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At least 307 records · Page 17

Seventh Annual Workshop on Meteorological and Environmental Inputs to Aviation Systems 26-28 October 1983, Tullahoma, Tennessee

A summary of reports and recommendations resulting from the Workshop on Meteorological and Environmental Inputs to Aviation Systems is presented. The Workshops have been held to characterize the interaction between aircraft and airport operators with the atmosphere, identify necessary meteorological enhancements, and establish criteria for meteorological data needed by the aviation community. The topics covered included winds and wind shear, turbulence, fog, visibility and ceiling, lightning and atmospheric electricity, icing, frost and snow, rain, ozone and acid rain. The recommendations issued included a denser meteorological network with more automated stations, the development of radar systems for icing forecasts and wind shear alerts, the accumulation of a greater data base on convective cells and lightning strikes, and further study of the impact of rain on aircraft performance.

Camp, D. W.↗

How Can Probabilistic Solar Power Forecasts Be Used to Lower Costs and Improve Reliability in Power Spot Markets? A Review and Application to Flexiramp Requirements

Net load uncertainty in electricity spot markets is rapidly growing. There are five general approaches by which system operators and market participants can use probabilistic forecasts of wind, solar, and load to help manage this uncertainty. These include operator situation awareness, resource risk hedging, reserves procurement, definition of contingencies, and explicit stochastic optimization. We review these approaches, and then provide a case study in which a method for using probabilistic solar forecasts to define needs for reserves is developed and evaluated. The case study has three parts. First, we describe building blocks for enhancing the Watt-Sun solar forecasting system to produce probabilistic irradiance and power forecasts. Second, relationships between Watt-Sun forecasts for multiple sites in California and the system's need for flexible ramp capability (flexiramp) are defined by machine learning and statistical methods. Third, the performance of present methods to defining flexiramp requirements, which are not conditioned on weather and renewables forecasts, is compared with that of probabilistic solar forecast-based requirements, using a multi-timescale production costing model with an 1820-bus representation of the WECC power system. Significant potential savings in fuel and flexiramp procurement costs from using solar-informed reserve requirements are found.

14 SOLAR ENERGY↗

Wind Fields in Category 1–3 Tropical Cyclones Are Not Fully Represented in Wind Turbine Design Standards

Abstract Offshore wind energy deployment in the U.S. is expected to increase in the years to come, with proposed wind farm sites located in regions with high risk for tropical cyclones. Yet, the wind turbine design criteria outlined by the International Electrotechnical Commission for extreme events may not account for wind field characteristics unique to tropical cyclones. To evaluate if current design standards capture the extreme conditions of these storms, we perform idealized large‐eddy simulations of three tropical cyclones (one Category 1, one Category 2, and one Category 3 storms) using the Weather Research and Forecasting model. Wind conditions near the eyewall of Cat‐1, Cat‐2, and Cat‐3 storms can exceed current design standards for offshore wind turbines. Winds at 90 m can be faster than outlined in the design criteria for Class I and Class T turbines for 50‐year recurrence periods. Wind speed shear across the turbine rotor layer is also larger than assumed in design specifications. Moreover, vertical variations in wind direction across the turbine rotor layer are large for tropical cyclones of all intensity levels, suggesting design standards should include veer, which can amplify loads in wind turbines. The existence of hurricane wind field characteristics that are not represented in design standards does not imply that damage or failure will certainly occur. Engineering safety factors incorporated in the design of the turbine's blades and structural components may prevent damage from occurring.

17 WIND ENERGY↗

Minimum Energy Routing through Interactive Techniques (MERIT) modeling

The MERIT program is designed to demonstrate the feasibility of fuel savings by airlines through improved route selection using wind observations from their own fleet. After a discussion of weather and aircraft data, manually correcting wind fields, automatic corrections to wind fields, and short-range prediction models, it is concluded that improvements in wind information are possible if a system is developed for analyzing wind observations and correcting the forecasts made by the major models. One data handling system, McIDAS, can easily collect and display wind observations and model forecasts. Changing the wind forecasts beyond the time of the most recent observations is more difficult; an Australian Mesoscale Model was tested with promising but not definitive results.

