A new wind speed scenario generation method based on spatiotemporal dependency structure
Published 2020 View Full Article
- Home
- Publications
- Publication Search
- Publication Details
Title
A new wind speed scenario generation method based on spatiotemporal dependency structure
Authors
Keywords
Scenario generation, Wind speed, Spatiotemporal dependence, Tail dependence, C-Vine copula
Journal
RENEWABLE ENERGY
Volume 163, Issue -, Pages 1951-1962
Publisher
Elsevier BV
Online
2020-10-30
DOI
10.1016/j.renene.2020.10.132
References
Ask authors/readers for more resources
Related references
Note: Only part of the references are listed.- Transmission and energy storage-expansion planning in the presence of correlated wind farms
- (2019) Sanaz Mahmoudi et al. International Transactions on Electrical Energy Systems
- A New Clustering Approach for Scenario Reduction in Multi-Stochastic Variable Programming
- (2019) Jinxing Hu et al. IEEE TRANSACTIONS ON POWER SYSTEMS
- Typical wind power scenario generation for multiple wind farms using conditional improved Wasserstein generative adversarial network
- (2019) Yufan Zhang et al. INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS
- Efficient scenario generation of multiple renewable power plants considering spatial and temporal correlations
- (2018) Chenghui Tang et al. APPLIED ENERGY
- Optimal integration and planning of renewable distributed generation in the power distribution networks: A review of analytical techniques
- (2018) Ali Ehsan et al. APPLIED ENERGY
- Optimal Siting of Wind Farms in Wind Energy Dominated Power Systems
- (2018) Raik Becker et al. Energies
- Generating Joint Scenarios for Renewable Generation: The Case for non-Gaussian Models with Time-Varying Parameters
- (2018) Henrique Hoeltgebaum et al. IEEE TRANSACTIONS ON POWER SYSTEMS
- Wind speed scenario generation based on dependency structure analysis
- (2018) Masoud Salehi Borujeni et al. JOURNAL OF WIND ENGINEERING AND INDUSTRIAL AERODYNAMICS
- High dimensional dependence in power systems: A review
- (2018) Edgar Nuño Martinez et al. RENEWABLE & SUSTAINABLE ENERGY REVIEWS
- Generation of Time-Coupled Wind Power Infeed Scenarios Using Pair-Copula Construction
- (2018) Raik Becker IEEE Transactions on Sustainable Energy
- Flexible wind speed generation model: Markov chain with an embedded diffusion process
- (2018) Jinrui Ma et al. ENERGY
- A scenario generation method based on the mixture vine copula and its application in the power system with wind/hydrogen production
- (2018) Yibin Qiu et al. INTERNATIONAL JOURNAL OF HYDROGEN ENERGY
- A novel method based on Weibull distribution for short-term wind speed prediction
- (2017) Orhan Kaplan et al. INTERNATIONAL JOURNAL OF HYDROGEN ENERGY
- Identification of vulnerable lines in power grids with wind power integration based on a weighted entropy analysis method
- (2017) Ruiming Fang et al. INTERNATIONAL JOURNAL OF HYDROGEN ENERGY
- Stochastic Optimal Dispatch of Power System Considering the Correlation of Multiple Wind Farm Outputs
- (2016) Hongming Yang et al. ELECTRIC POWER COMPONENTS AND SYSTEMS
- Multiple stochastic correlations modeling for microgrid reliability and economic evaluation using pair-copula function
- (2016) Shouxiang Wang et al. INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS
- The Wind Integration National Dataset (WIND) Toolkit
- (2015) Caroline Draxl et al. APPLIED ENERGY
- Spatiotemporal Modeling of Wind Generation for Optimal Energy Storage Sizing
- (2015) Hamed Valizadeh Haghi et al. IEEE Transactions on Sustainable Energy
- An Integrated Approach for Site Selection of Offshore Wind-Wave Power Production
- (2012) Yu-Hsien Lin et al. IEEE JOURNAL OF OCEANIC ENGINEERING
- A methodology to generate statistically dependent wind speed scenarios
- (2009) J.M. Morales et al. APPLIED ENERGY
Find Funding. Review Successful Grants.
Explore over 25,000 new funding opportunities and over 6,000,000 successful grants.
ExploreFind the ideal target journal for your manuscript
Explore over 38,000 international journals covering a vast array of academic fields.
Search