Search NASA⌕ Search

SEARCH · Search NASA

Results for “Load coordination”

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.

At least 109 records · Page 6
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

High- and Mid-Fidelity Modeling Comparison for a Floating Marine Turbine System

There is a lack of suitable numerical tools, particularly open-source tools, that can be used for designing and optimizing marine turbine systems. The National Renewable Energy Laboratory has added features to their widely used mid-fidelity wind turbine modeling code, OpenFAST, to enable modeling of axial-flow marine turbines. This necessitated the addition of several physical effects relevant to marine turbines that are neglected for wind turbines. These include buoyancy, added mass and inertial loads, wave-current superposition, and changes to the coordinate systems. This updated version of OpenFAST allows for the modeling of both fixed and floating marine turbines at a speed comparable to real time. While efficient for large sets of load cases and design studies, mid-fidelity codes make simplifying assumptions that may impact their accuracy. High-fidelity computational fluid dynamics (CFD) simulations can capture more flow effects with fewer assumptions and provide detailed body pressure mapping and flow-field information. It is important to compare predictions between mid-fidelity and high-fidelity codes, both to verify the models and to understand the limitations. A floating marine turbine system was modeled both with OpenFAST and with the commercial CFD code STAR-CCM+. The CFD model used a three-dimensional unsteady Reynolds-averaged Navier-Stokes solver for a volume-of-fluid numerical wave and current tank. The blade-resolved simulations used the sliding-interface technique for the spinning rotor and an overset grid to accommodate the rigid-body motion of the floating system. The mooring system was modeled with a custom coupling of the CFD solver with the open-source code MoorDyn. This improves upon the existing quasi-static catenary solver in STAR-CCM+, which lacks seabed contact or line-to-line connections. Simulation results for a floating marine turbine are compared between OpenFAST and CFD, highlighting the capabilities of the mid-fidelity code and identifying the areas where a high-fidelity approach is needed.

CFD↗
DOE OSTI2024

High- and Mid-Fidelity Modeling Comparison for a Floating Marine Turbine System: Preprint

There is a lack of suitable numerical tools, particularly open-source tools, that can be used for designing and optimizing marine turbine systems. The National Renewable Energy Laboratory (NREL) has added features to their widely used mid-fidelity wind turbine modeling code, OpenFAST, to enable modeling of axial flow marine turbines. This necessitated the addition of several physical effects relevant to marine turbines that can be neglected for wind turbines. These include buoyant loads, added mass and inertia loads, wave-current superposition, and changes to the coordinate systems. This updated version of OpenFAST allows for the modeling of both fixed and floating marine turbine systems at a speed comparable to real time. While efficient for long simulations, large sets of load cases, and design studies, mid-fidelity codes cannot capture all of the potentially important physical phenomenon impacting marine turbine systems. High-fidelity computational fluid dynamics (CFD) simulations can capture more flow effects with fewer assumptions and provide detailed body pressure mapping and flow-field information. It is important to compare predictions between mid-fidelity and high-fidelity codes, both to verify the models and to understand the limitations. A floating marine turbine system designed by NREL was modeled both with OpenFAST and with the commercial CFD code, STARCCM+. The CFD model used a 3-D unsteady Reynolds-averaged Navier-Stokes solver for a volume-of-fluid numerical wave and current tank. The blade-resolved simulations used the sliding-interface technique for the spinning rotor and an overset grid to accommodate the rigid-body motion of the floating system. The mooring system was modelled with a custom coupling of the CFD solver with the open-source code, MoorDyn. This improves upon the existing quasi-static catenary solver in STARCCM+, which lacks seabed contact or line-to-line connections. Spatial and temporal convergence studies were conducted. The simulation results for a combined current and wave condition are compared between OpenFAST and CFD, highlighting the capabilities of the mid-fidelity code and identifying the areas where a high-fidelity approach is needed.

