ResearchPad - alternative-energy https://www.researchpad.co Default RSS Feed en-us © 2020 Newgen KnowledgeWorks <![CDATA[Consensus based SoC trajectory tracking control design for economic-dispatched distributed battery energy storage system]]> https://www.researchpad.co/article/elastic_article_14556 The state-of-charge (SoC) of an energy storage system (ESS) should be kept in a certain safe range for ensuring its state-of-health (SoH) as well as higher efficiency. This procedure maximizes the power capacity of the ESSs all the times. Furthermore, economic load dispatch (ELD) is implemented to allocate power among various ESSs, with the aim of fully meeting the load demand and reducing the total operating cost. In this research article, a distributed multi-agent consensus based control algorithm is proposed for multiple battery energy storage systems (BESSs), operating in a microgrid (MG), for fulfilling several objectives, including: SoC trajectories tracking control, economic load dispatch, active and reactive power sharing control, and voltage and frequency regulation (using the leader-follower consensus approach). The proposed algorithm considers the hierarchical control structure of the BESSs and the frequency/voltage droop controllers with limited information exchange among the BESSs. It embodies both self and communication time-delays, and achieves its objectives along with offering plug-and-play capability and robustness against communication link failure. Matlab/Simulink platform is used to test and validate the performance of the proposed algorithm under load disturbances through extensive simulations carried out on a modified IEEE 57-bus system. A detailed comparative analysis of the proposed distributed control strategy is carried out with the distributed PI-based conventional control strategy for demonstrating its superior performance.

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<![CDATA[Effect of internal surface structure of the north wall on Chinese solar greenhouse thermal microclimate based on computational fluid dynamics]]> https://www.researchpad.co/article/Nf5b70015-c0ce-4e08-9dc5-5525c2c91d69

Chinese solar greenhouses are unique facility agriculture buildings and widely used in northeastern China, providing a favorable requirement for crop growth. The north wall configurations play an essential role in heat storage and thermal insulation and directly affect the management of the internal environment. This research is devoted to further improve the thermal performance of the greenhouse and explore the potential of the north wall. A mathematical model was designed to investigate the concave-convex wall configurations based on computational fluid dynamics. Four passive heat-storage north walls were analyzed by using the same constituent materials, including a plane wall, a vertical wall, a horizontal wall and an alveolate wall. The numerical model was validated by experimental measurements. The temperature distributions of the north walls were examined and a comparative analysis of the heat storage-release capabilities was carried out. The results showed that the heat-storage capacity of the north wall is affected by the surface structure. Moreover, the critical factor influencing the air temperature is the sum of the heat load released by the wall and the energy increment of greenhouse air. The results suggested that the alveolate wall has preferable thermal accumulation capacity. The concave-convex wall configurations have a wider range of heat transfer performance along the thickness direction, while the plane wall has a superior thermal environment. This study provides a basic theoretical reference to rationally design the internal surface structures of the north wall.

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<![CDATA[Assessment of a storage system to deliver uninterrupted therapeutic oxygen during power outages in resource-limited settings]]> https://www.researchpad.co/article/5c648cd4d5eed0c484c818b0

Access to therapeutic oxygen remains a challenge in the effort to reduce pneumonia mortality among children in low- and middle-income countries. The use of oxygen concentrators is common, but their effectiveness in delivering uninterrupted oxygen is gated by reliability of the power grid. Often cylinders are employed to provide continuous coverage, but these can present other logistical challenges. In this study, we examined the use of a novel, low-pressure oxygen storage system to capture excess oxygen from a concentrator to be delivered to patients during an outage. A prototype was built and tested in a non-clinical trial in Jinja, Uganda. The trial was carried out at Jinja Regional Referral Hospital over a 75-day period. The flow rate of the unit was adjusted once per week between 0.5 and 5 liters per minute. Over the trial period, 1284 power failure episodes with a mean duration of 3.1 minutes (range 0.08 to 1720 minutes) were recorded. The low-pressure system was able to deliver oxygen over 56% of the 4,295 power outage minutes and cover over 99% of power outage events over the course of the study. These results demonstrate the technical feasibility of a method to extend oxygen availability and provide a basis for clinical trials.

