Browse
Submit Data
Databases
API
Help

Dataset Information

34 Views

0 Connections

0 Citations

0 Reanalyses

0 Downloads

Omics score: 0

Saturation wind power potential and its implications for wind energy.

ABSTRACT: Wind turbines convert kinetic to electrical energy, which returns to the atmosphere as heat to regenerate some potential and kinetic energy. As the number of wind turbines increases over large geographic regions, power extraction first increases linearly, but then converges to a saturation potential not identified previously from physical principles or turbine properties. These saturation potentials are >250 terawatts (TW) at 100 m globally, approximately 80 TW at 100 m over land plus coastal ocean outside Antarctica, and approximately 380 TW at 10 km in the jet streams. Thus, there is no fundamental barrier to obtaining half (approximately 5.75 TW) or several times the world's all-purpose power from wind in a 2030 clean-energy economy.

SUBMITTER: Jacobson MZ

PROVIDER: S-EPMC3465402 | biostudies-literature | 2012 Sep

REPOSITORIES: biostudies-literature

ACCESS DATA

Json Xml

Publications

Saturation wind power potential and its implications for wind energy.

Jacobson Mark Z MZ Archer Cristina L CL

Proceedings of the National Academy of Sciences of the United States of America 20120910 39

Wind turbines convert kinetic to electrical energy, which returns to the atmosphere as heat to regenerate some potential and kinetic energy. As the number of wind turbines increases over large geographic regions, power extraction first increases linearly, but then converges to a saturation potential not identified previously from physical principles or turbine properties. These saturation potentials are >250 terawatts (TW) at 100 m globally, approximately 80 TW at 100 m over land plus coastal oc ...[more]

PMID: 23019353

Similar Datasets

Wind energy potential assessment based on wind speed, its direction and power data.

Project description:Based on wind speed, direction and power data, an assessment method of wind energy potential using finite mixture statistical distributions is proposed. Considering the correlation existing and the effect between wind speed and direction, the angular-linear modeling approach is adopted to construct the joint probability density function of wind speed and direction. For modeling the distribution of wind power density and estimating model parameters of null or low wind speed and multimodal wind speed data, based on expectation-maximization algorithm, a two-component three-parameter Weibull mixture distribution is chosen as wind speed model, and a von Mises mixture distribution with nine components and six components are selected as the models of wind direction and the correlation circular variable between wind speed and direction, respectively. A comprehensive technique of model selection, which includes Akaike information criterion, Bayesian information criterion, the coefficient of determination R2 and root mean squared error, is used to select the optimal model in all candidate models. The proposed method is applied to averaged 10-min field monitoring wind data and compared with the other estimation methods and judged by the values of R2 and root mean squared error, histogram plot and wind rose diagram. The results show that the proposed method is effective and the area under study is not suitable for wide wind turbine applications, and the estimated wind energy potential would be inaccuracy without considering the influence of wind direction.

| S-EPMC8377008 | biostudies-literature

India's potential for integrating solar and on- and offshore wind power into its energy system.

Project description:This paper considers options for a future Indian power economy in which renewables, wind and solar, could meet 80% of anticipated 2040 power demand supplanting the country's current reliance on coal. Using a cost optimization model, here we show that renewables could provide a source of power cheaper or at least competitive with what could be supplied using fossil-based alternatives. The ancillary advantage would be a significant reduction in India's future power sector related emissions of CO2. Using a model in which prices for wind turbines and solar PV systems are assumed to continue their current decreasing trend, we conclude that an investment in renewables at a level consistent with meeting 80% of projected 2040 power demand could result in a reduction of 85% in emissions of CO2 relative to what might be expected if the power sector were to continue its current coal dominated trajectory.

| S-EPMC7505833 | biostudies-literature

Accelerating deployment of offshore wind energy alter wind climate and reduce future power generation potentials.

Project description:The European Union has set ambitious CO2 reduction targets, stimulating renewable energy production and accelerating deployment of offshore wind energy in northern European waters, mainly the North Sea. With increasing size and clustering, offshore wind farms (OWFs) wake effects, which alter wind conditions and decrease the power generation efficiency of wind farms downwind become more important. We use a high-resolution regional climate model with implemented wind farm parameterizations to explore offshore wind energy production limits in the North Sea. We simulate near future wind farm scenarios considering existing and planned OWFs in the North Sea and assess power generation losses and wind variations due to wind farm wake. The annual mean wind speed deficit within a wind farm can reach 2-2.5 ms-1 depending on the wind farm geometry. The mean deficit, which decreases with distance, can extend 35-40 km downwind during prevailing southwesterly winds. Wind speed deficits are highest during spring (mainly March-April) and lowest during November-December. The large-size of wind farms and their proximity affect not only the performance of its downwind turbines but also that of neighboring downwind farms, reducing the capacity factor by 20% or more, which increases energy production costs and economic losses. We conclude that wind energy can be a limited resource in the North Sea. The limits and potentials for optimization need to be considered in climate mitigation strategies and cross-national optimization of offshore energy production plans are inevitable.

| S-EPMC8175401 | biostudies-literature

The potential wind power resource in Australia: a new perspective.

