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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 181 records · Page 10
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Estimating the impacts of natural gas power generation growth on solar electricity development: PJM's evolving resource mix and ramping capability

Abstract Expansion of distributed solar photovoltaic (PV) and natural gas‐fired generation capacity in the United States has put a renewed spotlight on methods and tools for power system planning and grid modernization. This article investigates the impact of increasing natural gas‐fired electricity generation assets on installed distributed solar PV systems in the Pennsylvania–New Jersey–Maryland (PJM) Interconnection in the United States over the period 2008–2018. We developed an empirical dynamic panel data model using the system‐generalized method of moments (system‐GMM) estimation approach. The model accounts for the impact of past and current technical, market and policy changes over time, forecasting errors, and business cycles by controlling for PJM jurisdictions‐level effects and year fixed effects. Using an instrumental variable to control for endogeneity, we concluded that natural gas does not crowd out renewables like solar PV in the PJM capacity market; however, we also found considerable heterogeneity. Such heterogeneity was displayed in the relationship between solar PV systems and electricity prices. More interestingly, we found no evidence suggesting any relationship between distributed solar PV development and nuclear, coal, hydro, or electricity consumption. In addition, considering policy effects of state renewable portfolio standards, net energy metering, differences in the PJM market structure, and other demand and cost‐related factors proved important in assessing their impacts on solar PV generation capacity, including energy storage as a non‐wire alternative policy technique. This article is categorized under: Photovoltaics > Economics and Policy Fossil Fuels > Climate and Environment Energy Systems Economics > Economics and Policy

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2022

A Bayesian Approach for In-Situ Stress Prediction and Uncertainty Quantification for Subsurface Engineering

Many subsurface engineering applications require accurate knowledge of the in-situ state of stress for their safe design and operation. Existing methods to meet this need primarily include field measurements for estimating one or more of the principal stresses from a borehole, or optimization methods for constructing a 3D geomechanical model in terms of geophysical measurements. These methods, however, often contain considerable uncertainty in estimating the state of stress. Here, in this paper, we build on a Bayesian approach to quantify uncertainty in stress estimations for subsurface engineering applications. This approach can provide an estimate of the 3D distribution of stress throughout the volume of interest and provide an estimate of the uncertainty arising from the stress measurement, the rheology parameters, and a paucity of measurements. The value of this approach is demonstrated using stress measurements from the In Salah carbon storage site, which was one of the world’s first industrial carbon capture and storage projects. This demonstration shows the application of this Bayesian approach for estimating the initial state of stress for In Salah and quantifying the uncertainty in the estimated stress. Also, an assessment of a maximum injection pressure to prevent geomechanical risks from CO 2 injection pressures is provided in terms of the probability distribution of the minimum principal stress quantified by the approach. With the In Salah case study, this paper demonstrates that using the Bayesian approach can provide additional insights for site explorations and/or project operations to make informed-site decisions for subsurface engineering applications.

58 GEOSCIENCES↗
DOE OSTI2023

A Smart Silicon Carbide Power Module With Pulse Width Modulation Over Wi-Fi and Wireless Power Transfer-Enabled Gate Driver, Featuring Onboard State of Health Estimator and High-Voltage Scaling Capabilities: Preprint

A wide range of utility applications require controllable switches with features such as high-voltage (HV) blocking and high-current carrying capacity especially at high pulse width modulation (PWM) frequency. Low and medium voltage utility applications such as motor drives and flexible AC transmission systems (FACTS) as well as solid state transformers (SST) could also benefit from a low-cost HV switching module. Wide band gap (WBG) semiconductors such as SiC and GaN MOSFETs are considered to be the present and next generation device choices, although they have their own limitations. For relatively HV applications with demanding thermal management, SiC is still the only choice, and GaN dominates the low voltage regime. This manuscript proposes a new half bridge power MOSFET module that is suitable for conventional H-bridge of multilevel configurations used in HV applications. Constructed from bare SiC dies, this half bridge module takes advantage of (1) optimized MOSFET placement inside the module, (2) customized heat exchanger, manifold and cooling, (3) integrated gate driver module with PWM over wi-fi to eliminate the need for low voltage signals, (4) wireless power transfer (WPT) enabled gate driver and other ancillary circuits, (5) and the option to incorporate an onboard state of health (SOH) estimator module onboard. The entire architecture has been designed and built at National Renewable Energy Laboratory (NREL), Golden, CO.

