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At least 19 records
All sourcesNASA NTRSDOE OSTI
DOE OSTI2018

Improvement of Transmission Line Ampacity Utilization by Weather-Based Dynamic Line Rating

Most of the existing overhead transmission lines (TLs) are assigned a static rating by considering the conservative environmental conditions (e.g., high ambient temperature and low wind speed). Such a conservative approach often results in underutilization of line ampacity because the worst conditions prevail only for a short period of time during the year. Dynamic line rating (DLR) utilizes local meteorological conditions and grid loadings to adaptively compute additional line ampacity headroom that may be available due to favorable local environmental conditions. This paper details Idaho National Laboratory-developed weather-based DLR, which utilizes a state-of-the-art general line ampacity state solver for real-time computation of thermal ratings of TLs. Performance of the proposed DLR solution is demonstrated in existing TL segments at AltaLink, Canada, and the potential benefits of the proposed DLR for enhanced transmission ampacity utilization are quantified. Moreover, we investigated a hypothetical case for emulating the impact of an additional wind plant near the test grid. Furthermore, the results for the given system and data configurations demonstrated that real-time ratings were above the seasonal static ratings for at least 76.6% of the time, with a mean increase of 22% over the static rating, thereby demonstrating huge potential for improvement on ampacity utilization.

17 WIND ENERGY↗
DOE OSTI2017

Transmission Line Ampacity Improvements of AltaLink Wind Plant Overhead Tie-Lines Using Weather-Based Dynamic Line Rating

Abstract—Overhead transmission lines (TLs) are conventionally given seasonal ratings based on conservative environmental assumptions. Such an approach often results in underutilization of the line ampacity as the worst conditions prevail only for a short period over a year/season. We presents dynamic line rating (DLR) as an enabling smart grid technology that adaptively computes ratings of TLs based on local weather conditions to utilize additional headroom of existing lines. In particular, general line ampacity state solver utilizes measured weather data for computing the real-time thermal rating of the TLs. The performance of the presented method is demonstrated from a field study of DLR technology implementation on four TL segments at AltaLink, Canada. The performance is evaluated and quantified by comparing the existing static and proposed dynamic line ratings, and the potential benefits of DLR for enhanced transmission assets utilization. For the given line segments, the proposed DLR results in real-time ratings above the seasonal static ratings for most of the time; up to 95.1% of the time, with a mean increase of 72% over static rating.

17 WIND ENERGY↗
DOE OSTI2024

An analysis of parameters affecting ampacity in aircraft bipolar MVDC power cables via coupled electrical, thermal, and computational fluid dynamic modelling

Abstract The next generation of aircraft, including more electric aircraft and all‐electric aircraft (AEA), requires electric power systems with high power density and low system mass specifications. Increasing the voltage of the system to the range of a few kV, medium voltage (MV), is a reasonable approach to achieving high‐power‐density and low‐system‐mass EPSs for aircraft applications. Higher voltages, however, pose many challenges for aviation MV power cables such as arcs and arc tracking, partial discharges (PDs), and thermal management. In this regard, thermal management is more challenging since heat transfer by convection is greatly reduced at wide‐body aircraft's cruising altitudes due to the reduced air pressure. In this paper, a finite element method (FEM) model is developed in COMSOL Multiphysics for an aircraft bipolar MVDC (±5 kV) power cable. Using the model, the maximum permissible cable current at a low pressure of 18.8 kPa (at an altitude of 12.2 km from sea level, the usual cruising altitude for wide‐body aircraft) is calculated. Also, an analytical model is developed based on analytical and proven empirical correlations governing conductive, radiative, and convective heat transfers at the steady state to estimate the ampacity of the bipolar cable system at reduced pressure. It was shown that the proposed analytical model can be used for atmospheric pressure and systems with a larger number of poles, expanding its range of applications. The results of the FEM and analytical models correlate at wide ranges of parameters such as ambient temperature, duct size, distance between the positive and negative pole cables, and the overall diameter of the cables. The influence of horizontal and vertical arrangement of poles is included in the analytical model. The results of this study can be used to design bipolar MVDC power cable systems for the envisaged wide‐body AEA.

