Synthetic Wind Generation Records for Australian Wind Farms

2020 ◽  
Author(s):  
Evgenia Titova ◽  
Rashmi Mittal
Keyword(s):  
Energy Demand ◽  
Large Scale ◽  
Power Spectra ◽  
Wind Farms ◽  
Reanalysis Data ◽  
Statistical Properties ◽  
Wind Generation ◽  
Wind Speeds ◽  
Scale Granularity ◽  
Electricity Systems

<p>In this study, we present methodology to create synthetic multi-year wind generation dataset at minute-scale granularity at the existing and future Australian wind farms. The purpose of the dataset  is to assist studies of penetration of large scale and distributed renewable generation into the electricity systems and its impact on power system security in the National Energy Market (NEM).</p><p>Synthetic historical records are based on a spatial and temporal blend of reanalysis datasets with the minute-scale wind speeds observations at Bureau of Meteorology weather station network. Strengths and weaknesses of reanalysis data are illustrated and a correction methodology discussed. A method to introduce minute-scale and sub-hourly fluctuations absent in the reanalyses records is presented. Expected statistical properties of sub-hourly fluctuations in the wind generation records are derived from the characteristics of the background atmospheric state in the vicinity of the wind farms.</p><p>The accuracy of the dataset is validated in terms of  power spectra and ramping frequencies in the simulated timeseries against existing minute-scale observations of wind generation at Australian Wind farms. The statistical properties of the observed and simulated timeseries match reasonably well, overall making the dataset suitable for the investigations of  the implications of wind ramping on energy demand and generation at the existing and foreseeable infrastructure build in the NEM.</p>

Biden backing spurs US offshore wind development

2021 ◽  
Keyword(s):  
Supply Chains ◽  
Large Scale ◽  
Wind Farms ◽  
Offshore Wind ◽  
Employment Opportunities ◽  
Content Type ◽  
Generation Capacity ◽  
New Generation ◽  
Electricity Systems

Significance Two large-scale wind farms have now received federal approval and Washington is bolstering its permitting capacity in response to a pipeline of projects now totalling more than 35 gigawatts. The emergence of offshore wind means renewables are likely to extend their already impressive domination of new generation capacity additions. Impacts System flexibility requirements will grow as a higher proportion of generation comes from variable sources. The growth of offshore wind supply chains should support substantial employment opportunities, both direct and indirect. As in Europe, US electricity systems are likely to face new grid investment and congestion challenges related to offshore wind.

scholarly journals The Kinetic Energy Budget of the Atmosphere (KEBA) model 1.0: a simple yet physical approach for estimating regional wind energy resource potentials that includes the kinetic energy removal effect by wind turbines

2020 ◽  
Vol 13 (10) ◽  
pp. 4993-5005
Author(s):  
Axel Kleidon ◽  
Lee M. Miller
Keyword(s):  
Kinetic Energy ◽  
Wind Energy ◽  
Energy Budget ◽  
Wind Turbines ◽  
Large Scale ◽  
Energy Resource ◽  
Wind Farms ◽  
Energy Yield ◽  
Wind Speeds ◽  
Kinetic Energy Budget

