Ram‐air kite airfoil and reinforcements optimization for airborne wind energy applications

We present a multidisciplinary design optimization method for the profile and structural reinforcement layout of a ram‐air kite rib. The aim is to minimize the structural elastic energy and to maximize the traction power of a ram‐air kite used for airborne wind energy generation. Because of the large deformations occurring during flight, a fluid‐structure interaction (FSI) routine is included in the optimization, which determines the actual deformed rib geometry and its corresponding aerodynamic characteristics. A qualitative comparison between FSI inclusion and exclusion in the optimization is given. Discrepancies in airfoil profile and structural layout are observed.     

Copula-based joint distribution analysis of wind speed and wind direction: Wind energy development for Hong Kong

Accurate and reliable assessment of wind energy potential has important implication to the wind energy industry. Most previous studies on wind energy assessment focused solely on wind speed, whereas the dependence of wind energy on wind direction was much less considered and documented. In this paper, a copula-based method is proposed to better characterize the direction-related wind energy potential at six typical sites in Hong Kong. The joint probability density function (JPDF) of wind speed and wind direction is constructed by a series of copula models. It shows that Frank copula has the best performance to fit the JPDF at hilltop and offshore sites while Gumbel copula outperforms other models at urban sites. The derived JPDFs are applied to estimate the direction-related wind power density at the considered sites. The obtained maximum direction-related wind energy density varies from 41.3 W/m² at an urban site to 507.9 W/m² at a hilltop site. These outcomes are expected to facilitate accurate micro-site selection of wind turbines, thereby improving the economic benefits of wind farms in Hong Kong. Meanwhile, the developed copula-based method provides useful references for further investigations regarding direction-related wind energy assessments at various terrain regions. Notably, the proposed copula-based method can also be applied to characterize the direction-related wind energy potential somewhere other than Hong Kong.     

Improving reliability and safety of airborne wind energy systems

Airborne wind energy systems use tethered flying devices to harvest wind energy beyond the height range accessible to tower‐based wind turbines. Current commercial prototypes have reached power ratings of up to several hundred kilowatts, and companies are aiming at long‐term operation in relevant environments. As consequence, system reliability, operational robustness, and safety have become crucially important aspects of system development. In this study, we analyze the reliability and safety of a 100‐kW technology development platform with the objective of achieving continuous automatic operation. We first outline the different components of the kite power system and its operational modes. In the next step, we identify failure modes, their causes, and effects by means of failure mode and effects analysis (FMEA) and fault tree analysis (FTA). Potentially hazardous situations and mechanisms which can render the system nonoperational are identified, and mitigation measures are proposed. We find that the majority of these measures can be performed by a failure detection, isolation, and recovery (FDIR) system for which we present a hierarchical architecture adapted from space industry.     

Using nacelle‐based wind speed observations to improve power curve modeling for wind power forecasting

Wind power forecasting for projection times of 0–48 h can have a particular value in facilitating the integration of wind power into power systems. Accurate observations of the wind speed received by wind turbines are important inputs for some of the most useful methods for making such forecasts. In particular, they are used to derive power curves relating wind speeds to wind power production. By using power curve modeling, this paper compares two types of wind speed observations typically available at wind farms: the wind speed and wind direction measurements at the nacelles of the wind turbines and those at one or more on‐site meteorological masts (met masts). For the three Australian wind farms studied in this project, the results favor the nacelle‐based observations despite the inherent interference from the nacelle and the blades and despite calibration corrections to the met mast observations. This trend was found to be stronger for wind farm sites with more complex terrain. In addition, a numerical weather prediction (NWP) system was used to show that, for the wind farms studied, smaller single time‐series forecast errors can be achieved with the average wind speed from the nacelle‐based observations. This suggests that the nacelle‐average observations are more representative of the wind behavior predicted by an NWP system than the met mast observations. Also, when using an NWP system to predict wind farm power production, it suggests the use of a wind farm power curve based on nacelle‐average observations instead of met mast observations. Further, it suggests that historical and real‐time nacelle‐average observations should be calculated for large wind farms and used in wind power forecasting. Copyright © 2011 John Wiley & Sons, Ltd.     

