Installed Wind Energy Capacity Research Articles

Explainability in wind farm planning: A machine learning framework for automatic site selection of wind farms

The process of wind farm site selection involves complex considerations spanning environmental, economic, and social factors, often handled through multi-criteria decision making (MCDM) methods. However, MCDM approaches face several challenges. To address these, integrating machine learning (ML) techniques offers promise. Nevertheless, existing studies have yet to employ a standalone ML-based approach for this purpose. This study seeks to pioneer an explainable ML-based framework for automated wind farm site selection. The framework incorporates feature selection techniques, seven ML algorithms, statistical tests, and a local explainability method. The experimental area was chosen as Balıkesir province, which hosts 13% of Türkiye's installed wind energy capacity. According to the prediction performances of the ML models, Extreme Gradient Boosting-XGBoost has the highest accuracy (0.9607), followed by Light Gradient Boosting Machine-LightGBM (0.9580), Random Forest-RF (0.9518), Histogram-based Gradient Boosting-HGB (0.9387), Classification and Regression Trees-CART (0.8946), Logistic Regression-LR (0.8856), and Naive Bayes-NB (0.8456). Additionally, McNemar’s tests revealed statistically significant differences among ML models. Based on the explanations provided by SHapley Additive exPlanations, wind speed, distance to transmission lines, distance to protected zones, and elevation were the top contributing criteria. Moreover, analysis revealed regions with elevated wind speeds, higher elevations, and closer proximity to transmission lines and protected areas as favorable for wind farm installation. The study's outcomes indicate strong agreement (97%) between current wind turbine locations and those identified as suitable by ML models. Within Balıkesir province, our research has identified a significant number of highly suitable areas where wind turbines have not yet been installed. These findings underscore the critical importance of these locations for future investments in wind farm development. The proposed framework could be highly efficient for wind farm siting studies in provinces that share similar characteristics with the study area used in this study offering a robust tool for future wind farm siting studies. Finally, the study contributes to achieving UN SDG 7 by employing ML to refine wind farm site selection, thereby facilitating the transition towards sustainable and universally accessible energy.

From Tinkerers to Consultants: Individual Engagement, Reunification and the Making of Germany’s Renewable Energy Sector

The article seeks to explain how and why reunified Germany saw a hundred-fold increase in its installed wind energy capacity during the 1990s. It argues that the development was largely due to private individuals’ practical work to solve local energy supply problems with wind power, and their later efforts to make renewable energy generation a worthwhile investment. The article begins by contrasting the East and West German governments’ understanding of renewables with that of individual advocates. It shows how different renewables looked from the top down than they did from the bottom up. It then shows how renewable advocates’ individual, entrepreneurial approach became accepted across the newly reunified Federal Republic of Germany in the early 1990s, meaning that the ‘wind boom’ of the 1990s went hand-in-hand with the emergence of the renewable energy sector as a business interest. This article was published open access under a CC BY-NC-ND 4.0 licence: https://creativecommons.org/licenses/by-nc-nd/4.0/ .

Nigerian wind energy status

This review paper evaluates the current status of the Nigeria wind energy sector to identify the available Wind Energy Potential, Installed Wind Energy Capacity and Renewable Energy Policies in a bid to provide accurate information to aid the exploration and exploitation of wind energy across Nigeria. Consequently, the huge expanse between the wind energy Potential across Cities in Nigeria, the poor numbers of installed wind capacity and Nigeria’s Renewable Energy policies show low interest in Wind Energy in comparison to other RE sources. All this calls for further investment in the Nigerian wind energy sector

Economic and environmental factors of wind energy deployment in the United States

Among the most promising clean energy sources in the electricity market, wind energy has substantially increased its share in the global energy portfolio. Since 2000, the installed wind energy generation capacity in the United States has been multiplied by 50, from 2,377 megawatts to 117,744 megawatts in 2020. We investigate the economic and environmental factors that have relationships with the wind energy generation capacity growth in the United States between 2000 and 2020 using fixed-effects panel data analysis. Economic factors include gross state product, the value of the agricultural sector, and the unemployment rate. Environmental factors include carbon dioxide emissions, nitrogen oxide emissions, and water use. The empirical findings provide strong evidence that in the United States, an increase in economic factors (except unemployment) is related to a significant increase in the installed wind energy capacity. In contrast, the relationship between the air emissions and installed wind capacity is negative. The results for water use are not reported in the current study as these data did not satisfy all fixed-effects panel data analysis assumptions. These findings are expected to contribute to understanding how states might best stimulate and support wind energy deployment.

