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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 145 records · Page 8
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Peak Load Management in Distribution Systems Using Legacy Utility Equipment and Distributed Energy Resources

The ability to perform peak load management in distribution systems has several benefits for utilities, including reduced demand charges and improved reliability, efficiency, and utilization of the network infrastructure. This paper demonstrates the coordinated operation of an advanced distribution management system (ADMS) and a distributed energy resource management system (DERMS) to achieve peak load management using a realistic laboratory test bed. A commercial ADMS reduces the peak demand by reducing system voltages using a dynamic voltage regulation (DVR) application. A prototype DERMS-based on real-time optimal power flow-controls distributed battery energy storage systems to further reduce the feeder power. Results from the experiments conducted using a model of a real distribution feeder show that the coordinated operation of the ADMS and DERMS is effective in accomplishing peak load management.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗
DOE OSTI2024

LoVoCCS. II. Weak Lensing Mass Distributions, Red-sequence Galaxy Distributions, and Their Alignment with the Brightest Cluster Galaxy in 58 Nearby X-Ray-luminous Galaxy Clusters

The Local Volume Complete Cluster Survey is an ongoing program to observe nearly a hundred low-redshift X-ray-luminous galaxy clusters (redshifts 0.03 < z < 0.12 and X-ray luminosities in the 0.1–2.4 keV band L X500c > 10 44 erg s −1 ) with the Dark Energy Camera, capturing data in the u, g, r, i, z bands with a 5σ point source depth of approximately 25th–26th AB magnitudes. Here, we map the aperture masses in 58 galaxy cluster fields using weak gravitational lensing. These clusters span a variety of dynamical states, from nearly relaxed to merging systems, and approximately half of them have not been subject to detailed weak lensing analysis before. In each cluster field, we analyze the alignment between the 2D mass distribution described by the aperture mass map, the 2D red-sequence (RS) galaxy distribution, and the brightest cluster galaxy (BCG). We find that the orientations of the BCG and the RS distribution are strongly aligned throughout the interiors of the clusters: the median misalignment angle is 19° within 2 Mpc. We also observe the alignment between the orientations of the RS distribution and the overall cluster mass distribution (by a median difference of 32° within 1 Mpc), although this is constrained by galaxy shape noise and the limitations of our cluster sample size. These types of alignment suggest long-term dynamical evolution within the clusters over cosmic timescales.

79 ASTRONOMY AND ASTROPHYSICS↗
NASA NTRS1977

Particle size distributions and the vertical distribution of suspended matter in the upwelling region off Oregon

Various methods of presenting and mathematically describing particle size distribution are explained and evaluated. The hyperbolic distribution is found to be the most practical but the more complex characteristic vector analysis is the most sensitive to changes in the shape of the particle size distributions. A method for determining onshore-offshore flow patterns from the distribution of particulates was presented. A numerical model of the vertical structure of two size classes of particles was developed. The results show a close similarity to the observed distributions but overestimate the particle concentration by forty percent. This was attributed to ignoring grazing by zooplankton. Sensivity analyses showed the size preference was most responsive to the maximum specific growth rates and nutrient half saturation constants. The verical structure was highly dependent on the eddy diffusivity followed closely by the growth terms.

Kitchen, J. C.↗
DOE OSTI2020

Decentralized Voltage optimization Method for Distribution Networks with Distributed PVs

In order to solve the voltage violations caused by high penetration distributed photovoltaics (PVs), this paper proposes a decentralized voltage optimization method for distribution networks. Through the optimal dispatch of distributed PVs and reactive power resources, it realizes the voltage security and economic operation of distribution systems and facilitates the integration of massive distributed PVs. The proposed method is inspired by the idea of locational marginal price (LMP) and feasible cutting plane. It separates the optimization of boundary bus voltage and power flow in adjacent regions and uses the interaction of boundary variables’ marginal prices to obtain the optimal solution. The effectiveness and accuracy of the proposed method are demonstrated via simulation test on a practical l0kV feeder in China.