CFD↗
DOE OSTI2026

Carbon nanodot precursors enable ultrahigh-loading copper single-atom catalysts for oxygen reduction reaction

Single-atom catalysts (SACs) have attracted significant attention in electrocatalysis due to their high metal utilization and tunable electronic structures; however, their practical implementation is often limited by poor atomic dispersion, low metal loadings (typically < 1 wt%), and insufficient anchoring of single metal atoms on catalyst supports. Herein, we report a simple and versatile strategy to synthesize copper single-atom catalysts (Cu-SACs) with ultrahigh metal loading using citric-acid-derived carbon nanodots as metal-capturing precursors. Through hydrothermal treatment followed by pyrolysis in the presence of urea, atomically dispersed copper atoms coordinated with nitrogen are incorporated into a carbon framework, achieving a Cu loading of up to 20 wt% while maintaining atomic dispersion. Notably, a significant fraction of the copper single atoms exists as Cu+–N2 coordination, which provides under-coordinated and catalytically active sites. The resulting Cu-SAC exhibits promising oxygen reduction reaction (ORR) activity in alkaline media, delivering a limiting current density comparable to that of commercial 20 wt% Pt/C with a predominant four-electron reduction pathway. Despite this high intrinsic activity, durability tests reveal gradual performance degradation under prolonged electrochemical operation, which is attributed to demetallation and aggregation of copper single atoms into metallic nanoparticles. These results demonstrate the potential of carbon nanodot-based platforms for synthesizing high-loading SACs, while underscoring the critical need to simultaneously control carbon porosity and metal–nitrogen coordination to enhance active-site accessibility and durability.

Sharma, Prakhar [University of Kentucky]↗
DOE OSTI2025

Recovery Simulator and Analysis Formulation: Mathematical Framework for Enhanced Resilience and Resource Allocation

This report introduces recovery simulator and analysis (RSA), a framework aimed at enhancing the resilience of electrical grids post-disruption. The RSA model leverages an optimization problem formulation that focuses on maximizing the load served (or optionally customers served) through a coordinated and cooptimized recovery of non-black start generation, transmission lines, feeders and substations subject to labor budget constraints. By integrating advanced linear programming techniques, the simulator selects efficient reocovery pathways, optimizing both short-term and long-term grid recovery strategies. The mathematical framework guides decision-making through a comprehensive evaluation of potential recovery actions, factoring in the trade-offs between labor constraints and load (or optionally customer) restoration efficacy. This enables grid operators to simulate diverse outage scenarios and delineate optimal recovery pathways, thereby prioritizing critical repair tasks and ensuring resource allocation is both economical and effective. The intended use case of RSA is to allow planners to explore many recovery scenarios quickly and determine assets most critical across a wide range of scenarios, and therefore strong candidates for hardening or additional investment. RSA might also be used in an operational setting, following a single event, for exploring efficient recovery pathways.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2021

Exploring the Ion Solvation Environments in Solid-State Polymer Electrolytes through Free-Energy Sampling

The success of poly(ethylene oxide) (PEO) in solid-state polymer electrolytes for lithium-ion batteries is well established. Recently, in order to understand this success and to explore possible alternatives, we studied polyacetal electrolytes to deepen the understanding of the effect of the local chemical structure on ion transport. Advanced molecular dynamics techniques using newly developed, tailored interaction potentials have helped elucidate the various coordination environments of ions in these systems. In particular, the competition between cation-Anion pairing and coordination by the polymer has been explored using free-energy sampling (metadynamics). At equivalent reduced temperatures, with respect to the polymer-specific glass-Transition temperature, two-dimensional free-energy plots reveal the existence of multiple coordination environments for the lithium (Li) ions in these systems and their relative stabilities. Furthermore, we observe that the Li-ion movement in PEO follows a serial, stepwise pathway when moving from one coordination state to another, whereas this happens in a more continuous and concerted fashion in a polyacetal such as poly(1,3-dioxalane) [P(EO-MO)]. The implication is that interconversion between coordination states of the Li ions may be easier in P(EO-MO). However, the overarching observation from our free-energy analysis is that Li-ion coordination is dominated by the polymer (in either case) and contact-ion pairs are rare. We rationalize the observed higher increase in glass-Transition temperature (Tg) with salt loading in polyacetals as due to intermolecular Li-ion coordination involving multiple polymer chains, rather than just one chain for PEO-based electrolytes. This interchain coupling in the polyacetals, resulting in the higher Tg, works against any gains due to variations in Li-ion coordination that might enhance transport processes over PEO. Further research is required to overcome the interdependence between local coordination and macroscopic properties to compete with PEO electrolytes at the same absolute working temperature.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2024

