Location Of Wind Turbines Research Articles

Assessment of earthing system location for wind turbines using finite element method

A new proposal for the assessment of earthing system location used for wind turbines is presented. This proposal depends on the simulation of the electric field as well as the calculation of current density at the ground surface above the earthing system and distribution inside the soil when the wind turbine is exposed to high voltage. The electrical potential simulation around the earthing system of wind turbine using ring earth electrode with and without auxiliary vertical rods was also studied. Accurate calculations and simulation of the electric field are prerequisite for the simulation of current density. The electric field distribution is obtained by calculating the electric potential in three-dimensional domain surrounding the earthing system using Finite Element Method. The boundary conditions satisfy both Dirichlet's and Neumann's equations. The simulated electrodes are energized with one per unit voltage to be available for different types of applied potential. The resistance of the earthing system is calculated. This simulation model shows reasonably close agreement which gives confidence in predicting the assessment of the earthing grid location which is around 66.6% out of the total depth length of the affected domain. Different types of soils were checked to satisfy this ratio of the location assessment. The results showed that the vertical component of electrical field intensity and current density were improved at the assessment location of the earthing grid.

A computational platform for considering the effects of aerodynamic and seismic load combination for utility scale horizontal axis wind turbines

The wide deployment of wind turbines in locations with high seismic hazard has led engineers to take into account a more comprehensive seismic design of such structures. Turbine specific guidelines usually use simplified methods and consider many assumptions to combine seismic demand with the other operational loads effecting the design of these structures. As the turbines increase in size and capacity, the interaction between seismic loads and aerodynamic loads becomes even more important. In response to the need for a computational tool that can perform coupled simulations of wind and seismic loads, a seismic module is developed for the FAST code and described in this research. This platform allows engineers working in this industry to directly consider interaction between seismic and other environmental loads for turbines. This paper details the practical application and theory of this platform and provides examples for the use of different capabilities. The platform is then used to show the suitable earthquake and operational load combination with the implicit consideration of aerodynamic damping by estimating appropriate load factors.

Drones scout out locations for energy-generating wind turbines

Along the northern coasts of Germany, wind turbines speckle the landscape, capitalizing on the flat, breezy countryside to generate renewable energy. But this region is far from the country’s industrial core, so the energy created here has to be transported across a great distance—an inefficient process. In contrast, the hilly Swabian Alps, which enjoy plenty of wind, directly border Germany’s industrial core. You might think this would be the ideal place for Germany’s wind energy installations. The problem here is that wind turbines work optimally when the breeze blows horizontally. And entrepreneurs worry that the wind turbulence created by the region’s undulating hills could kibosh the efficiency, and thus the success, of new wind energy installations. Here’s where drones equipped with turbulence sensors can help. These drones have the ability to scout out spots where the wind blows strongly and horizontally enough for turbines to be practical. Satellites don’t have

Effect of atmospheric stability on the estimation of wind power potentiaEffect potential

Analyzing the impact of atmospheric stability on vertical wind profile enables to assess the available wind resource in order to determine optimal locations for wind turbines. Different methods have been proposed to study the degree of stability of the atmosphere. These include the Richardson number, the profile method and the Monin-Obukhov length. Focus is here on the stability issue and its influence on the wind shear coefficient which plays an important role in processing experimental data with regards to the atmospheric surface-layer turbulence. Data collected from the Cabauw meteorological mast were analyzed in order to determine the characteristics of the wind resource at that location and to estimate the wind resource for power generation as affected by stability.

基于SBM模型的风机设备制造商竞争优势效率评价

近年来中国的本土风机整机制造商面临着越来越激烈的国内市场竞争，本文基于SBM模型和企业生态位理论建立了竞争优势评价指标体系，并以金风科技等7家上市公司为代表，运用实际数据对其进行了量化评估的实证研究。研究表明，该评价指标体系在实践应用中具有可行性。 In recent years, the competition between Chinese local wind turbine manufacturers (LWTMs) is increasingly fierce in domestic market. This paper has led to the design and establishment of a LWTMs’ Competitive Advantages Evaluation Index System according to Data Envelopment Analysis (DEA) method and Enterprise Niche Theory. Then the paper makes empirical research based on 7 listed representative enterprises’ annual reports using SBM model. The results show that the evaluation index system is practicable for application.

A Model Proposal for Locating Wind Turbines

Total energy demand has increased all around the world in recent years, as a result of growing population and industrialization. Most of the existing sources to generate energy are fossil fuels and it is known that fossil fuels are scarce. In order to satisfy increasing energy demand, searches for new energy generation sources have been conducted and these searches are ended with the proposal of generation of energy by using renewable sources. Decision makers are facing with some important decision problems related to energy generation from renewable sources. In the scope of this study, site selection problem which is one of the most important problems related to renewable energy is considered. Site selection decision consists of many alternatives and many conflicting decision criteria. Due to the hesitance of decision makers in criteria evaluation, a decision making approach based on hesitant fuzzy sets is proposed for solution of the problem. Weights of evaluation criteria for locating wind turbines are obtained by using the proposed decision making approach.

