Uncertainty analysis of wind energy potential assessment

This study presents a framework to assess the wind resource of a wind turbine using uncertainty analysis. Firstly, probability models are proposed for the natural variability of wind resources that include air density, mean wind velocity and associated Weibull parameters, surface roughness exponent, and error for prediction of long-term wind velocity based on the Measure–Correlate–Predict method. An empirical probability model for a power performance curve is also demonstrated. Secondly, a Monte-Carlo based numerical simulation procedure which utilizes the probability models is presented. From the numerical simulation, it is found that the present method can effectively evaluate the expected annual energy production for different averaging periods and confidence intervals. The uncertainty, which is 11% corresponding to the normalized average energy production in the present example, can be calculated by specifically considering the characteristics of the individual sources in terms of probability parameters.     

Estimation of wind energy production in various sites in Australia for different wind turbine classes: A comparative technical and economic assessment

This study examines the effect of different wind turbine classes on the electricity production of wind farms in three areas of Australia, which present low, low to medium, and medium to high wind potential: Gingin, Armidale, and Gold Coast Seaway. Wind turbine classes determine the suitability of installing a wind turbine in a particulate site. Wind turbine data from six different manufacturers have been used. For each manufacturer, at lest two wind turbines with identical rated power (in the range of 1.5 MW–3 MW) and different wind turbine classes (IEC I, IEC II and/or IEC III) are compared. The results show the superiority of wind turbines that are designed for lower wind speeds (higher IEC class) in all three locations, in terms of energy production. This improvement is higher for the locations with lower and medium wind potential (Gingin and Armidale), and varies from 5% to 55%. Moreover, this study investigates the economical feasibility of a 30 MW wind farm, for all combinations of site locations and wind turbine models.     

Assessment of the wind power potential at SANAE IV base, Antarctica: a technical and economic feasibility study

This paper presents a study for the utilization of wind energy at the South African research station, SANAE IV, in Antarctica (71°40’ S 2° 50’ W). A procedure to evaluate the feasibility of utilising wind power for Antarctic stations is given. The analysis is based on the technical and economic aspects of installing and operating a wind turbine at remote locations. Special attention has been given to conditions encountered at Antarctica, like site accessibility, low temperatures, icing and snow, long transportation distances and environmental issues. The aspect of externalities is incorporated into the economic analysis. The Northern Power Systems NW100/19 wind turbine is found to be the best-suited wind turbine for use at SANAE IV, given the harsh climatic conditions, like frequent windstorms and extreme temperatures. The wind turbine features a yearly energy output of 430 MWh with a capacity factor of 0.49, at a mean wind speed of 10.8 m/s. The study shows that a wind turbine installation at SANAE IV is an attractive solution to reduce fuel consumption and therefore emissions of the diesel electric generators considerably. The use of a wind turbine at SANAE IV could lead to a savings in externalities of about R110 000, -per annum.     

Feasibility assessment of wind energy resources in Malaysia based on NWP models

There is a common belief that countries located in the doldrums with prevailing monotonous weather, characterized by light winds, cannot harness the wind for feasible energy production. This paper reexamines such a belief and presents a novel approach to assess the techno-economic potential of wind turbine generator sites in Malaysia, which lies in the equatorial, low wind speed doldrums. Dissimilar to other techniques that account for planetary-scale winds only, a numerical weather prediction (NWP) prospecting tool for mesoscale winds is used to forecast the wind characteristics. Potential sites from the forecasting studies are further investigated for economic feasibility by using a commercial wind turbine generator and a financial analysis method. From the economic analysis, it is found that unlike what is widely touted, there is an actual potential of wind energy in Malaysia, manifested through the several economically viable wind turbine generating sites.     

Shape design and numerical analysis on a 1 MW tidal current turbine for the south-western coast of Korea

The study concentrates on the shape design and numerical analysis of a 1 MW horizontal axis tidal current turbine (HATCT), which can be applied near the southwest regions of Korea. On the basis of actual tidal current conditions of south-western region of Korea, configuration design of 1 MW class turbine rotor blade is carried out by blade element momentum theory (BEMT). The hydrodynamic performance including the lift and drag forces, is conducted with the variation of the angle of attack using an open source code of X-Foil. The optimized blade geometry is used for Computational Fluid Dynamics (CFD) analysis with hexahedral numerical grids. This study focuses on developing a new hydrofoil and designing a blade with relatively shorter chord length in contrast to a typical TCT blade. Therefore, after a thorough study of two common hydrofoils, (S814 and DU-91-W2-250, which show good performance for rough conditions), a new hydrofoil, MNU26, is developed. The new hydrofoil has a 26% thickness that can be applied throughout the blade length, giving good structural strength. Power coefficient, pressure and velocity distributions are investigated according to Tip Speed Ratio by CFD analysis. As cavitation analysis is also an important part of the study, it is investigated for all the three hydrofoils. Due to the shorter chord length of the new turbine blade in contrast to a typical TCT blade design, a Fluid Structure Interaction (FSI) analysis is also done. Concrete conclusions have been made after comparing the three hydrofoils, considering their performance, efficiency, occurrence of cavitation and structural feasibility.     

