Building Wind Farms Research Articles

Processos de vulnerabilização de empreendimentos eólicos em comunidade camponesa no Agreste Meridional de Pernambuco

ABSTRACT Amid sustainable agendas, renewable energy sources play a strong role, especially wind energy. However, the implementation of wind farms produces transformations in communities, causing impacts in different areas and vulnerability processes. The study aims to problematize the reports of the peasant population regarding the processes of vulnerability in the area of influence of the implementation of wind farms in a municipality in Pernambuco. This is an observational, descriptive research with a qualitative approach, carried out in a peasant community, located in the municipality of Caetés, Pernambuco, Brazil. Data collection was carried out through semi-structured interviews. Data analysis was based on the content analysis technique in the thematic modality. It was observed that the arrival and operation of the wind turbines coincided with the emergence of signs and symptoms, such as hearing and skin problems, anxiety, dizziness and headache. This situation allows us to consider a probable connection between the impacts caused by wind towers, already described in the literature, and those present in the participants’ reports. Prudence is necessary when planning and building wind farms, since such health problems can be temporary or permanent, leading the local community to constant suffering.

Elaboration of a Generalized Mixed Model for the wind speed distribution and an assessment of wind energy in Algerian Coastal regions and at the Capes

Understanding and evaluating wind energy involves various steps, including the observed temporal and directional variations in wind speed, choosing a suitable Probability Density Function (PDF) to describe wind regimes, and selecting an appropriate location for building wind farms. The wind speed data archived from nine meteorological stations along the northern coast of Algeria from 2017 to 2021 was used as a dataset to achieve these purposes. Zero-inflated mixed model (ZIMM) has been elaborated to model the wind speed regimes that combine two processes. The first process consists of mixing two PDFs that generate the counts data. The second process generates the residual zero-counts data. The estimation of ZIMM parameters is obtained with the Expectation–Maximization algorithm. ZIMM performances were evaluated at the selected sites using the commonly used goodness of fit (GOF) metrics: coefficient of determination (R2), root mean square error (RMSE), sum of square error (SSE), Kolmogorov–Smirnov (KS), Akaike information criterion (AIK), Bayesian Information Criterion (BIC), and compared with the widespread single PDFs: the two parameters Weibull, generalized extreme value (GEV) and Normal–Weibull mixed model. The datasets are used as input for assessing wind power and the feasibility of wind power plants in 24 Algerian Capes where the data is unavailable, using the Wind Atlas Analyses and Application Program (WAsP) and three different wind turbines, namely Nordex N50, Bonus B54, and Nordex N60. The results show significant variations in diurnal, monthly, and seasonal mean wind speed and power density. According to all GOF, the ZIMM PDF model outperforms conventional PDFs and the mixed model at the nine meteorological stations. The Bonus B54 wind turbine has the best capacity factor (Cp) with the lowest electrical production cost of all Algerian Capes, and the Cp exceeds 0.3 at 15 Capes from the 24 analyzed Capes. The highest Cp, about 0.467 with an annual electric production that reaches 4.09 GWh/year, is obtained at Cape Takouch with the lowest electrical production cost of 0.0414 $/kWh and 2.032 Kton/year of CO2 emission avoided.

Wind farms dry surface soil in temporal and spatial variation.

Wind energy is renewable and clean; however, the long-term operation of wind turbines can affect local climates. Soil moisture affects ecosystem balance, so determining the impact of wind farms on soil moisture is important. However, there has been little research on this, and only the impacts of wind farms on climate and vegetation have been considered. This study focuses on wind farms located in the grasslands of China. We analyzed changes in soil moisture in different wind directions and seasons and then judged the impacts of wind turbine operation on soil moisture. Our research shows that the operation of wind turbines will cause significant drying of soil, and this drought effect differs significantly according to season and wind direction. Our results show that 1) the soil moisture within wind farms decreases most significantly, with a decrease of 4.4 % observed; 2) in summer and autumn, the declines in soil moisture in the downwind direction are significantly greater than those in the upwind direction, with the opposite occurring in spring. (3) Wind farms aggravate the soil drying in grassland areas, which may have impacts on grassland ecosystems. Therefore, when building wind farms, we need to better understand their impacts on the environment.