A Mixed Integer Linear Programming-basedDistributed Energy Management for Three-phaseUnbalanced Active Distribution Network

A mixed integer linear programming (MILP)–baseddistributed energy management for three-phase unbalancedactive distribution network is proposed. Modern distributionnetworks have becoming more and more active with increasingdeployment of microgrids, distributed energy resources (DERs)as well as controllable loads. Considering various ownership andcontrol models of microgrids, DERs and controllable loads, adistributed energy management was formulated using the alternatingdirection method of multipliers (ADMM) algorithm. ByADMM, the distribution management system (DMS) and theseactive components are coordinated through price signals, whichare adjusted according to the generation-load mismatch per nodeper phase. To enable resolution of the ADMM-based distributedoptimization using more accessible and popular MILP solver,different linearization techniques were proposed to linearize theaugmented Lagrangian terms and other nonlinear terms. Resultsof case studies on a three-phase active distribution network withthree microgrids and several DERs and controllable loads validatedthe effectiveness of proposed MILP-based distributed energymanagement. In addition, the capability of proposed method inmitigating phase power unbalance has been demonstrated.

Liu, Guodong↗
DOE OSTI2021

GT Flex: A Coordinated Multi-Building Pilot Study

Buildings are a significant and untapped resource for providing utility electric grid services. Recent studies have estimated that buildings could reduce the peak demand on the electric grid in the U.S. by almost 25% through effective combinations of energy efficiency (EE) measures and load flexibility strategies (Langevin et al. 2021). The U.S. Department of Energy (DOE) has established a goal to triple energy efficiency and demand flexibility in both residential and commercial sections by 2030 compared to 2020 levels (Satchwell et al. 2021). Such findings place buildings alongside electric vehicles, photovoltaics, electric batteries, and other distributed energy resources (DERs) as primary technologies needed for supporting high renewable energy generation grids. Coordinating and optimizing multiple buildings and other DERs is more beneficial and valuable when compared with individual buildings and DERs operating as siloed resources, uncoordinated with others (Olgyay et al. 2020). A pilot study at the Georgia Institute of Technology (GIT) was conducted to evaluate value propositions of a multi-building scale project seeking carbon reduction, energy efficiency and grid-interactive capabilities, by demonstrating the means by which stakeholders can determine the technical and financial merits of grid-interactivity and energy efficiency technologies coordinated across multiple assets. The study focused on analyzing technical feasibility of deploying thermal load flexibility strategies at the multi-building scale, coordinated to not exceed existing infrastructure constraints at the pilot site. Results show that campus can provide 3-3.5 MW of potential load shed over a 4-hour event window through coordinated dispatch of thermal cooling load flexibility without exceeding existing infrastructure capacities. Under future high renewable scenarios, this thermal flexibility resource is also valuable when coordinated to reduce curtailment of intermittent renewables. Economic analyses were performed to effectively communicate various value propositions of grid-interactive and efficient building (GEB) thermal flexibility strategies. Load flexibility presents a financial value proposition to the campus today. By conducting rationalized, coordinated dispatch in response to real time price (RTP) fluctuations, the campus can benefit materially from daily price arbitrage. The RTP signal acts as an aggregating mechanism between the utility and customer to call on demand flexibility resources, with a large portion of the benefit deriving from a relatively small number of days. Realizing and maximizing this benefit with thermal load flexibility requires careful attention to the timing of pricing signals and parameterization of dispatch to overcome efficiency penalties. Grid value and signals are expected to evolve over time, and thermal load flexibility shows potential to adapt dispatch logic to support intermittent renewable generation.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2020

Policy Innovation and Governance for Irrigation Sustainability in the Arid, Saline San Joaquin River Basin