Design of optimal wind farm configuration using a binary particle swarm optimization at Huasai district, Southern Thailand

This paper proposes the design of optimal wind farm configuration using a new wind probability distribution map at Huasai district, the east coast of Southern Thailand. The new wind probability distribution map integrates both frequency of wind speed and direction data at a monitoring site. The linear wake effect model is used to determine the wind speed at downstream turbines for the total power extraction from a wind farm array. The component cost model and learning curve is used to express the initial investment cost, levelized cost and the annual energy production cost of a wind farm, depending on the number of wind turbines, the installed size, hub height and wake loss within a wind farm. Based on Thailand wind energy selling price consisting of the fixed wind premium on top of base tariff, the profit depends on revenue of selling electricity and cost of energy. In this paper, Binary Particle Swarm Optimization with Time-Varying Acceleration Coefficients (BPSO-TVAC) is proposed to maximize profit subject to turbine position, turbine size, hub height, annual energy production, investment budget, land lease cost, operation and maintenance cost and levelized replacement cost constraints. Test results indicate that BPSO-TVAC optimally locate wind turbines directly facing the high frequent wind speed and direction, leading to a higher profit than the conventional wind farm layout.

Simulation of wake effects of windfarms using an Actuator Disk implementation

AbstractWind turbines extract energy from the approaching flow field resulting in reduced wind speeds, increased turbulence and a wake downstream of the wind turbine. Wakes extending up to 20 km downstream of a windfarm are reported [1]. In [2] a multi‐scale numerical method is proposed that addresses length scales of the boundary layer, windfarm and meso‐scale. As a step towards full realization of the multi scale approach the implementation of an Actuator Disk (AD) model into OpenFOAM including a proper atmospheric boundary layer (ABL) is presented. For a meso‐scale area of open sea, the standard ABL conditions of OpenFOAM can not be used. The pre implemented ABL boundary condition for OpenFOAM is restricted to roughness lengths greater than 0.001 m. The boundary condition are modified in order to achieve adequate homogeneous flow properties throughout the considered domain enabling almost constant velocity profiles. A new AD class is implemented in OpenFOAM to establish an arbitrary number and location of windturbines. The class uses the standard k‐ϵ turbulence model. The wake effect of windfarms composed of windturbines with different heights and different lateral spacing is investigated. Specifically the windfarm Trianel Borkum in the North Sea of Germany is simulated. Within this work wakes extending up to 20 km in length could be observed, suggesting to study the ABL‐windfarm interaction in more detail. (© 2015 Wiley‐VCH Verlag GmbH & Co. KGaA, Weinheim)

Gone with the wind? The impact of wind turbines on tourism demand

While wind energy production is relatively free from environmental externalities such as air pollution, it is frequently considered to negatively impact landscapes' visual aesthetic values, thereby inducing negative effects on tourism demand. Existing evidence for Germany indeed points towards a negative relationship between tourism demand and wind turbine construction. However, the existing studies primarily rely on interview data and simple bivariate statistics. In contrast, we make use of secondary statistics on tourism and wind turbine locations at the level of German municipalities. Using spatial panel regression techniques, we confirm a negative relation between wind turbines around municipalities and tourism demand for municipalities not located near the coast. In the latter regions, the relation between wind turbines and tourism demand is more complex.

Effects of wind farms on Montagu's harrier (Circus pygargus) in southern Spain

To study the potential impact of wind turbines and associated structures on Montagu's harriers Circus pygargus, we located 111 nests over five years (18–28 nests per year) and compared their distances to several features (natural and anthropogenic) between wind farm pre- and post-construction periods using a before–after (BA) study design. We analysed abundance and density of nests and colonies through the study period. We also fitted a predictive model of nest occurrence using distance-to-feature variables and habitat as predictors. Lastly, Montagu's harrier fatalities from collision with wind turbines were estimated. No differences were detected between pre- and post-construction periods in nest or colony abundances. We found that harriers nested closer to the locations of wind turbines and power lines after wind farm construction, although distance to closest track did not change. We detected a higher spatial aggregation of Montagu's harrier nests after wind farms were installed, when the distribution of nests was mostly explained by habitat and distance to the closest track. Distance to wind turbine was apparently not influential. Fatality through collision was relatively uncommon during the study period. Our findings demonstrate that the construction, operation and maintenance of wind farms did not seem to adversely affect Montagu's harrier nesting decisions in our study area. However, we encourage further studies including reproductive parameters and foraging strategies of Montagu's harrier to provide a complete investigation of potential impacts of wind farms on this species.