Project description:Australia's wind resource is considered to be very good, and the utilization of this renewable energy resource is increasing rapidly: wind power installed capacity increased by 35% from 2006 to 2011 and is predicted to account for over 12% of Australia's electricity generation in 2030. Due to this growth in the utilization of the wind resource and the increasing importance of wind power in Australia's energy mix, this study sets out to analyze and interpret the nature of Australia's wind resources using robust metrics of the abundance, variability and intermittency of wind power density, and analyzes the variation of these characteristics with current and potential wind turbine hub heights. We also assess the extent to which wind intermittency, on hourly or greater timescales, can potentially be mitigated by the aggregation of geographically dispersed wind farms, and in so doing, lessen the severe impact on wind power economic viability of long lulls in wind and power generated. Our results suggest that over much of Australia, areas that have high wind intermittency coincide with large expanses in which the aggregation of turbine output does not mitigate variability. These areas are also geographically remote, some are disconnected from the east coast's electricity grid and large population centers, which are factors that could decrease the potential economic viability of wind farms in these locations. However, on the eastern seaboard, even though the wind resource is weaker, it is less variable, much closer to large population centers, and there exists more potential to mitigate it's intermittency through aggregation. This study forms a necessary precursor to the analysis of the impact of large-scale circulations and oscillations on the wind resource at the mesoscale.

| S-EPMC4079217 | biostudies-literature

Endangered Atlantic Sturgeon in the New York Wind Energy Area: implications of future development in an offshore wind energy site.

Project description:Imminent development of offshore wind farms on the outer continental shelf of the United States has led to significant concerns for marine wildlife. The scarcity of empirical data regarding fish species that may utilize development sites, further compounded by the novelty of the technology and inherent difficulty of conducting offshore research, make identification and assessment of potential stressors to species of concern problematic. However, there is broad potential to mitigate putatively negative impacts to seasonal migrants during the exploration and construction phases. The goal of this study was to establish baseline information on endangered Atlantic Sturgeon in the New York Wind Energy Area (NY WEA), a future offshore development site. Passive acoustic transceivers equipped with acoustic release mechanisms were used to monitor the movements of tagged fish in the NY WEA from November 2016 through February 2018 and resulted in detections of 181 unique individuals throughout the site. Detections were highly seasonal and peaked from November through January. Conversely, fish were relatively uncommon or entirely absent during the summer months (July-September). Generalized additive models indicated that predictable transitions between coastal and offshore habitat were associated with long-term environmental cues and localized estuarine conditions, specifically the interaction between photoperiod and river temperature. These insights into the ecology of marine-resident Atlantic Sturgeon are crucial for both defining monitoring parameters and guiding threat assessments in offshore waters and represent an important initial step towards quantitatively evaluating Atlantic Sturgeon at a scale relevant to future development.

| S-EPMC6711969 | biostudies-literature

Solar and wind power data from the Chinese State Grid Renewable Energy Generation Forecasting Competition.

Project description:Accurate solar and wind generation forecasting along with high renewable energy penetration in power grids throughout the world are crucial to the days-ahead power scheduling of energy systems. It is difficult to precisely forecast on-site power generation due to the intermittency and fluctuation characteristics of solar and wind energy. Solar and wind generation data from on-site sources are beneficial for the development of data-driven forecasting models. In this paper, an open dataset consisting of data collected from on-site renewable energy stations, including six wind farms and eight solar stations in China, is provided. Over two years (2019-2020), power generation and weather-related data were collected at 15-minute intervals. The dataset was used in the Renewable Energy Generation Forecasting Competition hosted by the Chinese State Grid in 2021. The process of data collection, data processing, and potential applications are described. The use of this dataset is promising for the development of data-driven forecasting models for renewable energy generation and the optimization of electricity demand response (DR) programs for the power grid.

| S-EPMC9492786 | biostudies-literature

Surface Wind Speed Changes and Their Potential Impact on Wind Energy Resources Across China During 1961-2021.