This paper provides a chronology and overview of events and policy initiatives aimed at addressing irrigation sustainability issues in the San Joaquin River Basin (SJRB) of California. Although the SJRB was selected in this case study, many of the same resource management issues are being played out in arid, agricultural regions around the world. The first part of this paper provides an introduction to some of the early issues impacting the expansion of irrigated agriculture primarily on the west side of the San Joaquin Valley and the policy and capital investments that were used to address salinity impairments to the use of the San Joaquin River (SJR) as an irrigation water supply. Irrigated agriculture requires large quantities of water if it is to be sustained, as well as supply water of adequate quality for the crop being grown. The second part of the paper addresses these supply issues and a period of excessive groundwater pumping that resulted in widespread land subsidence. A joint federal and state policy response that resulted in the facilities to import Delta water provided a remedy that lasted almost 50 years until the Sustainable Groundwater Management Act of 2014 was passed in the legislature to address a recurrence of the same issue. The paper describes the current state of basin-scale simulation modeling that many areas, including California, are using to craft a future sustainable groundwater resource management policy. The third section of the paper deals with unique water quality issues that arose in connection with the selenium crisis at Kesterson Reservoir and the significant threats to irrigation sustainability on the west side of the San Joaquin Valley that followed. The eventual policy response to this crisis was incremental, spanning two decades of University of California-led research programs focused on finding permanent solutions to the salt and selenium contamination problems constraining irrigated agriculture, primarily on the west side. Arid-zone agricultural drainage-induced water quality problems are becoming more ubiquitous worldwide. One policy approach that found traction in California is an innovative variant on the traditional Total Maximum Daily Load (TMDL) approach to salinity regulation, which has features in common with a scheme in Australia’s Hunter River Basin. The paper describes the real-time salinity management (RTSM) concept, which is geared to improving coordination of west side agricultural and wetland exports of salt load with east side tributary reservoir release flows to improve compliance with river salinity objectives. RTSM is a concept that requires access to continuous flow and electrical conductivity data from sensor networks located along the San Joaquin River and its major tributaries and a simulation model-based decision support designed to make salt load assimilative capacity forecasts. Web-based information dissemination and data sharing innovations are described with an emphasis on experience with stakeholder engagement and participation. The last decade has seen wide-scale, global deployment of similar technologies for enhancing irrigation agriculture productivity and protecting environmental resources.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Integrating Machine-learning-assisted Computer Vision with RICH System

Developments in artificial intelligence have vastly expanded the capabilities of robots. Currently, the Spallation Neutron Source (SNS) beamlines at Oak Ridge National Lab (ORNL) have robotic sample loaders to increase the efficiency of running experiments. However, they require retraining if anything about the situation changes, e.g., where the samples are, and cannot notice if errors occur. So, the viability of using computer vision and machine learning to enhance these sample loaders’ functionality was investigated. In this project, the RICH system with a Dobot CR3 6-axis robot present at the VULCAN beamline assisted by an Intel Realsense D435i camera, a unique camera that enables convenient translation of 2D pixel coordinates to 3D world points, was programmed to load ceramic crucibles into a thermogravimetric analyzer (TGA) furnace. An algorithm was constructed in Python with three major phases planned: (1) obtaining a sample, (2) moving it to the target location, and then (3) bringing the sample back to its original location once the experiment finished. In the first phase, the algorithm would dynamically detect sample locations using ArUco markers to recognize the samples’ general location and a custom-trained yolov5 object detection model to locate the crucibles’ centers. Afterward, the robot would be directed to pick up samples based on the crucibles’ calculated positions. In the second phase, the robot would move the sample to a secondary point, reorient its grip, and place the sample at the target location. In the final phase, the robot would determine whether the sample was intact and would bring it back to its original place if it was or raise an alarm. Using this algorithm, the robot was able to pick up different types of crucibles at varying positions. These results indicate that integrating machine-learning-assisted computer vision with robotic sample loaders can result in effective autonomous detection of samples.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2025

Image-Driven Hybrid Structural Analysis Based on Continuum Point Cloud Method with Boundary Capturing Technique