Azizi, Arian↗
DOE OSTI2017

GLASS: General Line Ampacity State Solver

The U.S. installed more than 8,000 megawatts of wind generation in 2016. Wind energy is now powering more than 20 million homes. Idaho National Laboratory technology uses real time weather information and computer models to help utilities integrate more wind energy, relieving transmission line congestion, and extending the life time of existing grid infrastructure.

17 WIND ENERGY↗
DOE OSTI2021

Forecasting Dynamic Line Rating with Spatial Variation Considerations

Dynamic line rating (DLR) is a technology that allows the ampacity of an electrical conductor to be calculated using real-time or forecasted weather conditions. Historically, the ampacity of a conductor has been determined using a static line rating method which assumes conservative weather assumptions. Therefore, not only can DLR give a more accurate measurement of the true ampacity of a conductor, but it can also increase its ampacity during weather conditions with greater thermal mitigations. The two primary cooling factors in the ampacity calculations are wind speed and direction. In complex terrain, wind speed and direction can have large variations over short distances. Therefore, accurately identifying the limiting span of a transmission line requires high spatial resolution of the wind along its path. One solution is to install dense weather stations along their path, though this can become costly over long distances. Therefore, researchers have investigated the use of Computation Fluid Dynamic (CFD) simulations to accurately compute the wind field along the path of a transmission line and use these results to identify the limiting section of the conductor. This work presents a case study that evaluates the coupling of CFD simulations and forecasted weather simulations using the High-Resolution Rapid Refresh (HRRR) model points over a 2-year span within a region in south eastern Idaho. The primary goal of the work is the evaluation of the number of HRRR model points used, i.e., weather stations, along the path of the line and the accuracy of the resulting DLR ampacity. This was done using 4, 10, 17, 26, and 35 HRRR model points along two transmission line paths. The results indicate that as the number of model points are increased, the DLR ampacity of the lines decrease, yet converge as more points are added and demonstrate little change with additional HRRR points. It is expected that these results can help transmission line operators identify the number of weather stations that must be installed when coupled with CFD simulations and DLR ampacity to ensure accurate ratings and safe operations.

17 WIND ENERGY↗
DOE OSTI2021

Forecasting Dynamic Line Rating with Spatial Variation Considerations

Dynamic line rating (DLR) is a technology that allows the ampacity of an electrical conductor to be calculated using real-time or forecasted weather conditions. Historically, the ampacity of a conductor has been determined using a static line rating method which assumes conservative weather assumptions. Therefore, not only can DLR give a more accurate measurement of the true ampacity of a conductor, but it can also increase its ampacity during weather conditions with greater thermal mitigations. The two primary cooling factors in the ampacity calculations are wind speed and direction. In complex terrain, wind speed and direction can have large variations over short distances. Therefore, accurately identifying the limiting span of a transmission line requires high spatial resolution of the wind along its path. One solution is to install dense weather stations along their path, though this can become costly over long distances. Therefore, researchers have investigated the use of Computation Fluid Dynamic (CFD) simulations to accurately compute the wind field along the path of a transmission line and use these results to identify the limiting section of the conductor. This work presents a case study that evaluates the coupling of CFD simulations and forecasted weather simulations using the High-Resolution Rapid Refresh (HRRR) model points over a 2-year span within a region in south eastern Idaho. The primary goal of the work is the evaluation of the number of HRRR model points used, i.e., weather stations, along the path of the line and the accuracy of the resulting ampacity. This was done using 4, 10, 17, 26, and 35 HRRR model points along two transmission line paths. The results indicate that as the number of model points are increased, the DLR ampacity of the lines decrease, yet converge as more points are added and demonstrate little change with additional HRRR points. It is expected that these results can help transmission line operators identify the number of weather stations that must be installed when coupled with CFD simulations and DLR ampacity to ensure accurate ratings and safe operations.