Abstract. With the current expansion of wind power as a renewable energy source, wind turbines increasingly extract kinetic energy from the atmosphere, thus impacting its energy resource. Here, we present a simple, physics-based model (the Kinetic Energy Budget of the Atmosphere; KEBA) to estimate wind energy resource potentials that explicitly account for this removal effect. The model is based on the regional kinetic energy budget of the atmospheric boundary layer that encloses the wind farms of a region. This budget is shaped by horizontal and vertical influx of kinetic energy from upwind regions and the free atmosphere above, as well as the energy removal by the turbines, dissipative losses due to surface friction and wakes, and downwind outflux. These terms can be formulated in a simple yet physical way, yielding analytic expressions for how wind speeds and energy yields are reduced with increasing deployment of wind turbines within a region. We show that KEBA estimates compare very well to the modelling results of a previously published study in which wind farms of different sizes and in different regions were simulated interactively with the Weather Research and Forecasting (WRF) atmospheric model. Compared to a reference case without the effect of reduced wind speeds, yields can drop by more than 50 % at scales greater than 100 km, depending on turbine spacing and the wind conditions of the region. KEBA is able to reproduce these reductions in energy yield compared to the simulated climatological means in WRF (n=36 simulations; r2=0.82). The kinetic energy flux diagnostics of KEBA show that this reduction occurs because the total yield of the simulated wind farms approaches a similar magnitude as the influx of kinetic energy. Additionally, KEBA estimates the slowing of the region's wind speeds, the associated reduction in electricity yields, and how both are due to the depletion of the horizontal influx of kinetic energy by the wind farms. This limits typical large-scale wind energy potentials to less than 1 W m−2 of surface area for wind farms with downwind lengths of more than 100 km, although this limit may be higher in windy regions. This reduction with downwind length makes these yields consistent with climate-model-based idealized simulations of large-scale wind energy resource potentials. We conclude that KEBA is a transparent and informative modelling approach to advance the scientific understanding of wind energy limits and can be used to estimate regional wind energy resource potentials that account for the depletion of wind speeds.

scholarly journals Drivers of Extreme Wind Events in Mexico for Wind Power Applications

2020 ◽  
Author(s):  
Simon Thomas ◽  
Oscar Martinez-Alvarado ◽  
Dan Drew ◽  
Hannah Bloomfield
Keyword(s):  
Gulf Of Mexico ◽  
Wind Power ◽  
Baja California ◽  
Southern Oscillation ◽  
Wind Farms ◽  
Reanalysis Data ◽  
Baja California Sur ◽  
Wind Speeds ◽  
The North ◽  
Wind Events

<p>In this talk, we investigate the causes of the strongest and weakest winds observed across Mexico and explore the consequences of these to current and future wind energy production in the country. Using 40 years of the ERA-5 atmospheric reanalysis data, we find that the strongest winds in this region are caused by cold surges, where an anticyclone moves South from the Central United States of America resulting in strong Northerly winds across the Gulf of Mexico which channel through the gap in the mountains to the South of Mexico. Other regions have different drivers for high and low wind speed events. The strongest winds across the East coast of Mexico originate from Easterly trade winds propagating across the Gulf of Mexico, whereas those in Baja California Sur are influenced by the proximity of the North Pacific High. These regions in Mexico have peak (and sustained low) wind speeds at different times of year which suggests that wind farms in different regions could compliment one another to optimise wind power generation. However, all stations but Baja California Sur see the same weather patterns associated with weak wind events, meaning that low wind power production may be unavoidable at these times. The conditions that proceed these sustained periods of strong and weak winds are explored to gain some predictability for wind power applications. The El Nino Southern Oscillation is found to influence wind speeds at some locations across Mexico at sub-seasonal time-scales.</p>

Effects of Large Scale Wind Power on Total System Variability and Operation: Case Study of Northern Ireland

2003 ◽  
Vol 27 (1) ◽  
pp. 3-20 ◽  
Author(s):  
Shashi Persaud ◽  
Brendan Fox ◽  
Damian Flynn
Keyword(s):  
Power Generation ◽  
Northern Ireland ◽  
Wind Power ◽  
Large Scale ◽  
Wind Farms ◽  
Wind Power Generation ◽  
Wind Generation ◽  
Total System ◽  
Power Capacity ◽  
Spinning Reserve