Disturbance observer‐based integral sliding mode control for wind energy conversion systems

Recently, wind power production has been under the focus in generating power and became one of the main sources of alternative energy. Generating of maximum power from wind energy conversion system (WECS) requires accurate estimation of aerodynamic torque and uncertainties presented in the system. The current paper proposed the generalized high‐order disturbance observer (GHODO) with integral sliding mode control (ISMC) for extraction of maximum power via variable speed wind turbine by accurate estimation of wind speed. The assumption in previous works that considers the aerodynamic torque as slow‐varying is not applicable for the real system. Therefore, the high‐order disturbance observers were designed for precise estimation of uncertainties with fast‐changing behavior. A robust control system was designed to control the speed of the rotor at the optimal speed ratio. The obtained simulation results have shown the better performance characteristics than conventional linear quadratic regulator (LQR) approach. The stability of the proposed algorithm was proven by Lyapunov stability anaysis. Simulations results were obtained in Matlab/Simulink environment.     

Investigation of wind energy potentials in Brunei Darussalam

Conventional power generation mainly depends on natural gas and diesel oil in Brunei Darussalam. The power utility company is now thinking of power generation using natural wind. In this paper, wind energy, being one of the most readily available renewable energy sources, was studied. The wind characteristic, velocity and directions were studied using Weibull distribution based on the measurement of wind speed at two different locations in Brunei Darussalam. These wind speed distributions were modeled using the Wind Power program. The wind rose graph was obtained for the wind direction to analyze the wind power density onshore and offshore. Based on this analysis, it has been found that the wind speed of 3 to 5 m/s has a probability of occurrence of 40%. Besides, the annual energy production at a wind speed of 5 m/s has been found to be in the range between 1000 and 1500 kWh for both the locations in Brunei Darussalam.     

Assessing the suitability of wind speed probabilty distribution functions based on wind power density

Three functions have so far predominantly been used for fitting the measured wind speed probability distribution in a given location over a certain period of time, typically monthly or yearly. In the literature, it is common to fit these functions to compare which one fits the measured distribution best in a particular location. During this comparison process, parameters on which the suitability of the fit is judged are required. The parameters that are mostly used are the mean wind speed or the total wind energy output (primary parameters). It is, however, shown in the present study that one cannot judge the suitability of the functions based on the primary parameters alone. Additional parameters (secondary parameters) that complete the primary parameters are required to have a complete assessment of the fit, such as the discrepancy between the measured and fitted distributions, both for the wind speed and wind energy (that is the standard deviation of wind speed and wind energy distributions). Therefore, the secondary statistical parameters have to be known as well as the primary ones to make a judgement about the suitability of the distribution functions analysed. The primary and secondary parameters are calculated from the 12-month of measured hourly wind speed data and detailed analyses of wind speed distributions are undertaken in the present article.     

Energy‐based excitation control of doubly‐fed induction wind generator for optimum wind energy capture

A novel nonlinear energy‐based excitation controlling strategy for variable‐speed doubly‐fed induction wind generator (DFIWG) is proposed in this paper. From the consideration of physical nature and energy flow of the DFIWG, the mechanical subsystem and the electromagnetical subsystem of the DFIWG first have their port‐controlled Hamiltonian (PCH) realization. Then taking advantage of the feedback interconnection between the subsystems, the entire PCH model of the DFIWG is established. On the basis of this model, the excitation control for the generator speed adjustment is achieved by energy shaping design with the purpose of optimum wind energy capture. Finally, simulation results via MATLAB/Simulink (MathWorks, Natick, MA, USA) confirm the effectiveness of the proposed approach for wind speeds in different operating stages. Copyright © 2012 John Wiley & Sons, Ltd.     