Wylie, Donald P.↗

The Significance of Water Vapor Isotopes in Improving Weather Prediction

Water vapor isotopes carry the integrated history of evaporation, condensation, mixing, and transport. Although previous studies have shown potential to improve forecasts under controlled conditions, real-world applications have been limited by systematic biases in both models and satellite retrievals arising from sparse measurements in the free troposphere. Here we assimilate mid‑tropospheric δD retrievals (peak sensitivity ~4.2 km) from the Infrared Atmospheric Sounding Interferometer into the Isotope‑incorporated Global Spectral Model and evaluate the added value beyond co‑assimilated temperature and specific humidity with identical spatial and temporal coverage. Assimilating δD improves 0–120 h forecasts of wind, temperature, specific humidity, and geopotential height, with the largest gains in the midlatitudes; heavy‑precipitation skill also increases for thresholds >3 mm per 6 h. Demonstrated in a coarse‑resolution configuration with limited observations, the results indicate that isotopic information strengthens transport tracking and hydrological constraints, motivating evaluation in operational high‑resolution forecasting systems.

Hydrology↗

Wind and Weather Variability within the Californian Offshore Wind Energy Areas

Weather variability over the Northeast Pacific (NEP) region and its influence on wind resources within the Californian offshore wind energy areas (WEAs) at Humboldt and Morro Bay are characterized using 20-years reanalysis model and satellite data. The hub-height (180 m) winds at both locations are predominantly northwesterly driven by the NEP high pressure system, with strong coastal gradients in surface pressure, fluxes, planetary boundary layer (PBL) depths and cloudiness. These sharp coastal gradients and strong annual cycles of temperature and moisture advections pose potential challenges in accurately modeling the local wind resource. Hub-height wind speeds and power capacity factors significantly vary for different regimes of PBL depths, surface fluxes and rain area fractions. This highlights the importance of studying the physical mechanisms driving these weather regimes, hence our analysis of how large-scale NEP weather variability drives the local meteorology at the WEAs. Furthermore, at both WEAs, PBL tops and cloud boundaries intersect the rotor layer (80-280 m) more than 30% and 20% of the time, respectively. While PBL depths significantly modulates hub-height winds and power, cloud boundaries do not have a similar impact, likely due to reanalysis errors in simulating cloud boundaries accurately. These findings underscore the challenges in deploying tall wind turbines in shallow cloudy boundary layers, where the interaction between clouds, precipitation, and atmospheric layers can impact turbine efficiency. As turbines grow taller and are deployed in more complex meteorological conditions, understanding these interactions is crucial for improving wind power forecasting and optimizing energy production in coastal regions.

17 WIND ENERGY↗

Decentralized wind uncertainty management: Alternating direction method of multipliers based distributionally-robust chance constrained optimal power flow

How to manage wind power uncertainty in system operation is an urgent and important issue, especially under substantially increasing penetration levels of wind generation in electric power systems. With increasing numbers of wind power plants (WPPs) integrated into power systems, their variability and uncertain power outputs become a challenge to maintaining system reliability. Traditional stochastic optimization-based models face the curse of dimensionality when the number of WPPs increases. This paper proposes a novel decentralized wind power uncertainty management model. In this model, conventional generators optimize their power capacity output and their participation to mitigate wind power uncertainty locally with only limited information exchange with the system operators. First, a distributionally-robust chance-constrained optimal power flow (DRCC-OPF) model is deployed to schedule the generation and reserve considering the wind power forecast uncertainty. Then, the alternating direction method of multipliers (ADMM) is used to reformulate the DRCC-OPF model into the distributed optimization model for each conventional generator and WPP. The tests on a small PJM 5-bus system and the IEEE 118-bus system demonstrate that the proposed decentralized model can increase the operation reliability without sacrificing system operating cost, especially when the wind power penetration levels are high. Using the proposed model, the optimal solutions can be obtained within one minute, for all studied cases, which verifies the computation efficiency of the proposed decentralized model. Furthermore, considering a large number of WPPs integrated into the system, the proposed decentralized method obtains a lower operating cost within one minute which demonstrates its efficiency to deal with high dimension of uncertainties.

