Search NASA⌕ Search

SEARCH · Search NASA

Results for “Distribution Systems”

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 865 records · Page 48
All sourcesNASA NTRSDOE OSTI
DOE OSTI2026

Development Fiber Optic Distributed System for Direct Detection of Subsurface Gases Leakages

Carbon, natural gas, and hydrogen gas storage is an emerging solution to safeguard us against pollution, support goals of negative carbon emission, and protect sources of renewable energy. Properly constructed storage wells provide a virtually impervious barrier to any unintended subsurface transmission. The ability to ensure the long-term integrity of such wells is vital to the success of any storage operation and be successful in the public eyes. Therefore, robust monitoring of any gas migration into the subsurface is highly sought. A fiber-optic distributed chemical sensor (DCS) enables monitoring of long-term well integrity along its depth, ensuring the success of any storage operation and bolsters public acceptance of the safety of the reservoir via leak early detection. The same technique can be applied to gas monitoring in pipeline networks and nuclear stockpile monitoring applications. Fiber based Raman spectroscopy enables DCS, as optical fibers can be deployed in virtually any environment and relay spectroscopic information over long distances back to the user. Hollow core fibers (HCF) make excellent DCSs as the air core of the fiber allows gas from the environment to diffuse into the core, which interacts with the laser signal that is carried in the air core. This work builds upon the previous LDRD project, Fiber Optic System for Direct Detection of Carbon Dioxide Leakage in Carbon Storage Wells (21-FS-003), in which the feasibility of Raman spectroscopy detection of Carbon Dioxide (CO2) in HCF detection was demonstrated. We mitigated the risk of this DCS technology by establishing and completing five objectives. The first objective was to model and optically characterize HCF uptake of CO2, establishing the relationship between HCF length, gas diffusion time, detectable gas concentration, and measured Raman intensity. In objective two, we developed a fiber core drilling recipe to enable additional diffusion ports in the fiber core and established a method for maintaining fiber strength and integrity post drilling. Objective three characterized the drilled fibers against the undrilled fibers, establishing the differences in the gas mechanics and optical properties and provided parameters to iterate the drilling process. In objective four, a fusion splicing technique was developed to join the HCF to conventional single-mode fibers, localizing the gas detection point at the drilled HCF hole, emulating a DCS. Lastly, objective five was the testing of the sensor in Edgar Mines at Colorado School of Mines on a CO2 pipeline with a simulated leak, to showcase the ability to detect CO2 leaks. This capstone result showed CO2 leak detection in < 10 minutes, raising the technology readiness level of HCF segments as deployable DCS.

organic↗
DOE OSTI2019

Toward a subhourly net zero energy district design through integrated building and distribution system modeling

A modeling framework integrating both building energy modeling and power system modeling is introduced for the design of net zero energy (NZE) districts for the simultaneous selection of both demand-side efficiency measures and supply-side generation technologies. A novel district control scheme is proposed for pursuing NZE on a subhourly basis while mitigating potential grid impacts such as power backfeeding and voltage violations. As a case study, Pena Station NEXT, a new 100-building, mixed-use district on a 1200-node distribution feeder in Denver, Colorado, is modeled in the integrated framework. An exhaustive scenario analysis is conducted for sizing the district's distributed energy resources, considering multiple objectives such as capital cost, net energy import, and equipment violations. Here, when trying to achieve annual NZE, the district incurs frequent operating violations, and achieving NZE on a 15-min basis is also limited by seasonal fluctuations in photovoltaic output, illustrating the need for diverse generation or seasonal storage. As a practical compromise, both annual and 15-min district import can be reduced by ~78% without significant violations.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2019

