3.1. Multi-Category Analysis
Some authors consider different categories when analyzing repowering options for onshore wind power plants.
Table 2 summarizes these contributions and identified the categories to be considered by each work.
In 2001, Klunne et al. studied the partial repowering of individual wind turbines, or total repowering of wind plants in their entirety, considering the technical and political aspects in the Netherlands [
36]. To achieve the expected long-term installed capacity objectives by combining both repowering strategies, they foresee an increase of 512 MW of installed wind power capacity. In 2013, the National Renewable Energy Laboratory (NREL) developed a technical report also based on partial and total repowering in USA scenarios [
48]. This report used the NREL’s System Advisor Model (SAM) to predict the estimated cash flows for different electricity generation technologies. The partial repowering was less economically attractive considering the electricity generation. Similarly, Paul and Prabu [
57] carried out a total repowering assessment of a wind power plant made up of old 2–bladed wind turbines in Gudimangalam (India), considering technical and economic aspects. The total repowering was accomplished through several stages of partial repowering (i.e., replacement of only few of the turbines). In fact, the presented methodology optimized the partial repowering options, thus resulting in the best possible total repowering. The technical analysis was carried out using the WAsP software, and the economic feasibility was studied based on several economic indices, such as Annual Levelized Cost of Generation (ALCoG), PBP or IRR. In 2006, Moller analyzed the visual impact on landscapes and the population during a repowering period in Northern Jutland (Denmark) [
37]. A Geographical Information System (GIS) analysis was used to find relations among population, landscapes, and the wind turbine development from 1982 to 2007. The repowering of wind power plants was justified due to the increase in technological efficiency, but implied an irregular development regarding visual space and social/public ownership, which may reduce the wind installation acceptance. A similar study was conducted by Ohl and Eichhorn in 2010 in West Saxony (Germany), also using a GIS-based model [
39]. In this case, they evaluated the bio-physical and administrative siting requirements for wind turbines of specific sizes, with the characteristics of the land, finding severe difficulties due to the differences between the spatial planning policy for wind energy at the state level and the economic planning for wind energy at the federal level. GIS was also used in a work published in 2017, where Serri et al. [
59] studied repowering in Italy, taking into account technical and economic factors. They proposed three hypotheses: the real case (the capacity of each repowered plant is the same as the end-of-life plant) and two more fictitious scenarios: the capacity of each repowered plant was 1.5 and 2 times that of the end-of-life plant. An incentive fee of 10–25 €/MWh was estimated to be necessary to ensure that results were economically viable.
Meyerhoff et al. focused on environmental and social factors in two different regions of Germany (Westsachsen and Nordhessen) through choice experiments conducted in May and June 2008 [
38]. In total, they interviewed more than 700 people, providing three different choices of wind power plant (including the size of the wind turbines, minimum distance to residential areas, impact on red kite population and the monthly surcharge to the power bill). According to the interview results, people in Westsachsen and Nordhessen preferred wind turbines to be further away from residential areas and consider the wind turbines’ impact on biodiversity as negative. A similar study was conducted in 2015 by Frantal at the government level and members of society in the Czech Republic, including economic, social, environmental, and political factors [
50]. In total, 95% of the government respondents, from an economic point of view, accepted the repowering, while the community, 59 %. With regard to social factors, 95% of the government respondents rejected repowering due to the majority opposition of neighbors. The community rejected it (63%) due to the visual impact. In general, the positive impact on repowering is palpable in the results, compared to the negative ones.
