scholarly journals Getting more with less? Why repowering onshore wind farms does not always lead to more wind power generation – A German case study

2021 ◽  
Author(s):  
Jan Frederick Unnewehr ◽  
Eddy Jalbout ◽  
Christopher Jung ◽  
Dirk Schindler ◽  
Anke Weidlich
Keyword(s):  
Power Generation ◽  
Wind Power ◽  
Wind Farms ◽  
Wind Power Generation ◽  
Onshore Wind

scholarly journals On the wake effect in wind farm power forecasting: a new data-driven approach

2020 ◽  
Vol 197 ◽  
pp. 08016
Author(s):  
Fabio Famoso ◽  
Sebastian Brusca ◽  
Antonio Galvagno ◽  
Michele Messina ◽  
Rosario Lanzafame
Keyword(s):  
Power Generation ◽  
Wind Power ◽  
Wind Farm ◽  
Wind Farms ◽  
Wind Power Generation ◽  
Physical Models ◽  
Production Forecast ◽  
Innovative Method ◽  
Power Forecasting

Wind power generation differs from other energy sources, such as thermal, solar or hydro, due to the inherent stochastic nature of wind. For this reason wind power forecasting, especially for wind farms, is a complex task that cannot be accurately solved with traditional statistical methods or needs large computational systems if physical models are used. Recently, the so-called learning approaches are considered a good compromise among the previous methods since they are able to integrate physical phenomena such as wake effects without presenting heavy computational loads. The present work deals with an innovative method to forecast wind power generation in a wind farm with a combination of GISbased methods, neural network approach and a wake physical model. This innovative method was tested with a wind farm located in Sicily (Italy), used as a case study. It consists of 30 identical wind turbines (850 kW each one), located at different heights, for an overall Power peak of 25 MW. The time series dataset consists of one year with a sampling time of 10 minutes considering wind speeds and wind directions. The output of this innovative model leaded to good results, especially for medium-term overall energy production forecast for the case study.

scholarly journals Different Models for Forecasting Wind Power Generation: Case Study

Energies ◽  
2017 ◽  
Vol 10 (12) ◽  
pp. 1976 ◽  
Author(s):  
David Barbosa de Alencar ◽  
Carolina de Mattos Affonso ◽  
Roberto Limão de Oliveira ◽  
Jorge Moya Rodríguez ◽  
Jandecy Leite ◽  
...  
Keyword(s):  
Power Generation ◽  
Wind Power ◽  
Wind Power Generation

scholarly journals Two methods for estimating limits to large-scale wind power generation

2015 ◽  
Vol 112 (36) ◽  
pp. 11169-11174 ◽  
Author(s):  
Lee M. Miller ◽  
Nathaniel A. Brunsell ◽  
David B. Mechem ◽  
Fabian Gans ◽  
Andrew J. Monaghan ◽  
...  
Keyword(s):  
Power Generation ◽  
Kinetic Energy ◽  
Wind Power ◽  
Energy Flux ◽  
Wind Turbines ◽  
Large Scale ◽  
Wind Farms ◽  
Wind Power Generation ◽  
Flux Method ◽  
Free Atmosphere

Wind turbines remove kinetic energy from the atmospheric flow, which reduces wind speeds and limits generation rates of large wind farms. These interactions can be approximated using a vertical kinetic energy (VKE) flux method, which predicts that the maximum power generation potential is 26% of the instantaneous downward transport of kinetic energy using the preturbine climatology. We compare the energy flux method to the Weather Research and Forecasting (WRF) regional atmospheric model equipped with a wind turbine parameterization over a 105 km2 region in the central United States. The WRF simulations yield a maximum generation of 1.1 We⋅m−2, whereas the VKE method predicts the time series while underestimating the maximum generation rate by about 50%. Because VKE derives the generation limit from the preturbine climatology, potential changes in the vertical kinetic energy flux from the free atmosphere are not considered. Such changes are important at night when WRF estimates are about twice the VKE value because wind turbines interact with the decoupled nocturnal low-level jet in this region. Daytime estimates agree better to 20% because the wind turbines induce comparatively small changes to the downward kinetic energy flux. This combination of downward transport limits and wind speed reductions explains why large-scale wind power generation in windy regions is limited to about 1 We⋅m−2, with VKE capturing this combination in a comparatively simple way.

Wind Data Analysis and a Case Study of Wind Power Generation in Hong Kong

2001 ◽  
Vol 25 (2) ◽  
pp. 115-123 ◽  
Author(s):  
Lin Lu ◽  
Hongxing Yang
Keyword(s):  
Power Generation ◽  
Hong Kong ◽  
Data Analysis ◽  
Wind Power ◽  
Wind Power Generation ◽  
Wind Data

scholarly journals Impacts of Integration of Wind Farms on Power System Transient Stability

2018 ◽  
Vol 8 (8) ◽  
pp. 1289 ◽  
Author(s):  
Shiwei Xia ◽  
Qian Zhang ◽  
S.T. Hussain ◽  
Baodi Hong ◽  
Weiwei Zou
Keyword(s):  
Power Generation ◽  
Wind Speed ◽  
Power System ◽  
Wind Power ◽  
Transient Stability ◽  
Wind Farms ◽  
Wind Power Generation ◽  
Wind Generation ◽  
System Operation ◽  
Power System Operation

To compensate for the ever-growing energy gap, renewable resources have undergone fast expansions worldwide in recent years, but they also result in some challenges for power system operation such as the static security and transient stability issues. In particular, as wind power generation accounts for a large share of these renewable energy and reduces the inertia of a power network, the transient stability of power systems with high-level wind generation is decreased and has attracted wide attention recently. Effectively analyzing and evaluating the impact of wind generation on power transient stability is indispensable to improve power system operation security level. In this paper, a Doubly Fed Induction Generator with a two-lumped mass wind turbine model is presented firstly to analyze impacts of wind power generation on power system transient stability. Although the influence of wind power generation on transient stability has been comprehensively studied, many other key factors such as the locations of wind farms and the wind speed driving the wind turbine are also investigated in detail. Furthermore, how to improve the transient stability by installing capacitors is also demonstrated in the paper. The IEEE 14-bus system is used to conduct these investigations by using the Power System Analysis Tool, and the time domain simulation results show that: (1) By increasing the capacity of wind farms, the system instability increases; (2) The wind farm location and wind speed can affect power system transient stability; (3) Installing capacitors will effectively improve system transient stability.

scholarly journals The Impact of Future Offshore Wind Farms on Wind Power Generation in Great Britain

Resources ◽  
2015 ◽  
Vol 4 (1) ◽  
pp. 155-171 ◽  
Author(s):  
Daniel Drew ◽  
Dirk Cannon ◽  
David Brayshaw ◽  
Janet Barlow ◽  
Phil Coker
Keyword(s):  
Power Generation ◽  
Great Britain ◽  
Wind Power ◽  
Wind Farms ◽  
Wind Power Generation ◽  
Offshore Wind ◽  
Offshore Wind Farms ◽  
The Impact
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