Performance evaluation of a horizontal axis wind turbine in operation

The operation of modern horizontal axis wind turbine (HAWT) includes a number of important factors, such as wind power (P), power coefficient (C_P), axial flow induction factor (a), rotational speed (Ω), tip speed ratio (λ), and thrust force (T). The aerodynamic qualities of these aspects are evaluated and discussed in this study. For this aim, the measured data are obtained from the Sebenoba Wind Energy Power Plant (WEPP) that is located in the Sebenoba region in Hatay, Turkey, and a wind turbine with a capacity of 2 MW is selected for evaluation. According to the results obtained, the maximum turbine power output, maximum power coefficient, maximum axial flow induction factor, maximum thrust force, optimum rotational speed, probability density of optimum rotational speed, and optimum tip speed ratio are found to be 2 MW, 30%, 0.091, 140 kN, 16.11 rpm, 46.76%, and 7, respectively. This study has revealed that wind turbines must work under optimum conditions in order to extract as much energy as possible for approaching the ideal limit.     

The hybrid model of empirical wavelet transform and relevance vector regression for monthly wind speed prediction

ABSTRACT

In order to improve the prediction ability for the monthly wind speed of RVR, the hybrid model of empirical wavelet transform and relevance vector regression (EWT-RVR) is proposed for monthly wind speed prediction in this study. Compared with empirical mode decomposition (EMD), empirical wavelet transform (EWT) can obtain a more consistent decomposition and have a mathematical theory. In order to testify the superiority of EWT-RVR, several traditional RVR models are used to compare with the proposed EWT-RVR method under the situation of the same embedding dimensions. The experimental results show that the proposed EWT-RVR method has a better prediction ability for monthly wind speed than RVR. It can be concluded that the proposed EWT-RVR method for monthly wind speed is effective.     

A hybrid model based on smooth transition periodic autoregressive and Elman artificial neural network for wind speed forecasting of the Hebei region in China

Wind energy, one of the most promising renewable and clean energy sources, is becoming increasingly significant for sustainable energy development and environmental protection. Given the relationship between wind power and wind speed, precise prediction of wind speed for wind energy estimation and wind power generation is important. For proper and efficient evaluation of wind speed, a smooth transition periodic autoregressive (STPAR) model is developed to predict the six-hourly wind speeds. In addition, the Elman artificial neural network (EANN)-based error correction technique has also been integrated into the new STPAR model to improve model performance. To verify the developed approach, the six-hourly wind speed series during the period of 2000–2009 in the Hebei region of China is used for model construction and model testing. The proposed EANN-STPAR hybrid model has demonstrated its powerful forecasting capacity for wind speed series with complicated characteristics of linearity, seasonality and nonlinearity, which indicates that the proposed hybrid model is notably efficient and practical for wind speed forecasting, especially for the Hebei wind farms of China.     

Design and analysis of artificial bee-colony-based MPPT algorithm for DFIG-based wind energy conversion systems

In this article, the proposed maximum power point tracking (MPPT) method is designed by taking rotor speed as an optimization problem, which is solved by artificial bee colony (ABC) algorithm to generate the maximum power output. The main advantage of this algorithm is that its optimal solution is independent of the initial positions and requirement of lesser number of control parameters, which leads to simple and robust MPPT algorithm than other algorithm. Furthermore, the hill climb search and particle swarm optimization-based MPPT algorithm are also discussed and the results obtained by these are compared to verify the effectiveness of proposed algorithm. Simulations for MPPT control along with doubly fed induction-generator-based wind energy conversion system is carried out in MATLAB/Simulink environment. Three statistical methods are used to evaluate the accuracy of each MPPT algorithm. All results are analyzed and compared under randomly selected wind as well as real wind speed configuration. Comparison of both numerical and simulation results under two different varying wind speed conditions strongly suggest that the proposed ABC-based MPPT algorithm is superior than other two MPPT algorithms.     

