Maximizing Average Power Output of an Airborne Wind Energy Generator Under Parametric Uncertainties

2015 ◽  
Author(s):  
Michelle A. Kehs ◽  
Chris Vermillion ◽  
Hosam K. Fathy
Keyword(s):  
Wind Speed ◽  
Wind Energy ◽  
Power Output ◽  
Average Power ◽  
Extremum Seeking ◽  
Energy Output ◽  
Wind Speeds ◽  
Average Power Output ◽  
The Difference ◽  
Optimal Average

This paper presents a controller for maximizing the time-averaged power output from an airborne wind energy generator in uncertain wind conditions. This system’s optimal energy output often involves flying in periodic figure-8 trajectories, but the precise optimal figure-8 shape is sensitive to environmental conditions, including wind speed. The literature presents controllers that are able to adapt to uncertainties, and this work expands on the current literature by using an extremum seeking based method. Extremum seeking is particularly well-suited for this application because of its well understood stability properties. In this work, extremum seeking is used to search through a family of optimal trajectories (computed offline) that correspond to discrete wind speeds. The controller is efficient in that it only searches for the optimum trajectory over the uncertain parameter (in this paper, wind speed). Results show that the controller converges to the optimal trajectory, provided it is initialized to a stable figure-8. The speed of convergence is dependent on the difference between the initial average power output and the optimal average power output.

Evaluation of the Power Output of a Wind Turbine With a Brimmed Diffuser Shroud in Fluctuating Flows

2007 ◽  
Author(s):  
S. Roberto Gonzalez A. ◽  
Yuji Ohya ◽  
Takashi Karasudani ◽  
Shusaku Iba ◽  
Kimihiko Watanabe
Keyword(s):  
Wind Speed ◽  
Power Plant ◽  
Wind Energy ◽  
Wind Turbine ◽  
Power Output ◽  
Alternative Energy ◽  
Fossil Fuels ◽  
Research Work ◽  
Energy Output ◽  
The World

Fossil fuels have been used extensively all over the world to satisfy energy demands. However, their availability is limited and their negative impact on the environment undeniable. Due to this, the need to develop alternative energy resources was recognized a few decades ago. Among different alternatives that have been developed, wind energy appears as a promising option to be implemented in many parts of the world. Nonetheless, its development and the cost per kW are still higher than that from fossil fuels. The intermittence of its capability to produce energy and the size of the wind power plant (as compared to a coal or nuclear power plant of the same energy output) have not made its implementation easier. In order to make wind energy more competitive and attractive to investors, new energy systems are desired. Specifically, it is desired to have a higher energy output. In this study a brimmed-diffuser shroud was incorporated into a 1 kW wind turbine. The turbine was then evaluated under fluctuating wind conditions. The experiments were conducted at the large boundary wind tunnel of Kyushu University. It is shown that power output increases for a fluctuating flow as opposed to a steady flow. The turbine power output is capable of following the changes in the wind speed accurately in the range of wind speed fluctuations tested. This is shown by correlation analysis and supported by the frequency spectrum. This study is part of a larger research work aimed at evaluating a novel wind turbine design. The current results are very encouraging. Possible wind sites of wind speed average lower than the current minimum accepted values can be exploited by using a turbine like the one evaluated in this work.

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.

scholarly journals Climate Change Induced Uncertainty of Wind Energy Potential for the Azov and Black Seas Coastal Zone

2020 ◽  
Author(s):  
V. P. Evstigneev ◽  
◽  
N. A. Lemeshko ◽  
V. A. Naumova ◽  
M. P. Evstigneev ◽  
...  
Keyword(s):  
Climate Change ◽  
Wind Speed ◽  
Wind Energy ◽  
Wind Power ◽  
Black Sea ◽  
Operating Time ◽  
Energy Output ◽  
Energy Potential ◽  
Wind Energy Potential ◽  
Wind Climate

The paper deals with assessing an impact of wind climate change on the wind energy potential of the Azov and Black Sea coast region. A lower estimate of operating time for wind power installation and a potential annual energy output for the region are given for the case of Vestas V117-4.2MW. Calculation has been performed of a long-term mean wind speed for two adjacent climatic periods (1954–1983 and 1984–2013) based on data from meteorological stations of the Black and Azov Sea region. The results show a decrease in wind speed at all meteorological stations except for Novorossiysk. The wind climate change is confirmed by comparing two adjoined 30-year periods and by estimating linear trends of the mean annual wind speed for the period 1954–2013, which are negative and significant for almost all meteorological stations in the region (α = 1 %). The trend values were estimated by the nonparametric method of robust linear smoothing using the Theil – Sen function. In the present study, the uncertainty of wind energy resource induced by a gradual wind climate change is estimated for perspective planning of this branch of energy sector. Despite the observed trends in the wind regime, average wind speeds in the Azov and Black Sea region are sufficient for planning the location of wind power plants.