Conventional approaches for the structural health monitoring of infrastructures often rely on physical sensors or targets attached to structural members, which require considerable preparation, maintenance, and operational effort, including continuous on-site adjustments. This paper presents an image-driven hybrid structural analysis technique that combines digital image processing (DIP) and regression analysis with a continuum point cloud method (CPCM) built on a particle-based strong formulation. Polynomial regressions capture the boundary shape change due to the structural loading and precisely identify the edge and corner coordinates of the deformed structure. The captured edge profiles are transformed into essential boundary conditions. This allows the construction of a strongly formulated boundary value problem (BVP), classified as the Dirichlet problem. Capturing boundary conditions from the digital image is novel, although a similar approach was applied to the point cloud data. It was shown that the CPCM is more efficient in this hybrid simulation framework than the weak-form-based numerical schemes. Unlike the finite element method (FEM), it can avoid aligning boundary nodes with regression points. A three-point bending test of a rubber beam was simulated to validate the developed technique. The simulation results were benchmarked against numerical results by ANSYS and various relevant numerical schemes. The technique can effectively solve the Dirichlet-type BVP, yielding accurate deformation, stress, and strain values across the entire problem domain when employing a linear strain model and increasing the number of CPCM nodes. In addition, comparative analysis with conventional displacement tracking techniques verifies the developed technique’s robustness. The proposed technique effectively circumvents the inherent limitations of traditional monitoring methods resulting from the reliance on physical gauges or target markers so that a robust and non-contact solution for remote structural health monitoring in real-scale infrastructures can be provided, even in unfavorable experimental environments.

Chemistry↗
DOE OSTI2020

Predictive and Cooperative Voltage Control with Probabilistic Load and Solar Generation Forecasting

This paper proposes predictive cooperative voltage control method in a power system with high penetration of photovoltaic (PV) units. Cooperative distributed control of the reactive power output of PV inverters is coordinated with operation of voltage regulators (VRs) to maintain system voltages within an appropriate bandwidth. Probabilistic forecasting of the solar power generation and the loads is applied to estimate voltage changes which, in turn, are used to set the VR tap positions for preventing large voltage fluctuations with the lowest risk considering the voltage distribution estimation. The fine tuning of voltage adjustment is achieved by cooperative control of PV inverters to maintain a uniform voltage profile across the system. The proposed method is tested on the modified IEEE 123-node test feeder with high PV penetration using real insolation data and with constant loads replaced by several different load profiles. Simulation results demonstrate the effectiveness of the coordinated approach for voltage control with cooperative PV and predictive VR controls taking into account probabilistic load and solar power forecasts.

Cooperative Control↗
DOE OSTI2026

Bridging Control and Deployment: A Cross-Layer Analysis of Scalable Building Cluster Control

Building cluster control has emerged as a promising approach for enabling flexible and coordinated operation of distributed building systems, yet its transition from pilot demonstrations to routine grid-interactive operation remains limited. This paper argues that this gap cannot be explained by control algorithms alone. Instead, it arises from interacting barriers in communication infrastructure, data and semantic interoperability, uncertainty management, stakeholder participation, market design, and policy support. Accordingly, the paper reviews both technical and non-technical barriers to building cluster control. Technical challenges include heterogeneous devices and protocols, communication latency and reliability, distributed decision-making, and uncertainty propagation across aggregated loads. Non-technical barriers include user participation, stakeholder coordination, incentive allocation, and data governance. Existing solution approaches are synthesized, including semantic interoperability frameworks, edge and hierarchical communication architectures, distributed and transactive control strategies, uncertainty-aware optimization, policy mechanisms, and market reforms. Based on this analysis, two research directions are identified: testing infrastructures that can evaluate control performance under realistic multi-building conditions, and abstraction methods that allow building clusters to interact with other energy sectors through standardized flexibility representations. Overall, the paper provides a structured review of how building cluster control can move from isolated demonstrations toward reproducible, market-compatible, and grid-relevant implementation.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2021

The Coordination Chemistry and Stoichiometry of Extracted Diglycolamide Complexes of Lanthanides in Extraction Chromatography Materials