Performance enhancement of a stand-alone induction generator-based wind energy system using neural network controller

ABSTRACT

The limitation of self-excited induction generator (SEIG) when used in the stand-alone wind energy system (WES) is poor voltage regulation at variable speed. The indirect vector control (IVC) technique is employed for both the generator-side converter (GSC) and load-side converter (LSC) to regulate the variation of SEIG speed, DC link voltage, and electromagnetic torque independently. Further performance of the proposed IVC technique has been analyzed independently with neural network controller (NNC) and fuzzy logic controller (FLC) as its components. The FLC is replaced by an NNC to improve the performance of the proposed system. IVC of SEIG-based WES has been simulated in MATLAB/SIMULINK software, and the prototype model of the proposed WES is developed to experimentally validate the performance using dSPACE DS-1104 R&D controller board.     

A low pressure direct gas injection system for a four stroke LPG: Diesel dual fuel engine

Internal combustion engines running on gaseous fuels produce low torque because the inducted gaseous fuel displaces air and reduces the volumetric efficiency. This can be overcome by injecting the gaseous fuel directly into the cylinder after the intake of air is completed. This work is a step in developing and demonstrating a cost effective system, as such systems are not readily available for small applications. A low-pressure gas injector was mounted on the cylinder barrel of a fully instrumented dual fuel engine. Its location is such that the injector will be exposed to the cylinder gases about 65.5 degrees before bottom dead center, where the cylinder pressure and temperature will be relatively low. An electronic controller was also developed to time the injection process to occur after the intake valve closes and also to control the duration of injection (quantity). Experiments were conducted with LPG (Liquefied petroleum gas) as the primary fuel that was injected with this new system and diesel as the pilot fuel at the rated speed of 1500 rpm with different amounts of LPG at 80% and 100% load. Comparisons of performance, combustion and emissions with the conventional manifold injection of LPG were done. The system allowed greater amounts of LPG to be used without knock as compared to manifold injection. On the whole the developed system has potential for application in small dual fuel and spark ignited gas engines and can be taken up for further optimization.     

A novel blade design for Savonius wind turbine based on polynomial bezier curves for aerodynamic performance enhancement

ABSTRACT

Advanced wind turbine designs and technologies have been evolved to take advantage of wind energy. Despite the significant progress already attained, the need for a dependable wind energy converter particularly devoted to small-scale applications remains a challenging issue. Due to its design simplicity, Savonius wind turbine is the most suitable candidate for such applications. It operates at low wind speed, with the necessary starting capacity and insensitivity to wind directions. Moreover, in the literature related to wind energy, the Savonius rotor is known for its low performance compared to other types of wind turbines. In this paper, we present a study into the utilization of Bézier curves and transient computational fluid dynamics (CFD) to optimize the conventional Savonius blade design. The k-ω SST turbulence model is employed to perform a series of CFD simulations in order to assess the power coefficient of each generated design. A validation of optimization results using the Taguchi method was carried out. The comparative analysis of the torque and power coefficients shows a significant increase in the power coefficient (C_p). The optimal C_p is 0.35 and is 29% higher than the conventional Savoniu wind turbine (SWT). Subsequently, the effectiveness of the innovative geometry is proved by improved pressure and velocity distributions around blades of novel design.     

A novel wind speed forecasting model for wind farms of Northwest China

Wind resources are becoming increasingly significant due to their clean and renewable characteristics, and the integration of wind power into existing electricity systems is imminent. To maintain a stable power supply system that takes into account the stochastic nature of wind speed, accurate wind speed forecasting is pivotal. However, no single model can be applied to all cases. Recent studies show that wind speed forecasting errors are approximately 25% to 40% in Chinese wind farms. Presently, hybrid wind speed forecasting models are widely used and have been verified to perform better than conventional single forecasting models, not only in short-term wind speed forecasting but also in long-term forecasting. In this paper, a hybrid forecasting model is developed, the Similar Coefficient Sum (SCS) and Hermite Interpolation are exploited to process the original wind speed data, and the SVM model whose parameters are tuned by an artificial intelligence model is built to make forecast. The results of case studies show that the MAPE value of the hybrid model varies from 22.96% to 28.87 %, and the MAE value varies from 0.47 m/s to 1.30 m/s. Generally, Sign test, Wilcoxon’s Signed-Rank test, and Morgan--Granger--Newbold test tell us that the proposed model is different from the compared models.     