In 2010, Sperling et al. proposed a wind energy support system that can coordinate several policy domains (i.e., financial, planning and administrative, and local and regional development perspectives), both to build new wind power plants and to repower old wind turbines [
40]. In this way, through the wide perspective obtained, it is possible to help develop and evaluate wind energy and planning policy by analyzing their effects on these fields. In 2011, Del Rio et al. [
42] analyzed the benefits, drivers, and barriers of repowering as well as the different experiences of leading countries in onshore wind power (Denmark, Germany, Spain, and California, USA). They extracted the main factors involved and carried out a multi-criteria analysis with political, technical, and economic factors. It showed that the capacity factor and investment costs were relevant variables within the repowering decision–making process. A similar study was also developed in 2011 by Himpler and Madlener, but focused on Denmark [
43]. The probability of annual repowering was determined from the income and investment costs, concluding that the uncertainty of the income costs is a relevant barrier in repowering, and a greater contribution of government incentives was vital. In 2015, Weiss et al. proposed several repowering scenarios for Germany [
54]. The first scenario was designed according to the height of the turbine limited by legislation (100 m); the rest of the scenarios were based on more modern technologies, without considering the height limitation. They found that the scenarios where height was not limited gave positive technical and economic results. Moreover, they concluded that laws had to be updated in parallel with technology or be mitigated with instruments of subsidies in order to favor repowering. Recently, Madlener et al. analyzed the evolution of the regulatory framework of RES laws in Germany, and proposed a model to determine the optimal moment to repower according to the EEG (’Erneuerbare Energien Gesetz’, Renewable Energy Law 2017), which also considers technical and economic factors [
64]. Economically, early repowering is more beneficial, and it is highly influenced by the rate granted at the beginning of the project. A case study developed in Spain by Castro et al. in 2011 highlighted the environmental and economic advantages of repowering [
41]. By using the existing civil infrastructures, a decrease in visual and acoustic impacts was obtained, whereas it increased the production and return on investment in less than 5 years. A similar study was also conducted by Madlener et al., but focused on Germany [
44]. The economic evaluation of repowering projects could be positive thanks to different aspects such as incentives, the simplification in the start-up process, the technical improvements, and the social acceptance caused mainly by changes in the tax legislation. Zimmermann et al. developed a methodology to optimize the repowering process, based on technical and environmental factors (CO
emissions), as well as energy demand. Such methodology was applied to different scenarios for Germany during the period 2002–2010 [
45].
Technical, economic, and political factors were studied in several papers published in 2013. Jansen identified which variables have the greatest influence on repowering in Germany [
46]. He indicated that the main variable in the repowering decision was the type of wind turbine chosen and, to a lesser extent, the incentive policies decreed until then in the country. Therefore, the viability of the project depended on the capacity–production relationship. Konstantinos analyzed the factors that influenced the early and necessary repowering of a wind power plant in Greece, caused by poor production results far from the initial forecasts of the project [
47]. New descriptive statistical studies of the wind resource in the area and the replacement of wind turbines with new technologies, using updated tools such as WAsP, guaranteed the viability of the project. Focusing on Spain, in [
49], it was concluded that public policies would significantly affect financial analysis. In fact, the repowering project would not be feasible in the absence of feed-in tariffs (FITs). Therefore, they are effective in promoting repowering. The most relevant variables in the decision to repower a wind power plant are greater productive efficiency, capital investments, and the increase in the installed capacity. On the other hand, operation and maintenance costs have a smaller influence on the repowering decision. A sensitivity analysis completed the investigation, identifying that, with a 1% increase in production, the effect on the Net Present Repowering Value (NPRV) was greater than the 1% decrease in investment costs per kWh.
The relationship between economic incentives decreed by different governments and the economic viability of the repowering of wind power plants was analyzed in 2015 in countries with high potential for repowering. In the case of Spain, Colmenar-Santos et al. showed that in many cases it is more feasible to repower than to construct new power plants [
51]. The costs of dismantling the eliminated turbines were absorbed by the production profits of the new wind turbines in more beneficial conditions with respect to wind potential. In fact, they emphasized that repowering required a specific framework, both technical and remunerative. In the case of India, Prabu et al. [
52] pointed out that government policies must evolve in order to benefit investors. They studied the economic advantages of partial repowering compared to total repowering, provided that the design of the new turbines is optimal according to the potential wind. In 2017, Romano et al. tried to resolve the dilemma about which the political instrument was the most appropriate in repowering from the point of view of uncertainty: quotas and FITs or British Renewable Obligation Certificates (ROCs), both mandatory [
58]. The methodology was based on a dynamic programming model, concluding that the price certainty according to FIT increased the probability of adopting new technologies, whereas an increase in capital costs did not affect the repowering of both instruments. Lie Dahl et al. carried out an analysis of the new turbines installed after repowering, compared to the existing turbines against the mortality of the birds in a wind power plant located in Norway [
53]. Different wind turbine models and separation among them were considered, highlighting the importance not only of the decrease in the number of turbines, but also their location. The best repowered plant, with 30 turbines (5 MW), would reduce the collision risk of 32% compared to the current plant. A similar study was carried out by Oliver in Tarifa (Spain) [
56]. He analyzed different alternatives from technical, economic, and environmental points of view to repower a wind power plant. The original wind power plant had a rated power of 23.4 MW with 78 turbines of 300 kW. Two different alternatives were considered, using turbines with a rated power of 2 MW: (i) keeping the same rated power of the plant, and (ii) increasing the rated power of the plant up to 35 MW. According to the results, both alternatives were economically viable and fulfilled the environmental regulations in the place. Recently, Grau et al. evaluated repowering in the case of Germany [
71]. The methodology was based on technical, social, and economic factors. When the capacity of the turbines was increased, they needed a greater distance among them and, consequently, a larger area was required by the wind installations. Therefore, the distance constraints on urban areas could be affected. In total, 15 scenarios were designed; in the best case, an increase of 110% of the energy produced might be reached by 2040, whereas the most negative case was 40%. Subsequently, without a massive expansion, the contribution of wind energy to Germany’s energy mix would diminish.
