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.     

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.     

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.     

Suitable error evaluation criteria selection in the wind energy assessment via the K-means clustering algorithm

In this paper, wind energy potential of four locations in Xinjiang region is assessed. The Weibull distribution as well as the Logistic and the Lognormal distributions are applied to describe the distributions of the wind speed at different heights. In determining the parameters in the Weibull distribution, four intelligent parameter optimization approaches including the differential evolutionary, the particle swarm optimization, and two other approaches derived from these two algorithms and combined advantages of these two approaches are employed. Then the optimal distribution is chosen through the Chi-square error (CSE), the Kolmogorov–Smirnov test error (KSE), and the root mean square error (RMSE) criteria. However, it is found that the variation range of some criteria is quite large, thus these criteria are analyzed and evaluated both from the anomalous values and by the K-means clustering method. Anomaly observation results have shown that the CSE is the first one should be considered to be eliminated from the consequent optimal distribution function selection. This idea is further confirmed by the K-means clustering algorithm, by which the CSE is clustered into a different group with KSE and RMSE. Therefore, only the reserved two error evaluation criteria are utilized to evaluate the wind power potential.     

Effects of Meteorological Parameters on Air Pollutant Concentrations in Elazig,Turkey

In the present study, air pollutant concentrations have been analyzed statistically with meteorological factors in the city of Elazig, which is located in the east Anatolia region of Turkey, for the months of September, October, November, December, January, February, March, and April during the years 2003 and 2004. SPSS code was used for statistical analyses. The relationship between monitored air pollutant concentrations, such as SO₂ and the total suspended particles (TSP) data, and meteorological factors such as wind speed, temperature, relative humidity and pressure was investigated. According to the results of linear and non-linear regression analysis, it was found that there is a moderate and weak level of relation between the air pollutant concentrations and the meteorological factors in Elazig. The correlation between the previous day's SO₂, TSP concentrations and actual concentrations of these pollutants on that day was investigated and the coefficient of determination R was found to be 0.80 and 0.76, respectively. The statistical models of SO₂ and TSP, including all of the meteorological parameters, gave an R of 0.50 and 0.40, respectively. Further, in order to develop this model, the previous day's SO₂ and TSP concentrations were added to the equations. The new model for SO₂ and TSP was improved considerably with R = 0.85 and 0.80, respectively.     

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.     

A stochastic approach for the operation of a wind and pumped storage plant under a deregulated environment

To improve the competiveness in the energy market, it is necessary that the wind power plants provide guaranteed power generation, although, it is not possible to forecast power availability from wind power plant accurately. This paper presents a stochastic model and solution technique for the combined operation of wind and pumped storage power plants to improve the power availability and increasing the profit considering uncertainties of wind power generation. In this model, uncertainties in wind data have been forecasted for grid connected day-ahead market using Weibull distribution model. The imbalances in the forecasted wind data and the market demand have been reduced by operating the pumped storage power plant. In this stochastic mixed integer problem, pumped storage plant can take the supply either from the grid or from the wind power plant for the pumping operation to store the energy in order to utilize this energy during peak hours for increasing the overall revenue. The reliability of the pumped storage is improved by replacing the conventional unit with the adjustable speed type pumped storage unit. In order to prove the optimality of the solution, two case studies were considered. In case study–I, scheduling is provided by operating the conventional pumped storage unit, whereas in case study–II, adjustable speed pumped storage unit has been used. It has been found that the adjustable speed pumped storage unit has further reduced the imbalance between generated power and demand. The complete approach has been formulated and implemented using AMPL software.     

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.     

LAKE SHORE PROTECTION AGAINST WIND-GENERATED WAVES1

ABSTRACT: A method is reported for estimating the height of wind waves in any lake for a given wind condition. Maximum wind speeds from five climatological stations in and around Ilinois for the period of 1950–1972 were analyzed and the maximum wind speed for various durations and return periods were presented. Statistical analysis of wind wave data collected from Carlyle Lake indicated the Rayleigh distribution fitted the wave height distribution reasonably well and that the nondimensional energy spectra followed the (f/f_m)^-5 rule in the equilibrium range of frequencies. From a consideration of various forces and physical properties of riprap particles and water, a relationship was developed to estimate the stable weight of riprap particles. A practical design criteria is proposed to stabilize lake shores against wind waves.     

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.     