WIND RESOURCE ASSESSMENT IN SOUTHERN ALBANIA: DATA COMPARISONS FROM THE BALKAN AND NEW EUROPEAN WIND ATLASES

This article describes a new method to more accurately evaluate the wind potential of 5 areas of interest in southern Albania. Using the WAsP simulation program, the authors were able to compare the wind data from the Balkan Wind Atlas (BWA) and the New European Wind Atlas (NEWA) to real wind measurements in Mamaj, Tepelenë, and showed that NEWA is closer to real wind conditions in Albania than BWA. Furthermore, by analyzing wind speed, power density and wind direction, the authors illustrate BWA and NEWA match closely in the five areas of interest in Albania, although BWA tends to overestimate wind potential more. The wind power class was evaluated and four from the five areas of interest were deemed appropriate for establishing wind farms. The authors analyzed eight different wind turbine types and identified the wind turbine with the highest capacity factor for the region to be SG 2.1-114 wind turbine. The potential electricity production from the proposed wind farms was evaluated using the RETScreen Expert program. This research allows for experts to more confidently use wind atlas data to evaluate wind potential in the region of Southern Albania. Finally, these results confirm the electricity potential from building wind farms in the areas of interest, which will contribute to the fulfillment of energy demand in the country and reduce imports in the energy sector.

Anticipating and defusing the role of conspiracy beliefs in shaping opposition to wind farms

Reaching net-zero targets requires massive increases in wind energy production, but efforts to build wind farms can meet stern local opposition. Here, inspired by related work on vaccinations, we examine whether opposition to wind farms is associated with a world view that conspiracies are common (‘conspiracy mentality’). In eight pre-registered studies (collective N = 4,170), we found moderate-to-large relationships between various indices of conspiracy beliefs and wind farm opposition. Indeed, the relationship between wind farm opposition and conspiracy beliefs was many times greater than its relationship with age, gender, education and political orientation. Information provision increased support, even among those high in conspiracy mentality. However, information provision was less effective when it was presented as a debate (that is, including negative arguments) and among participants who endorsed specific conspiracy theories about wind farms. Thus, the data suggest preventive measures are more realistic than informational interventions to curb the potentially negative impact of conspiracy beliefs.

A multi-criteria GIS-based model for wind farm site selection with the least impact on environmental pollution using the OWA-ANP method.

Wind energy is considered one of the most efficient and cost-effective ways to generate electricity, since it has a low environmental impact. So, it is essential to identify the best places to build wind farms that have the lowest impact on human health and the highest performance. In order to determine the appropriate locations for the construction of wind power plants, in the study first, the interpolation maps of the most important parameters for the construction of wind power plants were created. Then, using the analytic network process (ANP) method due to higher accuracy than other weighting methods (the two-by-two comparison of external and internal data), the weight of each criterion was determined by establishing the external and internal relationships between the criteria and sub-criteria. In this study, since the objective was to prepare land suitability maps with different levels of risk in order to further manage the area, the OWA method was used to prepare land suitability maps. Based on the results of the ANP method for weighing each parameter, wind speed and protected areas were the most and least important parameters to build the power plant. According to the results of the OWA method, 0.78 and 0.1% of the area were suitable for building power plants at high and low risk levels, respectively. The study also found that the number of wind turbines that can be built in the region at both high and low risk levels was 422 and 75, respectively. Using the buffer function, the number of turbines for the construction of high-risk power plants was reduced to 284 by using the appropriate distance from residential areas. The ANP and OWA methods were used to prepare several maps for the evaluation of land suitability with different levels of risk, one of which could be used for the construction of a power plant.

