufacturing-relevant prototype stage for solar industrial process heat applications, while establishing and validating a realistic pathway to commercial success. Key tasks included corrosion and mechanical durability testing to identify cost-effective materials, design investigations using physics-based simulation tools, techno-economic evaluations of system lifetime costs, and pilot-scale testing for performance verification. Corrosion testing of steel alloys under cyclic molten sulfur conditions showed that austenitic stainless steels in the 300 series performed particularly well, with no structural degradation of welds or joints. Thermal cyclic testing of pilot sulfur TES units up to 1.5 MWh quantified charge/discharge rates, heat losses, round-trip efficiency and validated the system's capability to operate effectively under intermittent charging conditions. A techno-economic model, informed by sulfur TES performance model validated using pilot test data, showed that hybrid solar+sulfur TES+NG boiler systems are economically competitive with incumbent natural gas boilers for multiple locations in the southwest US. In summary, this project established molten sulfur TES as a technically viable pathway to improve economic competitiveness of American manufacturing by lowering the cost of solar industrial process heat.

14 SOLAR ENERGY

West Coast Offshore Wind Transmission Study

As a primary federal investigation of the utility of transmission to support offshore wind emergence in the Western Interconnect, the West Coast Offshore Wind Transmission study evaluates five distinct West Coast-wide transmission scenarios and trades the economic benefits and costs of six development pathways from 2035 to 2050. In this time, 33 GW of OSW generation and supporting transmission are explored within the context of 350 additional GW of generation to support 100% clean electricity. Geospatial analysis informed plausible transmission topologies and cost estimates. All pathways to intraregional or interregional coordination transmission builds showed more than $\$$14 billion in present value cost savings, with a maximum of $\$$25 billion of savings in the interregional case. These savings are primarily driven by fuel costs and increased availability of power flows enabled by new transmission networks. Key considerations of clean, dispatchable generation options, geographic disaggregation of costs, system reliability reinforcements, resilience, and community values are also presented and discussed.

17 WIND ENERGY

Systems Analysis of Biomass and Coal Co-firing Power Plants with Deep Carbon Capture Toward Net-zero Emissions