A Weibull and finite mixture of the von Mises distribution for wind analysis in Mersing,Malaysia

Studies of wind direction receive less attention than that of wind speed; however, wind direction affects daily activities such as shipping, the use of bridges, and construction. This research aims to study the effect of wind direction on generating wind power. A finite mixture model of the von Mises distribution and Weibull distribution are used in this paper to represent wind direction and wind speed data, respectively, for Mersing (Malaysia). The suitability of the distribution is examined by the R² determination coefficient. The energy analysis, that is, wind power density, only involves the wind speed, but the wind direction is vital in measuring the dominant direction of wind so that the sensor could optimize wind capture. The result reveals that the estimated wind power density is between 18.2 and 25 W/m², and SSW is the most common wind direction for this data.     

On the wind resource mapping of Burkina Faso

In this work, mesoscale wind resource maps, at 5-km resolution, of the country of Burkina Faso (274,200 km²) were developed using the Anemoscope and mesoscale compressible community models. Results show that the northeast region of Burkina Faso has a good wind regime at 80 m above ground level (agl), while the wind regime in other parts of the country is generally low, even at 80 m agl. In addition, the technical power potential and the potential annual energy production that can be generated from the wind in Burkina Faso are identified using analysis tools based on geographical information systems and economic constraints. Results from the technical power potential at 80 m agl show that a total of 312 MW of wind farms, generating annually a total of 741 GWh of energy, could be installed in Burkina Faso. On the other hand, a total of 4411 MW of small wind turbines (50 kW) could be installed over the territory, corresponding to an annual energy production of 7843 GWh. The Wind Atlas of Burkina Faso provides an opportunity for local stakeholders to consider wind energy for the electricity portfolio of the country.     

Wind energy potential analysis for Thailand: Uncertainty from wind maps and sensitivity to turbine technology

Rapid development of wind energy has been witnessed in Thailand. However, different wind resource maps (over land) have brought great uncertainty to wind energy planning. Here, four important mesoscale wind maps were considered: DEDP (2001), World Bank (2001), Manomaiphiboon et al. (2010) of JGSEE, and DEDE (2010). The wind maps were first harmonized to a common grid at 100 m and then compared. The earlier wind maps (DEDP and World Bank) are shown to represent the lower and upper limits of predicted speed, respectively, while JGSEE and DEDE tend to be more moderate with predictions statistically closer to observations. A consolidated wind map was constructed based on their median and shown to have the best prediction performance. It was then used for the technical potential analysis, in which three large (2-MW) turbine models (two conventional and one designed for low wind speed) were considered. By GIS techniques, any land areas not feasible for large wind turbines were excluded, and the corresponding overall onshore technical potential ranges between 50 and 250 GW, depending on map and turbine model. Considering only economically feasible turbines (with capacity factors of 20%) and the median-based map, the final technical potential equals 17 GW when using the low-wind-speed model but is reduced to 5 GW with the conventional models, adequately meeting the national wind energy target of 3 GW by the year 2036. The results suggest a strong sensitivity of estimated technical potential to turbine technology and a suitability of low-wind-speed turbines for wind conditions in Thailand.     

Wind energy potential assessment and techno-economic performance of wind turbines in coastal sites of Buenos Aires province,Argentina

An assessment of wind energy potential was carried out in five sites (four onshore and one offshore) in South-West (SW) of Buenos Aires province (Argentina). We use high-resolution wind data (2 and 5 min) for the period 2009–2012. The power law was used to estimate the wind speed at 30, 40, and 60 m height from the anemometer position. Turbulence intensity and wind direction were analyzed. Statistical analyses were conducted using two-parameter Weibull distribution. A techno-economic analysis based on a set of commercial wind turbines was performed in those sites. The results derived from this work indicate that the SW of Buenos Aires province represents a promising area for the wind energy extraction, which would encourage the construction of wind farms for electricity generation.     