baseplate design↗
NASA NTRS1985

An efficient algorithm for estimating noise covariances in distributed systems

An efficient computational algorithm for estimating the noise covariance matrices of large linear discrete stochatic-dynamic systems is presented. Such systems arise typically by discretizing distributed-parameter systems, and their size renders computational efficiency a major consideration. The proposed adaptive filtering algorithm is based on the ideas of Belanger, and is algebraically equivalent to his algorithm. The earlier algorithm, however, has computational complexity proportional to p to the 6th, where p is the number of observations of the system state, while the new algorithm has complexity proportional to only p-cubed. Further, the formulation of noise covariance estimation as a secondary filter, analogous to state estimation as a primary filter, suggests several generalizations of the earlier algorithm. The performance of the proposed algorithm is demonstrated for a distributed system arising in numerical weather prediction.

Dee, D. P.↗
DOE OSTI2024

Cost of Wind Energy Review: 2024 Edition [Slides]

The primary elements of this analysis include: Estimated LCOE for (1) a representative land-based wind energy project installed in a moderate wind resource in the United States, (2) a representative fixed-bottom offshore wind energy project installed in the U.S. North Atlantic, and (3) a representative floating offshore wind energy project installed off the U.S. Pacific Coast. It also updates the LCOE estimates for representative residential-, commercial-, and large-scale distributed wind projects installed in a moderate wind resource in the United States. A sensitivity analyses is included that shows the range of effects that basic LCOE variables could have on the cost of wind energy for land-based and offshore wind projects and provides updated Fiscal Year 2024 values for land-based and offshore wind energy used for Government Performance and Results Act (GPRA) reporting and illustrated progress toward established GPRA targets.

17 WIND ENERGY↗
NASA NTRS2016

Determination of Celestial Body Principal Axes via Gravity Field Estimation

The determination of physical parameters of celestial bodies provides critical navigational and scientific information. Determining the mass, rotation state, and density distribution is an important task of the navigation team on an operational mission. One representation of the internal density distribution, spherical harmonics, may be leveraged to compute the orientation of the principal axis frame of the celestial body, which in turn informs the dynamics of the body’s motion. Using data from NASA’s Dawn mission to the massive asteroids (1) Ceres and (4) Vesta, a method is proposed that refines the knowledge of the principal axis frame by utilizing estimated spherical harmonic coefficients. Applying an iterative rotation scheme to the solved-for body-fixed frame leads to convergence on a frame that is very close to the actual dynamical principal axis frame.

Takahashi, Yu↗
DOE OSTI2025

A derecho climatology (2004–2021) in the United States based on machine learning identification of bow echoes

Due to their persistent widespread severe winds, derechos pose significant threats to human safety and property, with impacts comparable to many tornadoes and hurricanes. Yet, automated detection of derechos remains challenging due to the absence of spatiotemporally continuous observations and the complex criteria employed to define the phenomenon. This study presents an objective derecho detection approach capable of automatically identifying derechos through both observations and model results. The approach is grounded in a physically based definition of derechos and integrates three algorithms: (1) the Python Flexible Object Tracker (PyFLEXTRKR) algorithm to track mesoscale convective systems (MCSs), (2) a semantic segmentation convolutional neural network to identify bow echoes, and (3) a comprehensive classification algorithm to detect derechos within MCS life cycles and distinguish derecho-producing from non-derecho-producing MCSs. Using this approach, we developed a novel high-resolution (4 km and hourly) observational dataset of derechos and accompanying derecho-producing MCSs over the United States east of the Rocky Mountains from 2004 to 2021. The dataset consists of two subsets based on different gust speed data sources and is analyzed to document the climatology of derechos in the United States. On average, 12–15 derechos are identified per year, aligning with previous estimations (∼6–21 events annually). The spatial distribution and seasonal variation patterns are consistent with prior studies, showing peak occurrences in the Great Plains and the Midwest during the warm season. Additionally, during the study period, derechos account for approximately 3.1 % of measured damaging gusts (≥25.93 m s−1) over the eastern United States. The dataset is publicly available at https://doi.org/10.5281/zenodo.14835362 (Li et al., 2025).