In 2016, Lantz et al. evaluated the evolution that should be carried out in power systems of the United States to provide 35% of the end-use demand by 2050 with wind energy, considering technical and economic aspects [
55]. They estimated that, each year, from 2014 to 2020, 8 GW/year of wind energy should be installed; this value should be increased from 2021 to 2030, reaching 12 GW/year in such period; and from 2031 to 2050, 18 GW/year should be installed. In all cases, both new additions and repowering were considered. Moreover, according to this study, 25 billion Euro/year would be needed for repowering in 2050. Similar studies were carried out in 2018 by Jung et al., for Germany [
60], and by Ramírez et al., for Spain [
61]. In the case of Germany, the aim of the work was to determine the best wind turbine locations to provide 40% of the overall electricity consumption. According to the results, a capacity of 100 GW of wind energy (around 36,000 wind turbines) was enough to cover this target, which could be accomplished by around 2030 if the rate of wind energy expansion of Germany was maintained. Regarding the work focused on Spain, they analyzed the role of wind energy to meet the 2020 energy target of the country (i.e., cover at least 20% of gross final consumption of energy giving by RESs). In this work, both the repowering and commissioning of new wind power plants were assessed, combining them with the use of other RESs. Results showed that a minimum repowering level of 46% in combination with new wind power plants would be required to achieve the target. In 2020, Pryor et al. proposed theoretical scenarios to achieve a 20% electricity generation from wind energy in eastern USA [
69]. These scenarios were based on repowering wind power plants (avoiding competition for land) to analyze their impact on the environment and the power system’s efficiency. Two main scenarios were considered:
Doubling scenario: wind turbines with rated capacity under 2.1 MW were repowered with 3 MW turbines, and those with a rated power over 2.1 MW were replaced with 5.2 MW turbines;
Quadrupling scenario: wind turbines with rated capacity under 2.1 MW were repowered with 8.2 MW turbines, and those with a rated power over 2.1 MW were replaced with 5.2 MW turbines.
Under these scenarios, the results showed that, with the doubling scenario, gross CF increased slightly, whereas for the quadrupling scenario, gross CF decreased due to the saturation of the wind resource in some areas. With regard to the environment, it was seen that their impact on near-surface climate properties at the regional scale was minor, even under the quadrupling scenario. In fact, authors affirm that ’climate impacts from wind turbines are modest compared to regional changes induced by historical changes in land cover and to the global temperature perturbation induced by use of coal to generate an equivalent amount of electricity’.
Villena et al. performed an extensive techno-economic analysis of a real repowered wind power plant in Galicia (Spain) [
62]. The technical analysis considered the Annual Energy Production (AEP) and the Capacity Factor (CF) of the wind power plant. The economic analysis took into account the Present Value of Costs (PVC), the Cost of Energy (CoE), Net Present Value (NPV), Internal Rate of Return (IRR), Pay-Back Period (PBP) and the minimum Spot Price (SP min). Comparing the results between the old and the repowered wind power plant, the technical analysis showed that both indices doubled with the repowered wind power plant, and the economic analysis revealed that the repowered wind power plant was profitable. Other studies also focused on technical and economic factors in 2019. Michaud analyzed several hypotheses for repowering in France, such as dismantling and repowering all or just some wind turbines in the same location or others, in order to determine the economic viability [
66]. The most viable project was to repower some wind turbines with new models in different locations. Vicente re-designed a wind power plant for a specific case study in Mexico: a new analysis of the wind potential was carried out to determine the best location, as well as the electrical infrastructure, the project was viable with a payback of almost 7 years [
67]. Ziegler et al. analyzed the interaction among the technical, economic, and legal aspects for onshore wind turbine’ life extension in Denmark, Germany, Spain, and the UK [
63]. According to their study, such countries should start to face end-of-life solutions during 2020, and around 2000–4000 wind turbines would need, to be repowered or decommissioned to extend their lives. Moreover, as it is expected that wind technology in the near-future will progress slower than in recent decades, life-time extension is likely to become more attractive than repowering.