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<![CDATA[Have wind turbines in Germany generated electricity as would be expected from the prevailing wind conditions in 2000-2014?]]> https://www.researchpad.co/article/5c648cd6d5eed0c484c818e1

The planning of the energy transition from fossil fuels to renewables requires estimates for how much electricity wind turbines can generate from the prevailing atmospheric conditions. Here, we estimate monthly ideal wind energy generation from datasets of wind speeds, air density and installed wind turbines in Germany and compare these to reported actual yields. Both yields were used in a statistical model to identify and quantify factors that reduced actual compared to ideal yields. The installed capacity within the region had no significant influence. Turbine age and park size resulted in significant yield reductions. Predicted yields increased from 9.1 TWh/a in 2000 to 58.9 TWh/a in 2014 resulting from an increase in installed capacity from 5.7 GW to 37.6 GW, which agrees very well with reported estimates for Germany. The age effect, which includes turbine aging and possibly other external effects, lowered yields from 3.6 to 6.7% from 2000 to 2014. The effect of park size decreased annual yields by 1.9% throughout this period. However, actual monthly yields represent on average only 73.7% of the ideal yields, with unknown causes. We conclude that the combination of ideal yields predicted from wind conditions with observed yields is suitable to derive realistic estimates of wind energy generation as well as realistic resource potentials.

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<![CDATA[Features and drivers for energy-related carbon emissions in mega city: The case of Guangzhou, China based on an extended LMDI model]]> https://www.researchpad.co/article/5c6b2653d5eed0c484289825

Based on the apparent energy consumption data, a systematic and comprehensive city-level total carbon accounting approach was established and applied in Guangzhou, China. A newly extended LMDI method based on the Kaya identity was adopted to examine the main drivers for the carbon emissions increments both at the industrial sector and the residential sector. Research results are listed as follow: (1) Carbon emissions embodied in the imported electricity played a significant important role in emissions mitigation in Guangzhou. (2) The influences and impacts of various driving factors on industrial and residential carbon emissions are different in the three different development periods, namely, the 10th five-year plan period (2003–2005), the 11th five-year plan period (2005–2010), and the 12th five-year plan period (2010–2013). The main reasons underlying these influencing mechanisms were different policy measures announced by the central and local government during the different five-year plan periods. (3) The affluence effect (g-effect) was the dominant positive effect in driving emissions increase, while the energy intensity effect of production (e-effect-Production), the economic structure effect (s-effect) and the carbon intensity effect of production (f-effect-Production) were the main contributing factors suppressing emissions growth at the industrial sector. (4) The affluence effect of urban (g-effect-AUI) was the most dominant positive driving factor on emissions increment, while the energy intensity effect of urban (e-effect-Urban) played the most important role in curbing emissions growth at the residential sector.

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<![CDATA[Penumbra: A spatially distributed, mechanistic model for simulating ground-level incident solar energy across heterogeneous landscapes]]> https://www.researchpad.co/article/5c23f279d5eed0c484046db1

Landscape solar energy is a significant environmental driver, yet it remains complicated to model well. Several solar radiation models simplify the complexity of light by estimating it at discrete point locations or by averaging values over larger areas. These modeling approaches may be useful in certain cases, but they are unable to provide spatially distributed and temporally dynamic representations of solar energy across entire landscapes. We created a landscape-scale ground-level shade and solar energy model called Penumbra to address this deficiency. Penumbra simulates spatially distributed ground-level shade and incident solar energy at user-defined timescales by modeling local and distant topographic shading and vegetative shading. Spatially resolved inputs of a digital elevation model, a normalized digital surface model, and landscape object transmittance are used to estimate spatial variations in solar energy at user-defined temporal timesteps. The research goals for Penumbra included: 1) simulations of spatiotemporal variations of shade and solar energy caused by both objects and topographic features, 2) minimal user burden and parameterization, 3) flexible user defined temporal parameters, and 4) flexible external model coupling. We test Penumbra’s predictive skill by comparing the model’s predictions with monitored open and forested sites, and achieve calibrated mean errors ranging from -17.3 to 148.1 μmoles/m2/s. Penumbra is a dynamic model that can produce spatial and temporal representations of shade percentage and ground-level solar energy. Outputs from Penumbra can be used with other ecological models to better understand the health and resilience of aquatic, near stream terrestrial, and upland ecosystems.

