scholarly journals Wind Speed Modeling by Nested ARIMA Processes

Energies ◽  
2018 ◽  
Vol 12 (1) ◽  
pp. 69 ◽  
Author(s):  
So-Kumneth Sim ◽  
Philipp Maass ◽  
Pedro Lind

Wind speed modelling is of increasing interest, both for basic research and for applications, as, e.g., for wind turbine development and strategies to construct large wind power plants. Generally, such modelling is hampered by the non-stationary features of wind speed data that, to a large extent, reflect the turbulent dynamics in the atmosphere. We study how these features can be captured by nested ARIMA models. In this approach, wind speed fluctuations in given time windows are modelled by one stochastic process, and the parameter variation between successive windows by another one. For deriving the wind speed model, we use 20 months of data collected at the FINO1 platform at the North Sea and use a variable transformation that best maps the wind speed onto a Gaussian random variable. We find that wind speed increments can be well reproduced for up to four standard deviations. The distributions of extreme variations, however, strongly deviate from the model predictions.

2002 ◽  
Vol 124 (4) ◽  
pp. 427-431 ◽  
Author(s):  
Yih-huei Wan ◽  
Demy Bucaneg,

To evaluate short-term wind power fluctuations and their impact on electric power systems, the National Renewable Energy Laboratory, in cooperation with Enron Wind, has started a project to record output power from several large commercial wind power plants at the 1-Hertz rate. This paper presents statistical properties of the data collected so far and discusses the results of data analysis. From the available data, we can already conclude that despite the stochastic nature of wind power fluctuations, the magnitudes and rates of wind power changes caused by wind speed variations are seldom extreme, nor are they totally random. Their values are bounded in narrow ranges. Power output data also show significant spatial variations within a large wind power plant. The data also offer encouraging evidence that accurate wind power forecasting is feasible. To the utility system, large wind power plants are not really random burdens. The narrow range of power level step changes provides a lot of information with which system operators can make short-term predictions of wind power. Large swings of wind power do occur, but those infrequent large changes (caused by wind speed changes) are always related to well-defined weather events, most of which can be accurately predicted in advance.


Author(s):  
J. N. Carruthers

In July–August of three different years common surface-floating bottles were set adrift at International Station E2 (49° 27' N.—4° 42' W.). With them, various types of drag-fitted bottles were also put out. The journeys accomplished are discussed, and the striking differences as between year and year in the case of the common surface floaters, and as between the different types in the same year, are commented upon in the light of the prevailing winds. An inter-relationship of great simplicity is deduced between wind speed and the rate of travel of simple surface floating bottles up-Channel and across the North Sea from the results of experiments carried out in four different summers.


2021 ◽  
Author(s):  
Elin Andrée ◽  
Jian Su ◽  
Martin Drews ◽  
Morten Andreas Dahl Larsen ◽  
Asger Bendix Hansen ◽  
...  

<p>The potential impacts of extreme sea level events are becoming more apparent to the public and policy makers alike. As the magnitude of these events are expected to increase due to climate change, and increased coastal urbanization results in ever increasing stakes in the coastal zones, the need for risk assessments is growing too.</p><p>The physical conditions that generate extreme sea levels are highly dependent on site specific conditions, such as bathymetry, tidal regime, wind fetch and the shape of the coastline. For a low-lying country like Denmark, which consists of a peninsula and islands that partition off the semi-enclosed Baltic Sea from the North Sea, a better understanding of how the local sea level responds to wind forcing is urgently called for.</p><p>We here present a map for Denmark that shows the most efficient wind directions for generating extreme sea levels, for a total of 70 locations distributed all over the country’s coastlines. The maps are produced by conducting simulations with a high resolution, 3D-ocean model, which is used for operational storm surge modelling at the Danish Meteorological Institute. We force the model with idealized wind fields that maintain a fixed wind speed and wind direction over the entire model domain. Simulations are conducted for one wind speed and one wind direction at a time, generating ensembles of a set of wind directions for a fixed wind speed, as well as a set of wind speeds for a fixed wind direction, respectively.</p><p>For each wind direction, we find that the maximum water level at a given location increases linearly with the wind speed, and the slope values show clear spatial patterns, for example distinguishing the Danish southern North Sea coast from the central or northern North Sea Coast. The slope values are highest along the southwestern North Sea coast, where the passage of North Atlantic low pressure systems over the shallow North Sea, as well as the large tidal range, result in a much larger range of variability than in the more sheltered Inner Danish Waters. However, in our simulations the large fetch of the Baltic Sea, in combination with the funneling effect of the Danish Straits, result in almost as high water levels as along the North Sea coast.</p><p>Although the wind forcing is completely synthetic with no spatial and temporal structure of a real storm, this idealized approach allows us to systematically investigate the sea level response at the boundaries of what is physically plausible. We evaluate the results from these simulations by comparison to peak water levels from a 58 year long, high resolution ocean hindcast, with promising agreement.</p>


2014 ◽  
Vol 651-653 ◽  
pp. 1117-1122
Author(s):  
Zheng Ning Fu ◽  
Hong Wen Xie

Wind speed forecasting plays a significant role to the operation of wind power plants and power systems. An accurate forecasting on wind power can effectively relieve or avoid the negative impact of wind power plants on power systems and enhance the competition of wind power plants in electric power market. Based on a fuzzy neural network (FNN), a method of wind speed forecasting is presented in this paper. By mining historical data as the learning stylebook, the fuzzy neural network (FNN) forecasts the wind speed. The simulation results show that this method can improve the accuracy of wind speed forecasting effectively.


2020 ◽  
Author(s):  
Corinna Jensen ◽  
Jens Möller ◽  
Peter Löwe

<p>Within the “Network of experts” of the German Federal Ministry of Transport and Digital Infrastructure (BMVI), the effect of climate change on infrastructure is investigated. One aspect of this project is the future dewatering situation of the Kiel Canal (“Nord-Ostsee-Kanal” (NOK)). The Kiel Canal is one of the world’s busiest man-made waterways navigable by seagoing ships. It connects the North Sea to the Baltic Sea and can save the ships hundreds of kilometers of distance. With a total annual sum of transferred cargo of up to 100 million tons it is an economically very important transportation way. Additionally to the transportation of cargo, the canal is also used to discharge water from smaller rivers as well as drainage of a catchments area of about 1500 km².</p><p>The canal can only operate in a certain water level range. If its water level exceeds the maximum level, the water must be drained into the sea. In 90% of the time, the water is drained into the North Sea during time windows with low tide. If the water level outside of the canal is too high, drainage is not possible and the canal traffic has to be reduced or, in extreme cases, shut down. Due to the expected sea level rise, the potential time windows for dewatering are decreasing in the future. With a decrease in operational hours, there will be substantial economic losses as well as an increase in traffic around Denmark.</p><p>To get a better understanding of what causes tense dewatering situations other than sea level rise a linkage between high water levels on the outside of the canal and weather types is made. Weather types describe large-scale circulation patterns and can therefore give an estimate on tracks of low-pressure systems as well as the prevailing winds, which can explain surges and water levels at the coast. This analysis is conducted for one weather type classification method based solely on sea level pressure fields. Weather types derived from regionally coupled climate models as well as reanalyses are investigated.</p>


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