A comparison of methodologies for monthly wind energy estimation

Monthly wind energy estimations obtained by means of three different methodologies are evaluated. Hourly wind and wind power production data measured at five wind farms in the Northeast of Spain within the period spanning from June 1999 to June 2003 were employed for this purpose. One of the approaches is based on the combined contribution of the hourly wind speed frequency distribution and the corresponding power production. Several alternatives to represent the empirical wind power versus wind speed relationship are considered and their impacts on the error of monthly energy estimations assessed. Two more approaches derive monthly energy estimates directly from monthly wind values: one uses the theoretical power curve to obtain interpolated monthly wind power production values and the other consists in a simple linear regression between the observed wind speed and wind power monthly pairs, which serves as an approximation to the global power curve. The three methodologies reproduce reliably the total monthly wind energy. Results also reveal that linearity is a reasonable assumption for the relation between wind speed and power production at monthly timescales. This approach involves a simplification with respect to other standard procedures that require finer temporal resolution data. Copyright © 2009 John Wiley & Sons, Ltd.     

A simplified model for estimating the monthly performance of autonomous wind energy systems with battery storage

This paper presents a simplified algorithm to estimate the monthly performance of autonomous small-scale wind energy systems with battery storage. The novel model is drawn based on the simulation results, using eight-year long hour-by-hour measured wind speed data from five different locations throughout the world. An hourly constant load profile is used. The renewable energy simulation program (ARES) of the Cardiff School of Engineering is used. The ARES simulates the battery state of voltage (SoV) and is able to predict the system performance.The monthly performance values obtained from the simulations are plotted against increasing energy to load ratios for varying battery storage capacities to obtain performance curves. The novel method correlates the monthly system performance with the parameters of the Weibull distribution function, thus offering a universal use. The monthly performance curves are mathematically represented using a 2-parameter function. The novel method is validated by comparing the simulated performance values with those estimated from the simplified algorithm. The standard errors calculated in estimation of the system performance using the simplified algorithm are further presented for each battery capacity.     

Probabilistic analysis of weather data for a hybrid solar/wind energy system

In this paper, a procedure for the probabilistic treatment of solar irradiance and wind speed data is reported as a method of evaluating, at a given site, the electric energy generated by both a photovoltaic system and a wind system. The aim of the proposed approach is twofold: first, to check if the real probability distribution functions (PDFs) of both clearness index and wind speed overlap with Hollands and Huget and Weibull PDFs, respectively; and then to find the parameters of these two distributions that best fit the real data. Further, using goodness‐of‐fit tests, these PDFs are compared with another set of very common PDFs, namely the Gordon and Reddy and Lognormal functions, respectively. The results inform the design of a pre‐processing stage for the input of an algorithm that probabilistically optimizes the design of hybrid solar wind power systems. In this paper, the validity of the proposed procedure was tested using long‐term meteorological data from Acireale (Italy). Copyright © 2010 John Wiley & Sons, Ltd.     

A novel nonlinear observer‐based LQ control system design for wind energy conversion systems with single measurement

The issue of tracking the optimal power for wind energy conversion systems (WECSs) via regulating the rotor speed of the generator is taken into account in this study. Additionally, a novel polynomial observer is proposed for estimating not only aerodynamic torque in WECSs but also d‐axis and electromagnetic torque. Therefore, in this new approach, only the rotor speed of the generator is required to be measured instead of measuring all state variables. With the new observer form, the aerodynamic torque does not need to satisfy any constraints, which are mandatory in the previous methods. It should be noted that this methodology has not been investigated for the WECSs in any previous papers. To design a complete control system, a linear optimal control method cooperated with the polynomial observer is employed to track the optimal trajectory of a generator. Moreover, in this paper, the permanent magnet synchronous generator is used. In addition, on the basis of the Lyapunov theory and sum‐of‐square (SOS) technique, the conditions for observer synthesis are derived in the main theorems. Finally, the simulation results are provided to prove the effectiveness and merit of the proposed method.     

