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.     

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.     

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.     

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.     

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.     

A Single-Use Site Selection Technique, Using GIS, for Aquaculture Planning: Choosing Locations for Mangrove Oyster Raft Culture in Margarita Island, Venezuela

Oyster culture has a potential to generate income for coastal communities and to lessen pressure on natural overexploited populations. A project to transfer mangrove oyster Crassostrea rhizophorae raft culture technology to selected coastal communities in Margarita Island, Venezuela is being developed, and an optimum location selection technique was devised. To pick the variables or factors that determine site suitability, a bibliographic database was made, aspects of interest chosen, and the most comprehensive ones singled out, eliminating redundant ones. Twenty variables were grouped in criteria based on the way they influence the project. Variables were classified as intrinsic environmental, environmental extrinsic, logistic, and socioeconomic criteria. Thirty-five experts were asked to evaluate the factors and to score each according to their suitability weight. Logistic criterion received the highest values, followed by environmental extrinsic issues. A Geographic Information System using a base map compiled from 1:25,000 scale maps was developed. A thematic map for each factor was completed, dividing graphically the 3896-km² study area into polygons of equal weight for each factor. The Multi-Criteria Evaluation (MCE) was used to combine the variables. Resultant vectors in thematic maps were added to obtain smaller polygons with the same value sum. Finally, MCE was used to generate a final output: the optimum sites for oyster aquaculture resulting from the added values of over 3000 polygons in the maps, for the 20 criteria. Higher scores were reached in 13 areas covering 4.1 km², those places having the optimum conditions for oyster raft aquaculture in the region. Additional locations meeting 75% to 70% of the demanded criteria for a final suitable selection cover 137 sites encompassing 37.5 km².     

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.     

Decision making under uncertainty using PEES–fuzzy AHP–fuzzy TOPSIS methodology for landfill location selection

The location selection for landfill municipal solid waste is an important issue in waste management. Selection of the optimal location requires consideration of multiple alternative solutions and evaluation factors because of system complexity. Further, ranking of the alternative locations and selection of the most optimal and efficient locations for landfill waste are an important multi-criteria decision-making problem. In this study, the candidate locations for landfill are determined based on Political, Economical, Environmental and Social factors are assessed through decision-makers’ opinion and by the methodology that incorporates fuzzy analytic hierarchy process (fuzzy AHP) and fuzzy technique for order preference by similarity to ideal solution (fuzzy TOPSIS). Specifically, the fuzzy AHP technique is applied to determine the weights of selected criteria impacting the location selection process, and the fuzzy AHP is adapted to model the linguistic vagueness and ambiguity, which can also be expressed as triangular fuzzy numbers. Furthermore, fuzzy TOPSIS technique is employed to rank the alternative locations. The applicability of this methodology is demonstrated by a case study of landfill waste location selection in the region of Casablanca, Morocco, and the results are compared with other techniques. Finally, to complete the treatment, a sensitivity analysis is performed to examine the impact of the preferences given by decision-makers to choose the best location.     

海上风电变流器应用环境因素分析

为了清晰认识风电变流器海上应用环境,阐述了海上风电的困难及生命周期可遇的环境因素,并选取对风电变流器有危害和影响的主要环境因素进行了分析,以便开发人员提前识别海上风电变流器的环境应力并作出相应的设计。     

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.     

Environmental management framework for wind farm siting: Methodology and case study

This paper develops an integrated framework to evaluate land suitability for wind farm siting that combines multi-criteria analysis (MCA) with geographical information systems (GIS); an application of the proposed framework for the island of Lesvos, Greece, is further illustrated. A set of environmental, economic, social, and technical constraints, based on recent Greek legislation, identifies the potential sites for wind power installation. Furthermore, the area under consideration is evaluated by a variety of criteria, such as wind power potential, land cover type, electricity demand, visual impact, land value, and distance from the electricity grid. The pair-wise comparison method in the context of the analytic hierarchy process (AHP) is applied to estimate the criteria weights in order to establish their relative importance in site evaluation. The overall suitability of the study region for wind farm siting is appraised through the weighted summation rule. Results showed that only a very small percentage of the total area of Lesvos could be suitable for wind farm installation, although favourable wind potential exists in many more areas of the island.     