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<![CDATA[Impact of solar and wind development on conservation values in the Mojave Desert]]> https://www.researchpad.co/article/5c1ab81ed5eed0c484026c7e

In 2010, The Nature Conservancy completed the Mojave Desert Ecoregional Assessment, which characterizes conservation values across nearly 130,000 km2 of the desert Southwest. Since this assessment was completed, several renewable energy facilities have been built in the Mojave Desert, thereby changing the conservation value of these lands. We have completed a new analysis of land use to reassess the conservation value of lands in two locations in the Mojave Desert where renewable energy development has been most intense: Ivanpah Valley, and the Western Mojave. We found that 99 of our 2.59-km2 planning units were impacted by development such that they would now be categorized as having lower conservation value, and most of these downgrades in conservation value were due to solar and wind development. Solar development alone was responsible for a direct development footprint 86.79 km2: 25.81 km2 of this was primarily high conservation value Bureau of Land Management lands in the Ivanpah Valley, and 60.99 km2 was privately owned lands, mostly of lower conservation value, in the Western Mojave. Our analyses allow us to understand patterns in renewable energy development in the mostly rapidly changing regions of the Mojave Desert. Our analyses also provide a baseline that will allow us to assess the effectiveness of the Desert Renewable Energy Conservation Plan in preventing development on lands of high conservation value over the coming decades.

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<![CDATA[Linear and nonlinear causal relationship between energy consumption and economic growth in China: New evidence based on wavelet analysis]]> https://www.researchpad.co/article/5b0e53a1463d7e030321d289

The energy-growth nexus has important policy implications for economic development. The results from many past studies that investigated the causality direction of this nexus can lead to misleading policy guidance. Using data on China from 1953 to 2013, this study shows that an application of causality test on the time series of energy consumption and national output has masked a lot of information. The Toda-Yamamoto test with bootstrapped critical values and the newly proposed non-linear causality test reveal no causal relationship. However, a further application of these tests using series in different time-frequency domain obtained from wavelet decomposition indicates that while energy consumption Granger causes economic growth in the short run, the reverse is true in the medium term. A bidirectional causal relationship is found for the long run. This approach has proven to be superior in unveiling information on the energy-growth nexus that are useful for policy planning over different time horizons.

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<![CDATA[Adaptive management of energy consumption, reliability and delay of wireless sensor node: Application to IEEE 802.15.4 wireless sensor node]]> https://www.researchpad.co/article/5989db4fab0ee8fa60bdbc3d

Designing a Wireless Sensor Network (WSN) to achieve a high Quality of Service (QoS) (network performance and durability) is a challenging problem. We address it by focusing on the performance of the 802.15.4 communication protocol because the IEEE 802.15.4 Standard is actually considered as one of the reference technologies in WSNs. In this paper, we propose to control the sustainable use of resources (i.e., energy consumption, reliability and timely packet transmission) of a wireless sensor node equipped with photovoltaic cells by an adaptive tuning not only of the MAC (Medium Access Control) parameters but also of the sampling frequency of the node. To do this, we use one of the existing control approaches, namely the viability theory, which aims to preserve the functions and the controls of a dynamic system in a set of desirable states. So, an analytical model, describing the evolution over time of nodal resources, is derived and used by a viability algorithm for the adaptive tuning of the IEEE 802.15.4 MAC protocol. The simulation analysis shows that our solution allows ensuring indefinitely, in the absence of hardware failure, the operations (lifetime duration, reliability and timely packet transmission) of an 802.15.4 WSN and one can temporarily increase the sampling frequency of the node beyond the regular sampling one. This latter brings advantages for agricultural and environmental applications such as precision agriculture, flood or fire prevention. Main results show that our current approach enable to send more information when critical events occur without the node runs out of energy. Finally, we argue that our approach is generic and can be applied to other types of WSN.

