Comprehensive Risk Abatement

2018 ◽  
pp. 187-210
Author(s):  
Bruce D. McLaughlin
Keyword(s):  
Wind Energy ◽  
Wind Turbine ◽  
Power Grid ◽  
Substantial Improvement ◽  
American Power ◽  
Commercial Products ◽  
Customer Support ◽  
Abatement Strategies ◽  
Abatement Strategy

Conventional Analytical and Maintenance procedures are assimilated into a Comprehensive Risk Abatement Strategy comprising Process, Objectives, Balanced Progress Methodology and Lines of Communication between process and objectives. This Comprehensive Risk Abatement Strategy (Enterprise Wellness Way) is applicable to all types of enterprise (manufacturing, service and medical). This includes the various commercial products and customer support aspects of the enterprise as well as the production assets used to generate products and services. The modern wind turbine is used to illustrate the shortcomings of contemporary risk abatement strategies. The long-term viability of wind energy for the American power grid hinges on a substantial improvement in risk abatement.

scholarly journals Inter-annual variability of wind climates and wind turbine annual energy production

2018 ◽  
Author(s):  
Sara C. Pryor ◽  
Tristan J. Shepherd ◽  
Rebecca J. Barthelmie
Keyword(s):  
Standard Deviation ◽  
Wind Energy ◽  
Wind Turbine ◽  
Energy Production ◽  
Wind Farm ◽  
Wind Farms ◽  
Wind Speeds ◽  
Annual Variability ◽  
Eastern Usa

Abstract. Inter-annual variability (IAV) of expected annual energy production (AEP) from proposed wind farms plays a key role in dictating project financing. IAV in pre-construction projected AEP and the difference in 50th and 90th percentile (P50 and P90) AEP derives in part from variability in wind climates. However, the magnitude of IAV in wind speeds at/close to wind turbine hub-heights is poorly constrained and maybe overestimated by the 6 % standard deviation of annual mean wind speeds that is widely applied within the wind energy industry. Thus there is a need for improved understanding of the long-term wind resource and the inter-annual variability therein in order to generate more robust predictions of the financial value of a wind energy project. Long-term simulations of wind speeds near typical wind turbine hub-heights over the eastern USA indicate median gross capacity factors (computed using 10-minute wind speeds close to wind turbine hub-heights and the power curve of the most common wind turbine deployed in the region) that are in good agreement with values derived from operational wind farms. The IAV of annual mean wind speeds at/near to typical wind turbine hub-heights in these simulations is lower than is implied by assuming a standard deviation of 6 %. Indeed, rather than in 9 in 10 years exhibiting AEP within 0.9 and 1.1 times the long-term mean AEP, results presented herein indicate that over 90 % of the area in the eastern USA that currently has operating wind turbines simulated AEP lies within 0.94 and 1.06 of the long-term average. Further, IAV of estimated AEP is not substantially larger than IAV in mean wind speeds. These results indicate it may be appropriate to reduce the IAV applied to pre-construction AEP estimates to account for variability in wind climates, which would decrease the cost of capital for wind farm developments.

scholarly journals Influence of the ENSO and Monsoonal Season on Long-Term Wind Energy Potential in Malaysia

Energies ◽  
2018 ◽  
Vol 11 (11) ◽  
pp. 2965 ◽  
Author(s):  
Aliashim Albani ◽  
Mohd Ibrahim ◽  
Kim Yong
Keyword(s):  
Wind Energy ◽  
Wind Turbine ◽  
El Nino ◽  
Southwest Monsoon ◽  
Capacity Factor ◽  
Wind Data ◽  
Northeast Monsoon ◽  
Energy Potential ◽  
Wind Energy Potential

This paper assesses the long-term wind energy potential at three selected sites, namely Mersing and Kijal on the east coast of peninsular Malaysia and Kudat in Sabah. The influence of the El Niño-Southern Oscillation on reanalysis and meteorological wind data was assessed using the dimensionless median absolute deviation and wavelet coherency analysis. It was found that the wind strength increases during La Niña events and decreases during El Niño events. Linear sectoral regression was used to predict the long-term wind speed based on the 35 years of extended Climate Forecast System Reanalysis data and 10 years of meteorological wind data. The long-term monthly energy production was computed based on the 1.5 MW Goldwind wind turbine power curve. The measured wind data were extrapolated to the selected wind turbine default hub height (70 m.a.s.l) by using the site-specific power law indexed. The results showed that the capacity factor is higher during the Northeast monsoon (21.32%) compared to the Southwest monsoon season (3.71%) in Mersing. Moreover, the capacity factor in Kijal is also higher during the Northeast monsoon (10.66%) than during the Southwest monsoon (5.19%). However, in Kudat the capacity factor during the Southwest monsoon (36.42%) is higher compared to the Northeast monsoon (24.61%). This is due to the tail-effect of tropical storms that occur during this season in the South China Sea and Pacific Ocean.

scholarly journals Interannual variability of wind climates and wind turbine annual energy production

2018 ◽  
Vol 3 (2) ◽  
pp. 651-665 ◽  
Author(s):  
Sara C. Pryor ◽  
Tristan J. Shepherd ◽  
Rebecca J. Barthelmie
Keyword(s):  
Wind Energy ◽  
Wind Turbine ◽  
Interannual Variability ◽  
Energy Production ◽  
Wind Farm ◽  
Wind Farms ◽  
Power Curve ◽  
Wind Speeds ◽  
Eastern Usa