Potential impact of global stilling on wind energy production in China

The rapid increase in world's installed wind energy capacity may have masked the power loss caused by declining global surface wind speed (termed ‘global stilling’), particularly for China with huge wind energy investments. Here, we estimated the potential impact of global stilling on wind energy production in China, using data from 1226 meteorological stations between 1971 and 2015. We show that surface wind speeds have on average declined at a rate of 5.5% decade−1, while the corresponding wind power density dropped by 24.5% decade−1. Although the decline in wind speeds has slowed after 1991, the decline in wind power density did not show this slowdown. This was attributed to the absence of slowdown in the declining trend of strong winds. Compared with the wind speed levels in the 2000s, the mean capacity factor would have dropped from 20.7% in 2001 to 14.9% in 2015, with the largest absolute change in the “Three North” regions. Furthermore, wind electricity generation would have declined by 40 TWh/a using the installed capacity of 2015, representing a decrease of 16%. The correlation analysis indicates that the decreased wind speed is most likely caused by changes in the large-scale atmospheric circulation rather than increased surface roughness.

Demographic and potential biological removal models identify raptor species sensitive to current and future wind energy

AbstractA central challenge in applied ecology is understanding the effect of anthropogenic fatalities on wildlife populations and predicting which populations may be particularly vulnerable and in greatest need of management attention. We used three approaches to investigate the potential effects of fatalities from collisions with wind turbines on 14 raptor species for both current (106 GW) and anticipated future (241 GW) levels of installed wind energy capacity in the United States. Our goals were to identify species at relatively high vs low risk of experiencing population declines from turbine collisions and to also compare results generated from these approaches. Two of the approaches used a calculated turbine‐caused mortality rate to decrement population growth, where population trends were derived either from the North American Breeding Bird Survey or from a matrix model parameterized from literature‐derived demographic values. The third approach was potential biological removal, which estimates the number of fatalities that allow a population to reach and maintain its optimal sustainable population set by management objectives. Different results among the methods reveal substantial gaps in knowledge and uncertainty in both demographic parameters and species‐specific estimates of fatalities from wind turbines. Our results suggest that, of the 14 species studied, those with relatively higher potential of population‐level impacts from wind turbine collisions included barn owl, ferruginous hawk, golden eagle, American kestrel, and red‐tailed hawk. Burrowing owl, Cooper’s hawk, great horned owl, northern harrier, turkey vulture, and osprey had a relatively lower potential for population impacts, and results were not easily interpretable for merlin, prairie falcon, and Swainson’s hawk. Projections of current levels of fatalities to future wind energy scenarios at 241 GW of installed capacity suggest some species could experience population declines because of turbine collisions. Populations of those species may benefit from research to identify tools to prevent or reduce raptor collisions with wind turbines.

The Cost of Wind: Negative Economic Effects of Global Wind Energy Development

This paper provides a structured literature review of the negative economic effects associated with the development of wind energy and synthesized the evidence at an abstract level. We then developed an analytical framework to systematically review economic issues such as volatility, electricity price, housing values, and unemployment in relation to wind energy. Global wind energy development data from the time period from 2000 through 2019 were included for a more robust analysis. This period encompasses the vast majority of total global installed wind energy capacity. After amalgamating evidence from existing studies and data banks, we discuss the policy implications, suggest avenues for future research, and propose solutions to mitigate externalities. By understanding the negative economic impact created by the expansion of wind energy, we can better equip policy makers and developers to create more efficient and sustainable energy policy to benefit citizens and preserve the environment for generations to come.