17 WIND ENERGY↗

The influence of tropical wind data on the analysis and forecasts of the GLAS GCM for the Global Weather Experiment

Several densities of tropical divergent wind data were included in a fourth-order GCM to examine the effects on the accuracy of the model predictions. The experiments covered assimilation of all available tropical wind data, no tropical wind data between 20 deg N and 20 deg S, only westerly tropical wind data and only easterly tropical wind data. The predictions were all made for the 200 mb upper troposphere. Elimination of tropical data produced excessively strong upper tropospheric westerlies which in turn amplified the globally integrated rotational flow kinetic energy by around 10 percent and doubled the global divergent flow kinetic energy. Retaining only easterly wind data, ameliorated most of the error. Inclusion of all the tropical wind data however, did not lead to overall positive effects, as the data were linked to tropical wave energetics and ageostrophic winds which were already assimilated in the model.

Paegle, J.↗

Simulated wind farm wake sensitivity to configuration choices in the Weather Research and Forecasting model version 3.8.1

Wakes from wind farms can extend over 50 km downwind in stably stratified conditions. These wakes can undermine power production at downwind turbines, adversely impacting revenue. As such, wind farm wake impacts must be considered in wind resource assessments, especially in regions of dense wind farm development. The open-source Weather Research and Forecasting (WRF) numerical weather prediction model includes a wind farm parameterization to estimate wind farm wake effects, but model configuration choices can influence the resulting predictions of wind farm wakes. These choices include vertical resolution, horizontal resolution, and whether or not to include the addition of turbulent kinetic energy generated by the rotating wind turbines. Despite the sensitivity to model configuration, no clear guidance currently exists for these options. Here we compare simulated wind farm wakes produced by varying model configurations with meteorological observations near a land-based wind farm in flat terrain over several diurnal cycles. A WRF configuration comprised of horizontal resolutions of 3 km or 1 km paired with a vertical resolution of 10 m provides the most accurate representation of wind farm wake effects, such as the correct surface warming and elevated wind speed deficit. The inclusion of turbine-generated turbulence is also critical to produce accurate surface warming and should not be omitted.

17 WIND ENERGY↗

Case study of a bore wind-ramp event from lidar measurements and HRRR simulations over ARM Southern Great Plains

The rapid change of wind speed and direction on 21 August 2017 is studied using Doppler lidar measurements at five sites of the Atmospheric Radiation Measurement (ARM) Southern Great Plains (SGP) facility in north-central Oklahoma. The Doppler lidar data were investigated along with meteorological variables such as temperature, humidity, and turbulence available from the large suite of instrumentation deployed at the SGP Central Facility (C1) during the Land-Atmosphere Feedback Experiment in August 2017. Lidar measurements at five sites, separated by 55-70 km, allowed us to document the development and evolution of the wind flow over the SGP area, examine synoptic conditions to understand the mechanism that leads to the ramp event, and estimate the ability of the High-Resolution Rapid Refresh model to reproduce this event. The flow feature in question is an atmospheric bore, a small-scale phenomenon that is challenging to represent in models, that was generated by a thunderstorm outflow northwest of the ARM SGP area. The small-scale nature of bores, its impact on power generation, and the modeling challenges associated with representing bores are discussed in this paper. In conclusion, the results also provide information about model errors between sites of different surface and vegetation types.

54 ENVIRONMENTAL SCIENCES↗

Operational wind plants increase planetary boundary layer height: an observational study

As wind energy deployment grows, interactions between wind plants and the surrounding environment become more prevalent. The current investigation seeks to understand these interactions by characterizing the impact of wind plants on the planetary boundary layer height (PBLH), utilizing observations from the American WAKE experimeNt (AWAKEN) campaign. Given the ambiguity of the definition of PBLH under stable atmospheric conditions, where the impact of wind plants is expected to be strongest, a comparison of different methods for identifying PBLH is first conducted using data collected by multiple types of instruments. The Heffter method is selected as the thermodynamic method because it generates the most consistent results for the radiosonde and infrared spectrometer. A minimum vertical velocity variance method is used for a turbulence-based definition. Using both of these methods, the values of PBLH measured at spatially distributed sites are compared under a range of atmospheric conditions. Both methods show a clear increase in PBLH downstream of a wind plant for stable conditions. These impacts are strongest when the upstream PBLH is shallow (less than 0.25 km), with the thermodynamic method showing a PBLH increase of 35 %–39 % and the turbulence-based method showing a 143 % increase. At a site 20 km downstream of the wind plant, these effects are no longer observed, suggesting PBLH is not influenced by the wind plant at this distance. The results of this investigation show that wind plants can modify PBLH in their vicinity. As PBLH is a key parameter for numerical models, this insight into wind plant–atmosphere interactions can be used to validate and improve the accuracy of wind energy forecasts.