Habitat use by post-fledging white-tailed eagles shows avoidance of human infrastructure and agricultural areas

Habitat use studies provide invaluable information for the conservation of species that suffer from habitat loss or degradation. We used satellite telemetry to study the habitat use of white-tailed eagles (Haliaeetus albicilla) in relation to six habitat classes (artificial surfaces, agricultural areas, forests, semi-natural areas, wetlands and waterbodies) and five forest age classes (0–9, 10–19, 20–59, 60–99 and ≥ 100 years old) during the post-fledging period in Finland. The post-fledging period, defined here as the period between fledging and dispersal from the natal area, is a critical life-history stage. Our primary objective was to provide information that could be integrated into landscape planning, including wind-energy development (which poses a threat to white-tailed eagles). We found that the habitat classes that were selected by the young white-tailed eagles were forests, semi-natural areas (i.e., transitional woodland and bare rock) and wetlands. When using forests, the eagles selected stands of 0–9 years old, presumably due to the use of retention trees surrounded by a clear-cut as perching sites. Conversely, the habitat classes that were avoided were artificial surfaces, agricultural areas and (the immediate vicinity of) waterbodies. We conclude that the conversion of natural habitats into built and agricultural areas is detrimental to young white-tailed eagles because it reduces habitat availability. They, however, appear to be capable of using forests recently impacted by forestry if perch trees are present. Careful landscape planning is needed to protect priority habitats and avoid conflicts with an expanding white-tailed eagle population (e.g., by building wind farms in areas already environmentally disturbed).

Behavior of a Monopod Bucket Foundation Subjected to Combined Moment and Horizontal Loads in Silty Sand

AbstractKorea has started to build wind farms in the Yellow Sea, with the seabed consisting of a thick silty sand deposit. It is therefore important to understand the behavior of potential foundati...

A Hybrid RCS Reduction Method for Wind Turbines

Wind turbine towers produce significant scatterings when illuminated by radars. Their reflectivity affects air traffic control, military surveillance, vessel tracking, and weather data sensing processes. Reducing the radar cross-section (RCS) of wind turbines is an essential task when building wind farms. It has been proved that round and bumpy structures can scatter radar waves and reduce the RCS of a reflector. Other research showed that taper towers generate smaller radar returns than cylindrical towers. In this research, we combine both strategies to devise a more effective method for designing wind turbine towers in the hope that their RCS can be further reduced. The test results reveal that the proposed method out-performs current reshaping methods. Wind turbine towers possessing taper shapes and periodic surface bumps deflect incident electromagnetic waves to insignificant directions. Thus, radar returns in the back-scattering directions decrease. Other experiments also verify that the proposed method maintains its effectiveness for radar waves with varying frequencies and polarization.

Public preferences for wind farms involving electricity trade and citizen engagement in Ireland

International trade in electricity from renewable sources can offer a flexible means by which EU member states can meet their country targets but to date in Ireland initiatives to build wind farms for export have been resolutely contested by affected communities. Using a discrete choice experiment (DCE), a survey of respondents living within 10 km of an existing wind farm is conducted to estimate the social impact of wind turbines designed to produce electricity for export under different levels of financial benefit and participation. Most respondents are willing to make trade-offs to allow for an export market but financial compensation required is greater for exports compared to domestic supply. Respondents prefer greater levels of participation than currently offered but favour moderate levels of participation in the absence of financial benefits. Respondents that had a positive experience of living next to an existing wind farm in terms of financial benefits, employment and community representation are generally more accepting of wind farms. Conversely, subjects with a strong sense of place attachment or a less convincing experience in terms of financial benefits and participation were less tolerant of wind farms and more likely to pick the status quo of no new wind farm development.

Neural Networks Model to Detect Wind Turbine Dynamics

Wind has always represented a source of energy for human being. Currently, companies all over the world invest huge capital to build wind farms with the aim of obtaining the maximum possible economic return. Therefore, the identification of sites with the greatest windiness is necessary. These sites often reside in rural areas where the environmental impact of wind turbines, especially the noise impact, is significant. In this study, measurements of the noise emitted by several wind turbines located in South Italy were made. A selected range of the average spectral levels in a 1/3 octave band was used to identify the wind turbine operating conditions. A model based on neural network for detection operating conditions of the wind turbines was hence developed and applied. The results show the high accuracy of the forecast and identification model and suggest the adoption of this tool for several other applications.

