NewEnergyNews: MONDAY STUDY: Wind Turbines Last Longer Than Predicted

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  • MONDAY’S STUDY AT NewEnergyNews, July 13:
  • A Global New Energy Recovery

    Monday, June 08, 2020

    MONDAY STUDY: Wind Turbines Last Longer Than Predicted

    How Does Wind Project Performance Change with Age in the United States?

    Sofia D. Hamilton, Dev Millstein, Mark Bolinger, Ryan Wiser, Seongeun Jeong, May 13, 2020 (Joule)

    SUMMARY

    Wind-plant performance declines with age, and the rate of decline varies between regions. The rate of performance decline is important when determining wind-plant financial viability and expected lifetime generation. We determine the rate of age-related performance decline in the United States wind fleet by evaluating generation records from 917 plants. We find the rate of performance decline to be 0.53%/year for older vintages of plants and 0.17%/ year for newer vintages of plants on an energy basis for the first 10 years of operation, which is on the lower end of prior estimates in Europe. Unique to the United States, we find a significant drop in performance by 3.6% after 10 years, as plants lose eligibility for the production tax credit. Certain plant characteristics, such as the ratio of blade length to nameplate capacity, influence the rate of performance decline. These results indicate that the performance decline rate can be partially managed and influenced by policy.

    INTRODUCTION

    Wind power in the United States (US) now supplies an important portion of the nation’s electricity (in 2019, wind power supplied 7.3% of the US electricity generation1 and new wind capacity additions totaled 9,143 MW).2 Wind power is expected to continue to grow in importance, both in the United States and globally, due to its low cost and the carbon emission reduction goals of many states and countries. To understand wind power’s potential growth and impact on electricity systems, it is crucial to accurately estimate the future performance of wind plants. Importantly, wind-plant performance tends to deteriorate with plant age (a characteristic of all engineered systems). Understanding the rate at which wind plants degrade with age is not only necessary to model future growth of the wind sector, but also can impact the expected lifetime energy output, and even financial viability of proposed wind projects. Additionally, the performance of wind plants is an important factor in determining the levelized cost of wind energy (LCOE).3 Despite its importance, the rate of performance decline is not well established in the United States and a decline in performance due to aging is not typically accounted for in assessments of the LCOE in academic literature,4,5 government reports,6,7 or industry publications.8,9

    The reliability of wind turbines impacts operations and maintenance (O&M) costs and annual energy production.3 Failure rates for wind turbine components vary over the lifetime of a turbine, with increased failures at the beginning and end of a turbine’s lifetime.10 Failure rates have also been found to vary regionally—in Germany, turbines have exhibited higher failure rates than in Denmark, though the overall fleet-failure rates have been decreasing over time.10 Recently, the impact of age on the overall performance of wind fleets has been investigated in Sweden,11 Germany,12 the United Kingdom, and Denmark.13,14 These studies consider multiple forms of performance degradation in aggregate, accounting not only for component reliability and downtime, but also aerodynamic and mechanical efficiency losses that tend to grow as plants age, caused by phenomena, such as erosion of the leading edge of turbine blades.15 Germer and Kleidon12 found that the energy output of wind turbines in Germany declined at a rate of about 0.6% per year, consistent with similar research on the Swedish wind fleet.11 Staffell and Green14 examined the performance of wind projects in the United Kingdom and found a decline in performance of 1.6% per year, a greater rate than in other studies. These studies found performance declining linearly with age, but found a wide range in the magnitude of the estimated performance declines. Differences in technology, terrain, meteorology, fleet vintage, and even regulatory and contractual factors can create differences in how wind fleets age across these regions, so performance change with age must be assessed in different regions separately, with attention paid to the influence of plant characteristics and other regional factors that can impact performance. Despite research efforts in Europe, no study has comprehensively evaluated the impact of age on the performance of the US wind fleet—an important omission— because the US is the second-largest wind power market globally, after China.

