Concept: Capacity factor
- Proceedings of the National Academy of Sciences of the United States of America
- Published over 3 years ago
Recent forecasts suggest that African countries must triple their current electricity generation by 2030. Our multicriteria assessment of wind and solar potential for large regions of Africa shows how economically competitive and low-environmental-impact renewable resources can significantly contribute to meeting this demand. We created the Multicriteria Analysis for Planning Renewable Energy (MapRE) framework to map and characterize solar and wind energy zones in 21 countries in the Southern African Power Pool (SAPP) and the Eastern Africa Power Pool (EAPP) and find that potential is several times greater than demand in many countries. Significant fractions of demand can be quickly served with “no-regrets” options-or zones that are low-cost, low-environmental impact, and highly accessible. Because no-regrets options are spatially heterogeneous, international interconnections are necessary to help achieve low-carbon development for the region as a whole, and interconnections that support the best renewable options may differ from those planned for hydropower expansion. Additionally, interconnections and selecting wind sites to match demand reduce the need for SAPP-wide conventional generation capacity by 9.5% in a high-wind scenario, resulting in a 6-20% cost savings, depending on the avoided conventional technology. Strategic selection of low-impact and accessible zones is more cost effective with interconnections compared with solutions without interconnections. Overall results are robust to multiple load growth scenarios. Together, results show that multicriteria site selection and deliberate planning of interconnections may significantly increase the economic and environmental competitiveness of renewable alternatives relative to conventional generation.
Objective: The development of new wind farms in many parts of the world has been thwarted by public concern that subaudible sound (infrasound) generated by wind turbines causes adverse health effects. Although the scientific evidence does not support a direct pathophysiological link between infrasound and health complaints, there is a body of lay information suggesting a link between infrasound exposure and health effects. This study tested the potential for such information to create symptom expectations, thereby providing a possible pathway for symptom reporting. Method: A sham-controlled double-blind provocation study, in which participants were exposed to 10 min of infrasound and 10 min of sham infrasound, was conducted. Fifty-four participants were randomized to high- or low-expectancy groups and presented audiovisual information, integrating material from the Internet, designed to invoke either high or low expectations that exposure to infrasound causes specified symptoms. Results: High-expectancy participants reported significant increases, from preexposure assessment, in the number and intensity of symptoms experienced during exposure to both infrasound and sham infrasound. There were no symptomatic changes in the low-expectancy group. Conclusions: Healthy volunteers, when given information about the expected physiological effect of infrasound, reported symptoms that aligned with that information, during exposure to both infrasound and sham infrasound. Symptom expectations were created by viewing information readily available on the Internet, indicating the potential for symptom expectations to be created outside of the laboratory, in real world settings. Results suggest psychological expectations could explain the link between wind turbine exposure and health complaints. (PsycINFO Database Record © 2013 APA, all rights reserved).
Wind energy has developed rapidly over the last two decades to become one of the most promising and economically viable sources of renewable energy. Although wind energy is claimed to provide clean renewable energy without any emissions during operation, but it is only one side of the coin. The blades, one of the most important components in the wind turbines, made with composite, are currently regarded as unrecyclable. With the first wave of early commercial wind turbine installations now approaching their end of life, the problem of blade disposal is just beginning to emerge as a significant factor for the future. This paper is aimed at discovering the magnitude of the wind turbine blade waste problem, looking not only at disposal but at all stages of a blade’s lifecycle. The first stage of the research, the subject of this paper, is to accurately estimate present and future wind turbine blade waste inventory using the most recent and most accurate data available. The result will provide a solid reference point to help the industry and policy makers to understand the size of potential environmental problem and to help to manage it better. This study starts by estimating the annual blade material usage with wind energy installed capacity and average blade weight. The effect of other waste contributing factors in the full lifecycle of wind turbine blades is then included, using industrial data from the manufacturing, testing and in-service stages. The research indicates that there will be 43 million tonnes of blade waste worldwide by 2050 with China possessing 40% of the waste, Europe 25%, the United States 16% and the rest of the world 19%.