The paper simulates the potential impact of significant wind power capacity on key operational aspects of a medium-sized grid-power system, viz. generator loading levels, system reserve availability and generator ramping requirements. The measured data, from Northern Ireland, consist of three years of 1/2 hourly metered records of (i) total energy generation and (ii) five wind farms, each of 5 MW capacity. These wind power data were scaled-up to represent a 10% annual energy contribution, taking account of diversity on the specific variability of total wind power output. The wind power generation reduced the system non-wind peak-generation. This reduction equalled 20% of the installed wind power capacity. There was also a reduction in the minimum non-wind generation, which equalled 43% of the wind power capacity. The analysis also showed that the spinning-reserve requirement depended on the accuracy of forecasting wind power ahead of scheduling, i.e. on the operational mode. When wind power was predicted accurately, (i) it was possible to reduce non-wind generation without over-commitment, but, (ii) the spinning-reserve non-wind conventional generation would usually have to be increased by 25% of the wind power capacity, unless quick-start gas generation was available. However, with unpredicted wind power generation, (i) despite reductions in non-wind generation, there was frequent over-commitment of conventional generation, but (ii) usually the spinning-reserve margin could be reduced by 10% of the wind power capacity with the same degree of risk. Finally, it was shown that wind power generation did not significantly increase the ramping duty on the system. For accurately predicted and unpredicted wind power the increases were only 4% and 5% respectively.

scholarly journals Svalbard’s Mesoscale Environmental Factor Impact on the Wind Field

Atmosphere ◽  
2021 ◽  
Vol 12 (9) ◽  
pp. 1165
Author(s):  
Małgorzata Kitowska ◽  
Tomasz Petelski
Keyword(s):  
Large Scale ◽  
Sea Breeze ◽  
Reanalysis Data ◽  
Atmospheric Measurements ◽  
Atmospheric Circulation Patterns ◽  
Wind Speeds ◽  
Circulation Types ◽  
Circulation Patterns ◽  
The Difference

The mesoscale circulation along the west shore of Spitsbergen is largely controlled by the difference in temperature between the glaciers and surface sea temperatures. We describe how the mesoscale effect influences the atmospheric circulation patterns. The conducted research was based on reanalysis data, model data, and atmospheric measurements; wind data from different sources and scales were compared and analysed. We discuss the situations wherein the mesoscale effect can be identified by analysing the wind direction or its velocity. This study shows the role of the mesoscale effect on the wind in the Svalbard region. Different situations according to the atmospheric patterns taken from a catalogue of 21 circulation types for each day created for Svalbard are analysed and compared with cases of land-sea breeze type circulation for the 20-year period between 1994 and 2013. It is proved that even if it is not possible to distinguish this mesoscale effect based on the difference between local and large-scale wind directions, this factor can be observed by studying the wind speeds. It is claimed that as long as there are glaciers on Spitsbergen, there will be a mesoscale land-sea breeze type circulation controlled by the difference in air temperature over land and water.

scholarly journals Three variables are better than one: detection of european winter windstorms causing important damages

2014 ◽  
Vol 14 (4) ◽  
pp. 981-993 ◽  
Author(s):  
M.-S. Deroche ◽  
M. Choux ◽  
F. Codron ◽  
P. Yiou
Keyword(s):  
Sea Level ◽  
Large Scale ◽  
Insurance Industry ◽  
Surface Wind ◽  
Relative Vorticity ◽  
Reanalysis Data ◽  
Data Set ◽  
Sea Level Pressure ◽  
Level Pressure ◽  
Wind Speeds

Abstract. In this paper, we present a new approach for detecting potentially damaging European winter windstorms from a multi-variable perspective. European winter windstorms being usually associated with extra-tropical cyclones (ETCs), there is a coupling between the intensity of the surface wind speeds and other meso-scale and large-scale features characteristic of ETCs. Here we focus on the relative vorticity at 850 hPa and the sea level pressure anomaly, which are also used in ETC detection studies, along with the ratio of the 10 m wind speed to its 98th percentile. When analysing 10 events known by the insurance industry to have caused extreme damages, we find that they share an intense signature in each of the 3 fields. This shows that the relative vorticity and the mean sea level pressure have a predictive value of the intensity of the generated windstorms. The 10 major events are not the most intense in any of the 3 variables considered separately, but we show that the combination of the 3 variables is an efficient way of extracting these events from a reanalysis data set.

scholarly journals The Kinetic Energy Budget of the Atmosphere (KEBA) model 1.0: A simple yet physical approach for estimating regional wind energy resource potentials that includes the kinetic energy removal effect by wind turbines