Achieving a net-zero emission economy in the United States requires integrating diverse low-carbon and negative-emission technologies into the existing fossil fuel-dominant power fleet. Potential technologies from the low-carbon portfolio include renewable power, fossil power with carbon capture and storage (CCS), bioenergy with CCS (BECCS), and direct air capture (DAC). Renewable power is a clean energy source but has to pair with costly battery storage to provide dispatchable electricity. Fossil power with CCS offers dispatchable electricity yet still relies on DAC to offset residual emissions, even when deploying deep CCS with more than 90% CO2 capture. Coal-biomass co-firing with CCS, a subset of BECCS, is a reliable energy production technology that can be retrofitted from existing electricity generation units (EGUs). Power plant retrofit maximizes the use of the current U.S. coal power fleet without the need for large-scale deployment of new renewable power, battery storage, or DAC. Retrofitting coal-biomass co-firing with deep CCS in EGUs is a promising option, but not a universal solution. Biomass co-firing at a power plant introduces economic challenges and indirectly poses pressure on land and water resources. Meanwhile, retrofitting deep CCS affects plant efficiency and raises electricity generation costs. Overall, the technical feasibility and economic viability of plant retrofits vary across EGUs, as they are contingent upon the regional availability of biomass, unit-specific characteristics, site-specific fuel supply costs, and adjacent CO2 storage potential. Government incentives like 45Q can improve the retrofit viability, though the impact requires further quantification. A comprehensive analysis at the unit level is essential to address the question regarding the fate of the U.S. coal-fired electricity generation fleet toward the net-zero emission goal. This study conducts a systematic techno-economic-environmental assessment of EGUs to identify the viability of biomass co-firing and deep CCS retrofits in the U.S. coal-fired power fleet. Specifically, it characterizes the techno-economic performance of deep carbon capture, estimates life cycle greenhouse gas (GHG) emissions, and conducts a fleet-level assessment on retrofit viability. The key objectives are (1) to estimate the unit-specific performance and retrofitted cost under various biomass co-firing levels and CO2 capture rates; (2) to determine the possibility of reaching net-zero emission at the fleet level; (3) to quantify the cumulative capacities that are suitable for plant retrofits under current and future biomass supply scenarios; and (4) to improve the understanding of policy impacts on such retrofits to help the power sector’s transition to a net-zero economy. Techno-economic Model of Deep Carbon Capture. This study develops the performance and economic models for Monoethanolamine-based post-combustion CO2 capture at 95–99% capture rates. The process is simulated in Aspen Plus, analyzing the performance of carbon capture technology by varying the plant sizes, solvent lean loading, CO2 concentrations, and flue gas inlet temperature. Based on the key inputs and output parameters of CO2 capture, a reduced-order performance model of deep carbon capture is formulated. In addition, an engineering-economic model integrating the performance metrics is developed to estimate the capital as well as operation and maintenance (O&M) costs. Capital cost estimations follow the framework of the Integrated Environmental Control Model (IECM) and incorporate data regressions from three technical reports by IECM, the National Energy Technology Laboratory (NETL), and the National Renewable Energy Laboratory. The O&M cost estimation utilizes the actual inventory consumption rate and labor requirements. Both performance and cost models are embedded into IECM v13.0-beta, a fossil-fuel power plant modeling tool. Life Cycle Assessment of Power Plants. This study estimates the GHG emissions of power plants through life cycle assessment (LCA). The LCA scope includes fuel supply, combustion-based power generation, and CO2 transport and storage. The fuel-based life cycle module is designed following the framework of the NETL Unit Process Library and CO2U LCA Guidance Toolkit. The module is then incorporated into IECM v13.0-beta. The process-based LCA is applied to estimate the GHG emissions of coal and biomass supply, coal- and coal-biomass co-firing power plant operation, as well as CO2 pipeline transport and geographical sequestration. An uncertainty analysis is conducted to quantify the variability and uncertainty associated with the LCA using the Latin Hypercube Sampling (LHS) method. Fleet-level Assessment. This study evaluates the technical and economic feasibility of selected coal-fired EGUs, examines the role of tax credits in retrofit viability, and assesses the competitiveness of retrofitted units against other low-carbon options. Unit screening identifies EGUs for the study, focusing on new, efficient baseload units with air pollution controls. The power plant databases are then established to organize unit-specific information on performance and operating conditions from the relevant public databases. Biomass for co-firing retrofits is selected based on home and neighboring county availability, ensuring sustained operation with at least a 5% co-firing level. The CO2 storage site is determined by state-level storage potential, with ArcGIS Pro and NETL CO2 Saline Storage Cost Model used to identify the optimal balance between the nearest transport distances and affordable storage costs. The latest IECM v13.0-beta is then employed to configure and evaluate the eligible EGUs with or without the deployment of deep CCS and biomass co-firing. A supply curve is established to illustrate the cumulative installed capacity suitable for retrofits at different cost levels. A sensitivity analysis on tax credits for carbon sequestration is performed. Finally, a unit-level cost comparison is conducted among retrofitted plants, renewable power with battery storage, and abated fossil fuels with DAC. Expected Results. This study evaluates the technical, economic, and environmental metrics of each EGU across an array of CO2 capture rates and biomass co-firing level scenarios. Unit-level comparisons will identify critical factors influencing technical performance. The supply curves with and without tax incentives will provide insights into the impact of tax credits on biomass co-firing and CCS deployment. The cost comparisons with renewables and DAC-retrofit will assess the competitiveness of the retrofitted units. Life cycle emissions from each unit will be assessed to identify the scenarios under which net-zero emissions can be achieved. These analyses are expected to determine the total coal-fired capacity suitable for serving as a low-carbon energy source with or without tax incentives. The study results are novel in identifying optimal unit-specific strategies for producing carbon-neutral power, whether through retrofitting EGUs with deep CCS, biomass co-firing, DAC, or installing renewable power with battery. The findings will provide insight into nationwide efforts to ensure reliable, affordable, and low-carbon electricity. It also will inform investment decisions and policies in the deployment of deep carbon capture and negative emission technologies for a net-zero energy future.