Hysteretic behavior of grouted connections in offshore wind turbine support structures

Grouted connections (GCs) with shear keys have been widely applied in various offshore wind turbine support structures. The urgent energy demand in Eastern China makes building wind farms in offshore earthquake areas vital, however, the hysteretic behavior of the GCs has not been studied in depth. In this paper, three GC specimens were tested under different constant axial loads and cyclical horizontal forces. The different axial loads, i.e. the axial compression ratios were considered as the control parameter. The displacement ductility, energy dissipation capacity, and stiffness degradations of the specimens are discussed in detail. The results showed that an increasing axial compression ratio has detrimental effects on the hysteretic performance of GCs. It was also found, however, that all GC specimens exhibited favorable ductility and energy dissipation capacity, even the ones with high axial compression ratios. This indicates that GCs with shear keys are applicable for offshore support structures in seismic regions. Furthermore, finite element analyses in ABAQUS were conducted and compared with the experimental results. It was found that the numerical models could predict the hysteretic performance and crack propagation process of GCs. These models could be implemented in further parameter studies.

A hierarchical fuzzy data envelopment analysis for wind turbine site selection in Indonesia

The Indonesian archipelago has several suitable areas for building wind farms. In the site selection process, apart from wind intensity, there are other factors related to geographical and structural technicality that need to be considered. This research presents a hierarchical fuzzy data envelopment analysis model for identifying suitable locations for the construction of wind farms. The proposed hierarchy consists of two levels that are defined based on the 165 districts and 33 provinces in Indonesia based on data provided by different government organizations. Opinions from experts in different areas were collected and represented by the hesitant fuzzy linguistic term sets, which were converted to optimistic and pessimistic preferences by using linguistic aggregation and, later, integrated to the data envelopment analysis model. Principal component analysis by IBM SPSS was used to verify the importance of the factors that can reduce ineffective indicators from the analysis. The results show that the South Sumatra province has the highest potential for construction of wind farms, especially in the district of Palembang. The West Papua, Papua, and Maluku provinces have descending priority based on good infrastructure accessibility, high wind velocity, and lesser susceptibility to natural disasters.

Wind Turbine Site Selection in Indonesia, based on a hierarchical Dual Data Envelopment Analysis model

Due to an increasing demand of energy from renewable resources, wind energy is of high demand, especially in areas that have constant high wind intensity. Indonesia is considered an archipelago, where there are many areas that are suitable for building wind farms. However, there are different factors that may affect the site selection for a wind farm. In this study, we propose a hierarchical dual data envelopment analysis (DDEA) model that can be used to identify the suitable location for building a wind farm. Important factors related to geographical and structural technicality are considered in the analysis. Locations from each region of Indonesia were selected at both district and provincial levels. Districts and provinces are considered for decision-making units (DMUs) which are evaluated for efficiency scores based on the DDEA method. The DDEA method is a multi-criterion and non-parametric estimation method that can be used to measure DMU performances. The proposed hierarchy consists of two levels, which are defined based on 165 districts and 33 provinces in Indonesia. The results show that South Sumatra province has the highest potential for construction of wind farms, especially in the district of Palembang. West Papua, Papua, and Maluku provinces have descending priority based on good infrastructure accessibility, high wind velocity, and are less prone to natural disaster.

Etyczne aspekty budowy siłowni wiatrowych

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Impact of key factors on expected development of onshore wind energy sector in Poland and development scenarios

The aim of the paper was to analyse the wind power market in Poland by reviewing the factors that shape and influence its current state and the possible development prospects. The paper was focused on legislative, environmental, manufacturing, sociocultural and economic factors. Barriers to the development of onshore wind power market and the expected development of wind energy in Poland in the years 2017-2020 were identified and measured based on a survey. The review of individual factors and the study performed present that legislative barriers and the introduction of the ‘distance act’ are factors with the biggest influence on the current stagnation of onshore wind energy sector. A review of the recommendations concerning the distance (from protected areas and housing) required to build wind farms set forth in literature shows that Poland is the only country with such harsh restrictions. With its good environmental conditions and technical capacities, Poland can become a European leader in the production of energy from wind. The only barrier is the legislative environment and political instability on the national level. Without improvements in this sector, there is no chance for new wind projects, as these factors are crucial for development of this type of energy.

