scholarly journals Mutually Complementary Measure-Correlate-Predict Method for Enhanced Long-Term Wind-Resource Assessment

Mathematics ◽  
2020 ◽  
Vol 8 (10) ◽  
pp. 1795
Author(s):  
Woochul Nam ◽  
Ki-Yong Oh
Keyword(s):  
Wind Farm ◽  
Reference Data ◽  
Economic Feasibility ◽  
International Electrotechnical Commission ◽  
Short Term ◽  
Wind Speeds ◽  
Wind Potential ◽  
Wind Resource ◽  
Term Data

Evaluating the economic feasibility of wind farms via long-term wind-resource assessments is indispensable because short-term data measured at a candidate wind-farm site cannot represent the long-term wind potential. Prediction errors are significant when seasonal and year-on-year variations occur. Moreover, reliable long-term reference data with a high correlation to short-term measured data are often unavailable. This paper presents an alternative solution to predict long-term wind resources for a site exhibiting seasonal and year-on-year variations, where long-term reference data are unavailable. An analysis shows that a mutually complementary measure-correlate-predict method can be employed, because several datasets obtained over short periods are used to correct long-term wind resource data in a mutually complementary manner. Moreover, this method is useful in evaluating extreme wind speeds, which is one of the main factors affecting site compliance evaluation and the selection of a suitable wind turbine class based on the International Electrotechnical Commission standards. The analysis also shows that energy density is a more sensitive metric than wind speed for sites with seasonal and year-on-year variations because of the wide distribution of wind speeds. A case study with short-term data measured at Fujeij, Jordan, clearly identifies the factors necessary to perform the reliable and accurate assessment of long-term wind potentials.

Design and Inclusion of a Desalination System in a Floating Offshore Wind Farm

2019 ◽  
Author(s):  
Davide Miriello ◽  
Michael Walker ◽  
Loris Canizares ◽  
Aaron Smith ◽  
Dominique Roddier
Keyword(s):  
Wind Farm ◽  
Capital Expenditure ◽  
High Water ◽  
Economic Feasibility ◽  
Offshore Wind ◽  
Offshore Wind Farm ◽  
Gran Canaria ◽  
Wind Speeds ◽  
Operational Expenditure ◽  
Wind Resource

Abstract This paper investigates the techno-economic feasibility of integrating a desalination system to an offshore wind farm. The first part of the paper involves a proposal for the design of a desalination system fitted inside the WindFloat Atlantic hull. Taking into account of the power, footprint, volume and weight requirements of the desalination system, the desalination capacity is chosen to be 10,000 m3/d per platform2. A 3D model of the system is also presented. The second part of the paper focuses on the development of an economic model that gives as output the levelized cost of water (LCOW) for the studied technology. At first, a methodology to estimate capital expenditure (Capex) and operational expenditure (Opex) of an offshore desalination system with the above-mentioned characteristics is presented. Then, three locations with high wind speeds and with frequent exposure to droughts (Gran Canaria, California and South Africa) are chosen and the model is applied. Particularly interesting results are found for Gran Canaria, isolated system with favorable conditions (high electricity price, high water production cost and good offshore wind resource).

scholarly journals Wind potential assessment and optimized turbine distribution in wind farm using WAsP and WindPRO software

2020 ◽  
Vol 2 (3) ◽  
pp. 131-139
Author(s):  
Vinh Thanh Le
Keyword(s):  
Wind Farm ◽  
Offshore Wind ◽  
Wind Data ◽  
Weibull Function ◽  
Input Constraints ◽  
Short Term ◽  
Wind Potential ◽  
Wind Statistics ◽  
Scale Data

In order to develop a wind farm project, the wind potential assessment and siting wind turbine are very important. It directly impacts energy production – a huge influence on the economic efficiency of the wind farm project. So, this paper presents the method to assess wind potential and optimized turbine distribution in Vietnam's offshore wind farm site, based on data from the met mast of GIZ organization (2012 - 2017) at An Ninh Dong commune, Tuy An district, Phu Yen province. The paper presents wind statistics theory from measured data through Weibull function. Comparing the short-term and long-term wind data (from meso-scale data sources – NASA, Hydrometeorological Station ...) is done by module MCP (Measure-Correlate-Predict). Wind potential is assessed when considering the effects of elevation and terrain roughness from wind data that has been long-term adjusted through WAsP and WindPRO software. Jensen model assesses the effects of wake loss between the turbines. The method calculates the power output of the wind farm when considering the influence of turbines is presented, as well as the algorithm of optimized turbine distribution. The optimized turbine distribution is done through WindPRO software. Finally, the turbine distribution results are presented with wind potential has been assessed and the input constraints of optimization.