Machado et al., In 2019, linked technical factors (increase in nominal potential) and social factors (visual impact) to demonstrate the positive relationship between these factors in the design or relocation stage of wind turbines [
65]. The methodology was based on the use of two key indices: Magnitude of Visual Effect (MVE) and the Spanish method (SPM), each of them with different indicators. The data were processed at the pixel level of each wind turbine with high resolution, to obtain the equivalent visual impact. The case study, developed in Spain, showed repowering increased capacity by 37% without visual effects. This methodology, with the assessment only of the visual impact, should be completed with the economic and environmental assessment. Similarly, in 2020, Kitzing et al. proposed a comprehensive and social perspective on repowering wind power plants based on a project-level analysis in Denmark, considering technical(capacity), political(pre-permit process), and social (noise emissions, visual impact, space in land) aspects [
68]. According to their study, repowering was foreseen as an important technique to reach the maximum potential of wind energy, but involved complex technical, social, and political dimensions that must always be taken into account.
In 2021, two studies analyzed the technical–economic factors, Ceolin de Bona in Brazil [
70] and Al Hamed with a case study in Denmark [
72]. In the case of Brazil, 2 MW is the nominal power limit per wind turbine to change to others of higher rated power, unless they are replaced by taller towers. Furthermore, 179 wind power plants have a power limit of lower than 2 MW, making them a very attractive repowering market. The economic viability is closely linked to a decrease in rates. Given the inexperience with repowering in Brazil, a study of the regulatory framework in other successful countries, such as Germany, Denmark, and the UK, is recommended. In the case of Denmark, three technical scenarios were proposed with the premise of keeping the same land available: (i) same capacity as the original, (ii) increasing capacity by 50%, and (iii) doubling capacity. The results showed the economic viability of the first scenario. However, as the other scenarios must occupy the same space, the losses due to shadows were very high, causing a significant decrease in the electrical production. Indeed, good practices regarding the design of the location and orientation of wind turbines are of great importance to increase the productivity of the wind power plant [
73].
3.2. Single-Category Analysis
Table 3 summarizes contributions where only a single category is included for onshore wind power plant repowering strategies.
In 2012, Sen et al. analyzed the repowering potential of three regions of India (Tamilnadu, Gujarat, and Andhra Pradesh) [
78]. Considering the wind power plants installed until 1997 with more than two wind turbines of nominal power under 500 kW, in the regions under analysis, 519, 72, and 43 MW could be repowered, respectively. In 2013, Nivedh et al. carried out another technical repowering analysis of a wind power plant in India [
80]. The results were very positive, doubling the CP and increasing (24%) the Plant Load Factor (PLF). In 2020, Kadhirvel et al. studied the repowering of old wind turbines in India according to different rated powers of new turbines [
94]. By increasing the capacity in the repowered wind power plant by between 1.25 and 3 times, the overall electricity generation could be increased by 11 times. In 2016, Méndez and López proposed a new methodology to evaluate the limits of repowering and/or commissioning of new RESs in an isolated power system (Gran Canaria Island, Spain) [
87]. In this study, both the repowering of wind and solar installations was considered. According to the results, if more than 100 MW of RESs were installed, the power system could not operate in a secure manner; in fact, there would be frequent events of grid instability. In 2017, Santos-Alamillos et al. applied Markowitz’s mean variance (MV) portfolio optimization theory, with the aim of exploring repowering alternatives at the national level in Spain [
88]. They proposed three scenarios: (i) ideal repowering (total dismantling and redistribution of energy capacity in a more time-consuming way), (ii) full repowering (total dismantling but limited to the installation capacity of each region), and (iii) partial repowering (maintaining current capacity). They concluded that, according to the configuration of the optimization model, keeping the level of energy productivity constant could reduce up to 31% the hourly fluctuations in the supply, and more efficient combinations of wind turbine relocation could be obtained with increased productivity, which could be improved up to 55%. Similarly, Karoui et al. also focused on the impact of repowering a wind power plant of Tunisia on the power system stability [
91]. The initial wind power plant was based on type 1 wind turbines (i.e., squirrel cage induction generators), and the repowered one used type 3 turbines (i.e., doubly fed induction generators). The number of wind turbines was reduced by four times (from 32 to 8), whereas the power installed and the annual production substantially increased (by 2.5 and 4.1 times, respectively). Moreover, the grid stability was improved with the new turbines, being more suitable to power grid requirements (grid code). In 2020, Lacal et al. analyzed the empirical data on repowered wind power plants in Denmark and Germany, determining the evolution between the previous wind turbines and the new installed ones [
101]. They found the following:
New wind turbines were twice as high as the previous ones;
The rotor diameter of new wind turbines was three times larger than the previous blades, consequently having a swept area nine times larger;
Nominal power of new wind turbines was around six times the power of the initial turbines.