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS1987

Polarized fluorescence spectroscopy of O2(+)

Polarized fluorescence measurements involving the A 2Pi(u) - X 2Pi(g) and b 4Sigma(g)(-) - a 4Pi(u) transitions in O2(+) following narrow-band photoexcitation of O2/X 3Sigma(g)(-)/ are reported. The analysis, based on the conventional high-J limit, involves deducing the quadrupole alignment factor from which the relative strengths of degenerate photoexcitation channels responsible for the population distribution in the A 2Pi(u) and b 4Sigma(g)(-) states of O2(+) can be estimated. The measured A-channel polarization exhibits pronounced structure which correlates well with the known positions of Rydberg states, whereas the polarization signal in the b channel has broad and less prominent features. Discrepancies between theoretical and measured results can largely be accounted for by additional configuration mixing and autoionization considerations.

Keller, J. W.↗
DOE OSTI2025

National Modeling of Geothermal District Energy Systems with Ambient-Temperature Loops Using dGeo

Geothermal district energy systems (DES) with ambient-temperature loops, also known as thermal energy networks, are one option for decarbonizing space heating and cooling loads. Geothermal fifth-generation DES include an "ambient" temperature thermal loop that connects heat pumps at each building with thermal balancing sources such as geothermal borehole fields. Heating and cooling are provided via a water-source heat pump at each end-user. This project seeks to analyze the nationwide potential for ambient-temperature loop districts by creating a new module within the Distributed Geothermal Market Demand Model (dGeo). dGeo is an agent-based modeling tool for distributed geothermal resources; it can investigate potential on a nationwide or statewide scale using geospatial data for all 50 states and thermal demands for existing buildings. This process allows for high-level estimates of technical and economic potential for ambient-temperature loop districts across the United States. A lookup table was created using GHEDesigner to size borehole fields for different thermal loads and ground conditions experienced across the country. A cost and financing structure, along with incentives, were applied. Cost estimates include costs for the distribution network, borehole field installation and operation, and circulation pump operation, while savings are calculated based on energy bills for building owners (agents). This newly developed module can be used for assessing which areas of the country have the highest potential for agent benefits from ambient-temperature loop installation and assess the impact of future cost and price scenarios. Initial results for statewide analysis (for Vermont) and nationwide (for United States) are provided. Future work includes expanding the module to consider mixed residential and commercial districts as well as evaluating multiple cost scenarios.

ambient-temperature loop↗
DOE OSTI2024

NPFTURBULENCE: Best Estimate Aerosol Size Distribution by airborne measurements

The original data were collected during the field campaign of “Turbulent layers promoting New Particle Formation” experiment (NPFTURBULENCE; https://www.arm.gov/research/campaigns/aaf2024npfturbulence) over the Atmospheric Radiation Measurement (ARM) Southern Great Plains (SGP) Atmospheric Observatory (https://www.arm.gov/capabilities/observatories/sgp ) in north-central Oklahoma. The ARM Aerial Facility ArcticShark uncrewed aerial system (UAS) was based at Blackwell–Tonkawa Municipal Airport (IATA: BWL, ICAO: KBKN, FAA LID: BKN, 36.74475° N, 97.34918° W, 313.9 m MSL), for the field campaign from May 5 through May 29, 2024. The ArcticShark UAS performed 11 flights, including 10 research flights over the Central Facility of the ARM SGP to measure atmospheric state, turbulence, surface IT temperature and imagery, aerosol number concentration and size distribution. The current data set presents Best Estimate Aerosol Size Distribution: a merged aerosol size distribution composed of the data from 2 sensors: miniaturized Scanning Electrical Mobility Sizer (mSEMS) and Portable Optical Particle Spectrometer (POPS). The mSEMS data were interpolated to 1 second from “native” time resolution of about 15 second to match the other probe. The POPS data were converted from equivalent optical size into geometric size using value of aerosol refractive index of 1.477 from the HISCALE field campaign (same geographical area, altitudes, and time of year; http://www.arm.gov/campaigns/aaf2016hiscale ).

