scholarly journals The Network of Dominant Owners of Wind Development in Galicia (Spain) (1995–2017): An Approach Using Power Structure Analysis

Energies ◽  
2020 ◽  
Vol 13 (22) ◽  
pp. 6080
Author(s):  
Rosa María Regueiro-Ferreira ◽  
Xoán R. Doldán-García
Keyword(s):  
Structure Analysis ◽  
Political Institutions ◽  
Wind Farm ◽  
Wind Farms ◽  
Power Structure ◽  
International Investment ◽  
Investment Funds ◽  
The Matrix ◽  
Local Companies ◽  
The Individual

This article identifies and characterizes the network of dominant businesses which owned wind farms in Galicia (Spain) from 1995 to 2017. This research contributes to reduce the research gap about identifying the investment groups involved and to appreciate the real size of the wind sector. The novelty of the research lies in identifying the network of real owners of wind farms through the application of Domhoff’s power structure analysis, normally used in the analysis of the power structure of corporations and political institutions. With this method, it is possible to observe how the individual wind farm companies are assessed as well as the matrix company, and/or the principal shareholders to which the farm belongs are identified. The article shows that the installed wind power in Galicia is owned by large energy firms with the participation of international investment funds as well, even though the smaller number of local companies in the sector were given favored status under the existing regulations. This study concludes that although there is no single worldwide model for wind promotion, a network of dominant owners has been formed, and that this network consists of energy companies, investment funds, financial institutions, and construction firms. It can be surmised that if the capital were of mostly Galician origin, this would facilitate a bigger reinvestment of the profits in the region.

Wind farm cooperative control for optimal power generation

2018 ◽  
Vol 42 (6) ◽  
pp. 547-560 ◽  
Author(s):  
Fa Wang ◽  
Mario Garcia-Sanz
Keyword(s):  
Power Generation ◽  
Wind Turbines ◽  
Cooperative Control ◽  
Wind Farm ◽  
Wind Farms ◽  
Practical Method ◽  
Individual Case ◽  
Power Coefficient ◽  
The Individual ◽  
Large Wind

The power generation of a wind farm depends on the efficiency of the individual wind turbines of the farm. In large wind farms, wind turbines usually affect each other aerodynamically at some specific wind directions. Previous studies suggest that a way to maximize the power generation of these wind farms is to reduce the generation of the first rows wind turbines to allow the next rows to generate more power (coordinated case). Yet, other studies indicate that the maximum generation of the wind farm is reached when every wind turbine works at its individual maximum power coefficient CPmax (individual case). This article studies this paradigm and proposes a practical method to evaluate when the wind farm needs to be controlled according to the individual or the coordinated case. The discussion is based on basic principles, numerical computations, and wind tunnel experiments.

scholarly journals Sustainability Challenges of Wind Power Deployment in Coastal Ceará State, Brazil

2020 ◽  
Vol 12 (14) ◽  
pp. 5562
Author(s):  
Júlio César Holanda Araújo ◽  
Wallason Farias de Souza ◽  
Antonio Jeovah de Andrade Meireles ◽  
Christian Brannstrom
Keyword(s):  
Environmental Impact ◽  
Wind Power ◽  
Political Institutions ◽  
Migrant Workers ◽  
Wind Farm ◽  
Qualitative Interviews ◽  
Wind Farms ◽  
Host Community ◽  
Northeastern Brazil ◽  
Sustainability Challenges

Sustainable and socially just decarbonization faces numerous challenges, owing to high land demands for wind farms and weak economic and political institutions. In Brazil, a leader in the Global South in terms of rapid installation of wind power capacity since the 2001 electricity crisis, firms have built wind farms near host communities that are politically and economically marginalized, giving rise to numerous forms of subtle contention and overt opposition. We aimed to better understand the licensing materials for wind farms and the content of the host communities’ concerns about wind farms. We analyzed 18 “simplified” environmental impact reports, which created a legal path for wind farm construction, and conducted qualitative interviews in host communities in coastal Ceará state in northeastern Brazil. Our analysis reveals how firms appropriated and manipulated “crisis” in their environmental impact reports. Interviews with host community members reveal themes of ecological damage, fear, privatized land, employment, migrant workers and noise, in addition to evidence of active resistance to wind farms. These findings corroborate previous work on the overall nature of host community perceptions, add additional insight on the content of the licensing materials and expand the number of host communities analyzed for emerging sustainability challenges. More rigorous licensing procedures are needed to reduce corrupt practices, as well as the offering of avenues for community participation in the decision-making processes and eventual benefits of the wind farms.