Operational modal analysis of a 2.5 MW wind turbine using optical measurement techniques and strain gauges

This work presents the results of in‐field tests performed on a 2.5 MW, 80 m diameter wind turbine. During the two test campaigns, dynamic response of the structure was monitored by using three different measurement systems, namely conventional strain gauges, photogrammetry and laser interferometry, whereas the turbine was both at parked condition and rotating. The recorded data were analysed by using an operational modal analysis algorithm based on the least square complex exponential method and several turbine parameters (eigenfrequencies and damping ratios) were extracted. The obtained system parameters were then qualitatively compared with the results presented in a study from literature, which includes both aeroelastic simulations and in‐field measurements performed on a similar size and capacity wind turbine. Copyright © 2012 John Wiley & Sons, Ltd.     

On design,modelling, and analysis of a 10‐MW medium‐speed drivetrain for offshore wind turbines

The design of a medium‐speed drivetrain for the Technical University of Denmark (DTU) 10‐MW reference offshore wind turbine is presented. A four‐point support drivetrain layout that is equipped with a gearbox with two planetary stages and one parallel stage is proposed. Then, the drivetrain components are designed based on design loads and criteria that are recommended in relevant international standards. Finally, an optimized drivetrain model is obtained via an iterative design process that minimizes the weight and volume. A high‐fidelity numerical model is established via the multibody system approach. Then, the developed drivetrain model is compared with the simplified model that was proposed by DTU, and the two models agree well. In addition, a drivetrain resonance evaluation is conducted based on the Campbell diagrams and the modal energy distribution. Detailed parameters for the drivetrain design and dynamic modelling are provided to support the reproduction of the drivetrain model. A decoupled approach, which consists of global aero‐hydro‐servo‐elastic analysis and local drivetrain analysis, is used to determine the drivetrain dynamic response. The 20‐year fatigue damages of gears and bearings are calculated based on the stress or load duration distributions, the Palmgren‐Miner linear accumulative damage hypothesis, and long‐term environmental condition distributions. Then, an inspection priority map is established based on the failure ranking of the drivetrain components, which supports drivetrain inspection and maintenance assessment and further model optimization. The detailed modelling of the baseline drivetrain model provides a basis for benchmark studies and support for future research on multimegawatt offshore wind turbines.     

Analysis of technology improvement opportunities for a 1.5 MW wind turbine using a hybrid stochastic approach in life cycle assessment

This paper presents an analysis of potential technological advancements for a 1.5 MW wind turbine using a hybrid stochastic method to improve uncertainty estimates of embodied energy and embodied carbon. The analysis is specifically aimed at these two quantities due to the fact that LCA based design decision making is of utmost importance at the concept design stage. In the presented case studies, better results for the baseline turbine were observed compared to turbines with the proposed technological advancements. Embodied carbon and embodied energy results for the baseline turbine show that there is about 85% probability that the turbine manufacturers may have lost the chance to reduce carbon emissions, and 50% probability that they may have lost the chance to reduce the primary energy consumed during its manufacture. The paper also highlights that the adopted methodology can be used to support design decision making and hence is more feasible for LCA studies.     

A novel forecasting method based on the economic and demand response for FC/WT/PV unit and a 3 in 1 TES energy storage

Due to the lack of distribution resources and increasing demand in the daily market, the use of renewable resources is increasing. But renewable sources and market prices are uncertain behavior and cause economic problems. This paper introduces a novel market participation model include wind turbine, photovoltaic, fuel cell integrated with a novel hybrid TES energy storage system (3 in 1 concept) to minimize cost and improve load demand reliability. Also, to solve he mentioned problem a novel forecasting method are proposed. This model is a new multi artificial neural network based on the complete ensemble empirical mode decomposition which is coupled with Tanh function and using RMSE, MAPE and NMAE method the error rate of the proposed method is calculated. By using this method, the forecasting accuracy is improved and also with a novel energy storage the economic issue and market reliability are improved. Also, using the stochastic model the uncertainty system's behavior are modeled to obtain an accurate results of market participation and increase demand supply. Finally, a testing system includes wind turbine/photovoltaic/fuel cell/storage system and demand response are used to prove the superiority of the proposed model in comparison to other models.     

A heuristic method of variable selection based on principal component analysis and factor analysis for monitoring in a 300 kW MCFC power plant

In a commercialized 300 kW molten carbonate fuel cell (MCFC) power plant, a univariate alarm system that has only upper and lower limits is usually employed to identify abnormal conditions in the system. Even though univariate alarms have already been adopted for system monitoring, this simple monitoring system is limited for using in an extended monitoring system for fault diagnosis. Therefore, based on principal component analysis (PCA), a recursive variable grouping method for a multivariate monitoring system in a commercialized MCFC power plant is presented in this paper. In terms of development, since a principal component analysis model that contains all system variables cannot isolate a system fault, heuristic recursive variable selection method using factor analysis is presented here. To verify the performance of the fault detection, real plant operations data are used. Furthermore, comparison between type 1 and type 2 errors for four different variable groups demonstrates that the developed heuristic method works well when system faults occur. These monitoring techniques can reduce the number of false alarms occurring on site at MCFC power plant.