scholarly journals Improving Lidar-Derived Turbulence Estimates for Wind Energy

2016 ◽  
Author(s):  
Jennifer F. Newman ◽  
Andrew Clifton
Keyword(s):  
Machine Learning ◽  
Wind Speed ◽  
Wind Energy ◽  
Sonic Anemometer ◽  
Turbulence Models ◽  
Volume Averaging ◽  
Turbine Rotor ◽  
Error Reduction ◽  
Power Prediction ◽  
Wind Speeds

Abstract. Remote sensing devices such as lidars are currently being investigated as alternatives to cup anemometers on meteorological towers. Although lidars can measure mean wind speeds at heights spanning an entire turbine rotor disk and can be easily moved from one location to another, they measure different values of turbulence than an instrument on a tower. Current methods for improving lidar turbulence estimates include the use of analytical turbulence models and expensive scanning lidars. While these methods provide accurate results in a research setting, they cannot be easily applied to smaller, commercially available lidars in locations where high-resolution sonic anemometer data are not available. Thus, there is clearly a need for a turbulence error reduction model that is simpler and more easily applicable to lidars that are used in the wind energy industry. In this work, a new turbulence error reduction algorithm for lidars is described. The algorithm, L-TERRA, can be applied using only data from a stand-alone commercially available lidar and requires minimal training with meteorological tower data. The basis of L-TERRA is a series of corrections that are applied to the lidar data to mitigate errors from instrument noise, volume averaging, and variance contamination. These corrections are applied in conjunction with a trained machine-learning model to improve turbulence estimates from a vertically profiling WINDCUBE v2 lidar. L-TERRA was tested on data from three sites – two in flat terrain and one in semicomplex terrain. L-TERRA significantly reduced errors in lidar turbulence at all three sites, even when the machine-learning portion of the model was trained on one site and applied to a different site. Errors in turbulence were then related to errors in power through the use of a power prediction model for a simulated 1.5 MW turbine. L-TERRA also reduced errors in power significantly at all three sites, although moderate power errors remained for periods when the mean wind speed was close to the rated wind speed of the turbine and periods when variance contamination had a large effect on the lidar turbulence error. Future work will include the use of a lidar simulator to better understand how different factors affect lidar turbulence error and to determine how these errors can be reduced using information from a stand-alone lidar.

Ensemble-Based Data Assimilation for Wind Forecasting – Application to Wind Farm

2020 ◽  
Author(s):  
Yang-Ming Fan
Keyword(s):  
Wind Speed ◽  
Natural Gas ◽  
Data Assimilation ◽  
Wind Energy ◽  
Wind Farm ◽  
Initial Conditions ◽  
Wind Farms ◽  
Weather Conditions ◽  
Energy Output ◽  
Combining Data

<p>The purpose of this study is to develop an ensemble-based data assimilation method to accurately predict wind speed in wind farm and provide it for the use of wind energy intelligent forecasting platform. As Taiwan government aimed to increase the share of renewable energy generation to 20% by 2025, among them, the uncertain wind energy output will cause electricity company has to reserve a considerable reserve capacity when dispatching power, and it is usually high cost natural gas power generation. In view of this, we will develop wind energy intelligent forecasting platform with an error of 10% within 72 hours and expect to save hundred millions of dollars of unnecessary natural gas generators investment. Once the wind energy can be predicted more accurately, the electricity company can fully utilize the robustness and economy of smart grid supply. Therefore, the mastery of the change of wind speed is one of the key factors that can reduce the minimum error of wind energy intelligent forecasting.</p><p>There are many uncertainties in the numerical meteorological models, including errors in the initial conditions or defects in the model, which may affect the accuracy of the prediction. Since the deterministic prediction cannot fully grasp the uncertainty in the prediction process, so it is difficult to obtain all possible wind field changes. The development of ensemble-based data assimilation prediction is to make up for the weakness of deterministic prediction. With the prediction of 20 wind fields as ensemble members, it is expected to include the uncertainty of prediction, quantify the uncertainty, and integrate the wind speed observations of wind farms as well to provide the optimal prediction of wind speed for the next 72 hours. The results show that the prediction error of wind speed within 72 hours is 6% under different weather conditions (excluding typhoons), which proves that the accuracy of wind speed prediction by combining data assimilation technology and ensemble approach is better.</p>

Stochastic Dynamics of a Piezoelectric Energy Harvester Subjected to Lévy Flight Excitations

2017 ◽  
Author(s):  
Subramanian Ramakrishnan ◽  
Collin Lambrecht ◽  
Connor Edlund
Keyword(s):  
Power Output ◽  
Stochastic Dynamics ◽  
Duffing Oscillator ◽  
Average Power ◽  
Coupled System ◽  
Random Excitation ◽  
Small Scale ◽  
Vibration Energy Harvesting ◽  
Piezoelectric Energy ◽  
Average Power Output