The convective hot air drying of Lactuca sativa slices

The storage of fresh agricultural products is not easy because of its high moisture. Dehydration is an efficient preservation method. The investigation of drying modeling and transfer characteristics are important for selecting operating conditions and equipment design. The drying behavior of Lactuca sativa slices, with the thickness of 2 mm, was investigated at 60.0–80.0°C and 0.60–1.04 m sec^?1 velocity in a convective hot air drier. The mass transfer during the drying process was described using six thin drying models. The convective heat transfer coefficient α and mass transfer coefficient k_H were finally calculated. The results showed that the drying process could be separated into three stages including accelerating rate, constant rate, and falling rate period, which was influenced by hot air temperature and velocity, and the Modi?ed Page model agreed well with the experimental data. When the operating temperature was increased from 60.0°C to 80.0°C, α was found increased from 88.07 to 107.93 W·m^?2·K^?1, and k_H increased from 46.32 × 10^–3 to 68.04 × 10^–3 kg·m^?2·sec^?1·ΔH^?1. With the increase of air velocity from 0.60 to 1.04 m·sec^?1, α was increased from 78.85 to 101.35 W·m^?2·K^?1, and k_H was enhanced from 51.78 × 10^–3 to 65.85 × 10^–3 kg·m^?2·sec^?1·ΔH^?1.     

A comparative analysis of wind resource parameters using WAsP and windPRO

This paper investigates the accuracy of the wind resource estimation for a site in a central India region using a latest licensed version of WAsP 11 and windPRO 3.1. Whole one year measured met mast wind data has been taken using anemometer and wind vane at 10 m and 25 m height, respectively above ground level. The digitized elevation and roughness model of the corresponding site shows the roughness class 4 (roughness length 1.2525 m). The wind data has been extrapolated up to 80 m height by using power and log law models which provide the power density near about 120 W/m². As per the micro sitting guidelines for the virtual wind farm installation 5D X 7D mapping has been selected which Indicates the total power output by installing 8 Vestas V-90 1.8 MW wind turbine from WAsP is 31.561 GWh and from windPRO is 28.083 GWh.     

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.     

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.     

A case study of an isolated wind powered electricity system meeting 100% of local demand

Using meteorological and electricity demand data for a 4-year period, electricity demand in Shetland was modeled to provide an estimate of the demand over a 30-year period from 1 January 1981. That modeled demand was then compared to estimated wind power output over the same period using the WAsP model. The wind farm output was estimated for a range of sizes of wind farm up to the consented 370 MW Viking Wind Farm in Shetland. Some wind power was available for 94% of the time and the 370 MW wind farm would meet 100% of demand for nearly 80% of the time. The statistics of single and accumulated deficits were calculated for a range of wind farms and estimates of the amount of additional generation capacity and additional power requirements were assessed. The study suggests that with storage, wind power in Shetland could meet all electricity demand in Shetland at around £130 to £150/MWh (excluding subsidy) and with a grid connection allowing the sale of excess power, those costs could be reduced.     

Best location of the small wind turbine around a single high-rise building

This research is a three-dimensional investigation about the aerodynamic interaction between the wind flow and a single high-rise building. In order to find location(s) with high potential of velocity around the building, a wide variety of wind speeds ranging from 2 to 10 m/s is studied. On the other hand, a high-rise building with the ratio of height to width of H/W = 3 is considered. Computations are performed numerically by means of the finite volume approach. Several results are obtained in the present numerical study. For example, it is found that due to wind-structure vertical interaction, locations with enhanced velocities are developed on the building roof in which the rate of this enhancement increases with increasing the wind speed. In addition, over the building, “lines C and D” are realized as the best locations having high power potentials and low turbulence intensities. In addition, lateral wind-structure interaction revealed that for all wind speeds, location of L/W = 0.5 is the best for the small wind turbine installation.     

Possibility of converting indigenous Salvadora persica L. seed oil into biodiesel in Pakistan

In this research study, biodiesel has been successfully produced from vegetable seed oil of an indigenous plant Salvadora persica L. that meets the international biodiesel standard (ASTM D6751). The biodiesel yield was 1.57 g/5 g (31.4% by weight) and the in-situ transesterification ester content conversion was 97.7%. The produced biodiesel density was 0.894 g/mL, its kinematic viscosity 5.51 mm²/s, HHV 35.26 MJ/kg, flash point 210°C, cetane no. 61, and sulfur content 0.0844%. Thermal analysis of the biodiesel showed that 97% weight loss was achieved at 595°C with total oxidation of the biodiesel. The production energy efficiency was 0.46% with a lab scale setup, assuming the volume fraction ratio (volume of the sample/total volume of the equipment used). The results revealed that single-step in-situ transesterification method is suitable for the production of biodiesel from S. persica seed oil.     