17 WIND ENERGY↗
DOE OSTI2021

Feasibility and Prospects of the High Resolution Rapid Refresh Model For Dynamic Line Rating

The ampacity of transmission lines is defined as the maximum amount of current the conductor can safely carry. It is necessary for transmission line operators to apply ampacity limits due to the thermal properties of the conductor. Dynamic Line Rating (DLR) is a technology and technique that uses the environmental conditions or a set of the conditions to calculate the ampacity of the conductor. The way the DLR is calculated has depended upon some amount of physical technology to implement the solution. The High Resolution Rapid Refresh (HRRR) Model is an atmospheric model that may provide enough resolution to perform dynamic line rating without any hardware at all. The objective is to use this model to perform Dynamic Line Rating. This will solve two of the most pervasive problems in Dynamic Line Rating, how to instrument a transmission line hundreds of miles long and then how to predict near future ampacity sufficient for transmission operators to effectively use, This technique will use the Idaho National Laboratory site as the test location for analysis. The High Resolution Rapid Refresh model is a reliable, freely available, and well-maintained weather forecasting model for the entire United States of America. The model provides enough special resolution that additional local weather monitoring devices at location are not necessary to conduct dynamic line rating. The HRRR ratings are lower on average than the locally measured ratings which allows for an additional margin of safety. The adoption of using purely digital methods for dynamic line rating could allow for wide scale adoption of the technology with very little overhead expenditure of implementation.

17 WIND ENERGY↗
DOE OSTI2019

Coupling computational fluid dynamics with the high resolution rapid refresh model for forecasting dynamic line ratings

This study looks at forecasted dynamic line ratings in southern Idaho by using data from the High Resolution Rapid Refresh (HRRR) model for forecasted weather conditions. The HRRR model can provide accurate 18- hour forecasts with a 15-minute temporal resolution. Typical static ratings used for over head transmission lines use overly conservative assumptions for local weather conditions, such as using the maximum solar irradiance or temperature measured during the summer combined with low wind speed for an entire season. The HRRR forecast model used here has a high spatial resolution to provide local forecast conditions along the entire length of a transmission line. The area that is of interest in this study is in southern Idaho spanning a total of 15,000 square kilometers. The forecasted weather data is coupled with a computational fluid dynamics model of the wind in the region to improve the resolution to an even finer scale for resolving local convective cooling rates on each individual transmission line midpoint span. This high fidelity approach can be used to find the minimum ampacity limit across all given midpoints of a transmission line to determine the absolute minimum to be used for the line rating. The ability to increase the line rating above the conservative static approach with the forecasted weather data provides a large potential to alleviate congestion and provide data for the utility market transactions. Furthermore, this study shows that for the region of interest, using forecasted weather data coupled with CFD modeling will calculate DLR ampacity rating above static about 90% of the time, with only a small relative error in the forecasted ampacity over time.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2019

Using Computational Fluid Dynamics of Wind Simulations Coupled With Weather Data to Calculate Dynamic Line Ratings

Dynamic line rating is a technology that allows for the rating of electrical conductors to be calculated based on local weather conditions rather than using ”worst-case” assumptions of weather conditions. The static ratings are typically based on weather conditions that are conservative in nature, and thus dynamic line rating may provide room to increase the current capacity. The local weather conditions may estimate conditions more accurately near the transmission lines accounting for terrain such as nearby hills. One way to estimate the local weather conditions is through the use of computational fluid dynamics. The results of a wind field simulation can be coupled with sparsely located weather stations to provide an accurate assessment of the wind speeds along the path of the conductor. Here, the wind field simulations are calculated using a steady state Reynolds-averaged Navier-Stokes model. These results along with local solar radiance measurements can be used to provide estimates of the steady state ampacity with the standard IEEE equations. An advanced test case for this process involves performing these simulations in a complex terrain, Hells Canyon, the deepest river gorge in North America. The results show that by using weather-based sensors without considering localized wind conditions, the available ampacity may be over-predicted significantly.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2019

High current carrying and thermal conductive copper-carbon conductors

The surging demand for miniaturized compact devices has generated the need for new metal conductors with high current carrying ampacity, electric and thermal conductivity. Herein, we report carbon-metal conductors that exhibit a high breakdown current density (39% higher than copper) and electrical conductivity (e.g. 63% higher than that of copper at 363 K) in a broad temperature range. The mechanistic studies of thermal conductivity through first-principle modeling show that the multilayer graphene percolation networks efficiently decrease the electron-phonon coupling in the copper-graphene composites, even if phonon modes are activated at a high temperature. These results imply that the copper-based composites have the potential to be the next generation metal conductor with high electrical and thermal conductivity, as well as excellent current-carrying ampacity. More importantly, the developed composite can be deployed in the ink form, making it possible to be utilized by the microelectronic fabrication process.