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<![CDATA[Application of a Cloud Model-Set Pair Analysis in Hazard Assessment for Biomass Gasification Stations]]> https://www.researchpad.co/article/5989dac0ab0ee8fa60bb0899

Because a biomass gasification station includes various hazard factors, hazard assessment is needed and significant. In this article, the cloud model (CM) is employed to improve set pair analysis (SPA), and a novel hazard assessment method for a biomass gasification station is proposed based on the cloud model-set pair analysis (CM-SPA). In this method, cloud weight is proposed to be the weight of index. In contrast to the index weight of other methods, cloud weight is shown by cloud descriptors; hence, the randomness and fuzziness of cloud weight will make it effective to reflect the linguistic variables of experts. Then, the cloud connection degree (CCD) is proposed to replace the connection degree (CD); the calculation algorithm of CCD is also worked out. By utilizing the CCD, the hazard assessment results are shown by some normal clouds, and the normal clouds are reflected by cloud descriptors; meanwhile, the hazard grade is confirmed by analyzing the cloud descriptors. After that, two biomass gasification stations undergo hazard assessment via CM-SPA and AHP based SPA, respectively. The comparison of assessment results illustrates that the CM-SPA is suitable and effective for the hazard assessment of a biomass gasification station and that CM-SPA will make the assessment results more reasonable and scientific.

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<![CDATA[Reconciling Biodiversity Conservation and Widespread Deployment of Renewable Energy Technologies in the UK]]> https://www.researchpad.co/article/5989d9ebab0ee8fa60b6c81f

Renewable energy will potentially make an important contribution towards the dual aims of meeting carbon emission reduction targets and future energy demand. However, some technologies have considerable potential to impact on the biodiversity of the environments in which they are placed. In this study, an assessment was undertaken of the realistic deployment potential of a range of renewable energy technologies in the UK, considering constraints imposed by biodiversity conservation priorities. We focused on those energy sources that have the potential to make important energy contributions but which might conflict with biodiversity conservation objectives. These included field-scale solar, bioenergy crops, wind energy (both onshore and offshore), wave and tidal stream energy. The spatially-explicit analysis considered the potential opportunity available for each technology, at various levels of ecological risk. The resultant maps highlight the energy resource available, physical and policy constraints to deployment, and ecological sensitivity (based on the distribution of protected areas and sensitive species). If the technologies are restricted to areas which currently appear not to have significant ecological constraints, the total potential energy output from these energy sources was estimated to be in the region of 5,547 TWh/yr. This would be sufficient to meet projected energy demand in the UK, and help to achieve carbon reduction targets. However, we highlight two important caveats. First, further ecological monitoring and surveillance is required to improve understanding of wildlife distributions and therefore potential impacts of utilising these energy sources. This is likely to reduce the total energy available, especially at sea. Second, some of the technologies under investigation are currently not deployed commercially. Consequently this potential energy will only be available if continued effort is put into developing these energy sources/technologies, to enable realisation of their full potential.

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<![CDATA[Threshold for Onset of Injury in Chinook Salmon from Exposure to Impulsive Pile Driving Sounds]]> https://www.researchpad.co/article/5989da08ab0ee8fa60b76a28