54 ENVIRONMENTAL SCIENCES↗
NASA NTRS2015

Coupled Inertial Navigation and Flush Air Data Sensing Algorithm for Atmosphere Estimation

This paper describes an algorithm for atmospheric state estimation that is based on a coupling between inertial navigation and flush air data sensing pressure measurements. In this approach, the full navigation state is used in the atmospheric estimation algorithm along with the pressure measurements and a model of the surface pressure distribution to directly estimate atmospheric winds and density using a nonlinear weighted least-squares algorithm. The approach uses a high fidelity model of atmosphere stored in table-look-up form, along with simplified models of that are propagated along the trajectory within the algorithm to provide prior estimates and covariances to aid the air data state solution. Thus, the method is essentially a reduced-order Kalman filter in which the inertial states are taken from the navigation solution and atmospheric states are estimated in the filter. The algorithm is applied to data from the Mars Science Laboratory entry, descent, and landing from August 2012. Reasonable estimates of the atmosphere and winds are produced by the algorithm. The observability of winds along the trajectory are examined using an index based on the discrete-time observability Gramian and the pressure measurement sensitivity matrix. The results indicate that bank reversals are responsible for adding information content to the system. The algorithm is then applied to the design of the pressure measurement system for the Mars 2020 mission. The pressure port layout is optimized to maximize the observability of atmospheric states along the trajectory. Linear covariance analysis is performed to assess estimator performance for a given pressure measurement uncertainty. The results indicate that the new tightly-coupled estimator can produce enhanced estimates of atmospheric states when compared with existing algorithms.

Karlgaard, Christopher D.↗
NASA NTRS1994

Geometrical evidence for dark matter: X-ray constraints on the mass of the elliptical galaxy NGC 720

We describe (1) a new test for dark matter and alternate theories of gravitation based on the relative geometries of the X-ray and optical surface brightness distributions and an assumed form for the potential, of the optical light, (2) a technique to measure the shapes of the total gravitating matter and dark matter of an ellipsoidal system which is insensitive to the precise value of the temperature of the gas and to modest temperature gradients, and (3) a new method to determine the ratio of dark mass to stellar mass that is dependent on the functional forms for the visible star, gas and dark matter distributions, but independent of the distance to the galaxy or the gas temperature. We apply these techniques to X-ray data from the ROSAT Position Sensitive Proportional Counter (PSPC) of the optically flattened elliptical galaxy NGC 720; the optical isophotes have ellipticity epsilon approximately 0.40 extending out to approximately 120 sec. The X-ray isophotes are significantly elongated, epsilon = 0.20-0.30 for semimajor axis a approximately 100 sec. The major axes of the optical and X-ray isophotes are misaligned by approximately 30 deg +/- 15 deg. Spectral analysis of the X-ray data reveals no evidence of temperature gradients or anisotropies and demonstrates that a single-temperature plasma (T approximately 0.6 keV) having subsolar heavy element abundances and a two-temperature model having solar abundances describe the spectrum equally well. Considering only the relative geometries of the X-ray and optical surface brightness distributions and an assumed functional form for the potential of the optical light, we conclude that matter distributed like the optical light cannot produce the observed ellipticities of the X-ray isophotes, independent of the gas pressure, the gas temperature, and the value of the stellar mass; this comparison assumes a state of quasi-hydrostatic equilibrium so that the three-dimensional surfaces of the gas emissivity trace the three-dimensional isopotential surfaces -- we discuss the viability of this assumption for NGC 720. Milgrom's Modification of Newtonian Dynamics (MOND) cannot dispel this manifestation of dark matter. Hence, geometrical considerations require, without mention of pressure or temperature, the presence of an extended, massive dark matter halo in NGC 720. Employing essentially the technique of Buote & Canizares (1992; Buote 1992) we use the shape of the X-ray surface brightness to constrain the shape of the total gravitating matter. The total matter is modeled as either an oblate or prolate spheriod of constant shape and orientation having either a Ferrers (rho approximately r(exp -n)) or Hernquist density. Assuming the X-ray gas is in hydrostatic equilibrium, we construct a model X-ray gas distribution for various temperature profiles. We determine the ellipticity of the total gravitating matter to be epsilon approximately 0.50-0.70. Using the single-temperature model we estimate a total mass approximately (0.41-1.4) x 10(exp 12) h(sub 80) solar mass interior to the ellipsoid of semimajor axis 43.6 h(sub 80) kpc. Ferrers densities as steep as r(exp -3) do not fit the data, but the r(exp -2) and Hernquist models yield excellent fits. We estimate the mass distributions of the stars and the gas and fit the dark matter directly. For a given gas equation of state and functional forms for the visible stars, gas, and dark matter, these models yield a distance-independent and temperature-independent measurement of the ratio of dark mass to stellar mass M(sub DM)/M(sub stars). We estimate a minimum M(sub DM)/M(sub stars) greater than or equal to 4 which corresponds to a total mass slightly greater than that derived from the single-temperature models for distance D = 20h(sub 80) Mpc.