Zhang, Wei↗
DOE OSTI2025

Plug-in Electric Vehicle Charging Response Characterization for Grid Integration: Implications for Smart Charge Management

The rapid expansion of plug-in electric vehicles (PEVs) has created a unique challenge for electrical grids due to their significant power demand. At the same time, PEVs also create a unique opportunity to ease their own burden on the power grid, as they create a growing fleet of distributed energy resources capable of providing grid services such as demand response, frequency regulation, and renewable balancing. For aggregators and grid operators to effectively integrate PEVs into grid management, it is essential to first understand and characterize how they would respond in such situations. This study examines 25 models of PEVs across 25 makes, spanning model years from 2013 to 2025, to characterize their responses to the basic controls used in vehicle-grid integration (VGI): stopping, starting, and modulating the charge rate. Each vehicle was tested in a controlled laboratory setting to evaluate its performance in response to varying the maximum allowable current via the SAE J1772 control pilot signal, as well as its response to wake-up commands outlined in SAE J1772. Results show measurable differences across vehicle makes in the accuracy, latency, and precision with which PEVs respond to changes in ampacity, as well as varying sleep and wake-up behavior. The test results show that all vehicles respond to changes in ampacity, though with varying accuracy, precision, latency, and resolution. Wake-up behavior also differs across makes and models. These findings indicate that effective grid integration strategies must account for these differences. The results provide a foundation for understanding current vehicle behavior and advancing smart-charging methods while also highlighting the need for further testing, broader standardization, and manufacturer collaboration to ensure the successful integration of PEVs into the electrical grid.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2018

Using Computational Fluid Dynamics to Assess Dynamic Line Rating in Southern Idaho

The overall goal of the study is to combine computational fluid dynamics (CFD) simulations with weather data that is collected over a 1-year long period across southern Idaho to calculate the dynamic line ratings (DLR) of several transmission lines. These ratings can be compared to the static rating assumptions to show the potential for additional current carrying capacity along transmission lines through account for additional effects of convective cooling from the wind. The region of interest is quite large, sized at 144 km by 98 km; in order to cover this large region, the CFD simulations are split into four separate regions of over 80 million computational cells each. The weather data that was collected suggest initial assumptions used to make the static ratings were vastly over predicted with regards to summer temperatures and solar irradiance. The weather data is ran through the General Line Ampacity State Solver (GLASS) tool that was developed by Idaho National Laboratory (INL) to parse large quantities of weather data across thousands of transmission midpoint spans in the region. For shorter lines, the dynamic line ratings often show large improvement over static ratings. The case study here shows over 95% of the time DLR values are above static values on the short transmission lines. However, for long lines, a conundrum occurs, where due to the large number of weather stations associated with the line, there is often a single weather station which may read local wind speeds of zero. This often defaults the line rating to be limited by natural convective cooling and does not show as much improvement over static as might be expected from the weather data if DLR calculations are used with a minimum ampacity across all midpoints. Other methods with transient state calculations should be utilized for long lines.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2020

Sensitivity Effects of High Temperature Overhead Conductors to Line Rating Variables

IEEE/CIGRE standards provide a base for overhead transmission line ratings Steady State Ampacity industry standard for Static Ratings using conservative environmental assumptions Measurement of many types of sensors provide a possibility to provide more capacity as a time varying capability Direct sensors of line temperature, tension, or sag provide critical, location specific information. Require complex transformation to determine line ampacity rating Are direct measurements sensors placed at key location(s)? Testing and careful calibration of sensors required Need to understand impact of uncertainties on sensors/measurements/ and forecasts