Vibration energy harvesting seeks to exploit the energy of ambient random vibration for power generation, particularly in small scale devices. Piezoelectric transduction is often used as a conversion mechanism in harvesting and the random excitation is typically modeled as a Brownian stochastic process. However, non-Brownian excitations are of potential interest, particularly in the nonequilibrium regime of harvester dynamics. In this work, we investigate the averaged power output of a generic piezoelectric harvester driven by Brownian as well as (non-Brownian) Lévy stable excitations both in the linear and the Duffing regimes. First, a coupled system of stochastic differential equations that model the electromechanical system are presented. Numerical simulation results (based on the Euler-Maruyama scheme) that show the average power output from the system under Brownian and Lévy excitations are presented for the cases where the mechanical degree of freedom behaves as a linear as well as a Duffing oscillator. The results demonstrate that Lévy excitations result in higher expectation values of harvested power. In particular, increasing the noise intensity leads to significant increase in power output in the Levy case when compared with Brownian excitations.

Theoretical Performance Analysis of Solar Chimney Power Plant for Kota Region of Rajasthan, India

2015 ◽  
Vol 787 ◽  
pp. 157-161 ◽  
Author(s):  
Zainab Akhtar ◽  
K.V.S. Rao
Keyword(s):  
Power Plant ◽  
Solar Radiation ◽  
Power Output ◽  
Average Power ◽  
Energy Generation ◽  
Solar Chimney ◽  
Minute Interval ◽  
Average Power Output ◽  
Solar Chimney Power Plant ◽  
Theoretical Performance

A solar chimney power plant (SCPP) sometimes also called 'solar updraft tower' is a part of the solar thermal group of indirect solar conversion technologies, utilizing a combination of solar air collector and central updraft tube or chimney to generate a solar induced convective flow which drives pressure staged turbines to generate electricity. In this paper the performance of a solar chimney power plant (SCPP) is evaluated if established in the Kota region of Rajasthan in India. Kota has high intensity of solar radiation with more than 270 sunny days in a year. To investigate the theoretical performance evaluation of the solar chimney power plant in Kota region, total energy generation and average power output for every ten minute interval has been calculated on the basis of solar radiation and temperature data provided by Centre for wind energy Technology (C-WET) available for the period from June 2011-May 2012 for every ten minute interval. Subsequently day wise and month wise calculations have been performed for energy generation and power output for the year June 2011 - May 2012. Further, annual average power output of SCPP is calculated at Kota for different sets of dimensions of SCPP and assuming different values of collector efficiency. Power produced at the plant established in Kota region is compared with power output estimated by J. Schlaich by their experience gained from prototype of SCPP in Manzanares, Spain. Land area required for solar chimney power plant if installed in Kota region of Rajasthan India is calculated for 200 MW capacity plant.

Physiological Correlates of Perceived Exertion in Continuous and Intermittent Exercise with the Same Average Power Output

1972 ◽  
Vol 2 (2) ◽  
pp. 108-114 ◽  
Author(s):  
R. H. T. Edwards ◽  
A. Melcher ◽  
C. M. Hesser ◽  
O. Wigertz ◽  
L.-G. Ekelund
Keyword(s):  
Power Output ◽  
Perceived Exertion ◽  
Intermittent Exercise ◽  
Average Power ◽  
Average Power Output

scholarly journals Evaluation of wind energy potential of the state of Tamil Nadu, India based on trend analysis

2021 ◽  
Vol 49 (1) ◽  
pp. 244-251
Author(s):  
Narayanan Natarajan ◽  
S. Rehman ◽  
Nandhini Shiva ◽  
M. Vasudevan
Keyword(s):  
Wind Speed ◽  
Wind Energy ◽  
Trend Analysis ◽  
Tamil Nadu ◽  
Wind Farm ◽  
Linear Trend ◽  
Energy Output ◽  
Energy Yield ◽  
Energy Potential ◽  
Increasing Trend

An accurate estimate of wind resource assessment is essential for the identification of potential site for wind farm development. The hourly average wind speed measured at 50 m above ground level over a period of 39 years (1980-2018) from 25 locations in Tamil Nadu, India have been used in this study. The annual and seasonal wind speed trends are analyzed using linear and Mann-Kendall statistical methods. The annual energy yield, and net capacity factor are obtained for the chosen wind turbine with 2 Mega Watt rated power. As per the linear trend analysis, Chennai and Kanchipuram possess a significantly decreasing trend, while Nagercoil, Thoothukudi, and Tirunelveli show an increasing trend. Mann-Kendall trend analysis shows that cities located in the southern peninsula and in the vicinity of the coastal regions have significant potential for wind energy development. Moreover, a majority of the cities show an increasing trend in the autumn season due to the influence of the retreating monsoons which is accompanied with heavy winds. The mean wind follows an oscillating pattern throughout the year at all the locations. Based on the net annual energy output, Nagercoil, Thoothukudi and Nagapattinam are found to be the most suitable locations for wind power deployment in Tamil Nadu, followed by Cuddalore, Kumbakonam, Thanjavur and Tirunelveli.

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