The risk of effects to fishes and other aquatic life from impulsive sound produced by activities such as pile driving and seismic exploration is increasing throughout the world, particularly with the increased exploitation of oceans for energy production. At the same time, there are few data that provide insight into the effects of these sounds on fishes. The goal of this study was to provide quantitative data to define the levels of impulsive sound that could result in the onset of barotrauma to fish. A High Intensity Controlled Impedance Fluid filled wave Tube was developed that enabled laboratory simulation of high-energy impulsive sound that were characteristic of aquatic far-field, plane-wave acoustic conditions. The sounds used were based upon the impulsive sounds generated by an impact hammer striking a steel shell pile. Neutrally buoyant juvenile Chinook salmon (Oncorhynchus tshawytscha) were exposed to impulsive sounds and subsequently evaluated for barotrauma injuries. Observed injuries ranged from mild hematomas at the lowest sound exposure levels to organ hemorrhage at the highest sound exposure levels. Frequency of observed injuries were used to compute a biological response weighted index (RWI) to evaluate the physiological impact of injuries at the different exposure levels. As single strike and cumulative sound exposure levels (SELss, SELcum respectively) increased, RWI values increased. Based on the results, tissue damage associated with adverse physiological costs occurred when the RWI was greater than 2. In terms of sound exposure levels a RWI of 2 was achieved for 1920 strikes by 177 dB re 1 µPa2⋅s SELss yielding a SELcum of 210 dB re 1 µPa2⋅s, and for 960 strikes by 180 dB re 1 µPa2⋅s SELss yielding a SELcum of 210 dB re 1 µPa2⋅s. These metrics define thresholds for onset of injury in juvenile Chinook salmon.

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<![CDATA[Capturing Single Cell Genomes of Active Polysaccharide Degraders: An Unexpected Contribution of Verrucomicrobia]]> https://www.researchpad.co/article/5989dabcab0ee8fa60baef96

Microbial hydrolysis of polysaccharides is critical to ecosystem functioning and is of great interest in diverse biotechnological applications, such as biofuel production and bioremediation. Here we demonstrate the use of a new, efficient approach to recover genomes of active polysaccharide degraders from natural, complex microbial assemblages, using a combination of fluorescently labeled substrates, fluorescence-activated cell sorting, and single cell genomics. We employed this approach to analyze freshwater and coastal bacterioplankton for degraders of laminarin and xylan, two of the most abundant storage and structural polysaccharides in nature. Our results suggest that a few phylotypes of Verrucomicrobia make a considerable contribution to polysaccharide degradation, although they constituted only a minor fraction of the total microbial community. Genomic sequencing of five cells, representing the most predominant, polysaccharide-active Verrucomicrobia phylotype, revealed significant enrichment in genes encoding a wide spectrum of glycoside hydrolases, sulfatases, peptidases, carbohydrate lyases and esterases, confirming that these organisms were well equipped for the hydrolysis of diverse polysaccharides. Remarkably, this enrichment was on average higher than in the sequenced representatives of Bacteroidetes, which are frequently regarded as highly efficient biopolymer degraders. These findings shed light on the ecological roles of uncultured Verrucomicrobia and suggest specific taxa as promising bioprospecting targets. The employed method offers a powerful tool to rapidly identify and recover discrete genomes of active players in polysaccharide degradation, without the need for cultivation.

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<![CDATA[Hydropower's Biogenic Carbon Footprint]]> https://www.researchpad.co/article/5989da2bab0ee8fa60b82860

Global warming is accelerating and the world urgently needs a shift to clean and renewable energy. Hydropower is currently the largest renewable source of electricity, but its contribution to climate change mitigation is not yet fully understood. Hydroelectric reservoirs are a source of biogenic greenhouse gases and in individual cases can reach the same emission rates as thermal power plants. Little is known about the severity of their emissions at the global scale. Here we show that the carbon footprint of hydropower is far higher than previously assumed, with a global average of 173 kg CO2 and 2.95 kg CH4 emitted per MWh of electricity produced. This results in a combined average carbon footprint of 273 kg CO2e/MWh when using the global warming potential over a time horizon of 100 years (GWP100). Nonetheless, this is still below that of fossil energy sources without the use of carbon capture and sequestration technologies. We identified the dams most promising for capturing methane for use as alternative energy source. The spread among the ~1500 hydropower plants analysed in this study is large and highlights the importance of case-by-case examinations.