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2022

Forecasted Dynamic Line Ratings for Regional Transmission Lines

This report was prepared for the Wind Energy Technology Office for the FY 2022, quarter 3 deliverable. This details the use of forecasted dynamic line rating as an improvement over static rating for three transmission lines in three regions of interest. A selection of wind plants across Idaho, the Columbia River Gorge and offshore wind in the NYSERDA territory were modeled for their concurrent cooling effects for dynamic line rating. Regional transmission lines for the wind plant interconnections were determined and a CFD domain was created to determine local wind flows over the lines. A dynamic line rating for each of the lines was calculated for both weather observation data and HRRR model forecast data. The comparison of peaks in the wind power production were compared to the DLR peaks. It was determined that for shorter regional transmission lines, the effect of concurrent cooling that commonly occur with gen-tie lines were still valid. Concurrent cooling effects drop as the length of the regional transmission lines increase in distance from the wind plants. In addition, the accuracy of the forecasted ampacity to the weather observation data for ampacity was assessed. In general, the accuracy was best for the INL region with the NOAA-maintained sites. The Columbia River Gorge and Long Island sites showed similar levels of accuracy for the forecasted DLR. The accuracy levels were around 11% for the INL region, 15% for Columbia River Gorge and 7% for New York Long Island. The higher error for the Columbia Gorge region is likely due to the sparse availability of weather stations available, whereas both the INL site and Long Island are well instrumented.

24 POWER TRANSMISSION AND DISTRIBUTION↗
DOE OSTI2025

Dynamic Line Rating Models and Their Potential for a Cost‐Effective Transition to Carbon‐Neutral Power Systems

Most transmission system operators (TSOs) currently use seasonally steady-state models considering limiting weather conditions that serve as reference to compute the transmission capacity of overhead power lines. The use of dynamic line rating (DLR) models can avoid the construction of new lines, market splitting, false congestions, and the degradation of lines in a cost-effective way. DLR can also be used in the long run in grid extension and new power capacity planning. In the short run, it should be used to help operate power systems with congested lines. The operation of the power systems is planned to have the market trading into account; thus, it computes transactions hours ahead of real-time operation, using power flow forecasts affected by large errors. In the near future, within a “smart grid” environment, in real-time operation conditions, TSOs should be able to rapidly compute the capacity rating of overhead lines using DLR models and the most reliable weather information, forecasts, and line measurements, avoiding the current steady-state approach that, in many circumstances, assumes ampacities above the thermal limits of the lines. Here, this work presents a review of the line rating methodologies in several European countries and the United States. Furthermore, it presents the results of pilot projects and studies considering the application of DLR in overhead power lines, obtaining significant reductions in the congestion of internal networks and cross-border transmission lines.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2025

A cost–benefit framework to evaluate capacity upgrade options in overhead line transmission planning

This paper presents the methodology behind the new Reconductoring Economic and Financial Analysis (REFA) tool, an open-access software, used by transmission utilities to evaluate transmission capacity enhancement options. The proposed methodology is intended to be used in a new planning stage, after the capacity expansion and prior to the individual transmission project engineering, allowing capacity upgrade options (reconductoring, rebuild or voltage upgrade), and respective conductor selection, to be compared under the same economic basis. Furthermore, the REFA tool implements a methodology to rank project options and conductor types based on economic criteria, considering an approximation of the ampacity and sag constraints. Results, using 5 real transmission lines in the US, show that least-cost combinations of project and conductor types can be very diverse, which emphasizes the need for the proposed methodology and tool.

Advanced conductors↗
DOE OSTI2018

Transmission Route Engineering Analysis And Design

INL’s Transmission Route Engineering Analysis and Design [tool] (TREAD) is a tool meant for the design and routing of new transmission lines. TREAD is capable of taking an arbitrarily large amount of surface layers represented as geographical files and then using a modified version of Dijkstra’s Algorithm for finding the best path. TREAD is also capable of interacting with different weather models in order to gather weather data about the locations that are being routed to. This weather data is then used in conjunction with INL’s General Line Ampacity State Solver.

Lehmer, JacobP.↗