High stress wet aging of cable dielectrics-meeting new challenges

The development of large wind farms is seen as a part of the solution to lowering global carbon emissions through bulk renewable energy generation, and in Europe many wind farms have mainly been constructed offshore where wind and land resources are advantageous compared to onshore sites. Whether onshore or offshore, lowering the cost of production is driving the industry to build wind farms with more turbines each capable of generating more power [1]–[4]. In the UK, the Offshore Windfarm Accelerator, a collaborative R&D program led by the Carbon Trust, is aiming to reduce the cost of wind generation by 10% through a combination of technological advances.

An Improved Adaptive-Torque-Gain MPPT Control for Direct-Driven PMSG Wind Turbines Considering Wind Farm Turbulences

Maximum power point tracking (MPPT) plays an important role in increasing the efficiency of a wind energy conversion system (WECS). In this paper, three conventional MPPT methods are reviewed: power signal feedback (PSF) control, decreased torque gain (DTG) control, and adaptive torque gain (ATG) control, and their potential challenges are investigated. It is found out that the conventional MPPT method ignores the effect of wind turbine inertia and wind speed fluctuations, which lowers WECS efficiency. Accordingly, an improved adaptive torque gain (IATG) method is proposed, which customizes adaptive torque gains and enhances MPPT performances. Specifically, the IATG control considers wind farm turbulences and works out the relationship between the optimal torque gains and the wind speed characteristics, which has not been reported in the literature. The IATG control is promising, especially under the ongoing trend of building wind farms with large-scale wind turbines and at low and medium wind speed sites.

Locating of Wind Power Farms by Analytic Hierarchy Process Method (Case Study: Sistan and Baluchistan Province, Iran)

Limitation of fossil energy reserves in the world and increasing level of energy consumption, have always challenged human to replace new energy sources. Meanwhile, wind power as one of the new aspects of energy is of a special place. Due to the topography of the Sistan and Baluchistan province and its relative position, it is one of the best places to build wind farms. The aim of this study was to determine suitable locations for the construction of wind farms in the province. The following criteria were considered for various standards and due to the importance of data integration, Analytic Hierarchy Process (AHP) method was selected and implemented to weight the layer through Expert choice software. ArcGIS was used for layers spatial analysis and overlapping. After data analysis, the studied region, in terms of the susceptibility to build wind farms, was divided into four levels: excellent, good, fair, weak. Results indicated that GIS as a supportive and decision making system is helpful preparing data and modeling priorities and experts comments regarding various factors and help designers selecting a suitable place to build wind farms. In this study, we determined three priorities for the construction of wind farms, taking into account the limited overlap and conformity of limitations map and locating, the area of prioritized region, climate and the field observations; the priority order is excellent, good, average, including Zabol, central regions in Zabol and Chabahar.

Should we build wind farms close to load or invest in transmission to access better wind resources in remote areas? A case study in the MISO region

Wind speeds in remote areas are sometimes very high, but transmission costs to access these locations can be prohibitive. We present a conceptual model to estimate the economics of accessing high quality wind resources in remote areas to comply with renewable energy policy targets, and apply the model to the Midwestern grid (MISO) as a case study. We assess the goal of providing 40TWh of new wind generation while minimizing costs, and include temporal aspects of wind power (variability costs and correlation to market prices) as well as total wind power produced from different farms. We find that building wind farms in North/South Dakota (windiest states) compared to Illinois (less windy, but close to load) would only be economical if the incremental transmission costs to access them were below $360/kW of wind capacity (break-even value). Historically, the incremental transmission costs for wind development in North/South Dakota compared to in Illinois are about twice this value. However, the break-even incremental transmission cost for wind farms in Minnesota/Iowa (also windy states) is $250/kW, which is consistent with historical costs. We conclude that wind development in Minnesota/Iowa is likely more economical to meet MISO renewable targets compared to North/South Dakota or Illinois.