CONFIDENCE INTERVALS FOR FLOOD EVENTS UNDER A PEARSON 3 OR LOG PEARSON 3 DISTRIBUTION1

ABSTRACT: The Pearson type 3 (P3) and log Pearson type 3 (LP3) distributions are very frequently used in flood frequency analysis. Existing methods for constructing confidence intervals for quantiles (X_p) of these two distributions are very crude. Most of these methods are based on the idea of adjusting confidence intervals for quantiles Y_p of the normal distribution to obtain approximate confidence inervals for quantiles X_p of the P3/LP3 distribution. Since there is no theoretical reason why this “base” distribution, Y, should be taken to be normal, we search in the present study for the best possible base distribution for producing confidence intervals for P3/LP3 quantiles. We consider a group of base distributions such as the normal, log normal, Weibull, Gumbel, and exponential. We first assume that the skew coefficient, γ of X, to be known, and develop a method for adjusting confidence intervals for Y_p to produce approximate confidence intervals for X_p. We then compare this method (Method A) with another method (Method B) introduced by Stedinger. Simulation shows that the performance of each of these two methods depends on the base distribution Y that is being used, but as a whole, the normal distribution appears to be the best-fit distribution for producing confidence intervals for P3/LP3 quantiles when γ is assumed to be known. We then extend our method (Method A) to the more important case of unknown coefficient of skewness. It is shown that by taking Y to be Weibull, fairly accurate confidence intervals for P3/LP3 quantiles can be obtained for quite a wide range of sample sizes and coefficients of skewness commonly found in hydrology. The case of the P3 distribution with negative skewness needs further research.     

Model-Based Assessment of Aspen Responses to Elk Herbivory in Rocky Mountain National Park,USA

In Rocky Mountain National Park (RMNP), aspen (Populus tremuloides Michx.) has been observed to be declining on elk (Cervus elaphus nelsoni) winter range for many decades. To support elk management decisions, the SAVANNA ecosystem model was adapted to explore interactions between elk herbivory and aspen dynamics. The simulated probability of successful vegetative regeneration for senescent aspen stands declines sharply when elk densities reach levels of 3–5 elk/km², depending on model assumptions for the seasonal duration of elk foraging activities. For aspen stands with a substantial component of younger trees, the simulated regeneration probability declines more continuously with increasing elk density, dropping below 50% from densities at 8–14 elk/km².At the landscape scale, simulated aspen regeneration probability under a scenario of extensive seasonal use was little affected by elk population level, when this level was above 300–600 elk (25%–50% current population) over the ca. 107 km² winter range. This was because elk distribution was highly aggregated, so that a high density of elk occupied certain areas, even at low population levels overall. At approximately current elk population levels (1000–1200 elk), only 35%–45% of senescent aspen stands are simulated as having at least a 90% probability of regeneration, nearly all of them located on the periphery of the winter range. Successful management for aspen persistence on core winter range will likely require some combination of elk population reduction, management of elk distribution, and fencing to protect aspen suckers from elk browsing.     

深圳大气污染特征模拟及环境容量估算

本文根据深圳市8 个监测站点2013 年的逐日PM₁₀ 和PM_2.5 浓度监测数据、气象数据,统计风向、风速、稳定度联合频率等,利用污染物在大气中输送扩散模式,由实测的浓度值反推出污染物的产生量或排放量的方法,重点分析龙华新区PM₁₀ 和PM_2.5 的污染特征,并依据环境目标值,估算该区域剩余环境容量。研究结果表明,龙华新区全年盛行东风、南风,其风频分别为16.7%、13.2%,风速约为1.6m/s,PM₁₀、PM_2.5 浓度均呈现出季节性变化,秋、冬季浓度值较高,尤其在10 月到次年1 月份,其排放强度主要受本地污染源的影响。除此以外,其西、北部的污染源对其污染物浓度有一定的影响。新区PM₁₀ 和PM_2.5 的剩余环境容量均呈现负值,尤其以PM_2.5 最为突出,须大力加强减排控制,以达到环境目标值