Adaptive Voltage Regulation for Solar Power Inverters on Distribution Systems

The most recent version of IEEE 1547 has incorporated four reactive power control modes, including constant power factor, voltage-reactive power (Volt-Var), active power-reactive power and constant reactive power. These modes are specified to be mutually exclusive, and they don’t include every smart inverter function proposed by industry collaboration. In earlier work, we found that Volt-Var settings could be optimized but were sensitive to changes in the normal grid voltage. This sensitivity can be mitigated by combining Volt-Var with dynamic reactive current (DRC), but neither DRC nor combined modes appear in IEEE 1547. One problem with Volt-Var is the default dead-band; it mitigates the sensitivity to setpoint, but also limits the effectiveness in managing voltage fluctuations. There has been continued interest in tuning smart inverter functions locally, and in combining central with local control, but this process still requires extensive simulations. The goal is to find a default inverter setting that will effectively mitigate voltage fluctuations even as grid conditions change. It must be compatible with the current version of IEEE 1547. It should also be compatible with advanced control methods when available. Otherwise, it should not require communications, detailed engineering studies or field commissioning of custom settings. This would facilitate the integration of distributed solar in larger amounts. Adaptive voltage regulation (AVR) is a Volt-Var implementation, but with “autonomously adjusting” setpoint as described below Table 8 in IEEE 1547. Through simulation of a test system in OpenDSS, it was shown that AVR having a high gain and a time constant of 300 seconds could work well in any location. This mode and setting should be considered for a new universal default setting on smart inverters.

McDermott, Thomas E.↗
DOE OSTI2019

Developing and Testing a New Gas Distribution System for the Fluidized Bed of the Integrated Waste Treatment Unit (IWTU) Steam Reformer - 19219

The Integrated Waste Treatment Unit (IWTU) has been tasked with using steam reforming technology to treat 3.4 million liters of radioactive sodium-bearing waste (SBW) at the INL. Progress in developing steam reforming for SBW treatment has been hampered by numerous processing issues associated with the existing process equipment during simulant testing. The primary issue was high differential temperatures that developed in the fluidized bed of the denitration mineralization reformer (DMR). Based on technical evaluations and computer modeling, it was determined that the primary cause of poor fluidization in the DMR was the existing fluidized gas distributor. This distributor consisted of a combination of a ring header and four removable fluidizing gas rails. The combined ring header/rail system was unable to effectively fluidize the bed at the bottom of the DMR (around and below the ring header). As a result, a decision was made to design and test a new fluidized gas distributor. Conceptual designs focused on three different distributors: a modified design of the current system; a flat plate with bubble caps; and a conical bottom with dual plena. After testing the conceptual prototypes at Hazen Research Inc., the conical bottom distributor was chosen. A 30-day test with simulant SBW feed was then performed with the new distributor. During testing, a temperature differential of less than 2 deg. C was maintained in the DMR fluidized bed. The results supported the conclusion that poor fluidized gas distribution was the primary cause of high temperature differentials in the DMR fluidized bed. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2024

The power reliability event simulator tool (PRESTO): A novel approach to distribution system reliability analysis and applications

The growing interest in onsite solar photovoltaic and energy storage systems is partially motivated by customer concerns regarding grid reliability. However, accurately assessing the effectiveness of PVESS in mitigating these interruptions requires a comprehensive understanding of location-specific outage patterns and the ability to simulate realistic scenarios. To address the gap, we introduce the Power Reliability Event Simulation TOol (PRESTO), the first publicly available tool that simulates location-specific power interruptions at the county level. PRESTO allows for a more realistic assessment of system reliability by considering the unpredictability and location-specific patterns of power interruptions. We applied PRESTO in a case study of a single-family home across three U.S. counties, examining the performance of a solar photovoltaic system with 10kWh of battery storage during short-duration power interruptions. Our findings show that this system reliably met 93% of energy demand for essential non-heating and cooling loads, fully serving these loads in 84% of events, despite the constraints of daily time-of-use bill management which limits the battery's state-of-charge reserve. However, when heating and cooling loads were included, system performance decreased significantly, with only 70% of demand met and full service in 43% of events. These results highlight the challenges of using solar photovoltaic and energy storage systems for short-duration outages, emphasizing the need to consider factors like battery size and grid charging strategies to improve reliability. Our study demonstrates the practical applications of PRESTO, providing valuable insights into potential mitigation strategies including grid charging and optimizing battery size.