Biomass Co-firing

Solar Thermal Energy Planner (STEP 1): A New Decision Support Tool for Solar Industrial Process Heat Applications

Solar thermal technologies are a promising technology to supply low-cost thermal energy to industrial processes, but there are often significant barriers to entry to industrial owners considering these technologies for their energy demands. To overcome this barrier and convey economic value to customers, NREL and Sandia National Laboratories developed Solar Thermal Energy Planner (STEP 1), a new web-based decision support tool for solar industrial process heat systems. At SolarPACES 2024, the STEP 1 tool was still under development; progress, methodologies, and a preliminary case study was presented. With the STEP 1 tool launch in May 2025, in this work, the initial version of the full public tool will be presented with demonstrations of its capabilities using a few case studies. First, the user's process heat needs such as location, process media (e.g., steam, air), process temperature, land availability, electricity and fuel costs, among other parameters. STEP 1 features a mapping interface that allows users to draw land and roof boundaries. The process media and temperature inform technology selection criteria modules that determine the appropriate solar thermal collection technologies, as well as congruent heat transfer media (e.g., hot water, oil, salt). Once the solar thermal technology selected, its nominal thermal production for the given site is characterized using NREL's System Advisor Model (SAM). Then, a modified version of NREL's REopt optimal sizing and dispatch optimization tool determines cost-optimal sizing. Within minutes, the user receives the results of the technoeconomics analysis, including the size and performance of the cost-optimal solar-plus-storage system. The cost of the system is compared to business-as-usual (e.g., an existing, standalone natural gas boiler). Users can download key results to store for sensitivity analyses. Examples of flat plate collector, parabolic trough, and molten salt tower applications with and without PV hybridization for different industrial facility types are presented in this work. The STEP 1 tool aims to reduce barriers to the adoption of solar heating solutions stemming from a lack of familiarity and technical background with solar system design options and costs among industry stakeholders.

14 SOLAR ENERGY

NG-CT Peaker Upgrades with Bottoming Cycle: Preliminary Analysis

The National Energy Technology Laboratory (NETL) has conducted a preliminary analysis exploring a significant opportunity to increase the nation's power grid capacity and reliability. The study focuses on retrofitting under-utilized natural gas combustion turbines (NG-CTs), often called "peaker" plants, with a bottoming cycle to capture waste heat and generate additional electricity. This analysis shows that upgrading these existing assets could add approximately 26,250 MW of new power capacity across the United States. A detailed study of the PJM Interconnection, the nation's largest grid operator, confirmed the benefits of these upgrades. Key findings for the PJM region include: - A median increase in the plants' capacity factor by 17 percentage points. - A projected 36.2% median reduction in the levelized cost of electricity (LCOE) for the upgraded plants, with nearly 88% of them expected to break even. - An average reduction in the regional wholesale price of electricity by approximately 3.0% in the year 2030. - A significant boost to grid reliability, with a 46% reduction in projected Loss of Load Hours (LOLH). These findings suggest that retrofitting peaker plants is a promising and economically viable strategy to enhance grid performance, reduce electricity costs, and meet future demand without the challenges associated with building entirely new facilities.

bottoming cycle

Craig Energy Center Feasibility Study

Tri-State Generation and Transmission Association Inc. (“Tri-State”) provides wholesale electric power to its member cooperatives and public power districts that collectively deliver electricity to more than a million consumers in Colorado, Nebraska, New Mexico and Wyoming. The Craig Power Station has been an integral part of Tri-State’s dispatchable generation fleet that ensures an affordable, reliable and resilient energy supply for its members. The ownership of the Craig Station Unit 1&2 is a collaborative between Tri-State, Salt River Project Agricultural Improvement and Power District, Platte River Power Authority, PacifiCorp, and Public Service Company of Colorado and is known as the Yampa Project. Tri-State owns all of Craig Unit 3 and is the operator of all three units. All three of the Craig units have planned retirement dates that will not extend beyond 2028 and Tri-State Generation wanted to evaluate carbon-neutral emitting technologies that could provide approximately 300 megawatts (“MWs) of capacity and energy that will be lost after Unit 3 ceases operation, as well as provide a similar level of economic benefits to the Craig community. This report is to serve as a technology feasibility study constrained to the current land area available at the Craig site and was conducted based on the limitations of the region.