2020 ◽  
Author(s):  
Axel Kleidon ◽  
Lee M. Miller
Keyword(s):  
Kinetic Energy ◽  
Wind Energy ◽  
Energy Budget ◽  
Wind Turbines ◽  
Large Scale ◽  
Energy Resource ◽  
Wind Farms ◽  
Energy Yield ◽  
Wind Speeds ◽  
Kinetic Energy Budget

Abstract. With the current expansion of wind power as a renewable energy source, wind turbines increasingly extract kinetic energy from the atmosphere, thus impacting its energy resource. Here we present a simple, physics-based model (KEBA) to estimate wind energy resource potentials that explicitly account for this removal effect. The model is based on the regional kinetic energy budget of the atmospheric boundary layer that encloses the wind farms of a region. This budget is shaped by horizontal and vertical influx of kinetic energy from upwind regions and the free atmosphere above as well as the energy removal by the turbines, dissipative losses due to surface friction and wakes, and downwind outflux. These terms can be formulated in a simple, yet physical way, yielding analytic expressions for how wind speeds and energy yields are reduced with increasing deployment of wind turbines within a region. We show that KEBA estimates compare very well to the modelling results of a previously published study in which wind farms of different sizes and in different regions were simulated interactively with the WRF atmospheric model. Compared to a reference case without the effect of reduced wind speeds, yields can drop by more than 50 % at scales greater than 100 km, depending on turbine spacing and the wind conditions of the region. KEBA is able to reproduce these reductions in energy yield compared to the simulated climatological means in WRF (n = 36 simulations; r2 = 0.822). The kinetic energy flux diagnostics of KEBA show that this reduction occurs because the total yield of the simulated wind farms approaches a similar magnitude as the influx of kinetic energy. Additionally, KEBA estimates the slowing of the region's wind speeds, the associated reduction in electricity yields, and how both are due to the depletion of the horizontal influx of kinetic energy by the wind farms. This limits typical large-scale wind energy potentials to less than 1 W m−2 of surface area for wind farms with downwind lengths of more than 100 km, although this limit may be higher in windy regions. This reduction with downwind length makes these yields consistent with GCM-based idealized simulations of large-scale wind energy resource potentials. We conclude that KEBA is a transparent and informative modelling approach to advance the scientific understanding of wind energy limits, and can be used to estimate regional wind energy resource potentials that account for the depletion of wind speeds.

scholarly journals Summer Covariability of Surface Climate for Renewable Energy across the Contiguous United States: Role of the North Atlantic Subtropical High

2018 ◽  
Vol 57 (12) ◽  
pp. 2749-2768 ◽  
Author(s):  
Kenji Doering ◽  
Scott Steinschneider
Keyword(s):  
United States ◽  
Renewable Energy ◽  
North Atlantic ◽  
Energy Demand ◽  
Large Scale ◽  
Wind Speeds ◽  
North Atlantic Subtropical High ◽  
The North ◽  
Surface Climate ◽  
The North Atlantic

AbstractThis study examines the joint spatiotemporal variability of summertime climate linked to renewable energy sources (precipitation and streamflow, wind speeds, and insolation) and energy demand drivers (temperature, relative humidity, and a heat index) across the contiguous United States (CONUS) between 1948 and 2015. Canonical correlation analysis is used to identify the primary modes of joint variability between wind speeds and precipitation and related patterns of the other hydrometeorological variables. The first two modes exhibit a pan-U.S. dipole with lobes in the eastern and central CONUS. Composite analysis shows that these modes are directly related to the displacement of the western ridge of the North Atlantic subtropical high (NASH), suggesting that a single, large-scale feature of atmospheric circulation drives much of the large-scale climate covariability related to summertime renewable energy supply and demand across the CONUS. The impacts of this climate feature on the U.S. energy system are shown more directly by examining changes in surface climate variables at existing and potential sites of renewable energy infrastructure and locations of high energy demand. Also, different phases of the NASH are related to concurrent and lagged modes of oceanic and atmospheric climate variability in the Pacific and Atlantic Ocean basins, with results suggesting that springtime climate over both oceans may provide some potential to predict summer variability in the NASH and its associated surface climate. The implications of these findings for the impacts of climate variability and change on integrated renewable energy systems over the CONUS are discussed.