17 WIND ENERGY↗

Analysis of Rapidly Developing Low Cloud Ceilings in a Stable Environment

This report describes the work done by the Applied Meteorology Unit (AMU) in developing a database of days that experienced rapid (< 90 minutes) low cloud formation in a stable atmosphere, resulting in ceilings at the Shuttle Landing Facility (TTS) that violated Space Shuttle Flight Rules (FR). The meteorological conditions favoring the rapid formation of low ceilings include the presence of any inversion below 8000 ft, high relative humidity beneath the inversion, and a clockwise turning of the winds from the surface to the middle troposphere (approx. 15000 ft). The AMU compared and contrasted the atmospheric and thermodynamic conditions between days with rapid low ceiling formation and days with low ceiling resulting from other mechanism. The AMU found that the vertical wind profile is the probable discerning factor between the rapidly-forming ceiling days and other low ceiling days at TTS. Most rapidly-developing low ceiling days had a clockwise turning of the winds with height, whereas other low ceiling days typically had a counter-clockwise turning of the winds with height or negligible vertical wind shear. Forecasters at the Space Meteorology Group (SMG) issue 30 to 90 minute forecasts for low cloud ceilings at TTS to support Space Shuttle landings. Mission verification statistics have shown ceilings to be the number one forecast challenge. More specifically, forecasters at SMG are concerned with any rapidly developing clouds ceilings below 8000 ft in a stable, capped thermodynamic environment, Therefore, the AMU was tasked to examine archived events of rapid stable cloud formation resulting in ceilings below 8000 ft, and document the atmospheric regimes favoring this type of cloud development. The AMU examined the cool season months of November to March during the years of 1993-2003 for days that had low-level inversions and rapid, stable low cloud formation that resulted in ceilings violating the Space Shuttle FR. The AMU wrote and modified existing code to identify inversions from the morning Cape Canaveral, FL rawinsonde (XMR) during the cool season and output pertinent sounding information. They parsed all days with cloud ceilings below 8000 ft at TTS, forming a database of possible rapidly-developing low ceiling events. Days with precipitation or noticeable fog bum-off situations were excluded from the database. Only the daytime hours were examined for possible ceiling development events since low clouds are easier to diagnose with visible satellite imagery. Follow-on work would expand the database to include nighttime cases, using a special enhancement of the infrared imagery for identifying areas of low clouds. The report presents two sample cases of rapidly-developing low cloud ceilings. These cases depict the representative meteorological and thermodynamic characteristics of such events. The cases also illustrate how quickly the cloud decks can develop, sometimes forming in 30 minutes or less. The report also summarizes the composite meteorological conditions for 20 event days with rapid low cloud ceiling formation and 48 non-events days consisting of advection or widespread low cloud ceilings. The meteorological conditions were quite similar for both the event and non-event days, since both types of days experienced low cloud ceilings. Both types of days had a relatively moist environment beneath the inversion based below 8000 ft. In the 20 events identified, de onset of low ceilings occurred between 1200-1800 UTC in every instance. The distinguishing factor between the event and non-event days appears to be the vertical wind profile in the XMR sounding. Eighty-five percent of the event days had a clockwise turning of the winds with height in the lower to middle troposphere whereas 83% of the non-events had a counter-clockwise turning of the winds with height or negligible vertical wind shear. A clockwise turning of the winds with height indicates a warm advection regime, which supports large-scale rising motn and possible cloud formation. Meanwhile, a counter-clockwise turning of the winds with height indicates cold advection or sinking motion in a post-cold frontal environment.