Wind power potential assessment for three buoys data collection stations in the Ionian Sea using Weibull distribution function

The present article utilizes wind measurements from three buoys data collection stations in Ionian Sea to study the wind speed and power characteristics using the Weibull shape and scale parameters. Specifically, the site dependent, annual, and monthly mean patterns of mean wind speed, Weibull parameters, frequency distribution, most probable wind speed, maximum energy carrying wind speed, wind power density and wind energy density characteristics have been analyzed. The Weibull distribution was found to represent the wind speed distribution with more than 90% accuracy, in most of the cases. Moreover, the correlation between the percentages of times the wind speed was above cut-in-speed and the measured mean wind speed for the three selected sites, as the correlation between the aforementioned percentages and the scale parameter c were examined and were found linear. At all these sites, no definite increasing or decreasing trends in annual mean wind speed values could be detective over the data reporting period. The mean values of wind speed, scale parameter, most probable wind speed, maximum energy carrying wind speed, wind power and wind energy density values showed higher values during winter time and lower in summer time in Pylos and Zakynthos. Moreover, Pylos and Zakynthos were found to be the best sites from wind power harnessing point of view.     

Hedgerows and hedgerow networks in landscape ecology

Hedgerows originated and coexist with agriculture. Their internal structure and species diversity vary widely with origin (planted, spontaneous, or remnant), farming practices in adjacent fields, and the refined art of hedgerow management. Most hedgerow species are forest-edge species, and apparently none is limited to hedgerows. Wide hedgerows composed of trees and shrubs appear to function as corridors for movement of many plants and animals across a landscape. The reduction of crop loss, by dampening pest population fluctuations with hedgerow predators, remains a hypothesis for study.Field microclimate downwind of a hedgerow is modified about 16 times the hedgerow height (h) for evaporation, and approximately 28 h for wind speed. A turbulent wind pattern with harsher microclimate is present at 6–8 h if a second hedgerow is nearby downwind. Zones of higher crop productivity at 3- to 6-h downwind, and 2- to 6-h upwind of a second hedgerow may be expected. Overall, we expect little short-term difference in farm-field production with or without hedgerows.Evidence suggests that hedgerow networks, and especially their mesh size (of fields), exert a major control on many major landscape fluxes. Such fluxes include animal populations, wind speed, evapotranspiration and soil desiccation, soil erosion and nutrient runoff, species movement along network lines, and movement of field species across the network. In a relatively short period, the hedgerow ecosystem, with no unique species, has attained a metastable equilibrium, which is regulated by enormous human inputs.More than 20 economic roles of hedgerows are pinpointed. The roles, providing resources and protection of resources, are poorly known quantitatively. We conclude that hedgerows perform diverse functions for society and the farmer that are both economically and ecologically significant.     

An Analysis of the Wind Energy Potential of Elazig,Turkey

Abstract

In this study, the wind energy potential of Elazig is statistically analyzed based on hourly measured wind speed data over the five-year period from 1998 to 2002. The probability density distributions are derived from cumulative distribution functions. Two probability density functions are fitted to the measured probability distribution on a yearly basis. The wind energy potential of the location is studied based on the Weibull and Rayleigh distributions. It was found that the numerical values of both Weibull parameters (k and c) for Elazig vary over a wide range. The yearly values of k range from 1.653 to 1.878 with an average value of 1.819, while those of c are in the range of 2.757–2.994 m/s with an average value of 2.824 m/s. In addition, yearly mean wind speed and mean power density of Elazig is found as 2.79 m/s and 38.76 W/m², respectively. The wind speed distributions are represented by Weibull distribution and also by Rayleigh distribution, with a special case of the Weibull distribution for k = 2. As a result, the Rayleigh distribution is found to be suitable to represent the actual probability of wind speed data for Elazig.     

Blade thickness effect on the aerodynamic performance of an asymmetric NACA six series blade vertical axis wind turbine in low wind speed

ABSTRACT

Vertical axis wind turbine (VAWT) is an economic and widely used energy converter for converting wind energy into useful form of energy, like mechanical and electrical energy. For efficient energy conversion in low wind speed and to have improved power coefficient of asymmetric blade VAWT, selection of optimum blade thickness is needed thus entailing its detailed investigation with respect to different operating wind speed conditions. Present study methodically explores the impact of thickness to chord (t/c) ratio on aerodynamic performance of a three bladed asymmetrical blade H-Darrieus VAWT at different low wind speed conditions by using 2D unsteady CFD simulations. The optimal t/c is obtained on the basis of maximum power coefficient and average moment coefficient of the turbine. The aerodynamic performance curves are obtained at different operating and t/c conditions and the performance insights are corroborated with the findings from the flow physics study to come to some concrete conclusions on the effects of the thickness to chord ratio. The present study identifies large blade curvature to create a large diverging passage on the blade suction surface as the prominent reason for aerodynamic performance drop at a high t/c ratio.     

