A5083287286- Climate variability and models
- Energy Load and Power Forecasting
- Hydrology and Drought Analysis
- demographic modeling and climate adaptation
- Image Retrieval and Classification Techniques
- Wind Energy Research and Development
- Solar Radiation and Photovoltaics
- Complex Systems and Time Series Analysis
- Computational Physics and Python Applications
- Advanced Mathematical Modeling in Engineering
- Wind and Air Flow Studies
- Water resources management and optimization
- Fire effects on ecosystems
- Meteorological Phenomena and Simulations
- Lightning and Electromagnetic Phenomena
- Neural Networks and Applications
- Science and Climate Studies
University of Patras
2011-2021
Abstract. The COST (European Cooperation in Science and Technology) Action ES0601: advances homogenization methods of climate series: an integrated approach (HOME) has executed a blind intercomparison validation study for monthly algorithms. Time series temperature precipitation were evaluated because their importance studies they represent two important types statistics (additive multiplicative). algorithms validated against realistic benchmark dataset. contains real inhomogeneous data as...
Views Icon Article contents Figures & tables Video Audio Supplementary Data Peer Review Share Twitter Facebook Reddit LinkedIn Tools Reprints and Permissions Cite Search Site Citation V. K. C. Venema, O. Mestre, E. Aguilar, I. Auer, J. A. Guijarro, P. Domonkos, G. Vertacnik, T. Szentimrey, Stepanek, Zahradnicek, Viarre, Müller-Westermeier, M. Lakatos, N. Williams, Menne, R. Lindau, D. Rasol, Rustemeier, Kolokythas, Marinova, L. Andresen, F. Acquaotta, S. Fratiannil, Cheval, Klancar,...
Abstract. The COST (European Cooperation in Science and Technology) Action ES0601: Advances homogenization methods of climate series: an integrated approach (HOME) has executed a blind intercomparison validation study for monthly algorithms. Time series temperature precipitation were evaluated because their importance studies they represent two important types statistics (additive multiplicative). algorithms validated against realistic benchmark dataset. contains real inhomogeneous data as...
Since wind energy covers an important part of the increasing electricity demands, accurate speed and direction forecasts are essential for optimal operation both farms grid. Here we present set-up optimisation a selected feed-forward neural network model in order to forecast, 24-hour ahead, at specific points three farms, using past data measured same locations. The combines k-fold cross-validation method selecting appropriate input consisted either hourly or 10-min average values, while...
Wind energy power plants are vulnerable, among others, to abrupt weather changes caused especially by thunderstorms associated with lightning activity and the accompanying severe wind gusts rapid direction changes. Due a range of damages such phenomena may cause, knowledge relationship between storm systems produced field is essential establish plant during construction operation phase as well. In first part this study, in regard farm hilly region western Greece investigated. data come from...
The significant increase of wind energy production worldwide revealed the necessity its accurate forecasting. However, this is a very complex and, despite progress made, more forecasting methods are still needed. Accurate forecasts will contribute to better power plant and grid management by solving problems related distribution storage produced electricity, maximizing thus profits investments, contributing ultimately their further enhancement. Here we present development validation selected...