Industrial rare earth element (REE) separations predominantly utilize solvent extraction processes tailored toward conventional resources such as bastnäsite, monazite, and ion adsorption clays. Advances in diglycolamide (DGA) chemistry have shown effective extraction characteristics for REE separations. However, limitations associated with traditional DGA solvent extraction techniques, such as third-phase formation and gelling, have hindered commercial viability. By supporting DGA extractants on porous resins such as polystyrene divinyl benzene (PS-DVB), the desirable combination of solvent extraction selectivity and ease of operation of sorbent columns can be achieved. To design a low-cost model for such solid-supported DGAs, extraction characteristics as influenced by the underlying coordination chemistry must be explored to achieve efficient functional systems. Within this study, we report novel DGA resin materials, each incorporating one of the DGAs N,N,N’,N’-tetra-(1-octyl)-3-oxapentane-1,5-diamide (TODGA), N,N'-dimethyl-N,N'-dioctyl-3-oxapentane-1,5-diamide (DMDODGA), and 2,2'-oxybis(1-(3-(((2-ethylhexyl)thio)methyl)-4-methylpyrrolidin-1-yl)ethan-1-one) (DEHPDGA). The affinity of DGAs across the lanthanide (Ln) series was evaluated for both hydrochloric acid and nitric acid media with varying Ln feed concentrations to study distribution ratios and loading characteristics. Focusing on dysprosium, extended X-Ray Absorption Fine Structure (EXAFS) and density functional theory (DFT) calculations were also utilized to explore coordination chemistry and their effects on ligand performance. The general trend for both acid media resulted in DMDODGA having the highest extraction strength of all three DGAs at varying acid concentrations. Coordination-chemistry analysis supported by loading data, DFT calculations, and EXAFS results under forced loading conditions posited less than the expected 3:1 ligand-to-metal coordination.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
DOE OSTI2020

Thermal Activation of a Copper-Loaded Covalent Organic Framework for Near-Ambient Temperature Hydrogen Storage and Delivery

Copper(II) formate is efficiently incorporated into the pores of a 2D imine-based covalent organic framework (COF) via coordination with the phenol and imine groups. The coordinated metal ion is then reduced to Cu(I) with a thermal treatment that evolves CO 2 . After loading with hydrogen gas, the majority of H 2 desorbs from the coordinatively saturated Cu(II) COF at temperatures < -100 degrees C. However, the activated Cu(I) COF retains adsorbed H 2 above room temperature. Adsorption/desorption of H 2 was highly reversible. Diffuse reflectance infrared Fourier transform spectroscopy (DRIFTS) strongly supports a molecular hydrogen interaction with Cu(I). A Kissinger analysis of variable ramp rate desorption experiments estimates the enthalpy of H 2 desorption from Cu(I) at 15 kJ mol -1 . The results represent an advance toward practical H 2 storage and delivery in a lightweight, stable, and highly versatile material.

08 HYDROGEN↗
DOE OSTI2020

An intelligent energy router for managing behind-the-meter resources and assets

With increase in distributed energy resources (DERs) and smart loads, each energy resource and load need a separate power conversion system leading to complex coordination and interaction, reduced energy conversion efficiency, coordinating compliance to grid standards (IEEE 1547) from multiple sources, reduced security. Also, multiple vendors with legacy system designs and proprietary communications interfaces result in redundancy and increase in cost of power electronics systems. This paper presents an energy router concept for buildings applications which provides autonomous power flow between sources and loads with a novel agent-based software interface.

Chinthavali, Madhu Sudhan↗
DOE OSTI2026

Mitigating Data Center Impact on Grid Stability: A Coordinated Control Strategy Using Verrus StabiliGrid Architecture

