Very-Short-Term Probabilistic Wind Power Forecasts by Sparse Vector Autoregression

IEEE Transactions on Smart Grid - United States
doi 10.1109/tsg.2015.2424078
Full Text
Abstract

Available in full text

Date
Authors
Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Related search

Trading Wind Generation From Short-Term Probabilistic Forecasts of Wind Power

IEEE Transactions on Power Systems
Electronic EngineeringPower TechnologyElectricalEnergy Engineering
2007English

Probabilistic Short-Term Wind Power Forecasting Using Sparse Bayesian Learning and NWP

Mathematical Problems in Engineering
MathematicsEngineering
2015English

On the Use of Dual-Doppler Radar Measurements for Very Short-Term Wind Power Forecasts

Remote Sensing
EarthPlanetary Sciences
2018English

Probabilistic Upscaling and Aggregation of Wind Power Forecasts

Energy, Sustainability and Society
DevelopmentEnergy EngineeringRenewable EnergySustainabilityPower Technologythe Environment
2020English

Quantifying the Influences on Probabilistic Wind Power Forecasts

E3S Web of Conferences
EarthEnergyPlanetary SciencesEnvironmental Science
2018English

Very Short-Term Wind Power Forecasting Based on SVM-Markov

2015English

Probabilistic Forecasts of Wind Power Generation Accounting for Geographically Dispersed Information

IEEE Transactions on Smart Grid
Computer Science
2014English

Short-Term Wind Power Forecasting Using Support Vector Regression and Harmony Search Algorithm

2016English

Research on Short-Term Wind Power Forecasting by Data Mining on Historical Wind Resource

Applied Sciences (Switzerland)
InstrumentationMaterials ScienceFluid FlowEngineeringComputer Science ApplicationsProcess ChemistryTransfer ProcessesTechnology
2020English

Amanote Research

Note-taking for researchers

Follow Amanote

© 2024 Amaplex Software S.P.R.L. All rights reserved.

Privacy PolicyRefund Policy