Assessment of Offshore Wind Resource in China Using CFSR Data

2014 ◽  
Vol 1070-1072 ◽  
pp. 303-308
Author(s):  
Shuang Long Jin ◽  
Shuang Lei Feng ◽  
Bo Wang ◽  
Ju Hu ◽  
Zhen Qiang Ma ◽  
...  
Keyword(s):  
Wind Power ◽  
Large Scale ◽  
Wind Farms ◽  
Resource Assessment ◽  
Reanalysis Data ◽  
Offshore Wind ◽  
Ground Vegetation ◽  
Observation Data ◽  
Wind Resource Assessment ◽  
Wind Resource

The offshore wind farms have many advantages over the onshore ones: they are not affected by the terrain, ground vegetation, buildings and other landscape features, so they have stronger and steadier wind, higher wind power density, smaller turbulence intensity and other advantages. Therefore, offshore wind power becomes the developing trends of wind power industry nowadays. However, its development faces the challenge of how to assess offshore wind resources accurately. It is difficult to get accurate, long-term, large-scale measured data on sea, and the nearshore observations cannot be substitute for the offshore wind conditions directly. This paper applies the NCEP CFSR reanalysis data (combines with the WMO marine observation data) to research the offshore wind resource assessment of China. We find that CFSR reanalysis data is consistent with the observation data, and it can provide a reference for China offshore wind resource assessment. The result of China offshore wind resource distribution is obtained finally.

SHAPING OF AN AUTONOMOUS POWER SYSTEM FOR GUARANTEED POWER SUPPLY WITH THE PREDOMINANCE WIND ENERGY

2018 ◽  
pp. 28-50
Author(s):  
S. G. Ignatiev ◽  
S. V. Kiseleva
Keyword(s):  
Energy Storage ◽  
Wind Speed ◽  
Wind Energy ◽  
Wind Turbine ◽  
Wind Turbines ◽  
Energy Demand ◽  
Diesel Generator ◽  
Average Wind Speed ◽  
Wind Speeds ◽  
Average Wind

Optimization of the autonomous wind-diesel plants composition and of their power for guaranteed energy supply, despite the long history of research, the diversity of approaches and methods, is an urgent problem. In this paper, a detailed analysis of the wind energy characteristics is proposed to shape an autonomous power system for a guaranteed power supply with predominance wind energy. The analysis was carried out on the basis of wind speed measurements in the south of the European part of Russia during 8 months at different heights with a discreteness of 10 minutes. As a result, we have obtained a sequence of average daily wind speeds and the sequences constructed by arbitrary variations in the distribution of average daily wind speeds in this interval. These sequences have been used to calculate energy balances in systems (wind turbines + diesel generator + consumer with constant and limited daily energy demand) and (wind turbines + diesel generator + consumer with constant and limited daily energy demand + energy storage). In order to maximize the use of wind energy, the wind turbine integrally for the period in question is assumed to produce the required amount of energy. For the generality of consideration, we have introduced the relative values of the required energy, relative energy produced by the wind turbine and the diesel generator and relative storage capacity by normalizing them to the swept area of the wind wheel. The paper shows the effect of the average wind speed over the period on the energy characteristics of the system (wind turbine + diesel generator + consumer). It was found that the wind turbine energy produced, wind turbine energy used by the consumer, fuel consumption, and fuel economy depend (close to cubic dependence) upon the specified average wind speed. It was found that, for the same system with a limited amount of required energy and high average wind speed over the period, the wind turbines with lower generator power and smaller wind wheel radius use wind energy more efficiently than the wind turbines with higher generator power and larger wind wheel radius at less average wind speed. For the system (wind turbine + diesel generator + energy storage + consumer) with increasing average speed for a given amount of energy required, which in general is covered by the energy production of wind turbines for the period, the maximum size capacity of the storage device decreases. With decreasing the energy storage capacity, the influence of the random nature of the change in wind speed decreases, and at some values of the relative capacity, it can be neglected.

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