Abstract. The interannual variability (IAV) of expected annual energy production (AEP) from proposed wind farms plays a key role in dictating project financing. IAV in preconstruction projected AEP and the difference in 50th and 90th percentile (P50 and P90) AEP derive in part from variability in wind climates. However, the magnitude of IAV in wind speeds at or close to wind turbine hub heights is poorly defined and may be overestimated by assuming annual mean wind speeds are Gaussian distributed with a standard deviation (σ) of 6 %, as is widely applied within the wind energy industry. There is a need for improved understanding of the long-term wind resource and the IAV therein in order to generate more robust predictions of the financial value of a wind energy project. Long-term simulations of wind speeds near typical wind turbine hub heights over the eastern USA indicate median gross capacity factors (computed using 10 min wind speeds close to wind turbine hub heights and the power curve of the most common wind turbine deployed in the region) that are in good agreement with values derived from operational wind farms. The IAV of annual mean wind speeds at or near typical wind turbine hub heights in these simulations and AEP computed using the power curve of the most commonly deployed wind turbine is lower than is implied by assuming σ=6 %. Indeed, rather than 9 out of 10 years exhibiting AEP within 0.9 and 1.1 times the long-term mean AEP as implied by assuming a Gaussian distribution with σ of 6 %, the results presented herein indicate that in over 90 % of the area in the eastern USA that currently has operating wind turbines, simulated AEP lies within 0.94 and 1.06 of the long-term average. Further, the IAV of estimated AEP is not substantially larger than IAV in mean wind speeds. These results indicate it may be appropriate to reduce the IAV applied to preconstruction AEP estimates to account for variability in wind climates, which would decrease the cost of capital for wind farm developments.

Telescopic Wind Turbines to Capture Energy at Low Wind Speeds

2009 ◽  
Author(s):  
Mustahib Imraan ◽  
Rajnish N. Sharma ◽  
Richard G. J. Flay
Keyword(s):  
Wind Speed ◽  
Wind Energy ◽  
Energy Conversion ◽  
Wind Turbine ◽  
Power Output ◽  
Wind Energy Conversion System ◽  
Wind Energy Conversion ◽  
Conversion System ◽  
Energy Conversion System

The reduction in cost of energy of wind turbines requires many technical contributions from all areas of the Wind Energy Conversion System. The variations in the wind (e.g. Diurnal, Monthly, Seasonal and Long term) as normally shown on probability density distributions directly affect the wind turbine performance. The turbine power output is also dependent upon a number of other variables, and a lot of research has been carried out to increase the power coefficient that has an upper limit of 0.593 called the Betz Limit. A possible way for improving the power output of a turbine is to control the swept area by controlling the diameter of the rotor. Ideally the wind turbine designer will use the long term mean wind speed to design and establish the rated power output of the wind energy conversion system. The stochastic nature of wind will fluctuate the power output of the turbine. Therefore to maintain the design rated power of the turbine, the telescopic wind turbine concept can be used. When the wind speed drops, the telescopic blades extend in order to maintain the power output, and when the wind speed increases, the telescopic blades retract in order to reduce the loads on the system. By telescoping the blades, the capacity factor of the wind energy conversion system is thus enhanced. The wind energy characteristic of a region in New Zealand was studied and the results show an 18% increase in annual energy production of a 10 kW wind turbine with telescopic blades.

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.

Aerodynamic Shape Influence and Optimum Thickness Distribution Analysis of Perceptive Wind Turbine Blade

2018 ◽  
Vol 7 (3) ◽  
pp. 1
Author(s):  
J. V. Muruga Lal Jeyan ◽  
Akhila Rupesh ◽  
Jency Lal
Keyword(s):  
Wind Energy ◽  
Wind Turbine ◽  
Thickness Distribution ◽  
Turbine Blades ◽  
Reduced Form ◽  
Load Factor ◽  
Strong Impact ◽  
Theory Approach ◽  
Distribution Analysis ◽  
Optimum Thickness

The aerodynamic module combines the three-dimensional nonlinear lifting surface theory approach, which provides the effective propagated incident velocity and angle of attack at the blade section separately, and a two-dimensional panel method for steady axisymmetric and non-symmetric flow has to be involved to obtain the 3D pressure and velocity distribution on the wind mill model blade. Wind mill and turbines have become an economically competitive form of efficiency and renewable work generation. In the abroad analytical studies, the wind turbine blades to be the target of technological improvements by the use of highly possible systematic , aerodynamic and design, material analysis, fabrication and testing. Wind energy is a peculiar form of reduced form of density source of power. To make wind power feasible, it is important to optimize the efficiency of converting wind energy into productivity source. Among the different aspects involved, rotor aerodynamics is a key determinant for achieving this goal. There is a tradeoff between thin airfoil and structural efficiency. Both of which have a strong impact on the cost of work generated. Hence the design and analysis process for optimum design requires determining the load factor, pressure and velocity impact and optimum thickness distribution by finding the effect of blade shape by varying thickness on the basis of both the aerodynamic output and the structural weight.

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