Xue, Yaosuo↗
DOE OSTI2019

OE0000878-Master thesis Observability Analysis of Power Distribution Systems with Distributed Energy Resources Using Correlational Measurements

In this thesis, an observability analysis framework is proposed for power distribution systems. The framework analyzes the sufficiency of the available measurements for monitoring the system. In the areas of the network where sufficient sensors have been deployed, the complex voltage at the nodes may be estimated. The framework also provides a metric that quantifies the accuracy of these voltage estimates. Due to the cost of sensors and the size of distribution systems, it is frequently the case that the available measurements are insufficient for complete observability of the system. In this thesis, the author proposes the use of Correlational Measurements (CMs) for improving distribution system observability by leveraging correlation between loads and between Distributed Energy Resources (DERs). Load correlation due to class-residential, commercial, industrial, etc.- is captured via correlational load measurements, the first type of CM. Injection correlation of DERs-such as wind turbines located in proximity-is captured via correlational DER measurements, the second type of CM. This thesis presents the CM formulation and derives modified node voltage and branch current based state estimators (NVSE and BCSE) accommodating CMs. Additionally, this thesis contains an on-line parameter estimation scheme for CMs that improves the accuracy of state estimates over time. The observability analysis framework with CMs is demonstrated through simulations on the IEEE 123 Node Distribution Test Feeder. It is shown that the introduction of CMs leads to improved observability of the system with only a 0.7% decrease in state estimation accuracy for NVSE and a 0.5% increase in state estimation accuracy for BCSE.

John, Yohan M↗
DOE OSTI2023

A Robust Parallel Distributed State Estimation for Large Scale Distribution Systems

The growing need and interest in real-time monitoring of large distribution networks motivated by the rapid population of renewable sources, EVs and etc. demand a computationally efficient state estimation framework. Furthermore, this paper presents an improved computational framework for implementing a robust state estimator using a multi-core processor. The main contribution of the paper is the proposed computational framework along with two partitioning strategies which enable fast and robust state estimation for large scale radial and/or meshed distribution systems. Formulation of the proposed method and its implementation are described in detail. Performance of the estimator is tested by simulations first using a small 84-bus radial distribution system. Then the method’s scalability is demonstrated by simulations on two very large scale distribution networks one configured radially and the other meshed each containing over 12,500 buses.

42 ENGINEERING↗
DOE OSTI2021

Iteration-based Linearized Distribution-level Locational Marginal Price for Three-phase Unbalanced Distribution Systems

Distributed energy resources (DERs) are rocking the utilities’ business landscape. It calls for competitive market environments that incentivize DERs to form maximum operating efficiency. Among proposed pricing schemes, distribution-level locational marginal price (DLMP) is effective in signaling the marginal generation cost differences driven by energy losses and network constraints. It can be derived from a distribution-level optimal power flow (OPF) framework, as it essentially presents the sensitivity of optimized generation cost towards incremental loads. However, due to the high resistance-to-inductance ratio and unbalanced characteristics of distribution networks, computational affordable DLMPs are highly challenged. This article provides a linear-approximated DLMP that can be solved efficiently and generalized to account for reactive power flow, three-phase unbalanced loads and meshed network structure. The successive linear programming technique is introduced to enhance the model accuracy. Case studies on an IEEE 123-Bus system validate its accuracy against a nonlinear benchmark and capability in offering proper incentives.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2021

Sensors with Intelligent Measurement Platform and Low-cost Equipment (SIMPLE) for Monitoring and Control of Medium Voltage Distribution Systems with High Penetration of Intermittent Distributed Energy Resources

The primary focus of the SIMPLE project was to develop, commission, test and introduce intelligent voltage and current sensor platform with enhanced characteristics (accuracy, bandwidth and harmonic range) and high measurement granularity for medium voltage distribution system monitoring, protection and control. The enhancements incorporated existing (commercially available) sensors and made them suitable for applications such as voltage regulation, frequency support, fault detection and location, distribution system state estimation, power quality measurements and electrical distribution network topology processing. The development of the intelligent sensor platform was driven by the need for high-fidelity monitoring and control of medium voltage distribution feeder to enable higher penetration of renewable resources and microgrid operation.