Structural analysis and optimization of a tethered swept wing for airborne wind energy generation

In this paper, we present an aero‐structural model of a tethered swept wing for airborne wind energy generation. The carbon composite wing has neither fuselage nor actuated aerodynamic control surfaces and is controlled entirely from the ground using three separate tethers. The computational model is efficient enough to be used for weight optimisation at the initial design stage. The main load‐bearing wing component is a nontypical “D”‐shaped wing‐box, which is represented as a slender carbon composite shell and further idealised as a stack of two‐dimensional cross section models arranged along an anisotropic one‐dimensional beam model. This reduced 2+1D finite element model is then combined with a nonlinear vortex step method that determines the aerodynamic load. A bridle model is utilised to calculate the individual forces as a function of the aerodynamic load in the bridle lines that connect the main tether to the wing. The entire computational model is used to explore the influence of the bride on the D‐box structure. Considering a reference D‐box design along with a reference aerodynamic load case, the structural response is analysed for typical bridle configurations. Subsequently, an optimisation of the internal geometry and laminate fibre orientations is carried out using the structural computation models, for a fixed aerodynamic and bridle configuration. Aiming at a minimal weight of the wing structure, we find that for the typical load case of the system, an overall weight savings of approximately 20% can be achieved compared with the initial reference design.     

Estimation of variability and predictability of large‐scale wind energy in The Netherlands

This paper presents a data‐driven approach for estimating the degree of variability and predictability associated with large‐scale wind energy production for a planned integration in a given geographical area, with an application to The Netherlands. A new method is presented for generating realistic time series of aggregated wind power realizations and forecasts. To this end, simultaneous wind speed time series—both actual and predicted—at planned wind farm locations are needed, but not always available. A 1‐year data set of 10‐min averaged wind speeds measured at several weather stations is used. The measurements are first transformed from sensor height to hub height, then spatially interpolated using multivariate normal theory, and finally averaged over the market resolution time interval. Day‐ahead wind speed forecast time series are created from the atmospheric model HiRLAM (High Resolution Limited Area Model). Actual and forecasted wind speeds are passed through multi‐turbine power curves and summed up to create time series of actual and forecasted wind power. Two insights are derived from the developed data set: the degree of long‐term variability and the degree of predictability when Dutch wind energy production is aggregated at the national or at the market participant level. For a 7.8 GW installed wind power scenario, at the system level, the imbalance energy requirements due to wind variations across 15‐min intervals are ±14% of the total installed capacity, while the imbalance due to forecast errors vary between 53% for down‐ and 56% for up‐regulation. When aggregating at the market participant level, the balancing energy requirements are 2–3% higher. Copyright © 2008 John Wiley & Sons, Ltd.     

A comparison of methods for assessing power output in non‐uniform onshore wind farms

Wind resource assessments are used to estimate a wind farm's power production during the planning process. It is important that these estimates are accurate, as they can impact financing agreements, transmission planning, and environmental targets. Here, we analyze the challenges in wind power estimation for onshore farms. Turbine wake effects are a strong determinant of farm power production. With given input wind conditions, wake losses typically cause downstream turbines to produce significantly less power than upstream turbines. These losses have been modeled extensively and are well understood under certain conditions. Most notably, validation of different model types has favored offshore farms. Models that capture the dynamics of offshore wind conditions do not necessarily perform equally as well for onshore wind farms. We analyze the capabilities of several different methods for estimating wind farm power production in 2 onshore farms with non‐uniform layouts. We compare the Jensen model to a number of statistical models, to meteorological downscaling techniques, and to using no model at all. We show that the complexities of some onshore farms result in wind conditions that are not accurately modeled by the Jensen wake decay techniques and that statistical methods have some strong advantages in practice.     

Adaptive post‐processing of short‐term wind forecasts for energy applications

We present a new method of reducing the error in predicted wind speed, thus enabling better management of wind energy facilities. A numerical weather prediction model, COSMO, was used to produce 48 h forecast data every day in 2008 at horizontal resolutions of 10 and 3 km. A new adaptive statistical method was applied to the model output to improve the forecast skill. The method applied corrective weights to a set of forecasts generated using several post‐processing methods. The weights were calculated based on the recent skill of the different forecasts. The resulting forecast data were compared with observed data, and skill scores were calculated to allow comparison between different post‐processing methods. The total root mean square error performance of the composite forecast is superior to that of any of the individual methods. Copyright © 2010 John Wiley & Sons, Ltd.     