Wheeler, Mark M.↗

Robust Scheduling of Microgrids Considering Unintentional Islanding Conditions

This paper proposes a robust scheduling model for microgrids considering the stochastic unintentional islanding conditions. The proposed model minimizes the total operating cost of the microgrid by efficiently coordinating the supply of power from local distributed energy resources and the main grid. To capture the prevailing uncertainties in renewable generation and demand as well as unintentional islanding conditions, a two-stage adaptive robust optimization model is formulated to minimize the total operating cost under the worst realization of the modeled uncertainties. The column and constraint generation (C&CG) method is used to solve the problem in an iterative manner. The solution of the proposed scheduling model ensures robust microgrid operation in consideration of all possible realization of renewable generation, demand and unintentional islanding condition. Numerical simulations on a microgrid consisting of a wind turbine, a PV panel, a fuel cell, two micro-turbines, a diesel generator and a battery demonstrate the effectiveness of the proposed approach.

Liu, Guodong↗

Impact of Uncertainty from Load-Based Reserves and Renewables on Dispatch Costs and Emissions

Aggregations of controllable loads are considered to be a fast-responding, cost-efficient, and environmental-friendly candidate for power system ancillary services. Unlike conventional service providers, the potential capacity from the aggregation is highly affected by factors like ambient conditions and load usage patterns. Previous work modeled aggregations of controllable loads (such as air conditioners) as thermal batteries, which are capable of providing reserves but with uncertain capacity. A stochastic optimal power flow problem was formulated to manage this uncertainty, as well as uncertainty in renewable generation. In this paper, we explore how the types and levels of uncertainty, generation reserve costs, and controllable load capacity affect the dispatch solution, operational costs, and CO2 emissions. We also compare the results of two methods for solving the stochastic optimization problem, namely the probabilistically robust method and analytical reformulation assuming Gaussian distributions. Case studies are conducted on a modified IEEE 9-bus system with renewables, controllable loads, and congestion. We find that different types and levels of uncertainty have significant impacts on dispatch and emissions. More controllable loads and less conservative solution methodologies lead to lower costs and emissions.

24 POWER TRANSMISSION AND DISTRIBUTION↗

WindView [SWR-18-51]

The National Laboratory of the Rockies (NLR) FKA: National Renewable Energy Laboratory (NREL) and Argonne National Laboratory (ANL) developed an open-source situational awareness and decision support platform called WindView that provides grid operators with knowledge on the state and performance of wind power on their system. University Texas Dallas is contracted by NLR to create a wind power forecaster that will be integrated into WindView. WindView does not provide any data, it is a visualization platform which requires the user to provide their own data. During the three year project, there has been collaboration with industry through technical review committees and specifically the Western Area Power Authority's, WAPA's Energy Training Power Center, EPTC to develop a production-level version of WindView which will work for industry.

Gamble, Christine↗

County-Level Climate Uncertainty for Risk Assessments: Volume 19 Appendix R - Forecast Maximum Near-Surface Wind Speed

This report uses the CMIP5 series of climate model simulations to produce country- level uncertainty distributions for use in socioeconomic risk assessments of climate change impacts. It provides appropriate probability distributions, by month, for 169 countries and autonomous-areas on temperature, precipitation, maximum temperature, maximum wind speed, humidity, runoff, soil moisture and evaporation for the historical period (1976-2005), and for decadal time periods to 2100. It also provides historical and future distributions for the Arctic region on ice concentration, ice thickness, age of ice, and ice ridging in 15-degree longitude arc segments from the Arctic Circle to 80 degrees latitude, plus two polar semicircular regions from 80 to 90 degrees latitude. The uncertainty is meant to describe the lack of knowledge rather than imprecision in the physical simulation because the emphasis is on unfalsified risk and its use to determine potential socioeconomic impacts. The full report is contained in 27 volumes.

54 ENVIRONMENTAL SCIENCES↗

Forecasts for Land-Based Wind Deployment in the United States: Wind Industry Survey Results [Slides]

Recent land-based wind deployment in the United States has been sluggish, and expectations for future growth have moderated in recent years. Berkeley Lab conducted a brief survey of wind industry stakeholders to better understand barriers and solutions. The focus of the survey was on land-based wind projects in the United States – not offshore wind or distributed small wind projects. Respondents identified challenges related to the grid and to siting as the most pressing concerns.

17 WIND ENERGY↗