scholarly journals Data-Driven Decentralized Algorithm for Wind Farm Control with Population-Games Assistance

Energies ◽  
2019 ◽  
Vol 12 (6) ◽  
pp. 1164 ◽  
Author(s):  
Julian Barreiro-Gomez ◽  
Carlos Ocampo-Martinez ◽  
Fernando Bianchi ◽  
Nicanor Quijano
Keyword(s):  
Power Generation ◽  
Wind Farm ◽  
Control Strategies ◽  
Wind Farms ◽  
Data Driven ◽  
Population Games ◽  
Decision Variables ◽  
Control Scheme ◽  
The Individual

In wind farms, the interaction between turbines that operate close by experience some problems in terms of their power generation. Wakes caused by upstream turbines are mainly responsible of these interactions, and the phenomena involved in this case is complex especially when the number of turbines is high. In order to deal with these issues, there is a need to develop control strategies that maximize the energy captured from a wind farm. In this work, an algorithm that uses multiple estimated gradients based on measurements that are classified by using a simple distributed population-games-based algorithm is proposed. The update in the decision variables is computed by making a superposition of the estimated gradients together with the classification of the measurements. In order to maximize the energy captured and maintain the individual power generation, several constraints are considered in the proposed algorithm. Basically, the proposed control scheme reduces the communications needed, which increases the reliability of the wind farm operation. The control scheme is validated in simulation in a benchmark corresponding to the Horns Rev wind farm.

scholarly journals A Review of Approaches for the Detection and Treatment of Outliers in Processing Wind Turbine and Wind Farm Measurements

Energies ◽  
2020 ◽  
Vol 13 (16) ◽  
pp. 4228
Author(s):  
Mingzhe Zou ◽  
Sasa Z. Djokic
Keyword(s):  
Wind Farm ◽  
Wind Farms ◽  
General Term ◽  
Accurate Information ◽  
Negative Effects ◽  
Outlier Removal ◽  
Outlier Identification ◽  
Operational Characteristics ◽  
The Common ◽  
The Individual

Due to the significant increase of the number of wind-based electricity generation systems, it is important to have accurate information on their operational characteristics, which are typically obtained by processing large amounts of measurements from the individual wind turbines (WTs) and from the whole wind farms (WFs). For further processing of these measurements, it is important to identify and remove bad quality or abnormal data, as otherwise obtained WT and WF models may be biased, or even inaccurate. There are wide ranges of both causes and manifestations of these bad/abnormal data, which are often denoted with the common general term “outlier”. This paper reviews approaches for the detection and treatment of outliers in processing WT and WF measurements, starting from the discussion of the commonly measured parameters, variables and resolutions, as well as the corresponding requirements and recommendations in related standards. Afterwards, characteristics and causes of outliers reported in existing literature are discussed and illustrated, as well as the requirements for the data rejection in related standard. Next, outlier identification methods are reviewed, followed by a review of approaches for testing the success of outlier removal procedures, with a discussion of their potential negative effects and impact on the WT and WF models. Finally, the paper indicates some issues and concerns that could be of interests for the further research on the detection and treatment of outliers in processing WT and WF measurements.

Modeling Large-Scale Wind Farms for Reliability Analysis Considering Wake Effect

2014 ◽  
Vol 543-547 ◽  
pp. 647-652
Author(s):  
Ye Zhou Hu ◽  
Lin Zhang ◽  
Pai Liu ◽  
Xin Yuan Liu ◽  
Ming Zhou
Keyword(s):  
Power Generation ◽  
Wind Speed ◽  
Wind Power ◽  
Large Scale ◽  
Wind Farm ◽  
Wind Farms ◽  
Wind Power Generation ◽  
Wake Effect ◽  
Effect Model ◽  
The Individual

Large scale wind power penetration has a significant impact on the reliability of the electric generation systems. A wind farm consists of a large number of wind turbine generators (WTGs). A major difficulty in modeling wind farms is that the WTG not have an independent capacity distribution due to the dependence of the individual turbine output on the same energy source, the wind. In this paper, a model of the wind farm output power considering multi-wake effects is established according to the probability distribution of the wind speed and the characteristic of the wind generator output power: based on the simple Jenson wake effect model, the wake effect with wind speed sheer model and the detail wake effect model with the detail shade areas of the upstream wind turbines are discussed respectively. Compared to the individual wake effect model, this model takes the wind farm as a whole and considers the multi-wakes effect on the same unit. As a result the loss of the velocity inside the wind farm is considered more exactly. Furthermore, considering the features of sequentially and self-correlation of wind speed, an auto-regressive and moving average (ARMA) model for wind speed is built up. Also the reliability model of wind farm is built when the output characteristics of wind power generation units, correlation of wind speeds among different wind farms, outage model of wind power generation units, wake effect of wind farm and air temperature are considered. Simulation results validate the effectiveness of the proposed models. These models can be used to research the reliability of power grid containing wind farms, wind farm capacity credit as well as the interconnection among wind farms