Wind energy is a rapidly growing form of renewable energy in the United States. While summary information on the total amounts of installed capacity are available by state, a free, centralized, national, turbine-level, geospatial dataset useful for scientific research, land and resource management, and other uses did not exist. Available in multiple formats and in a web application, these public domain data provide industrial-scale onshore wind turbine locations in the United States up to March 2014, corresponding facility information, and turbine technical specifications. Wind turbine records have been collected and compiled from various public sources, digitized or position verified from aerial imagery, and quality assured and quality controlled. Technical specifications for turbines were assigned based on the wind turbine make and model as described in public literature. In some cases, turbines were not seen in imagery or turbine information did not exist or was difficult to obtain. Uncertainty associated with these is recorded in a confidence rating.
A combination of declining costs and policy measures motivated by greenhouse gas (GHG) emissions reduction and energy security have driven rapid growth in the global installed capacity of solar photovoltaics (PV). This paper develops a number of unique datasets, namely: calculation of distribution of global capacity factor for PV deployment; meta-analysis of energy consumption in PV system manufacture and deployment; and documentation of reduction in energetic costs of PV system production. These data are used as input into a new net energy analysis of the global PV industry, as opposed to devise level analysis. In addition, the paper introduces a new concept: a model tracking energetic costs of manufacturing and installing PV systems, including balance of system (BOS) components. The model is used to forecast energy requirements to scale up the PV industry and determine the energy balance of the global PV industry to 2020. Results suggest that the industry was a net consumer of electricity as recently as 2010. However, there is a >50% that in 2012 the PV industry is a net electricity provider and will “pay back” the energy required for its early growth before 2020. Further reducing energetic costs of PV deployment will enable more rapid growth of the PV industry. There is also great potential to increase the capacity factor of PV deployment. These conclusions have a number of implications for R&D and deployment, including: monitoring of the energy embodied within PV systems; designing more efficient and durable systems and; deploying PV systems in locations that will achieve high capacity factors.
Small passerines, sometimes referred to as perching birds or songbirds, are the most abundant bird group in the United States (US) and Canada, and the most common among bird fatalities caused by collision with turbines at wind energy facilities. We used data compiled from 116 studies conducted in the US and Canada to estimate the annual rate of small-bird fatalities. It was necessary for us to calculate estimates of small-bird fatality rates from reported all-bird rates for 30% of studies. The remaining 70% of studies provided data on small-bird fatalities. We then adjusted estimates to account for detection bias and loss of carcasses from scavenging. These studies represented about 15% of current operating capacity (megawatts [MW]) for all wind energy facilities in the US and Canada and provided information on 4,975 bird fatalities, of which we estimated 62.5% were small passerines comprising 156 species. For all wind energy facilities currently in operation, we estimated that about 134,000 to 230,000 small-passerine fatalities from collision with wind turbines occur annually, or 2.10 to 3.35 small birds/MW of installed capacity. When adjusted for species composition, this indicates that about 368,000 fatalities for all bird species are caused annually by collisions with wind turbines. Other human-related sources of bird deaths, (e.g., communication towers, buildings [including windows]), and domestic cats) have been estimated to kill millions to billions of birds each year. Compared to continent-wide population estimates, the cumulative mortality rate per year by species was highest for black-throated blue warbler and tree swallow; 0.043% of the entire population of each species was estimated to annually suffer mortality from collisions with turbines. For the eighteen species with the next highest values, this estimate ranged from 0.008% to 0.038%, much lower than rates attributed to collisions with communication towers (1.2% to 9.0% for top twenty species).
More than 12 GW of offshore wind turbines are currently in operation in European waters. To optimise the use of the marine areas, wind farms are typically clustered in units of several hundred turbines. Understanding wakes of wind farms, which is the region of momentum and energy deficit downwind, is important for optimising the wind farm layouts and operation to minimize costs. While in most weather situations (unstable atmospheric stratification), the wakes of wind turbines are only a local effect within the wind farm, satellite imagery reveals wind-farm wakes to be several tens of kilometres in length under certain conditions (stable atmospheric stratification), which is also predicted by numerical models. The first direct in situ measurements of the existence and shape of large wind farm wakes by a specially equipped research aircraft in 2016 and 2017 confirm wake lengths of more than tens of kilometres under stable atmospheric conditions, with maximum wind speed deficits of 40%, and enhanced turbulence. These measurements were the first step in a large research project to describe and understand the physics of large offshore wakes using direct measurements, together with the assessment of satellite imagery and models.