USA Wind Energy-Caused Bat Fatalities Increase with Shorter Fatality Search Intervals

Wind turbine collision fatalities of bats have likely increased with the rapid expansion of installed wind energy capacity in the USA since the last national-level fatality estimates were generated in 2012. An assumed linear increase of fatalities with installed capacity would expand my estimate of bat fatalities across the USA from 0.89 million in 2012 to 1.11 million in 2014 and to 1.72 million in 2019. However, this assumed linear relationship could have been invalidated by shifts in turbine size, tower height, fatality search interval during monitoring, and regional variation in bat fatalities. I tested for effects of these factors in fatality monitoring reports through 2014. I found no significant relationship between bat fatality rates and wind turbine size. Bat fatality rates increased with increasing tower height, but this increase mirrored the increase in fatality rates with shortened fatality search intervals that accompanied the increase in tower heights. Regional weighting of mean project-level bat fatalities increased the national-level estimate 17% to 1.3 (95% CI: 0.15–3.0) million. After I restricted the estimate’s basis to project-level fatality rates that were estimated from fatality search intervals <10 days, my estimate increased by another 71% to 2.22 (95% CI: 1.77–2.72) million bat fatalities in the USA’s lower 48 states in 2014. Project-level fatality estimates based on search intervals <10 days were, on average, eight times higher than estimates based on longer search intervals. Shorter search intervals detected more small-bodied species, which contributed to a larger all-bat fatality estimate.

The offshore-onshore conundrum: Preferences for wind energy considering spatial data in Denmark

Installed wind energy capacity has been increasing steadily across the world and is expected to continue to do so in the future, in response to lowering costs of technology as well as increased renewable energy goals put forth by governments. Nonetheless, public opposition has been increasing and the discussion regarding siting wind turbines onshore or offshore is consistently present in public discourse. In combining a stated preference study with spatial data processed via GIS (Geographic Information Systems), spatial preferences for onshore and offshore wind turbines are explored while considering their visual impact and costs as well as controlling for the respondents' socioeconomic characteristics. In general, respondents state strong preferences towards offshore wind turbines as opposed to onshore. Furthermore, spatial data is found to be significant with regard to the preferences of the respondents, particularly respondents' distance to the coast and potential offshore wind farms and the number of wind turbines seen from the residence and the number of turbines in the postal area. As a secondary result, findings suggest socioeconomic characteristics such as age and income are significantly related to respondents’ preferences, in line with previous research.

Overcoming barriers to onshore wind farm implementation in Brazil

Brazil has been failing to offer the most favorable conditions for the implementation of onshore wind farms, due to the presence of multiple barriers. However, the country has observed a fast and expressive wind energy (WE) diffusion (the installed WE capacity grew 37 times in the last decade). Furthermore, its onshore wind farms have reached impressive capacity factors (with productivity levels much higher than the average around the world) and a very low levelized cost of electricity. This study aims at identifying how wind developers plan onshore wind farms to overcome existing barriers. Based on forty-one interviews with relevant stakeholders of the Brazilian WE sector, the study identified efforts targeted at overcoming twenty-four previously identified barriers. Although most barriers may be overcome directly through developer initiatives, addressing higher level barriers, namely an unstable macroeconomic environment, a poor transmission infrastructure, and inadequate access to capital, depends on government actions.

Assessing the feasibility of wind energy as a power source in Turkmenistan; a major opportunity for Central Asia's energy market

While Asia as a continent has enjoyed nearly 40% of the total installed wind energy capacity, the contribution of some countries in the region is less significant. Turkmenistan as an important oil and gas producing country is a major exporter of electricity in the Central Asia region. The country has an enormous potential for wind and solar energy development overshadowed by its wealth of oil and gas. This paper aims to assess the wind energy potential of Turkmenistan by taking into account the hourly wind speed data of eighteen different locations in a typical meteorological year. The widely utilized and validated two-parameter Weibull distribution function is utilized for calculating the power and energy density of the locations in the country. Fifteen commercially available wind turbines are also employed and compared against each other in terms of annual power output, energy output, and capacity factor for the considered locations. Finally, the economic metric indicator of the levelized cost of energy (LCOE) is employed to assess the feasibility of the system. The obtained results are expected to be a guideline for investors and policymakers regarding the wind energy development in the country while showing a major opportunity for Central Asia's energy market in the future.