Nacelle anemometer measurement‐based extremum‐seeking wind turbine region‐2 control for improved convergence in fluctuating wind

For region‐2 operation of wind turbines in practice, the optimal torque gain can deviate from the nominal value because of the variations in turbine and wind conditions. The extremum‐seeking control (ESC) has shown its potential as a model‐free region‐2 control solution in some recent work; however, the ESC with rotor power feedback suffers from undesirable convergence under fluctuating wind. In this paper, we propose to use an estimated power coefficient as the objective function for the torque‐gain ESC, where the hub‐height free‐stream wind speed (FSWS) is estimated with the nacelle anemometer measurement on the basis of the so‐called nacelle transfer function (NTF) between the nacelle anemometer and met‐tower measurement. A sensitivity analysis is performed to quantify the impact of the wind speed estimation error on the estimation of power coefficient. An ESC integrated interregion switching scheme is proposed to avoid the load increase. Simulation results show that, compared with the power feedback‐based ESC, the proposed method can greatly improve the convergence rate of ESC under fluctuating wind, even under relatively large wind speed estimation error. Evaluation for the fatigue loads of wind turbine shows that the proposed control strategy induces mild increase of the wind turbine load.     

The effects of vehicle‐to‐grid systems on wind power integration

Renewable energy portfolio standards have created a large increase in the amount of renewable electricity production, and one technology that has benefited greatly from these standards is wind power. The uncertainty inherent in wind electricity production dictates that additional amounts of conventional generation resources be kept in reserve, should wind electricity output suddenly dip. The introduction of plug‐in hybrid electric vehicles into the transportation fleet presents an possible solution to this problem through the concept of vehicle‐to‐grid power. The ability of vehicle‐to‐grid power systems to help solve the variability and uncertainty issuess in systems with large amounts of wind power capacity is examined through a multiparadigm simulation model. The problem is examined from the perspectives of three different stakeholders: policy makers, the electricity system operator and plug‐in hybrid electric vehicle owners. Additionally, a preliminary economic analysis of the technology is performed, and a comparison made with generation technologies that perform similar functions. Copyright © 2011 John Wiley & Sons, Ltd.     

Flow characterization in the near‐wake region of a horizontal axis wind turbine

An experimental study is conducted to investigate the flow dynamics within the near‐wake region of a horizontal axis wind turbine using particle image velocimetry (PIV). Measurements were performed in the horizontal plane in a row of four radially distributed measurement windows (tiles), which are then patched together to obtain larger measurement field. The mean and turbulent components of the flow field were measured at various blade phase angles. The mean velocity and turbulence characteristics show high dependency on the blade phase angle in the near‐wake region closer to the blade tip and become phase independent further downstream at a distance of about one rotor diameter. In the near‐wake region, both the mean and turbulent characteristics show a systemic variation with the phase angle in the blade tip region, where the highest levels of turbulence are observed. The streamlines of the instantaneous velocity field at a given phase allowed to track a tip vortex which showed wandering trend. The tip vortices are mostly formed at r/R > 1, which indicates the wake expansion. Results also show the gradual movement of the vortex region in the axial direction, which can be attributed to the dynamics of the helical tip vortices which after being generated from the tip, rotate with respect to the blade and move in the axial direction because of the axial momentum of the flow. The axial velocity deficit was compared with other laboratory and field measurements. The comparison shows qualitative similarity. Copyright © 2015 John Wiley & Sons, Ltd.     

Integrated energy balance analysis of a stand‐alone wind power system for various typical Aegean Sea regions

The wind power industry is nowadays a mature energy production sector disposing to market commercial wind converters from 50 W up to 5 MW. In the present work the possibility of using stand‐alone electricity production systems based on a small wind turbine in order to meet the electricity requirements of remote consumers is analysed for selected Aegean Sea regions possessing representative wind potential types. The proposed configuration results from an extensive long‐term meteorological data analysis on a no‐load rejection condition basis during the entire time period examined. Accordingly, an integrated energy balance analysis is carried out for the whole time period investigated, including also the system battery depth‐of‐discharge distribution versus time. Finally, the predicted optimum system configuration is compared to other existing technoeconomic alternatives on a simplified total production cost basis. The results support the viability of similar solutions, especially for areas of high or medium wind potential. Copyright © 2002 John Wiley & Sons, Ltd.