Long-term simulation of the mean wind speed

Torrielli, Alessio; Repetto, Maria Pia; Solari, Giovanni

doi:10.1016/j.jweia.2011.08.003

Cited by 31 publications

(11 citation statements)

References 28 publications

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“…No unanimous agreement still exists, in the scientific community, on the probability distribution involving the best regression of the experimental data. Recent studies on different models of the extreme wind velocity statistics of long-period databases (Torrielli et al, 2011(Torrielli et al, , 2012 have suggested the use of the process analysis (Lagomarsino et al, 1992) to infer the probability distribution of the yearly maximum mean wind velocity:…”

Section: Single Point Wind Statisticsmentioning

confidence: 99%

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The wind forecast for safety management of port areas

Solari

Repetto

Burlando

et al. 2012

Journal of Wind Engineering and Industrial Aerodynamics

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111

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Section: Single Point Wind Statisticsmentioning

confidence: 99%

“…Torrielli et al (2011Torrielli et al ( , 2012) demonstrated that expressing l as a function of v gives rise to a relevant growth of the regression precision. The databases available for the present project are not long enough to perform such an analysis.…”

Section: Single Point Wind Statisticsmentioning

confidence: 99%

The wind forecast for safety management of port areas

Solari

Repetto

Burlando

et al. 2012

Journal of Wind Engineering and Industrial Aerodynamics

Self Cite

111

View full text Add to dashboard Cite

“…A similar, but more advanced technique of producing synthetic time series of wind speed has been proposed by Torrielli et al . (, , ). Their method is based on replicating the macro‐meteorological spectrum of the time series as reported in the studies by Van der Hoven (), Harris (), and Romanic et al .…”

Section: Resultsmentioning

confidence: 99%

Homogeneity analysis of wind data from 213 m high Cabauw tower

Petrović

Romanić

Ćurić

2018

Intl Journal of Climatology

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Homogeneous meteorological data are a prerequisite for reliable climatological studies. This paper investigates the homogeneity of wind data from 213 m high Cabauw tower located in The Netherlands. The wind measurements are conducted at 10, 20, 40, 80, 140 and 200 m above ground. The analysed data cover the period from February 1986 to January 1997 and from April 2000 to December 2015. This study presents the first homogeneity analysis of wind data from a tall meteorological mast. Homogeneities of wind speed and wind direction series were investigated independently using the ReDistribution Method. Overall, the wind measurements at Cabauw tower are very homogeneous. The only wind speed inhomogeneity was detected at 200 m above ground and it seems to be, at least to a certain extent, caused by the rapid expansion of the town of Lopik in the 1990s. Lopik's growth to the west, however, only influenced the east winds on the Cabauw tower. Small inhomogeneities in wind direction data were detected at 20, 40 and 80 m levels, whereas a fairly large inhomogeneity was observed at 10 m above ground. Several potential causes of inhomogeneities in wind direction data are discussed, but the major contributor could not be determined with certainty. In addition, the homogeneity of real measurements from Cabauw tower is compared against the synthetically created wind data for Cabauw tower using the Monte‐Carlo method of random sampling. The results show that the detected anomalies are not due to the random noise in the time series.

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“…The energy price P t is forecasted on the base of the historical results of the electricity market, whereas the expected production capacity Q t,iU depends on the wind speed at time t and on the technical characteristics of the generating unit iU. In particular, the wind distribution in the short time (few days ahead) is modeled using a Navier-Stokes computational system [64], whereas for longer periods the wind forecast is based on statistical models. Moreover, Support Vector Machines (SVMs) are used for statistical forecast based on historical time series [65].…”

Section: Symbol Descriptionmentioning

confidence: 99%

Encompassing Electricity Market Predictions and Weather Forecasts in Power Plan O&M Strategies

Ponta¹,

Oneto²,

Anguita³

et al. 2017

Preprint

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Abstract:The paper deals with the problem of choosing the best O&M strategy for wind power plants. Current maintenance theory considers just production opportunities and minimizes the maintenance costs, but with the liberalization of the electricity market also the electricity price has become an important variable to take into account in the O&M scheduling. Another important variables that is often neglected by the existing maintenance theory is the weather condition. This paper proposes a new strategy that takes into account the electricity price and weather conditions, improves the expected profit of the systems, and reduce the overall maintenance and logistic costs. The maintenance schedule is formalized as an optimization problem where the discounted cumulative profit of a wind generation portfolio in a fixed-time horizon (e.g. two years ahead), subject to the technologically-derived maintenance time constraints is optimized. Both the theoretical and computational aspects of the proposed O&M strategy are discussed. Results show that taking into account market and weather opportunities in the design of the maintenance strategy, it is possible to achieve a more complete scheduling for a given set of wind power plants.

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Long-term simulation of the mean wind speed

Cited by 31 publications

References 28 publications

The wind forecast for safety management of port areas

The wind forecast for safety management of port areas

Homogeneity analysis of wind data from 213 m high Cabauw tower

Encompassing Electricity Market Predictions and Weather Forecasts in Power Plan O&M Strategies

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Long-term simulation of the mean wind speed

Cited by 31 publications

References 28 publications

The wind forecast for safety management of port areas

The wind forecast for safety management of port areas

Homogeneity analysis of wind data from 213 m high Cabauw tower

Encompassing Electricity Market Predictions and Weather Forecasts in Power Plan O&amp;M Strategies

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Product

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Encompassing Electricity Market Predictions and Weather Forecasts in Power Plan O&M Strategies