Lifetime Extension, Repowering or Decommissioning? Decision Support for Operators of Ageing Wind Turbines

In Germany, more than one third of the installed wind energy capacity will leave the feed-in tariff funding between 2021 and 2025. Operators of affected turbines are therefore increasingly concerned with the design of profitable end-of-funding strategies. This requires feasibility analyses of both lifetime extension and repowering options and entails the subsequent challenge to determine the optimal lifetime extension and corresponding repowering timing. To support operators and other stakeholders dealing with wind turbines’ end-of-life issues, this study presents a geographic information system that permits evaluating optimal end-of-funding strategies at different spatial scales reaching down to detailed analyses on individual turbine level. The decision support system processes topographic, wind, turbine, and finance data in an integrated system of resource simulations, spatial planning analyses and economic viability assessments. Case-study results show that a uniform end-of-funding strategy cannot be applied to all ageing turbines. Conducted sensitivity analyses rather indicate that the best strategy highly depends on various turbine-specific aspects, especially the location, type and maintenance costs as well as exogenous factors, including the developments of electricity spot market prices and tendered feed-in premiums. In light of latest trends regarding the exogenous factors, lifetime extension and repowering potentials increase. However, the results also indicate that dismantling, disposal and recycling of numerous ageing turbines will become a major challenge for the wind energy sector in the next decade.

Assessment of frequency performance by wind integration in a large‐scale power system

AbstractLarge‐scale grid integration of wind energy particularly in the southeastern portion of the Mexican interconnected power system has affected available transfer capability and imposed additional uncertainty on power system operation. Integrating large amounts of wind energy into the system is challenging because of the variability in power system dynamics and a more complex active and reactive power dispatch.Wind plants have been installed in the Mexican systems during the past few years. The total installed wind energy capacity of the system is around 2.5 GW; the total wind energy generation represents 4% of current installed generation in the Mexican system. Increase of the wind power is expected to have an impact on power system control and transient behavior, especially as the amount of wind generation represents a significant portion of the local generation and wind farms grow in size and complexity.Using recent planning and operation wind data, detailed studies on the effects of new wind generation on power system dynamic behavior are carried out. Analyses of the dynamic impact of large wind parks on power system dynamic performance are conducted. Operating impact studies include frequency behavior and the response of wind farms to major disturbances.Simulation studies on a realistic 4000‐bus dynamic model of the Mexican interconnected system show that large wind generating plants have a significant effect on system dynamic behavior.

Air pumping for alleviation of heavy smog in Beijing

Beijing often suffers under heavy smog. During such events which occur mostly in autumn and winter, people are desperate for fresh air. The formation of heavy smog is due to foremost human induced air pollution, but geographic and meteorological conditions, especially below a surface inversion, play an important role. We propose to destroy the inversion by pumping air from above the inversion layer to the surface layer to alleviate the severity of the smog. While long-term air quality improvement depends on the reduction of air pollution emission, air pumping may provide relief in the interim for the Beijing citizens. We estimate that an air pumping at a rate 2×107 m3 s–1 can lead to significantly improved air quality in Beijing, due to (1) direct clean air input; (2) increased instability and vertical mixing and (3) a positive radiation-mixing feedback. The pumping requires an energy input of 10 GW, comparable with the energy consumption in Beijing for air conditioning in summer. We propose to use wind energy from Inner Mongolia for the pumping, which has currently an installed wind energy capacity of 70 GW.