Optimization of the Wind Turbines Location in Kaberten Wind Farm in Algeria

This paper consists in the study of a wind farm intended for the production of the electrical energy in the southwest of Algeria exactly in Adrar. The region of Adrar possesses a big wind potential which need to be exploited and optimized. Our study consists in optimizing the location of wind turbines in the park of Kaberten and in reducing the losses due to the effect of trail by using the GH WindFarmer and WAsP software. Ten turbines (10 x 1 MW) were used on the GH WindFarmer, to determine the best positions of wind generators. The results of simulations are presented and discussed.

Distributed Model Predictive Control of a Wind Farm for Optimal Active Power ControlPart II: Implementation With Clustering-Based Piece-Wise Affine Wind Turbine Model

This paper presents distributed model predictive control (D-MPC) of a wind farm for optimal active power control using the fast gradient method via dual decomposition. The objectives of the D-MPC control of the wind farm are power reference tracking from the system operator and wind turbine mechanical load minimization. The optimization of the active power control of the wind farm is distributed to the local wind turbine controllers. The D-MPC developed was implemented using the clustering-based piece-wise affine wind turbine model. With the fast gradient method, the convergence rate of the D-MPC has been significantly improved, which reduces the iteration numbers. Accordingly, the communication burden is reduced. A wind farm with ten wind turbines was used as the test system. Case studies were conducted and analyzed, which include the operation of the wind farm with the D-MPC under low and high wind conditions, and the dynamic performance with a wind turbine out of service. The robustness of the D-MPC to errors and uncertainties was tested by case studies with consideration of the errors of system parameters.

A Two-Echelon Wind Farm Layout Planning Model

In this paper, a two-echelon layout planning model is proposed to determine the optimal wind farm layout to maximize its expected power output. In the first echelon, a grid composed of cells with equal size is utilized to model the wind farm, whereas the center of each cell is the potential slot for locating a wind turbine. Optimization models are developed to determine the optimal size of grid cells and the optimal cells for locating wind turbines. In the second echelon, the selected grid cells are then translated to sets of Cartesian coordinates. The model for determining the optimal coordinate rather than the center in a grid cell for locating each wind turbine is formulated. Due to the model complexity in both echelons, the random key genetic algorithm (RKGA) and particle swarm optimization (PSO) algorithm are applied to obtain the optimal solutions in the first and second echelon separately. The comparative analysis between the proposed two-echelon planning model and the traditional grid/coordinate-based planning models is conducted.

DFIG-based offshore wind power plant connected to a single VSC-HVDC operated at variable frequency: Energy yield assessment

The existence of HVDC (High Voltage Direct Current) transmission systems for remote offshore wind power plants allows devising novel wind plant concepts, which do not need to be synchronized with the main AC grid. This paper proposes an OWPP (offshore wind power plant) design based on variable speed wind turbines driven by DFIGs (doubly fed induction generators) with reduced power electronic converters connected to a single VSC-HVDC converter which operates at variable frequency and voltage within the collection grid. It is aimed to evaluate the influence of the power converter size and wind speed variability within the WPP on energy yield efficiency, as well as to develop a coordinated control between the VSC-HVDC converter and the individual back-to-back reduced power converters of each DFIG-based wind turbine in order to provide control capability for the wind power plant at a reduced cost. To maximise wind power generation by the OWPP, an optimum electrical frequency search algorithm for the VSC-HVDC converter is proposed. Both central wind power plant control level and local wind turbine control level are presented and the performance of the system is validated by means of simulations using MATLAB/Simulink®.

Layout optimization for maximizing wind farm power production using sequential convex programming

This paper describes an efficient method for optimizing the placement of wind turbines to maximize the expected wind farm power. In a wind farm, the energy production of the downstream wind turbines decreases due to reduced wind speed and increased level of turbulence caused by the wakes formed by the upstream wind turbines. As a result, the wake interference among wind turbines lower the overall power efficiency of the wind farm. To improve the overall efficiency of a wind farm, researchers have studied the wind farm layout optimization problem to find the placement locations of wind turbines that maximize the expected wind farm power. Most studies on wind farm layout optimization employ heuristic search-based optimization algorithms. In spite of their simplicity, optimization algorithms based on heuristic search are computationally expensive and have limitation in optimizing the locations of a large number of wind turbines since the computational time for the search tends to increase exponentially with increasing number of wind turbines. This study employs a mathematical optimization scheme to efficiently and effectively optimize the locations of a large number of wind turbines with respect to maximizing the wind farm power production. To formulate the mathematical optimization problem, we derive a continuous wake model and express the expected wind farm power as a continuous and smooth function in terms of the locations of the wind turbines. The constructed wind farm power function is then maximized using sequential convex programming (SCP) for the nonlinear mathematical problem. We show how SCP can be used to evaluate the efficiency of an existing wind farm and to optimize a wind farm layout consisting of 80 wind turbines.