25 ENERGY STORAGE

A method for assessing economic, environmental, and reliability tradeoffs of interregional transmission connecting ERCOT (the Texas grid) to the eastern and western grids

Reliable development of the power grid is an evolving concern for humanity due to extreme weather that frequently threatens power sector infrastructure. The state of Texas is a uniquely structured testbed for grid planners to study when looking for solutions to development, innovation, and overcoming such challenges. Because of its size and islanded structure, Texas is small enough to model, but big enough to matter. Texas is a global leader in energy production, energy consumption, and maintains an unusually diverse fuel mix. In addition, the state has experienced winter freezes, heat waves, wind storms, droughts and floods that have threatened power sector infrastructure or caused recent blackouts and calls for demand side conservation. One of the most devastating of these events was the North American winter storm, dubbed “Winter Storm Uri” by the Weather Channel, that froze the region in February 2021 and led to an extended power outage event that put the majority of Texan residents in darkness for days. While preparing to avoid such outage events in the future, various tools have been proposed to improve grid reliability, including energy efficiency, demand response, and distributed energy resources. An additional option would be to develop interregional transmission that connects the Texas grid to other national grids. To assess the merits of this idea, we developed a novel, universally-applicable and internationally-relevant framework to study how the Texas grid would evolve alongside access to various interregional ties. This method allows us to stress the synthetic grid structure and analyze how it would respond to the shock of a simulated winter storm event. Our method leverages open-source modeling tools, such as PowerGenome, pyGRETA, and GenX to synthesize unique zonal grid data, construct a consolidated network of model regions, and simulate different developmental pathways of capacity expansion and operational dispatch. We demonstrate our method with an analysis connecting the Electric Reliability Council of Texas (ERCOT), the grid that serves most of Texas, the Western Electricity Coordinating Council (WECC), the grid that serves the western half of the contiguous U.S., and the Eastern Interconnect, the grid that serves the eastern half of the contiguous U.S. Our results indicate that the cost-optimal capacity of interregional transmission connecting the ERCOT grid to other grids lies between 9–13 GW assuming baseline conditions. Building this amount of connecting capacity in one or multiple directions lowers the costs and emissions of development and operation by up to $16 billion and 257 million metric tonnes (MMT) respectively. Additionally, our results show that the interregional connections between ERCOT and other national grids reduce the amount of total load shed required through mild winter storm events. However, our results also show that there is a threshold of very extreme winter storm conditions, spanning multiple service areas, above which the connections exacerbate resource adequacy problems. Therefore, the results indicate that the connections need to be carefully planned alongside the rest of the grid infrastructure to avoid over-reliance on specific resources or technology options.