14 SOLAR ENERGY↗
NASA NTRS1981

Aerosol generation and distribution system for the Third International Cloud Condensation Nuclei Workshop

In order to obtain identical samples participating CCN instruments and aerosol characterizing equipment were located along and connected to a 8.2 cm diameter aluminum tube through which the test aerosols were pumped directly from the source at very slight overpressure. Of the total of 29 experiments, 18 were carried out with artificial NaCl or (NH4)2SO4 aerosols. These were generated from salt solutions by pneumatic atomizers of special design to ensure high constancy of the aerosol output concentration. In three experiments with insoluble CCN (AgI, paraffin wax) the aerosols were generated thermally. In some of the tests, an electrostatic classifier was used for narrowing the particle size distributions.

Katz, U.↗
DOE OSTI2025

Mini Guide: Community Engagement Approaches for Distribution System Resilience

The focus on electric grid resilience has gained significant momentum in recent years. The imperatives behind this focus are multifaceted, including the escalating threats of climate change, extreme weather events, and cyber and physical attacks. These challenges expose the vulnerabilities of the country’s aging grid infrastructure and underscore the important

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2021

Peer-to-peer Communication Control Architecture for Engaging Ubiquitous DERs to Support Distribution System Resiliency

In this project, we developed a leader-follower consensus (LFC) control architecture to coordinate between GFM and GFL inverters with the former being leaders and the latter being followers. The objective is to simultaneously achieve a fast frequency and voltage regulation along with accurate real power and var sharing among all inverters under various disturbances. The distinction of our work is that we consider both GFM and GFL inveters for frequency and voltage regulations. In addition, rather than a standard consensus algorithm, our work utilized a leader-follower consensus algorithm which exploits the physical characteristics of GFM-GFL inverters: (i) the GFM inverters directly control frequency and voltage, and hence, serve as leaders, (ii) the GFL inverters measure frequency/voltage to modulate their outputs, and hence, they should serve as followers. The effectiveness of the proposed LFC coordination was tested on a networked microgrid test system under different disturbances and communication degradation events. We demonstrated that the proposed fully coordinated control is robust to disturbances, while outperforming uncoordinated and GFM-only coordinated approaches. Overall, this work emphasized the necessity and benefits of the GFMGFL coordination in the secondary control of microgrids.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2018

Distribution System V1G PEV Charging Impacts Report

Plug-in Electric Vehicles (PEVs) are a clean form of transportation that will require a new control paradigm between the energy supply and the transportation sectors as PEV adoption continues to grow. Meeting the projected PEV energy demands will require implementing PEV / grid integration methods beyond charging PEVs at incentivized times. MATLAB was used to simulate the daily vehicle trip demands and charging processes of hundreds of PEVs. The National Household Travel Survey (NHTS) data was used as the source of vehicle travel data, and EV Project provided measured PEV charging data to calibrate the PEV population models. GridLAB-D analyses used a prototypical feeder and PEV population models to evaluate residential PEV V1G (unidirectional) charging in multiple locations, V1G PEV distribution feeder impacts, Time-Of-Use (TOU) rate effects on PEV charging, and charging control methods. The key findings were: optimized charging using California TOU rates could result in savings of over $20 per month for non-TOU program participants; non-TOU participants consume 30-40% of PEV charging energy; about 50% of PEV drivers have their transportation fuel bill reduced by 50 dollars per month; 6.6kW charging will cause distribution transformer power limits to be exceeded on prototypical feeders if the household PEV adoption rate reaches 0.75 PEVs per home; distribution feeder loading is proportional to PEV charging rate; a method was devised to remotely identify when residential transformer overloads occur using changes in PEV charging rate; and the low-cost TOU period is composed of a distribution of PEVs needing small, medium and larger energy needs that can be more effectively shifted as groups to mitigate the TOU peak power and enable a higher PEV adoption rate per household without overloading distribution transformers.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2020

Measurements from an Electrical Distribution System Substation During Hurricane Zeta

Hurricane Zeta made landfall on the United States mainland on October 29, 2020. The hurricane’s impacts on electrical service within the storm path included millions of customers losing power. The eye of the hurricane crossed over Chattanooga, Tennessee, USA, where advanced sensors were monitoring the operational state of a utility substation. A report on the measurement capability and rudimentary results is presented here.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2022