Location wise comparison of mixture distributions for assessment of wind power potential: A parametric study

Scientific literature discussed various types of mixture models and models derived from maximum entropy principle using short-term wind speed data for their relative assessment. The literature on suitability of these mixture models for long-term data is rarely available. However, for correct assessment of wind power potential both wind speed and wind direction are equally important. Therefore, in this paper, both wind speed and wind direction are simultaneously analyzed using several types of mixture distribution and compared the same with conventional Weibull distribution. For wind speed and wind power density assessment, the mixture distributions such as Weibull--Weibull distribution, Gamma--Weibull distribution, Truncated Normal--Weibull distribution, Truncated Normal--Normal distribution, proposed Truncated Normal--Gamma distribution and Gamma--Gamma distribution along with MEP-distribution are compared with conventional 2-parameter Weibull distribution. Similarly, for wind direction analysis, the finite mixtures of von-Mises distribution are compared with conventional von-Mises distribution. Judgment criteria include R², RMSE, Kolmogorov--Smirnov test and relative percentage error in wind power density. The sites selected are the three onshore locations of India, viz., Calcutta, Trivandrum, and Ahmedabad. The results show that for wind speed assessment, mixture distribution performs better than the conventional Weibull distribution for analyzing wind power density. However, location wise comparison of all mixture distribution is of prime importance. For wind direction analysis, finite mixture of two von-Mises distributions proved to be a suitable candidate for Indian climatology.     

气象因素对大连空气中PM_(2.5)的去除效应分析

根据2013年1月1日至2月15日大连市环境监测中心PM2.5监测数据和大连市气象局风向、风速、降水量等资料,研究了降雪、降雨、风等气象因素对大气中PM2.5的去除效应。结果表明,大连市冬季采暖期PM2.5污染较重,PM2.5浓度受气象因素影响较明显。降雪、降雨、风三种气象因素对大气中PM2.5均有明显的去除效果,因去除机理不同,各气象因素对PM2.5的去除能力大小依次为风、降雨、降雪,去除效率分别为61.6%、46.0%、34.5%。     

The effects of sinusoidal leading edge of turbine blades on the power coefficient of horizontal-axis wind turbine (HAWT)

In order to improve the aerodynamic performance of horizontal-axis wind turbine (HAWT), a sinusoidal shape is applied to turbine blade. In this study, four types of modified blades were chosen based on variations in amplitude and wavelength of protuberance along the leading edge. Compared with the baseline model, the power coefficients (C_p) of HAWT with modified blades were improved, especially at low tip speed ratios. At low wind speed (V = 6 m/s), blades with short wavelength obtain significant improvement in C_p compared with the baseline model. As wind speed increases, this improvement decreases. In addition, turbine blade with large amplitude and long wavelength obtains better C_p values at higher wind speeds than lower ones, which have a great potential to be more superior at relatively higher wind speeds.     

The implementation of a measurement system for brushless DC motor parameters

Most of the energy conversion in industrial devices and equipment is completed by the motor. The acquirement of motor parameters becomes very important for designing the motor drives. The aim of this paper is to design and implement a motor measurement system. Through the processing of an Advanced RISC Machines (ARM) microcontroller, the various parameters of motors such as input voltage, input current, input power, motor speed, and motor torque can be obtained. Consequently, the torque constant, load torque, viscous friction, and the inertia of the motor are calculated and achieved. The motor parameters can be commanded and displayed in the designed human interface of a PC via USB communication. The hardware system designed in this system includes an ARM microcontroller, an inverter, a voltage sensor, a current sensor, a torque sensor, and power supply. The software programming is developed under the Visual Studio 2012 environment development platform using the C language. Finally, the prototype of the motor measurement system is completed and verified. The experimental results for the motor parameters and torque/speed characteristic are demonstrated and show the feasibility of the complete designed system.