Large data centers, which now represent a significant and growing share of the total U.S. grid load, can inadvertently destabilize the electrical grid when they disconnect simultaneously during brief voltage disturbances. The July 10, 2024, Eastern Interconnection incident, in which a sub-100-millisecond transmission fault triggered the cascading loss of approximately 1,500 MW of data center load, illustrates this vulnerability. While commercial battery energy storage systems (BESS) deployed in data centers provide device-level fault ride-through per IEEE 1547, they lack coordination with facility protection logic and uninterruptible power supplies (UPS), limiting their effectiveness as grid-stabilizing assets. This report presents the Verrus StabiliGrid architecture, a coordinated control framework that integrates BESS, UPS, and point-of-interconnection (POI) protection settings to enable data centers to ride through both undervoltage and overvoltage grid contingencies without disconnecting. The four-step strategy encompasses: (1) high-resolution power quality monitoring to detect the grid state during events such as undervoltage, overvoltage, underfrequency, and overfrequency; (2) POI protection settings that allow for extended ride-through and grid-connected operation during grid contingencies; (3) grid state-driven autonomous dispatch of assets to improve grid resilience by reducing power draw during undervoltage or absorbing more power during overvoltage events; and (4) coordinated post-recovery dispatch of data center assets to restore firm load to pre-contingency levels. Validated through controller-hardware-in-the-loop (C-HIL) simulations at the National Laboratory of the Rockies, results show grid import restoration to pre-fault levels within 100 milliseconds of voltage recovery. This work advances the ability of data centers to transition from passive, disturbance-sensitive loads to active participants in grid stability, a capability increasingly required by emerging NERC and ERCOT regulatory frameworks.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2021

Integrating Transactive Energy into Reliability Evaluation for a Self-healing Distribution System with Microgrid

Non-utility owned distributed energy resources (DERs) are mostly untapped currently, but they can provide many grid services such as voltage regulation and service restoration, if properly controlled, and can improve the distribution systems reliability when coordinated with utility-owned assets such as self-healing control and microgrids. This paper integrates transactive energy control into the distribution system reliability evaluation to quantitatively assess the impact of non-utility owned DERs on reliability improvement. Here, a transactive reactive power control strategy is designed to incentivize the DERs to provide reactive power support for improving voltage profiles thus enabling additional customer load restoration during an outage. Also, an operational sequence to coordinate the non-utility owned DERs with the utility owned self-healing control and utility owned microgrids is designed and integrated into the service restoration process with the operational constraints guaranteed by checking the three-phase unbalanced power flow for post-fault network reconfiguration. The reliability indices are then calculated through a Monte Carlo simulation. The transactive reactive power control strategy is tested on a four-feeder distribution system operated by Duke Energy in the U.S. Results demonstrate that the non-utility owned DERs with the transactive control improve the reliability of both the system and critical loads by more than 30%.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2023

Efficiency and Demand Flexibility in Large Office Buildings: The Potential for Cost Savings and CO 2 Reductions from Lighting and Cooling Measures

This report presents the estimated impact of lighting and cooling efficiency and demand flexibility measures in large office buildings in each state in the contiguous United States. It provides modeled results for three different metrics: bill savings, regional grid operational costs savings, and carbon dioxide (CO 2 ) emissions reductions. Lighting efficiency and demand flexibility are estimated to reduce load by up to 80 MWh/yr in a single large office building. These load reductions result in customer bill savings of up to $8,800/yr per building, with the highest savings in southern and midwestern states. Grid operating cost savings are estimated at up to $3,240/yr/building, with greatest benefit in southern and northeastern states. CO 2 emissions reduction potential is highest in the Dakotas, Nebraska, across the Midwest, in West Virginia, and in Mississippi (<48,200 kg/yr/building). Comparatively, cooling measures are found to have less load reduction potential (<28.5 MWh/yr/building), with the greatest potential in southern states including Texas, which ranks top of the list across several of the metrics studied. In numerous states, shifting cooling load to off-peak hours is found to increase costs and CO 2 emissions because precooling results in increased load during high-cost or high-CO 2 emissions periods. In general, focusing on cooling efficiency and load shedding has the potential for more savings. In all cases, the specific rate structure is a significant determinant in actual bill savings, which are up to $4,000/yr/building. To realize the full potential for bill savings through an energy measure, building operators must identify how the measure will change the building load pattern and the interaction of this load change with the applicable rate tariff. To realize CO 2 emissions reductions, industry and state coordination is needed to verify which fuel source is on the margin and then to create incentives for end users to reduce load during high-CO 2 emissions hours. Regular updates to data sets and analyses are critical. Regulators and policymakers are well positioned to facilitate the necessary coordination between the electric industry and building energy managers to develop appropriate price signals and incentives.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