All these changes led to an electricity generation that was increased by nine times compared to the old turbines. Other authors have focused on partial repowering. In 2020, Syed et al. presented a methodology for the partial repowering of wind power plants, considering the reduction in generation due to the wake interactions inside the wind power plant (and with neighboring wind power plants), using a case study in Jhimpir (Pakistan) [
98]. The partial repowering consisted of modifying the hub height of the turbines. Moreover, the methodology demonstrated the need to consider the wake interactions among wind turbines inside the power plant, and with nearby wind power plants as well. Hu et al. proposed a repowering approach to tubular steel wind turbine towers [
99]. This solution was numerically carried out with a finite element software (ABAQUS).
In recent decades, only three contributions have been focused on economic factors alone. In 2010, Goyal [
76] focused on financial highlights of onshore wind repowering in India. The main factors affecting the IRR of the repowering project are the capital costs and the cumulative utilization factor of the places. With regard to the capital costs, Goyal found that although the capital costs were high, the IRR was still more attractive than for greenfield projects. On the other hand, the cumulative utilization factor seems to have a greater effect on the IRR of the project. In fact, they determined that an increase of 1% of the cumulative utilization factor causes an increase in IRR of 1.6%. In 2016, Castro et al. proposed a methodology to determine the main costs and the feasibility of repowering onshore wind farms, considering Galicia (Spain) as a case study [
85]. The methodology combined two methods, considering the following: (i) Spanish legislation for repowering and (ii) different types of wind turbines. A total of 9 alternatives for repowering were defined. These alternatives were then compared considering: non–financing (all the investment is supported by the enterprise) and financing (external investor, probably a bank) in terms of the Net Present Value (NPV), Internal Rate of Return (IRR), and Pay-Back Period (PBP). Their analysis concluded that NPV is not greatly influenced if the project has (or not) external financing, whereas both IRR and PBP are. In fact, all the alternatives have a higher IRR and a lower PBP value when the project has external financing. Based on these economic indicators, the optimal repowering option was obtained. Recently, in 2020, Fuchs et al. examined the economic viability of investments for repowering older wind power plants in Mecklenburg-Western Pomerania (Germany) [
96]. That study resulted in a high profitability of the investment. Moreover, a risk analysis was accomplished, showing that the economic viability of repowering wind power plants depends on the feed-in tariff, although it would still be cost-effective if the feed-in tariff reduced to 40 €/MWh.