Small-Signal Stability Support from Dynamically Configurable Grid-Forming/Following Inverters for Distribution Systems: Preprint

As the penetration of inverter-based resources (IBRs) continues to increase in modern power systems, system stability is challenged by the insufficient inertia induced by IBRs; hence, there is a need to develop various methods to address the potential instabilities. In this paper, grid-forming (GFM) and grid-following (GFL) controls are implemented for inverters with flexible-mode transitions between them. The operation mode transition between GFM and GFL controls is adopted as an additional degree of control flexibility to adjust the small signal stability margin. Further, a holistic and detailed small signal model of the entire system with the dynamics from both synchronous generators (SGs) and IBRs is derived. The effectiveness of the proposed work in adjusting the system small signal stability margin is validated by conducting case studies with varying penetration levels of IBRs. A test system with one SG and five inverters was implemented in MATLAB/Simulink to demonstrate the effectiveness of the proposed approach. Index Terms - grid-following control, grid-forming control, operation mode transition, small-signal stability analysis

grid-following control↗
DOE OSTI2019

A VSM-Based DER Dispatch MINLP for Volt-VAR Control in Unbalanced Power Distribution Systems

This paper presents an optimal dispatch algorithm to coordinate customer-owned controllable loads and smart solar inverters with utility-owned voltage regulators and capacitors to meet voltage control objectives. The optimization problem is formulated as a mixed-integer nonlinear programming (MINLP) problem. A voltage sensitivity matrix (VSM) is used to linearize the effect of control actions on the voltage at customer nodes when solving the MINLP. The VSM is recalculated at each time step to improve the computational accuracy. Both discrete switching actions of the capacitor and VRs and the continuous adjustment of real and reactive power from load and smart inverters are considered in the MINLP volt-var problem formulation. The objective function minimizes the cost of all control actions and the magnitude of voltage fluctuations from the previous time period. Constraints ensure that the voltage at each node is maintained within ANSI limits and the feeder power factor is controlled within the desired range. The algorithm is tested using an actual 3-phase unbalanced distribution feeder model. Simulation results demonstrate that the proposed algorithm is computationally feasible on real circuits and improves voltage control while minimizing operational costs.

McEntee, Catie↗
DOE OSTI2018

Accurate, Fast and Scalable Kernel Ridge Regression on Parallel and Distributed Systems

Kernel Ridge Regression (KRR) is a fundamental method in machine learning. Given an n-by-d data matrix as input, a traditional implementation requires Θ(n2) memory to form an n-by-n kernel matrix and Θ(n3) flops to compute the final model. These time and storage costs prohibit KRR from scaling up to large datasets. For example, even on a relatively small dataset (a 520k-by-90 input requiring 357 MB), KRR requires 2 TB memory just to store the kernel matrix. Additionally, the reason is that n usually is much larger than d for real-world applications. On the other hand, weak scaling becomes a problem: if we keep d and n/p fixed as p grows (p is # machines), the memory needed grows as Θ(p) per processor and the flops as Θ(p2) per processor. In the perfect weak scaling situation, both the memory needed and the flops grow as Θ(1) per processor (i.e. memory and flops are constant). The traditional Distributed KRR implementation (DKRR) only achieved 0.32% weak scaling efficiency from 96 to 1536 processors. In this work, we propose two new methods to address these problems: the Balanced KRR (BKRR) and K-means KRR (KKRR). These methods consider alternative ways to partition the input dataset into p different parts, generating p different models, and then selecting the best model among them. Compared to a conventional implementation, KKRR2 (optimized version of KKRR) improves the weak scaling efficiency from 0.32% to 38% and achieves a 591x speedup for getting the same accuracy by using the same data and the same hardware (1536 processors). BKRR2 (optimized version of BKRR) achieves a higher accuracy than the current fastest method using less training time for a variety of datasets. For the applications requiring only approximate solutions, BKRR2 improves the weak scaling efficiency to 92% and achieves 3505x speedup (theoretical speedup: 4096x).