A Study of a Wind Farm Power System

2002 ◽  
Author(s):  
E. Muljadi ◽  
Y. Wan ◽  
C. P. Butterfield ◽  
B. Parsons
Keyword(s):  
Power Systems ◽  
Power System ◽  
Wind Farm ◽  
Wind Farms ◽  
Case Scenario ◽  
Worst Case ◽  
Different Types ◽  
Wind Power System ◽  
The Individual ◽  
Conventional Power Plant

A wind power system differs from a conventional power system. In a conventional power plant, the operator can control the plant’s output. The output of a wind farm cannot be controlled because the output fluctuates with the wind. In this study, we investigated only the fixed-frequency induction generator, often used with wind turbines. We adopted the worst-case scenario and conducted a per-phase, per-turbine analysis. Our analysis showed a strong interaction among the wind farm, the utility grid, and the individual generator. In this paper, we investigate the power-system interaction resulting from power variations at wind farms using steady-state analysis. We use the characteristic of a real windsite on a known weak grid. We present different types of capacitor compensations and use phasor diagrams to illustrate the characteristics of these compensations. The purpose of our study is to provide wind farm developers with somc insights on wind farm power systems.

Statistical Post-Processing with Standardized Anomalies and Variable Selection for Wind Farm Forecasts

2020 ◽  
Author(s):  
Markus Dabernig ◽  
Alexander Kann ◽  
Irene Schicker
Keyword(s):  
Variable Selection ◽  
Wind Farm ◽  
Mesoscale Model ◽  
Wind Farms ◽  
Selection Method ◽  
Post Processing ◽  
Variable Selection Method ◽  
Wind Park ◽  
The Individual ◽  
Different Sources

<p>Numerical weather predictions are often too coarse to represent single turbines in a wind park and post-processing of the individual turbines is necessary. However, individual post-processing can lead to inconsistencies in forecasts for a wind farm. Using standardized anomalies allows to forecast all turbines simultaneously. Therefore, a climatological mean is subtracted from observations/predictions and then divided by a climatological spread which eliminates any site-specific characteristics.</p><p>Additionally, different sources of input can be used, such as variables from a global model, a mesoscale model or observations to improve forecasts. However, to prevent overfitting a variable selection method is needed to determine the most important predictors. The combination of standardized anomalies and a variable selection method provides a convenient method for good forecasts of wind farms.</p>

Evaluating Community Engagement and Benefit-Sharing Practices in Australian Wind Farm Development

2017 ◽  
Vol 1 (1) ◽  
pp. 1-6 ◽  
Author(s):  
Nina Lansbury Hall ◽  
Jarra Hicks ◽  
Taryn Lane ◽  
Emily Wood
Keyword(s):  
Community Engagement ◽  
Community Involvement ◽  
Wind Farm ◽  
Social Acceptance ◽  
Wind Farms ◽  
Clean Energy ◽  
Benefit Sharing ◽  
Delphi Panel ◽  
Government Organizations

The wind industry is positioned to contribute significantly to a clean energy future, yet the level of community opposition has at times led to unviable projects. Social acceptance is crucial and can be improved in part through better practice community engagement and benefit-sharing. This case study provides a “snapshot” of current community engagement and benefit-sharing practices for Australian wind farms, with a particular emphasis on practices found to be enhancing positive social outcomes in communities. Five methods were used to gather views on effective engagement and benefit-sharing: a literature review, interviews and a survey of the wind industry, a Delphi panel, and a review of community engagement plans. The overarching finding was that each community engagement and benefit-sharing initiative should be tailored to a community’s context, needs and expectations as informed by community involvement. This requires moving away from a “one size fits all” approach. This case study is relevant to wind developers, energy regulators, local communities and renewable energy-focused non-government organizations. It is applicable beyond Australia to all contexts where wind farm development has encountered conflicted societal acceptance responses.

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