The Power of Positive and Negative Expectations to Influence Reported Symptoms and Mood During Exposure to Wind Farm Sound
- Health psychology : official journal of the Division of Health Psychology, American Psychological Association
- Published almost 7 years ago
Objective: Wind farm developments have been hampered by claims that sound from wind turbines causes symptoms and negative health reports in nearby residents. As scientific reviews have failed to identify a plausible link between wind turbine sound and health effects, psychological expectations have been proposed as an explanation for health complaints. Building on recent work showing negative expectations can create symptoms from wind turbines, we investigated whether positive expectations can produce the opposite effect, in terms of a reduction in symptoms and improvements in reported health. Method: 60 participants were randomized to either positive or negative expectation groups and subsequently exposed to audible wind farm sound and infrasound. Prior to exposure, negative expectation participants watched a DVD incorporating TV footage about health effects said to be caused by infrasound produced by wind turbines. In contrast, positive expectation participants viewed a DVD that outlined the possible therapeutic effects of infrasound exposure. Results: During exposure to audible windfarm sound and infrasound, symptoms and mood were strongly influenced by the type of expectations. Negative expectation participants experienced a significant increase in symptoms and a significant deterioration in mood, while positive expectation participants reported a significant decrease in symptoms and a significant improvement in mood. Conclusion: The study demonstrates that expectations can influence symptom and mood reports in both positive and negative directions. The results suggest that if expectations about infrasound are framed in more neutral or benign ways, then it is likely reports of symptoms or negative effects could be nullified. (PsycINFO Database Record © 2013 APA, all rights reserved).
- Philosophical transactions. Series A, Mathematical, physical, and engineering sciences
- Published almost 6 years ago
Wind power has expanded significantly over the past years, although reliability of wind turbine systems, especially of offshore wind turbines, has been many times unsatisfactory in the past. Wind turbine failures are equivalent to crucial financial losses. Therefore, creating and applying strategies that improve the reliability of their components is important for a successful implementation of such systems. Structural health monitoring (SHM) addresses these problems through the monitoring of parameters indicative of the state of the structure examined. Condition monitoring (CM), on the other hand, can be seen as a specialized area of the SHM community that aims at damage detection of, particularly, rotating machinery. The paper is divided into two parts: in the first part, advanced signal processing and machine learning methods are discussed for SHM and CM on wind turbine gearbox and blade damage detection examples. In the second part, an initial exploration of supervisor control and data acquisition systems data of an offshore wind farm is presented, and data-driven approaches are proposed for detecting abnormal behaviour of wind turbines. It is shown that the advanced signal processing methods discussed are effective and that it is important to adopt these SHM strategies in the wind energy sector.
- Proceedings of the National Academy of Sciences of the United States of America
- Published over 5 years ago
Most aquatic vertebrates use suction to capture food, relying on rapid expansion of the mouth cavity to accelerate water and food into the mouth. In ray-finned fishes, mouth expansion is both fast and forceful, and therefore requires considerable power. However, the cranial muscles of these fishes are relatively small and may not be able to produce enough power for suction expansion. The axial swimming muscles of these fishes also attach to the feeding apparatus and have the potential to generate mouth expansion. Because of their large size, these axial muscles could contribute substantial power to suction feeding. To determine whether suction feeding is powered primarily by axial muscles, we measured the power required for suction expansion in largemouth bass and compared it to the power capacities of the axial and cranial muscles. Using X-ray reconstruction of moving morphology (XROMM), we generated 3D animations of the mouth skeleton and created a dynamic digital endocast to measure the rate of mouth volume expansion. This time-resolved expansion rate was combined with intraoral pressure recordings to calculate the instantaneous power required for suction feeding. Peak expansion powers for all but the weakest strikes far exceeded the maximum power capacity of the cranial muscles. The axial muscles did not merely contribute but were the primary source of suction expansion power and generated up to 95% of peak expansion power. The recruitment of axial muscle power may have been crucial for the evolution of high-power suction feeding in ray-finned fishes.