97 MATHEMATICS AND COMPUTING↗
NASA NTRS1996

A Secure Key Distribution System of Quantum Cryptography Based on the Coherent State

The cryptographic communication has a lot of important applications, particularly in the magnificent prospects of private communication. As one knows, the security of cryptographic channel depends crucially on the secrecy of the key. The Vernam cipher is the only cipher system which has guaranteed security. In that system the key must be as long as the message and most be used only once. Quantum cryptography is a method whereby key secrecy can be guaranteed by a physical law. So it is impossible, even in principle, to eavesdrop on such channels. Quantum cryptography has been developed in recent years. Up to now, many schemes of quantum cryptography have been proposed. Now one of the main problems in this field is how to increase transmission distance. In order to use quantum nature of light, up to now proposed schemes all use very dim light pulses. The average photon number is about 0.1. Because of the loss of the optical fiber, it is difficult for the quantum cryptography based on one photon level or on dim light to realize quantum key-distribution over long distance. A quantum key distribution based on coherent state is introduced in this paper. Here we discuss the feasibility and security of this scheme.

Guo, Guang-Can↗
DOE OSTI2025

Advanced Intelligent Sensor Development and Demonstration for Future Distribution Systems with High Penetration DERs

The nation’s electric grid is evolving to supply the electricity needed for economic growth, health, and quality of life. As the DOE has pointed out “Old Tools Won’t Solve New Problems” This project conceived, designed, built, and demonstrated a new tool that promises to make the emerging grid dependable at a lower cost. The tool is a smart sensor with the sensitivity and the bandwidth to measure actionable information about grid health that was unmeasurable.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2022

Signal-Based Fast Tripping Protection Schemes for Electric Power Distribution System Resilience

This report is a summary of a 3-year LDRD project that developed novel methods to detect faults in the electric power grid dramatically faster than today’s protection systems. Accurately detecting and quickly removing electrical faults is imperative for power system resilience and national security to minimize impacts to defense critical infrastructure. The new protection schemes will improve grid stability during disturbances and allow additional integration of renewable energy technologies with low inertia and low fault currents. Signal-based fast tripping schemes were developed that use the physics of the grid and do not rely on communication to reduce cyber risks for safely removing faults.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2017

Noise propagation effects in power supply distribution systems for high-energy physics experiments

High-energy physics experiments are supplied by thousands of power supply units placed in distant areas from the front-end electronics. The power supply units and the front-end electronics are connected through long power cables that propagate the output noise from the power supplies to the detector. Here, this paper addresses the effect of long cables on the noise propagation and the impact that those cables have on the conducted emission levels required for the power supplies and the selection of EMI filters for the front-end electronic low-voltage input. Lastly, this analysis is part of the electromagnetic compatibility based design focused on functional safety to define the type of cable, shield connections, EMI filters and power supply specifications required to ensure the successful integration of the detector and, specifically, to achieve the designed performance of the front-end electronics.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2024

RuralAI in Tomato Farming: Integrated Sensor System, Distributed Computing, and Hierarchical Federated Learning for Crop Health Monitoring

Precision horticulture is evolving due to scalable sensor deployment and machine learning (ML) integration. These advancements boost the operational efficiency of individual farms, balancing the benefits of analytics with autonomy requirements. However, given concerns that affect wide geographic regions (e.g., climate change), there is a need to apply models that span farms. Federated learning (FL) has emerged as a potential solution. FL enables decentralized ML across different farms without sharing private data. Traditional FL assumes simple two-tier network topologies and, thus, falls short of operating on more complex networks found in real-world agricultural scenarios. Networks vary across crops and farms and encompass various sensor data modes, extending across jurisdictions. New hierarchical FL (HFL) approaches are needed for more efficient and context-sensitive model sharing, accommodating regulations across multiple jurisdictions. Here, we present the RuralAI architecture deployment for tomato crop monitoring, featuring sensor field units for soil, crop, and weather data collection. HFL with personalization is used to offer localized and adaptive insights. Model management, aggregation, and transfers are facilitated via a flexible approach, enabling seamless communication between local devices, edge nodes, and the cloud.

60 APPLIED LIFE SCIENCES↗