The technical potential for wind energy in Illinois

The demand for harnessing clean, renewable energy sources like wind energy has increased greatly over the past decade due to a confluence of political and environmental concerns. Although wind energy is recognized as a promising source of clean energy, some decision-makers are asking how much wind energy should ultimately be installed. As the level of installed wind energy capacity increases, it is possible that at some point the aggregated generation mix could produce electrical power exceeding electrical demand. This situation could require excessive generator curtailment. In this investigation several different criteria are explored to develop an optimum level of in-state wind energy penetration into the existing generation infrastructure. In this way, the benefit to society may be maximized. Three scenarios are studied: 1) a scenario in which the wind carve-out remains at 75% of the state's Renewable Portfolio Standard, 2) a scenario in which all of the wind energy that is generated must be fully utilized, and 3) a scenario in which wind energy is allowed to be curtailed at a rate equal to the rate that energy is used internally at thermal generation plants.

Extracting Maximum Power Optimization in Wind Turbine Using Neuro Fuzzy Logic Control

4 Abstract - Wind energy has steadily established itself as one of the most reliable and affordable renewable energy resources. Of the country's wind energy generation capacity of around 14,000MW per year, TN accounts for 6,547MW. Tamil Nadu has an installed wind energy capacity of 6,696 MW, which is 41 per cent that of the country. The paper presents an advanced prediction system that integrates models based on fuzzy-neural networks. The main objective of this paper is to fully control the wind turbine system with induction generator to maximize the power generation. The output power of a wind turbine is function of wind velocity cubed. The system has been optimized for operating around 15 m/s, and though the wind power continues to increase above this point. The advanced method to introduce the new ability of estimating variable speed control . By using the controller, the speed can be tuned until it get similar to the desired output that user need. In this paper, neural networks are used in a novel way to solve the problem of tuning a fuzzy logic controller. The neuron fuzzy controller uses the neural network learning techniques to tune the membership function. The aim is to ensure that by 2030, wind energy will be the most cost-efficient energy source on the market. However, with the growing demand for green electricity worldwide, rising turbine costs and increased competition to supply green electricity to the grid, wind farm operators must improve their existing power output. In India, the total installed capacity of wind power generation is 8754 MW in the year 2008.By the end of 2012, the total installed capacity is going to be reached to 12000 MW according to ministry of new and renewable energy, India and total installed capacity of wind energy is estimated to be more than 160 GW (WWEA) all around the world. The scopes include the simulation study, implementation of Neuron fuzzy logic controller to actual DC motor using MATLAB simulator.

Editorial

Renewable energy plays a key role in societal development, particularly given the increasing demand for energy coupled with pressing environmental and energy security issues. In January 2009, the European Commission announced that e500 m of the e5 bn economic recovery package will finance offshore wind energy projects. Additional support of e1.75 bn was pledged to energy infrastructure including strategic electric grid interconnectors, which are a vital component of expanding wind energy installations and integrating power from renewables into the European electricity network. Targets are ambitious. The European Wind Energy Association (EWEA) estimates that of the total 180 GW wind energy capacity expected to be installed in the European Union (EU) in 2020, between 20 and 40 GW will be offshore. EWEA projections are that of the total 300 GW of wind energy to be installed in the EU in 2030, half (150 GW) will be offshore. In 2007, installed wind energy capacity worldwide was 94 GW, with offshore capacity passing 1.0 GW. By the end of 2008, 1.5 GW of offshore wind was operating. Although the pace of developments offshore is not as fast as had been expected, due in part to financing issues, according to the EWEA, an additional 2.5 GW is under construction. Although not all plans may come to fruition, planned offshore wind farms in the EU by 2015 have a total capacity close to 30 GW. Plans for offshore developments are also well underway outside of the EU in Norway, the USA, China, Canada, India and Japan. In the space of less than 20 years from the first installation of an offshore wind farm, enormous progress has been made. From the 5 MW Vindeby wind farm with two rows of 450 kW turbines in 1991, the average size of an offshore wind farm will increase to over 100 MW in 2009, and the standard size of turbines will be at least 3.6 MW. This is therefore a good time to take stock of what has been learnt from offshore wind farm development, installation and operation over the past 5 years, a period that marks the transition from smaller research wind farms into large-scale commercial developments. Some of the challenges facing successful development of offshore wind energy are evident, focusing on the need for cost-effective and efficient solutions to resource and environment assessment, design of turbines and installation equipment, and creation of innovative safety-conscious operation and maintenance procedures. Other challenges relate to the desire of the market for an ever-increasing amount of low-carbon energy, but at costs that are difficult to match given the harsh physical environment in which the power of the wind must be harnessed. One challenge that is less evident is how to optimize the way in which the wind energy industry transforms from research-based activity to full-scale commercial production without losing vital links between research and commercial partners. In this special issue of Wind Energy, the authors share their experience in developing techniques and methods for all areas of offshore wind energy from public perception, environmental issues, meteorology, power prediction on resource time scales to short-term forecasting, economics, grid stability, operation and maintenance and design. In the first part of the special issue, we focus mainly on meteorological, environmental and social aspects of offshore wind energy. Despite the obvious success of wind energy to date, it is evident that research is required in the future to design turbines and wind farms at the most cost-effective size and form, and for increased efficiency in planning, integration and operation. In the second part of this special issue to be published later in 2009, we focus mainly on technical and design aspects of offshore wind energy. We hope this special issue will be a good reference collection for those working in the field of sustainable energy and encourage commercial, public and academic partners to continue to collaborate sharing ideas and results to promote the success of offshore wind energy.