14 SOLAR ENERGY↗
DOE OSTI2025

Distribution Cybersecurity: Cybersecurity Considerations of Distributed Resources

This presentation is focused on cybersecurity of the distribution system. It will educate attendees about the evolving cybersecurity threats facing energy infrastructure through exploring relevant cybersecurity incidents. Additionally, Participants will gain an understanding of Distributed Energy Resources and their growing role in grid architecture. Finally, the session will examine critical standards and guidelines, including Cybersecurity Baselines for Electric Distribution Systems and the IEEE 1547.3 standard.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2020

Fine Root and Soil Organic Carbon Depth Distributions are Inversely Related Across Fertility and Rainfall Gradients in Lowland Tropical Forests

Humid tropical forests contain some of the largest soil organic carbon (SOC) stocks on Earth. Much of this SOC is in subsoil, yet variation in the distribution of SOC through the soil profile remains poorly characterized across tropical forests. We used a correlative approach to quantify relationships among depth distributions of SOC, fine root biomass, nutrients and texture to 1 m depths across 43 lowland tropical forests in Panama. The sites span rainfall and soil fertility gradients, and these are largely uncorrelated for these sites. We used fitted b parameters to characterize depth distributions, where b is a numerical index based on an asymptotic relationship, such that larger b values indicate greater concentrations of root biomass or SOC at depth in the profile. Root b values ranged from 0.82 to 0.95 and were best predicted by soil pH and extractable potassium (K) stocks. For example, the three most acidic (pH < 4) and Kpoor (< 20 g K m -2 ) soils contained 76 ± 5% of fine root biomass from 0 to 10 cm depth, while the three least acidic (pH > 6.0) and most K-rich (> 50 g K m -2 ) soils contained only 41 ± 9% of fine root biomass at this depth. Root b and SOC b values were inversely related, such that a large fine root biomass in surface soils corresponded to large SOC stocks in subsoils (50–100 cm). SOC b values were best predicted by soil pH and base cation stocks, with the three most base-poor soils containing 34 ± 8% of SOC from 50 to 100 cm depth, and the three most base-rich soils containing just 9 ± 2% of SOC at this depth. Nutrient depth distributions were not related to Root b or SOC b values. Here, these data show that large surface root biomass stocks are associated with large subsoil C stocks in strongly weathered tropical soils. Further studies are required to evaluate why this occurs, and whether changes in surface root biomass, as may occur with global change, could in turn influence SOC storage in tropical forest subsoils.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Conservation Voltage Reduction (CVR) via Two-Timescale Control in Unbalanced Power Distribution Systems

Voltage control devices are employed in power distribution systems to reduce the power consumption by operating the system closer to the lower acceptable voltage limits; this technique is called conservation voltage reduction (CVR). The different modes of operation for system’s legacy devices (with binary control) and new devices (e.g. smart inverters with continuous control) coupled with variable photovoltaic (PV) generation results in voltage fluctuations which makes it challenging to achieve CVR objective. This paper presents a two-timescale control of feeder’s voltage control devices to achieve CVR that includes (1)a centralized controller operating in a slower time-scale to coordinate voltage control devices across the feeder and (2) local controllers operating in a faster timescale to mitigate voltage fluctuations due to PV variability. The centralized controller utilizes a three-phase optimal power flow model to obtain the decision variables for both legacy devices and smart inverters. The local controllers operate smart inverters to minimize voltage fluctuations and restore nodal voltages to their reference values by adjusting the reactive power support. The proposed approach is validated using the IEEE-123 bus (medium-size) and R3-12.47-2 (large-size) feeders. It is demonstrated that the proposed approach is effective in achieving the CVR objective for unbalanced distribution systems.