Buote, David A.↗
DOE OSTI2024

National Modeling of Geothermal District Energy Systems with Ambient-Temperature Loops Using dGeo: Preprint

Geothermal district energy systems (DES) with ambient-temperature loops, also known as thermal energy networks, are one option for decarbonizing space heating and cooling loads. Geothermal fifth-generation DES include an "ambient" temperature thermal loop that connects heat pumps at each building with thermal balancing sources such as geothermal borehole fields. Heating and cooling are provided via a water-source heat pump at each end-user. This project seeks to analyze the nationwide potential for ambient-temperature loop districts by creating a new module within the Distributed Geothermal Market Demand Model (dGeo). dGeo is an agent-based modeling tool for distributed geothermal resources; it can investigate potential on a nationwide or statewide scale using geospatial data for all 50 states and thermal demands for existing buildings. This process allows for high-level estimates of technical and economic potential for ambient-temperature loop districts across the United States. Using GHEDesigner, a lookup table was created to size borehole fields for different thermal loads and ground conditions experienced across the country. A cost and financing structure, along with incentives, were applied. Cost estimates include costs for the distribution network, borehole field installation and operation, and circulation pump operation, while savings are calculated based on agent energy bills. This newly developed module can be used for assessing which areas of the country have the highest potential for agent benefits from ambient-temperature loop installation and assess the impact of different costing and pricing future scenarios. While the code is still under development and nationwide simulations are ongoing, initial results for two states are provided. Future work includes expanding the module to consider mixed residential and commercial districts and considering multiple costing scenarios.

ambient temperature loop↗
NASA NTRS2016

Coupled Inertial Navigation and Flush Air Data Sensing Algorithm for Atmosphere Estimation

This paper describes an algorithm for atmospheric state estimation based on a coupling between inertial navigation and flush air data-sensing pressure measurements. The navigation state is used in the atmospheric estimation algorithm along with the pressure measurements and a model of the surface pressure distribution to estimate the atmosphere using a nonlinear weighted least-squares algorithm. The approach uses a high-fidelity model of atmosphere stored in table-lookup form, along with simplified models propagated along the trajectory within the algorithm to aid the solution. Thus, the method is a reduced-order Kalman filter in which the inertial states are taken from the navigation solution and atmospheric states are estimated in the filter. The algorithm is applied to data from the Mars Science Laboratory entry, descent, and landing from August 2012. Reasonable estimates of the atmosphere are produced by the algorithm. The observability of winds along the trajectory are examined using an index based on the observability Gramian and the pressure measurement sensitivity matrix. The results indicate that bank reversals are responsible for adding information content. The algorithm is applied to the design of the pressure measurement system for the Mars 2020 mission. A linear covariance analysis is performed to assess estimator performance. The results indicate that the new estimator produces more precise estimates of atmospheric states than existing algorithms.

Karlgaard, Christopher D.↗
NASA NTRS1988

Parameter estimation in nonlinear distributed systems - Approximation theory and convergence results

An abstract approximation framework and convergence theory is described for Galerkin approximations applied to inverse problems involving nonlinear distributed parameter systems. Parameter estimation problems are considered and formulated as the minimization of a least-squares-like performance index over a compact admissible parameter set subject to state constraints given by an inhomogeneous nonlinear distributed system. The theory applies to systems whose dynamics can be described by either time-independent or nonstationary strongly maximal monotonic operators defined on a reflexive Banach space which is densely and continuously embedded in a Hilbert space. It is demonstrated that if readily verifiable conditions on the system's dependence on the unknown parameters are satisfied, and the usual Galerkin approximation assumption holds, then solutions to the approximating problems exist and approximate a solution to the original infinite-dimensional identification problem.