Wind Energy Potential in Turkey

The aim of this paper is to investigate the wind energy potential in Turkey. In Turkey, wind energy has great potential. According to the Organization for Economic Cooperation and Development (OECD), Turkey theoretically has 160 Terra Watt hours (TWh) a year of wind potential, which is about twice as much as the current electricity consumption of Turkey. The technical potential of Turkey's wind energy is approximately 88,000 MW, its total established power is only 18.9 MW according to data for 2001. Turkey had a share of 0.11% in Europe's installed capacity in 2001. As seen in the table, the installed capacity of Turkey's wind energy has increased from 9 MW in 1998 tol9 MW in 2001. But the installed wind energy capacity is very small.

Three Decades of Renewable Electricity Policies in Germany

Of the large industrial countries, Germany is clearly leading with regard to new renewable energy sources, occupying the first rank in terms of installed wind energy capacity, and the second rank in photovoltaics. This capacity is not due to an exceptional natural resource base but to policy, despite the fact that this policy was conducted in a rather lukewarm fashion until 1997. This led to a remarkable expansion of this sector. The red-green coalition, in office since 1998, developed the vision of achieving 50 percent and more of electricity generated from RES by 2050, a goal that seems well accepted by the public but not by the established energy interests or the leaders of the conservative-liberal opposition, even though the cost appears to be comparatively modest. The article gives a historical account of German RES-E policy since 1974 and focuses in particular on the evolution of “feed-in” legislation from 1990 to 2004. The first 15 years of RES-E policy after 1974 were devoted to R&D. Market creation measures only came into effect after 1988; of these, the Feed-In Law was the most important. During the 1990s, it barely managed to survive, but significant improvement occurred after the 1998 election; the new majority greatly strengthened RES-E support, particularly for photovoltaics and biomass. However, this legislation is still not fully accepted on both the domestic and the EU levels.

Practical Wind Resource Assessment for Tayside Region in Scotland

This paper presents the results of a study which estimates the practical wind energy resource for the Tayside Region of Scotland. The study considered all technical, environmental and legislative factors relevant to wind energy development. Due consideration was also given to National Planning Policy Guideline (NPPG6): Renewable Energy and Planning Advice Note 45 (PAN45): Renewable Energy Technology, issued by the Scottish Office Environment Department, in addition to the policies of the planning authorities within Tayside with regards to such matters as development in National Scenic Areas and other designated areas. An area of 1290 km2 was identified as being the minimum practical resource which is free from environmental and technical constraints and which has sufficiently high wind speeds to make extraction of energy from the wind commercially viable. This area could accommodate an installed wind energy capacity of 9675 MW and produce 24.6 TWh of wind generated electricity per annum.