optimal control, distributed generation, fluctuati↗
DOE OSTI2023

Distribution Network Capacity Market Design: Marginal Distribution Capacity Pricing Mechanism for Efficient Investment and Cost Allocation

As electricity markets begin to shift from reliance on large, centralized power plants and towards distributed energy resources (DERs), there is a growing acknowledgement that more efficient planning, operations, and oversight is needed in the distribution system. This paper addresses one step in that direction by proposing an auction mechanism that uses a detailed distribution system planning model that allocates permits to end-used customers who request capacity to install new devices at their location and network upgrade contracts to utilities or 3rd-party companies who offer to upgrade system components. The resulting plan maximizes market surplus, that is, maximizes the total benefit to consumers minus the cost of network upgrades. We apply a marginal pricing scheme to the auction’s results such that the cost of each permits or contracts is differentiated by time and location, based on the Lagrangian multipliers of binding network constraints. These prices are shown to be no greater than the bid price of any awarded contract and no less than the offered cost of any awarded upgrade contract. Furthermore, the nonlinearity of power flows in the planning model result in an additional surplus that would be collected by the entity that hosts the auction, which could then be refunded to market participants or used to cover overhead costs of running the market. We provide four example auction results in a simple three-node distribution feeder to demonstrate the properties of the design. Results suggest that larger or more realistic case studies could be a promising next step.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2021

Distributed Data-Driven Power Iteration for Strongly Connected Networks

Here, this paper presents data-driven power iteration to distributively estimate the dominant eigenvalues of an unknown linear time-invariant system. The proposed strategy only requires a single trajectory data or measurements. Furthermore, in order to perform the distributed estimation, the communication network topology can be chosen to be any strongly connected directed graphs. The proposed data-driven power iteration is demonstrated using several numerical examples and is then applied to estimate the generalized algebraic connectivity of cooperative systems and to control the epidemic spreading.

Gusrialdi, Azwirman↗
DOE OSTI2020

Robust Medium-Voltage Distribution System State Estimation using Multi-Source Data

Due to the lack of sufficient online measurements for distribution system observability, pseudo-measurements from short-term load or distributed renewable energy resources (DERs) forecasting are used. However, the accuracy of them is low and thus significantly limits the performance of distribution system state estimation (DSSE). In this paper, a robust DSSE that integrates multi-source measurement data is proposed. Specifically, the historical low-voltage (LV) side smart meters are used to forecast load and DERs injections via the support vector machine (SVM) with optimally tuned parameters. By contrast, the online smart meters at LV side are utilized to derive equivalent power injections at the MV/LV transformers, yielding more accurate pseudo-measurements compared to the forecasted injections. Furthermore, to deal with bad data caused by communication loss, instrumental errors and cyber attacks, robust DSSE that relies on generalized maximum-likelihood (GM)-estimation criterion is developed. The projection statistics are developed to adjust the weights of each measurement, leading to better balance between pseudo- and real-time measurements. Numerical results conducted on modified IEEE 33-bus system with DG integration demonstrate the effectiveness and robustness of the proposed method.

distribution system state estimation↗
DOE OSTI2022

Multiarea Distribution System State Estimation via Distributed Tensor Completion

Here, this paper proposes a model-free distribution system state estimation method based on tensor completion using canonical polyadic decomposition. In particular, we consider a setting where the network is divided into multiple areas. The measured physical quantities at buses located in the same area are processed by an area controller. A three-way tensor is constructed to collect these measured quantities. The measurements are analyzed locally to recover the full state information of the network. A distributed closed-form iterative algorithm based on the alternating direction method of multipliers is developed to obtain the low-rank factors of the whole network state tensor where information exchange happens only between neighboring areas. The convergence properties of the distributed algorithm and the sufficient conditions on the number of samples for each smaller network that guarantee the identifiability of the factors of the state tensor are presented. To demonstrate the efficacy of the proposed algorithm and to check the identifiability conditions, numerical simulations are carried out using the IEEE 123-bus system and a large-scale real utility feeder.

24 POWER TRANSMISSION AND DISTRIBUTION↗