Optimum hub height of a wind turbine for maximizing annual net profit

The optimization method of the hub height, which can ensure the economic feasibility of the wind turbine, is proposed in this study. Annual Net Profit is suggested as an objective function and the optimization procedure is developed. The effects of local wind speed and wind turbine power characteristics on the optimum hub height are investigated. The optimum hub height decreased as the mean wind speed and wind shear exponent increased. Rated power had little effect on optimum hub height; it follows that the economies of scale are negligible in the rated power range of 0.75–3MW. Among the wind turbine power characteristics, rated speed and cut-out speed most strongly affected the optimum hub height.

Wind turbines location: How many and how far?

Abstract Existing research relating to visual impact of wind turbines (WTs) affirms this to be an essential parameter for public acceptance in most cases as well as for the planning process and permitting of planned wind farms. This study brings new findings about the impact of two crucial factors: numbers of WTs (1–25) visible and distances of WTs (0.75–15 km) from the observer (e.g. from residential buildings, landmarks, observation points). Photographs of three aesthetically varying landscapes with various numbers of WTs (Vestas V90, height 105 m, rotor diameter 90 m) at various distances were evaluated in terms of visual preferences. The results show significant effect from the aesthetic value of a given landscape on the impact of both tested factors. An important finding is that the landscape with the highest aesthetic quality initially was evaluated to be the absolute worst after the addition of WTs and vice versa. Increasing numbers of WTs in the least attractive landscape had less visual impact than did doing so in the two more attractive landscapes. This helps explain strong public opposition to locating WTs in aesthetically valuable landscapes and their greater acceptance in less-attractive landscapes. Increasing stepwise from 1 to 25 WTs within a given landscape progressively decreased visual preferences, although the cumulative effect of a higher number of WTs was not confirmed. We also established threshold distances after which the negative visual impact of a WT disappeared (10 km for the most attractive landscape, 5 km for the least attractive one). Based on these findings, visibility zones were proposed for practical assessment of WTs’ visual impact. The study’s results can make a substantial contribution towards reducing negative visual impact in WT planning and thus achieving greater public acceptance of these devices.

Evaluating the accuracy of CFSR reanalysis hourly wind speed forecasts for the UK, using in situ measurements and geographical information

Climate data can be used in simulations to estimate the output of wind turbines in locations where meteorological observations are not available. We perform the most comprehensive evaluation of the NCEP CFSR reanalysis model hourly wind speed hindcasts to date, and the first for the UK, by correlating the data against 264 onshore and 12 offshore synoptic weather stations, over a period of 30 years. The correlation of CFSR data to in situ measurements is similar to alternative approaches used in other studies both onshore and offshore. We investigate the impact of the topography, land use and mean wind speed on the onshore locations for the first time. The analysis of these spatial factors shows that CFSR represents the variety of terrain over UK well, and that the worst correlated sites are those at the highest elevations.

Effects of climate oscillations on wind resource variability in the United States

Natural climate variations in the United States wind resource are assessed by using cyclostationary empirical orthogonal functions (CSEOFs) to decompose wind reanalysis data. Compared to approaches that average climate signals or assume stationarity of the wind resource on interannual time scales, the CSEOF analysis isolates variability associated with specific climate oscillations, as well as their modulation from year to year. Contributions to wind speed variability from the modulated annual cycle (MAC) and the El Nino-Southern Oscillation (ENSO) are quantified, and information provided by the CSEOF analysis further allows the spatial variability of these effects to be determined. The impacts of the MAC and ENSO on the wind resource are calculated at existing wind turbine locations in the United States, revealing variations in the wind speed of up to 30% at individual sites. The results presented here have important implications for predictions of wind plant power output and siting.

Optimal Wind Turbines Micrositing in Onshore Wind Farms Using Fuzzy Genetic Algorithm

With the fast growth in the number and size of installed wind farms (WFs) around the world, optimal wind turbines (WTs) micrositing has become a challenge from both technological and mathematical points of view. An appropriate layout of wind turbines is crucial to obtain adequate performance with respect to the development and operation of the wind power plant during its life span. This work presents a fuzzy genetic algorithm (FGA) for maximizing the economic profitability of the project. The algorithm considers a new WF model including several important factors to the design of the layout. The model consists of wake loss, terrain effect, and economic benefits, which can be calculated by locations of wind turbines. The results demonstrate that the algorithm performs better than genetic algorithm, in terms of maximum values of net annual value of wind power plants and computational burden.