The concern about the negative impact on birds and bats with the repowering of wind farms dates back to 2006, when Hermann Hotker [
74] carried out a detailed study in Germany. He concluded that the evaluation should be different according to the variety of bird species. In this line of mortality analysis according to species, Smallwood et al. in 2009 (California-USA) carried out a Digital Elevation Model (DEM) of collision hazardmaps and hazard ratings of wind turbines to guide careful repowering to modern turbines [
75]. In 2010, Smallwood et al. studied the impacts of birds and bats with wind turbines in California (USA) [
77]. According to this study, wind turbines that have a low capacity factor cause more fatalities/GWh. Consequently, the impacts of birds and bats with wind turbines could be reduced by repowering old turbines with more modern and efficient ones. Similar results were obtained in 2014 by Everaert, analyzing the impact of bird collisions in Flanders (Belgium) [
82]. He proposed repowering wind power plants with larger wind turbines—and, subsequently, larger rated power, but fewer turbines may decrease the impacts of birds and, thus, total mortality in some regions. Similarly, other authors affirmed that repowering wind power plants with fewer but larger turbines can reduce the mortality of birds impacts [
83,
84,
89,
93,
102]. In contrast to previous studies, in 2016, Ferri et al. analyzed the impact of a repowered wind power plant located in central Italy on bats [
86]. They considered not only the mortality of bats due to collision, but also the habitat changes and disturbances. The results showed that some bats could also be sensitive to repowering. Moreover, they could suffer apparent stress due to the repowering processes. A recent quantitative study published in 2021 contradicts the results of previous contributions. According to Huso et al., if the same energy is generated after repowering smaller wind turbines with larger machines, slight differences in wildlife mortality will occur [
100].
From the environmental impact point of view, in 2012, Zimmerman proposed a new methodology to identify the environmentally preferable option to repower wind power plants using the specific energy demand as an indicator [
79]. The proposed method provided different repowering options at a particular site in terms of their specific energy demand. In 2018, Martínez et al. analyzed the environmental impact and benefits of a wind power plant repowering process though a life cycle assessment model [
92]. Wind turbines had an important impact on the repowering process, with values of 2.43 × 10
kg CO
; the substation and electrical lines (5.14 × 10
kg CO
) also had a severe impact. However, these impacts are balanced by the increase in the electrical generation derived from wind energy, reducing the kg CO
with a value of −9.03 × 10
kg CO
. Therefore, repowering old wind power plants (low rated power wind turbines) with new turbines with a higher rated power is an interesting option from an environmental point of view. Recently, in 2020, Szumilas-Kowalczyk et al. focused on the visual impact of old wind power plants in California (USA) [
103]. In fact, wind power plants modify the landscapes where the wind turbines are installed, having an aesthetic impact on such areas. According to this study, there are four options for the transformation of old wind power plants: (i) full decommissioning, (ii) constant repowering, (iii) repowering preceded by full decommissioning, and (iv) transition towards a tourist attraction. To reduce the landscape impact, among the two strategies related to repowering, repowering preceded by full decommissioning is better than constant repowering, as constant repowering could involve different wind turbine sizes and styles.
With regard to the political analysis category of repowering onshore wind power plants, it is a necessity to establish a reliable and solid regulatory framework to increase the opportunities for expansion in wind power (new installations or repowering). Rodríguez et al. focused on 2013 on the case of Spain [
81]. The supportive state legislation, combined with the launching of Spanish manufacturing of turbines and the attraction of investors caused the massive development of wind energy by 2010 in that country. In 2013, the Royal Decree 661/2007 regulated the wind power plants repowering in Spain, and only those installations fulfilling several conditions (i.e., final registration date, installed power, supply continuity during voltage dips, and power increase after repowering) could receive a premium upgrade. Moreover, it concluded that 1/4 of the wind power plants installed by then could not withstand power outages, subsequently creating an excellent opportunity for the wind repowering market. Recently, in 2020, Das et al. analyzed the main factors that were influencing the onshore wind energy deployment in India, being the presence of repowering policy one of them [
95]. However, in that country, only four states have such type of politics. Consequently, these states are more preferable to repower wind power plants. Guan [
97] carried out a comparison between Germany and China considering administrative, legislative, policy, and planning aspects for onshore wind power plants. The main difference between these two countries is that Germany is facing the challenge of how to transfer to the second generation of wind turbines, whereas China is still establishing its first generation. From this point, China can consider the different problems that Germany has already confronted related to repowering issue, and deal with them in a suitable way for China. In fact, one of the main issues that Germany has faced, is the difference between the current height of wind turbines, in contrast to those installed more than 20 years ago. As the new wind turbines can reach up to 200 m height, current planning procedures need to be amended, or new ones created, to ease the repowering of older wind power plants with taller wind turbines.
Finally, regarding the social analysis category, no repowering studies were found in the specific literature. However, an interesting study focused on surveys to analyze the attitude towards wind energy carried out in Spain and Poland reveals that there are several disagreements in relation to the aesthetics of wind turbines and the perceived cost of wind power [
104].