Coherence between marine and land use planning: public attitudes to landscapes in the context of siting a wind park along the Latvian coast of the Baltic Sea

The aim of this paper is to contribute to coherence in marine, coastal and land use planning and management from the perspective of landscape values. At a time when new sea uses are emerging and marine spatial planning laws and regulations are being adopted, but have not yet been put into practice, research studies are required that provide spatial planners with informed insights concerning public stakeholder attitudes to controversial policies. The undertaken research explored the attitudes of two important social groups (local residents and tourists/recreational users) regarding locating wind parks in the marine and/or terrestrial environment along the Latvian coast of the Baltic Sea. The results of the study indicate that both groups support land-based wind park development versus offshore. Moreover, the visibility of wind turbines influences the willingness of tourists to visit recreation sites and impacts directly on their duration of stay. Research findings indicate that policy makers and spatial planners from both marine and land domains should adopt a broader and more integrated approach when setting priorities and allocating space for development activities where both domains are involved.     

江苏沿海风能资源禀赋与开发利用研究

江苏沿海地区拥有丰富的风能资源,开发前景十分广阔,尤其是中部、南部地区拥有广阔的沿海滩涂和辐射沙洲,建设沿海风电场的条件优越,是打造江苏"海上三峡"新能源基地的希望所在。阐述了江苏沿海风能资源开发的重要意义,分析了沿海风能资源的禀赋与时空分布特点,指出江苏沿海岸区风能资源丰富,且沿海滩涂宽广,是建立大型风力发电场的理想之地,在此基础上提出发展江苏沿海绿色能源基地的构想。     

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.     

Short-term wind speed forecasting: Application of linear and non-linear time series models

This study forecasts day-ahead wind speed at 15 minute intervals at the site of a wind turbine located in Maharashtra, India. Wind speed exhibits non-stationarity, seasonality and time-varying volatility clustering. Univariate linear and non-linear time series techniques namely MSARIMA, MSARIMA-GARCH and MSARIMA-EGARCH have been employed for forecasting wind speed using data span ranging from 3 days to 15 days. Study suggests that mean absolute percentage error (MAPE) values first decrease with the increase in data span, reaches its minima and then start increasing. All models provide superior forecasting performances with 5 days data span. It is further evident that ARIMA-GARCH model generates lowest MAPE with 5 days data span. All these models provide superior forecasts with respect to current industry practices. This study establishes that employing various linear and non-linear time series techniques for forecasting day-ahead wind speed can benefit the industry in terms of better operational management of wind turbines and better integration of wind energy into the power system, which have huge financial implications for wind power generators in India.     

Economic and employment impacts of offshore wind for Ireland: A value chain analysis

ABSTRACT

The imminent development of a number of offshore wind farms in the Republic of Ireland presents a sizable opportunity to stimulate the Irish economy through the growth of an indigenous and globally competitive offshore wind supply chain. This study uses a value chain analysis to evaluate the economic and employment potential of the offshore wind sector for Ireland. The analysis is based on the expenditure on products and services required to develop an offshore wind farm, the planned capacity of projects in the pipeline, and the ability of Irish companies to supply the sector. Results suggest that by 2030, 2.5–4.5GW of domestic offshore wind development could create between 11,424 and 20,563 supply chain jobs and generate between €763 m and €1.4bn in gross value added. This is the first study to estimate domestic GVA potential for the sector.     

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.     

Optimization of grid tied hybrid power system in smart premises

Tapping of renewable energy sources like solar and wind is given great priority by power producers all over the world. Technical problems of linking them to the grid are solved. The cost constraints of utilizing renewable energy at specific locations are to be determined. In this work, a model is developed for grid tied hybrid power system (HPS) consisting of photovoltaic (PV) module and wind mill at the roof top of smart premises. The grid is capable of delivering and receiving energy. Objective function is formed with constraints taking into account the cost of PV module, wind mill, and grid tied inverter with controller. The constraints are rating of HPS and energy that can be delivered to the grid. Using this model, case studies were conducted in three locations in India, each location having two different demands. The results are presented. With the optimal rating of HPS, results shows that, conventional energy cost is higher.     

Estimation of the effect of the degree of sewage treatment on the status of pollution along the coastline of the Mediterranean Sea using broad scale modelling

A preliminary investigation was performed to estimate the effect of the degree of treatment in Sewage Treatment Plants (STPs) on the status of pollution along the coastlines of the Mediterranean Sea. Data from questionnaires and the literature were collected and processed (a) to identify 18 approximate 1D surface coastal currents, (b) to estimate their prevailing direction and average flow velocity and (c) to estimate the water pollution loads and identify their locations of discharge. Then, a simplified 1D water quality model was formulated and applied for the existing conditions and two hypothetical scenarios: (1) all coastal cities have STPs with secondary treatment and (2) all coastal cities have STPs with tertiary treatment to determine BOD(5), TN and TP concentrations in the 18 surface coastal currents. Calculated concentrations were compared and discussed. A main conclusion is that, to reduce pollution in the Mediterranean Sea measures should be adopted for upgrading the water quality of the rivers discharging into the Mediterranean Sea, along with the construction of STPs for all the coastal cities.     

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.