Using Regional Climate Center Data to Predict Small Wind Turbine Performance

Elmore, Andrew Curtis; Gallagher, Ron

doi:10.1061/(asce)1090-025x(2009)13:1(14)

Cited by 11 publications

(3 citation statements)

References 3 publications

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“…Furthermore, Simic et al [12] present a paper focused on SWTs potential estimation. They studied seven SWTs with rated power from 3.0 kW to 3.5 kW using an experimental wind speed dataset, while Curtis Elmore and Gallagher [13] propose an approach to predict the wind power performances using regional climate dataset. Moreover an analysis of small wind turbines with less than 10 kW of power for the installation in Croatia is presented in Ref.…”

Section: Literature Reviewmentioning

confidence: 99%

Performance and viability analysis of small wind turbines in the European Union

et al. 2014

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Nowadays, wind energy plays a key role as a sustainable source of energy and wind turbines are a relevant source of power for many countries world-wide. In such a context, this paper investigates the technical and economic feasibility of small wind turbines for five of the main European Union countries (France, Germany, Italy, Spain and The Netherlands). Ten commercial turbines with rated power from 2.5 kW to 200 kW are evaluated considering their installation and operative conditions. Several parameters most affecting wind turbine performances are evaluated and the estimation of the annual cash flows during the expected plant life-time are determined as a function of both the installation location (wind speed probability distribution, national incentive scheme and tax level) and the wind turbine characteristics (rated power curve, maintenance, installation and shipping costs). The obtained data are presented and discussed through a parametric analysis based on the Net Present Value capital budget approach, showing the conditions making these systems profitable or non-profitable and explaining the relative motivations. Moreover, the analysis outcomes are further investigated highlighting the dependence of the turbine profitability from the considered parameters, including a comparative analysis among the five analyzed European countries

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Section: Literature Reviewmentioning

confidence: 99%

Performance and viability analysis of small wind turbines in the European Union

et al. 2014

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“…Different approaches have been used to generate synthetic wind data with hourly timesteps. Kaminsky et al 7 present and compare several such methods including independent and identically distributed values [8][9][10][11][12] one-or two-step Markov chain models, [13][14][15][16] Box-Jenkins or auto-regressive (moving average) (AR(MA)) models, 17 which have been used for synthetic wind speed data, 18 and Markov chain models. 7 They pointed out that most methods lack lower frequency information, i.e., diurnal effects are typically neglected even though autocorrelation for several hours may be included.…”

Section: B Synthetic Wind Speed Data In Energy Modellingmentioning

confidence: 99%

A method for including daily patterns to synthetic wind speed data for energy systems planning: Validation in the Azores Islands

Suomalainen

Silva

Ferrão

et al. 2012

Journal of Renewable and Sustainable Energy

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A high penetration of renewable electricity generation requires an improved understanding and modelling capability of renewable energy resource dynamics. This paper develops such a capability for wind. Using historical hourly wind speed data, an enhanced methodology for modelling wind, which includes seasonal, daily, hourly, and location related factors, has been developed. The methodology uses a set of day types, evaluating their frequency in real wind data, to generate hourly synthetic wind speed data, which is critical to designing a high wind penetration energy system. The methodology is applied to three different locations and the results compared to a commonly used method for synthetic wind speed data. It is concluded that the new method constitutes an important advance in simulating the occurrence of different types of wind days, which is particularly relevant in energy systems planning, especially in evaluating the frequency and scale of surpluses and shortages of wind power, and the necessity for and dimensioning of a storage system. V C 2012 American Institute of Physics.

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“…The power generated by wind turbines depends on wind speeds. Research to improve the effectiveness of converting wind flow to power has shown that wind turbine performance can be improved by analyzing wind velocity data [2], or by refinement of operating curves of wind turbines due to atmospheric environment [3].…”

Section: Introductionmentioning

confidence: 99%

Reliability Based Maintenance Planning of Wind Turbine Using Bond Graph

Mo¹,

Chan²

2017

ujme

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Wind power generation is an effective form of clean, renewable energy which operates both on land and offshore. The primary means of converting wind to power is by wind turbines. The issue with wind turbines is high uncertainty of operating environment resulting in low life cycle reliability. Frequent breakdown failures resulting in reactive maintenance is costly which results in downtime and loss of production. FMEA has been used in some cases to develop maintenance schedule but the effect is minimal. This paper investigates a new method of determining faults from adverse operating conditions by bond graph model and combines with the concept of failure mode and effects analysis to simulate the effects of maintenance strategies on the mean time to failure of wind turbine components. The mean time to failure data can then be used to refine the maintenance task with additional inspections and replacements that can prevent breakdown failures and maximize the utilization rate of expensive components.

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Using Regional Climate Center Data to Predict Small Wind Turbine Performance

Cited by 11 publications

References 3 publications

Performance and viability analysis of small wind turbines in the European Union

Performance and viability analysis of small wind turbines in the European Union

A method for including daily patterns to synthetic wind speed data for energy systems planning: Validation in the Azores Islands

Reliability Based Maintenance Planning of Wind Turbine Using Bond Graph

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