Banks, H. T.↗
NASA NTRS2015

System and Method for Monitoring Distributed Asset Data

A computer-based monitoring system and monitoring method implemented in computer software for detecting, estimating, and reporting the condition states, their changes, and anomalies for many assets. The assets are of same type, are operated over a period of time, and outfitted with data collection systems. The proposed monitoring method accounts for variability of working conditions for each asset by using regression model that characterizes asset performance. The assets are of the same type but not identical. The proposed monitoring method accounts for asset-to-asset variability; it also accounts for drifts and trends in the asset condition and data. The proposed monitoring system can perform distributed processing of massive amounts of historical data without discarding any useful information where moving all the asset data into one central computing system might be infeasible. The overall processing is includes distributed preprocessing data records from each asset to produce compressed data.

Gorinevsky, Dimitry↗
DOE OSTI2021

Distributed electric field sensing using fibre optics in borehole environments

In the past decade, rapid advances in distributed optical fibre sensing technologies have made it possible to record various geophysical data (e.g. strain, temperature and pressure) continuously in both time and space along the fibre, providing an unprecedented quantity and spatial density of data compared to traditional geophysical measurements as well as reducing data acquisition cost. To date, no distributed fibre-based electromagnetic field sensing system has been implemented although electromagnetic sensing could have a broad range of applications to geophysical imaging and monitoring in borehole environments. The goal of this paper is to provide a theoretical feasibility study regarding the design and use of an electromagnetic sensing optical fibre for geophysical applications. First, we present the sensitivity analysis of a ‘hypothetical’ optical fibre coated with polyvinylidene fluoride, a polymer that provides relatively high piezoelectric properties, yet unlike ceramics, is flexible. Next, using a two-dimensional electromagnetic modelling algorithm, we simulate the earth electric-field-to-fibre-strain transfer function and estimate the theoretical sensitivity of the optical fibre to electric fields. Given the state-of-the-art distributed acoustic sensing strain sensitivities in the picometres strain range, our numerical modelling analysis suggests that a perfectly coupled polyvinylidene fluoride–coated optical fibre can measure electric field values in the mV/m to V/m amplitude range. We then apply a cylindrically symmetric modelling algorithm to simulate numerical models demonstrating the applicability of such a fibre in an oilfield environment. Scenarios investigated employ an electric field source and suggest that the measurements can be used to distinguish the oil versus water ratio with a fibre mounted inside a producing steel cased oil well as well as distinguishing between brine and hydrocarbon filled reservoir zones with a fibre located outside of the casing.

58 GEOSCIENCES↗
DOE OSTI2023

Blockchain for Fault-Tolerant Grid Operations

Radial topology and vast geographic coverage make distribution systems prone to widespread power outages upon the failure of a single (or multiple) upstream component. Fault-handling algorithms depend heavily on correct estimations of the system’s state to effectively isolate the affected area and reduce the number of affected customers while maintaining operational safety. The work described here leverages the core features of distributed, consensus-based decision-making processes and the immutability of blockchain, and demonstrates their value in improving fault-tolerant grid operations. In this work, blockchain was used to create a trusted data-sharing platform that enables independent actors to reconstruct the system state; this enables distributed resources to make intelligent decisions with limited knowledge. Although the process requires data sharing, its algorithms have been designed to limit the amount of private information that is exchanged, which helps preserve business-sensitive data and maintain customer privacy. In addition, by reducing the information that must be shared, the communication requirements are also reduced; (however, an in-depth analysis of the communication requirements is beyond the scope of this project). The proposed use cases are intended to represent a foundational basis for third parties to develop functional solutions that can eventually be deployed in the field. To further provide guidance, the envisioned use cases have incorporated design requirements that consider the blockchain characteristics and a need to limit information from surrounding resources, which preserve the assumption and the possibility that such resources could belong to different entities. This report presents a detailed design of the three use cases with the tools needed to enable the analysis being tested. The implemented gross error detection method can detect mismatches when the error exceeds 3.8 times the sensor’s rated accuracy. Detection of the circuit breaker state successfully identified the correct states across all simulation tests. A distribution-system power-flow solution in the simulator OpenDSS generally possesses a convergency tolerance of 0.01% on the voltage magnitude. The evaluation of possible reconnection using voltage magnitude—preserving the data ownership—has a voltage magnitude difference smaller than 0.001% from the OpenDSS result. The results preserving data ownership have a difference within the expected power flow tolerance with full knowledge of the system, which surpasses expectations.

24 POWER TRANSMISSION AND DISTRIBUTION↗