Project description:Enabling the rational use of energy and the realization of the "dual carbon goals" across China will require systematic analysis of temporal and spatial changes in surface wind speed (SWS), determination of key factors influencing SWS, and quantification of wind energy resources. We investigated changes of SWS and their potential impact on wind energy resources using daily SWS data from meteorological observations and based on wind power density (WPD) across China during 1961-2021. The SWS changes were related to atmospheric circulation, surface friction (urbanization and vegetation changes), aerosol emissions and the replacement of observation instruments. The increase of SWS after 2015 was closely related to changes of atmospheric circulation that were reflected by changes of Asian Meridional Circulation Index, North Atlantic Oscillation, and Arctic Oscillation. Compared with the mean SWS, the extreme SWS exhibited a more obvious downward trend and earlier abrupt change. The annual mean SWS decreased by 16.80% in the last six decades, resulting in a decrease of 47.78% in wind energy potential. Regions with annual WPD more than 100 W · m-2 were mainly in western China, northeastern China, northwestern China and some coastal areas. The WPD decreased mainly in northeastern China, northern China, and some coastal areas during the last six decades; it increased mainly in western China. Regions with annual WPD more than 100 W · m-2 and robust coefficient of variation less than 0.5 are high-quality wind energy resource areas and were found mainly in western China, northern China, northeast China, and coastal areas.

| S-EPMC10424299 | biostudies-literature

The impact of energy storage on the reliability of wind and solar power in New England.

Project description:In this study, the potential of wind and solar power to reliably meet the electricity demand of New England is evaluated, as well as the role of energy storage in improving the reliability of the region's renewable energy system. Using 44 years of hourly weather data from 1980 to 2023 obtained from the NASA MERRA-2 reanalysis product, the variability of these renewable resources and their impact on the region's electricity supply and demand is investigated. With varying mixes of wind and solar resources and sufficient resources capacity to generate electricity equal to annual demand, we find that a wind-dominant system can meet approximately 73% of the region's hourly electricity demand, whereas a solar-dominant system can only meet about 69%. However, incorporating 12 h of energy storage enhances the overall reliability of a wind-dominant system to 86%. In comparison, incorporating the same amount of energy storage in a solar-dominant system results in an overall reliability of approximately 87%. Ultimately, our analysis shows that achieving 100% reliability in meeting the annual electricity demand of New England requires addressing the mismatch between electricity demand and resource availability in terms of both location and time. This can be achieved through the integration of significant amounts of energy storage and/or wind and solar resources installations capable of generating electricity that exceeds peak demand by at least 3 times.

| S-EPMC10955263 | biostudies-literature

Method for maximum power point tracking and verification by modeling a unified wind energy conversion system.

Project description:Maximum power point tracking in wind turbines is a topic that has attracted many researchers' interest; however, the studies presented are usually carried out only at the simulation level, so they lack a verification in the system through real measurements. On the other hand, the system's modeling is usually quite complex, making it challenging to meet the control objectives. There are unified models in which the system is treated in a generalized way according to various research purposes. This work presents a methodology that simplifies the unified system through a series of dynamic tests that applied to obtained a simplified model much easier to handle without sacrificing the system's dynamic richness. • An alternative approach for a unified wind energy conversion system is established by employing physical dynamic tests applied to the wind set. • A maximum power point tracking is verified by real-time measurements managed by an open-source platform. • Methodology related to electronic instrumentation and programming is described so the tests can be reproduced without much difficulty.

| S-EPMC8374303 | biostudies-literature

Wind Power Persistence Characterized by Superstatistics.

Project description:Mitigating climate change demands a transition towards renewable electricity generation, with wind power being a particularly promising technology. Long periods either of high or of low wind therefore essentially define the necessary amount of storage to balance the power system. While the general statistics of wind velocities have been studied extensively, persistence (waiting) time statistics of wind is far from well understood. Here, we investigate the statistics of both high- and low-wind persistence. We find heavy tails and explain them as a superposition of different wind conditions, requiring q-exponential distributions instead of exponential distributions. Persistent wind conditions are not necessarily caused by stationary atmospheric circulation patterns nor by recurring individual weather types but may emerge as a combination of multiple weather types and circulation patterns. This also leads to Fréchet instead of Gumbel extreme value statistics. Understanding wind persistence statistically and synoptically may help to ensure a reliable and economically feasible future energy system, which uses a high share of wind generation.

| S-EPMC6934744 | biostudies-literature

OmicsDI is part of the ELIXIR infrastructure

OmicsDI is an Elixir interoperability service. Learn more ›

Tweets

OmicsDI Databases

PRIDE
PeptideAtlas
MassIVE
JPOST Repository
Physiome Model Repository

EGA
EVA
ENA
LINCS
PAXDB
Cell Collective

MetaboLights
Metabolomics Workbench
MetabolomeExpress
GNPS
BioModels
FAIRDOMHub

ArrayExpress
dbGaP
ExpressionAtlas
GEO
NODE

Information

Databases
Help
API
Contact us
Code on GitHub
Terms of use
Submit Data