    This study addresses the research gap identified above by analyzing the performance of 917 onshore wind projects across the contiguous United States (Figure 1). The sample size of wind projects in this study is much larger than the sample sizes in previous work in the European countries, as we analyze a fleet that is roughly an order of magnitude larger, in terms of installed capacity, and which spans a dramatically larger geographic area that encompasses many different climates. It builds on the methods and approaches of the European research efforts to quantify the performance trends of the US onshore wind plants. We pay particular attention to issues that are unique to the US market, such as the effect of policy mechanisms, including the production tax credit (PTC), on performance trends. We were able to remove the effects of the market-based curtailment of wind plants by producing new estimates, informed by market price signals, of plant-level curtailment. Finally, we explored the influence of plant characteristics on the rate of performance decline through a multivariate analysis. The results from this study help clarify the rate of performance decline across the US wind plants, while also providing insight into how the impact of age on fleet performance has changed with newer wind power technology and how policy and market factors can impact performance outcomes…

    DISCUSSION

    Like any engineered system, wind plants experience some deterioration over the course of their lifetime. For the wind fleet in the US, this degradation does not appear to happen smoothly over time, but involves a step-change in performance after 10 years of operation. The majority of wind projects in the US have taken advantage of the PTC, which provides wind plants with a production-based tax credit for their first 10 years of operation. The results described here suggest that, in addition to potentially more frequent component failures and downtime as well as growing mechanical and aerodynamic efficiency losses as plants age, the US plants are operated differently after they age out of the 10-year PTC window. Previous studies on various European wind fleets found linearly declining performance with time.11,12,14 Different policies for incentivizing the expansion of wind energy in Europe and the United States could be influencing the way in which the US and the European wind plants age differently. In particular, European policies have not generally featured a short 10-year window of eligibility, such as that with the PTC, which could be a reason they did not follow the pattern of the US wind plants. This also implies that wind-plant degradation is not simply a physical process, but is also a function of weighing the costs of maintenance against the value of operation of a wind project. Dao et al.3 also found that there was a strong relationship between maintenance expenditures and reliability, and thus annual energy production, of wind turbines. It appears that in the US, the PTC makes it cost-effective to both minimize turbine downtime and maintain turbines at a high level while they can still take advantage of the tax credit, but that after year 10, a different maintenance optimization routine is applied.

    Overall, the US fleet has experienced levels of performance decline on the low end of the range found in Europe. The fixed-effects regression showed that after 17 years, aging had caused the performance of plants to drop to 87% of their initial levels. This performance decline is less than 1% per year and is closer to the decline of 0.6% per year as described by Germer et al.,12 than the 1.6% as described by Staffell and Green.14 Furthermore, the performance of newer plants (i.e., plants that began generating power in 2008 or later) was found to be lower still, with the fixed-effects regression indicating performance declines of only 0.17% per year. It remains to be seen whether this newest set of plants will experience the same sort of drop in performance after their 10 years of PTC revenue ends.

    Among newer plants (defined as beginning production during 2008 or later) the rate of performance decline was correlated with a limited number of plant characteristics. Most notably, plants with lower specific power were correlated with lower degradation rates, while plants in rougher terrain were correlated with higher degradation rates. Interestingly, the rate of decline was not found to be correlated with project ownership or plant size. Additionally, characteristics such as average wind speed and the proximity of nearby plants showed little significant correlation with the rate of performance decline. The explanatory power of some of these characteristics may be limited by confounding effects.

    The results described here can be used by investors and energy system modelers to refine estimates of wind-plant performance and levelized energy costs. For example, electric sector ‘‘capacity-expansion’’ models, often used by researchers and policy makers to assess how the electricity system will evolve over the next decade, or longer, are sensitive to wind-plant cost and performance assumptions. Additionally, investors could use these results to refine long-term wind-plant performance estimates and associated financial models.

    Throughout the paper, we have identified uncertainties to which the conclusions are most sensitive, and we hope that future research will address these challenges and topics. First, in a few years there will be enough data to see if the newer set of plants continues to display the 10-year drop in performance found in the older set of plants. It will also be important to confirm that degradation rates have remained relatively low for the newer set of plants. Future research may also develop a set of more-refined plant characteristics to further diagnose the driving factors of performance decline with age. While terrain roughness was found to be a statically significant indicator of increased degradation, roughness is not a direct measure of turbulence, and so refining this metric in particular could produce valuable results. Also of interest are refinements to metrics related to maintenance network efficiencies and inter-plant wake effects. Finally, it would be useful to develop alternate weather correction methods as the potential exists that wind trends not represented in the re-analysis data may have impacted these results; especially sensitive may be the difference in performance decline between the newest set of plants and the oldest. The challenge here is the lack of publicly available wind speed observations near to wind plants, and at representative heights above ground. The development of improved wind speed estimates could be supported through either improved modeling or measurement campaigns, or, ideally, through large-scale data sharing from wind project operators…

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