24 POWER TRANSMISSION AND DISTRIBUTION

FORCE Update 2024

The Framework for Optimization of Resources and Economics (FORCE) tool suite is the U.S. Department of Energy’s Nuclear Integrated Energy Systems (IES) Program flagship tool suite for technoeconomic IES analysis of IES. This tool suite is useful for analysis designed to evaluate and improve the technoeconomics of energy production systems, particularly for systems including nuclear technology. In this report, we document the development activity for the FORCE tool suite to extend its capabilities as performed during fiscal year 2024. In addition to reliability and accessibility, capability is one of the three standards guiding the development of the FORCE tool suite and the software codes that are its constituent parts. Extending the capabilities of the FORCE tool suite allows analysis both within the IES program as well as industry, university, and laboratory partners to perform analysis with more accuracy, insight, and impactful narrative. Four areas of capability development were the focus of activity this year: economic parameter uncertainty quantification, multiresolution analysis, components-to-optimization workflow automation, and statespace construction workflows for real-time optimal control. In economic parameter uncertainty quantification, the ability of HERON to capture risk due to scenarios (weather and energy demand uncertainty) was expanded to also include uncertainties in financial parameters such as capital cost or operation and maintenance costs. By including these sources of uncertainty, which are sometimes very large compared with scenario uncertainty, HERON is better able to capture the risk posed by investment in various IES technology. Because of this, analysts can also consider the reduction in risks that can be realized by choice of some technologies. In multiresolution analysis, development activity extended on work completed previously. In fiscal year 2023, methods for decomposing time series signals, such as demand, solar and wind availability, and price profiles, were analyzed and down-selected to those most effective at splitting signals into different resolutions. These resolutions allow considering the influence of different energy demand and supply behaviors across different time scales. For example, energy demand might be divided into seasonal, weekly, and hourly profiles. In fiscal year 2024, this preliminary work was extended and implemented within the Risk Analysis Virtual Environment (RAVEN) risk and uncertainty analysis platform, which is used throughout the FORCE framework. This development of the “multi-resolution time series analysis” (MR-TSA) module in RAVEN allows training synthetic history generators on complex time series. These synthetic history generators can then be used in HERON for generating scenarios that represent possible market and weather scenarios that can be analyzed on different time scales. We envision completing this work in the future, implementing multiresolution dispatch optimization strategies that can make the most beneficial use of these stratified time histories. In components-to-optimization workflow development, workflows for translating user inputs of components into algorithms for algebraic optimization were selected and implemented. Similar algorithms within the Holistic Energy Resource Optimization Network (HERON) were separated from the main code base of HERON and gathered with the components-to-optimization workflows in the new Dispatch Optimization Variable Engine (DOVE) software library. This modularization allows FORCE users to analyze dispatch optimization and energy system duty cycles independently of HERON, which previously was a burdensome task. Additionally, these dispatch optimization algorithms, set up in an independent library, can now be used across all software applications within FORCE, especially including the real-time optimal control software Optimization of Real-time Capacity Allocation (ORCA). Allowing FORCE software to share dispatch optimization algorithms within a single library allows for improved software maintenance and reliability. In statespace characterization workflow development, alternative workflows for optimizing dispatch with additional technical accuracy was the focus, particularly to improve the real-time optimization decision making in ORCA. Using algorithms and workflows initially developed for the Feasible Actuator Range Modifier (FARM), workflows for determining the statespace representation of IES were identified and demonstrated. The resulting dispatch optimization required a more robust optimization algorithm than that originally used in HERON (and moved to DOVE), which required adding an alternate workflow to DOVE that can more accurately match the behavior of physical systems using a partial differential equation representation. In conclusion, capability developments in the FORCE tool suite in fiscal year 2024 have improved the ability of the FORCE tool suite to perform

29 ENERGY PLANNING, POLICY, AND ECONOMY

A Systematic Review on Coordinated Restoration Strategies for Power Distribution Grids

Power distribution grids are increasingly exposed to High-Impact Low-Probability (HILP) events, which cause widespread disruptions with severe societal and economic impacts. The growing complexity of modern grids, driven by the integration of distributed energy resources and smart grid technologies, has introduced new challenges to effective service restoration. While significant research has explored individual restoration strategies, such as network reconfiguration and microgrid formation, limited attention has been given to methods in which they can be effectively coordinated. Furthermore, the absence of systematic review papers addressing this issue hampers the development of cohesive restoration frameworks capable of addressing the operational complexities of modern grids. This paper presents a systematic review synthesizing existing knowledge on power grid restoration, identifying key limitations, and highlighting opportunities for coordinated strategies. By addressing research gaps and emphasizing the integration of diverse approaches, this study provides critical insights for advancing grid resiliency and recovery, offering a foundation for future research and practical applications in the face of HILP events.

Systematic review