Prediction of Long Term Stress Rupture Data for 2124

2006 ◽  
Vol 519-521 ◽  
pp. 1041-1046 ◽  
Author(s):  
Brian Wilshire ◽  
H. Burt ◽  
N.P. Lavery
Keyword(s):  
Q Methodology ◽  
Fracture Behavior ◽  
Stress Rupture ◽  
Creep Data ◽  
Short Term ◽  
Rupture Data ◽  
Term Creep ◽  
Term Data ◽  
Short Term Creep

The standard power law approaches widely used to describe creep and creep fracture behavior have not led to theories capable of predicting long-term data. Similarly, traditional parametric methods for property rationalization also have limited predictive capabilities. In contrast, quantifying the shapes of short-term creep curves using the q methodology introduces several physically-meaningful procedures for creep data rationalization and prediction, which allow straightforward estimation of the 100,000 hour stress rupture values for the aluminum alloy, 2124.

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 A Multi-Year Examination of Gardening Experience and Fruit and Vegetable Intake During College

Nutrients ◽  
2019 ◽  
Vol 11 (9) ◽  
pp. 2088 ◽  
Author(s):  
Daniel Staub ◽  
Sarah E. Colby ◽  
Melissa D. Olfert ◽  
Kendra Kattelmann ◽  
Wenjun Zhou ◽  
...  
Keyword(s):  
Vegetable Intake ◽  
Fruit And Vegetable Intake ◽  
Farmers Markets ◽  
Fruit And Vegetable ◽  
Short Term ◽  
Second Year ◽  
Locally Grown ◽  
Term Data ◽  
Time Point

Gardening has been positively associated with fruit and vegetable (FV) consumption based on short-term studies among children, but long-term data among adolescents and young adults are lacking. This investigation sought to elucidate the association between gardening experience and FV intake among college students over a two-year period. Students (N = 593) from eight universities were assessed at the end of their freshman (Y1) and sophomore (Y2) years during the springs of 2016 and 2017, respectively. At each time point, participants completed the NCI FV Screener and questions related to gardening experience and FV-related attitudes and behaviors. Students were then categorized into four groups based on gardening experience: Gardened only during the first or second year (Y1 only and Y2 only gardeners), gardened both years (Y1+Y2 gardeners), and non-gardeners. While both Y1 only and Y1+Y2 gardeners reported significantly higher FV intake relative to non-gardeners at Y1 (2.3 ± 0.9 and 2.6 ± 0.7 versus 1.9 ± 0.6 cup equivalents (CE)/day, respectively; p < 0.01), only Y1+Y2 gardeners differed from non-gardeners at Y2 (2.4 ± 0.6 versus 1.8 ± 0.5 CE/day; p < 0.001). Additionally, Y1+Y2 gardeners reported more frequent engagement of several FV-related behaviors, including shopping at farmers’ markets, eating locally grown foods, and cooking from basic ingredients; and were five times more likely to have gardened during childhood (OR: 5.2, 95%, CI: 3.5–8.8; p < 0.001). Findings suggest that while isolated gardening experiences during college are associated with FV intake, reoccurring experience may be essential for sustained benefit.

Lurasidone and risk for metabolic syndrome: results from short- and long-term clinical studies in patients with schizophrenia

CNS Spectrums ◽  
2020 ◽  
pp. 1-11
Author(s):  
Michael Tocco ◽  
John W. Newcomer ◽  
Yongcai Mao ◽  
Andrei Pikalov ◽  
Antony Loebel
Keyword(s):  
Metabolic Syndrome ◽  
Dose Range ◽  
Dose Effect ◽  
Short Term ◽  
Open Label ◽  
Quetiapine Xr ◽  
Long Term Treatment ◽  
Short And Long Term ◽  
Term Data

Abstract Objective To assess the effects of treatment with lurasidone on risk for metabolic syndrome (MetS) in patients with schizophrenia. Methods Rates of metabolic syndrome during treatment with lurasidone (40-160 mg/d) were analyzed using pooled, short-term data from three randomized, double-blind, placebo-controlled studies (vs olanzapine and quetiapine XR); long-term data from two active-comparator-controlled studies (vs risperidone and quetiapine XR); and data from two open-label studies in which patients were switched from olanzapine or risperidone to lurasidone. Results MetS was defined based on the National Cholesterol Education Program criteria. In short-term studies, the odds of meeting criteria for MetS at week 6 LOCF (adjusted for baseline metabolic syndrome status) was similar for the lurasidone and placebo groups (OR = 1.18; [95% CI, 0.81-1.71]; P = .39), but the odds (vs placebo) were significantly greater for olanzapine (OR = 2.81; [95% CI, 1.53-5.15]; P < .001) and quetiapine (OR = 3.49; [95% CI, 1.93-6.29]; P < .0001). No dose effect was observed for lurasidone across the dose range of 40-160 mg/d. In long-term studies, the odds of MetS after 12 months of treatment was significantly higher for risperidone compared with lurasidone (OR = 2.12; 95% CI, 1.15-3.90; P = .016) and for quetiapine XR compared with lurasidone (OR = 3.92; 95% CI, 1.15-13.40; P = .029). In open-label extension studies, the rate of MetS decreased in patients switched to lurasidone after 6 weeks of treatment with olanzapine or 12 months of treatment with risperidone. Conclusion In this analysis of lurasidone clinical trials, the odds of developing metabolic syndrome were minimal during short- and long-term treatment with lurasidone (40-160 mg/d).

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