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<![CDATA[Photovoltaic Grid-Connected Modeling and Characterization Based on Experimental Results]]> https://www.researchpad.co/article/5989d9faab0ee8fa60b71a6a

A grid-connected photovoltaic (PV) system operates under fluctuated weather condition has been modeled and characterized based on specific test bed. A mathematical model of a small-scale PV system has been developed mainly for residential usage, and the potential results have been simulated. The proposed PV model based on three PV parameters, which are the photocurrent, IL, the reverse diode saturation current, Io, the ideality factor of diode, n. Accuracy of the proposed model and its parameters evaluated based on different benchmarks. The results showed that the proposed model fitting the experimental results with high accuracy compare to the other models, as well as the I-V characteristic curve. The results of this study can be considered valuable in terms of the installation of a grid-connected PV system in fluctuated climatic conditions.

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<![CDATA[Electricity forecasting on the individual household level enhanced based on activity patterns]]> https://www.researchpad.co/article/5989db53ab0ee8fa60bdca3a

Leveraging smart metering solutions to support energy efficiency on the individual household level poses novel research challenges in monitoring usage and providing accurate load forecasting. Forecasting electricity usage is an especially important component that can provide intelligence to smart meters. In this paper, we propose an enhanced approach for load forecasting at the household level. The impacts of residents’ daily activities and appliance usages on the power consumption of the entire household are incorporated to improve the accuracy of the forecasting model. The contributions of this paper are threefold: (1) we addressed short-term electricity load forecasting for 24 hours ahead, not on the aggregate but on the individual household level, which fits into the Residential Power Load Forecasting (RPLF) methods; (2) for the forecasting, we utilized a household specific dataset of behaviors that influence power consumption, which was derived using segmentation and sequence mining algorithms; and (3) an extensive load forecasting study using different forecasting algorithms enhanced by the household activity patterns was undertaken.

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<![CDATA[Marine Habitat Selection by Marbled Murrelets (Brachyramphus marmoratus) during the Breeding Season]]> https://www.researchpad.co/article/5989dabeab0ee8fa60bafb85

The marbled murrelet (Brachyramphus marmoratus) is a declining seabird that is well-known for nesting in coastal old-growth forests in the Pacific Northwest. Most studies of habitat selection have focused on modeling terrestrial nesting habitat even though marine habitat is believed to be a major contributor to population declines in some regions. To address this information gap, we conducted a 5-year study of marine resource selection by murrelets in Washington, which contains a population experiencing the steepest documented declines and where marine habitat is believed to be compromised. Across five years we tracked 157 radio-tagged murrelets during the breeding season (May to August), and used discrete choice models to examine habitat selection. Using an information theoretic approach, our global model had the most support, suggesting that murrelet resource selection at-sea is affected by many factors, both terrestrial and marine. Locations with higher amounts of nesting habitat (β = 21.49, P < 0.001) that were closer to shore (β = -0.0007, P < 0.001) and in cool waters (β = -0.2026, P < 0.001) with low footprint (β = -0.0087, P < 0.001) had higher probabilities of use. While past conservation efforts have focused on protecting terrestrial nesting habitat, we echo many past studies calling for future efforts to protect marine habitat for murrelets, as the current emphasis on terrestrial habitat alone may be insufficient for conserving populations. In particular, marine areas in close proximity to old-growth nesting habitat appear important for murrelets during the breeding season and should be priorities for protection.

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<![CDATA[PSO-Based Smart Grid Application for Sizing and Optimization of Hybrid Renewable Energy Systems]]> https://www.researchpad.co/article/5989dafcab0ee8fa60bc4fec

This paper introduces an optimal sizing algorithm for a hybrid renewable energy system using smart grid load management application based on the available generation. This algorithm aims to maximize the system energy production and meet the load demand with minimum cost and highest reliability. This system is formed by photovoltaic array, wind turbines, storage batteries, and diesel generator as a backup source of energy. Demand profile shaping as one of the smart grid applications is introduced in this paper using load shifting-based load priority. Particle swarm optimization is used in this algorithm to determine the optimum size of the system components. The results obtained from this algorithm are compared with those from the iterative optimization technique to assess the adequacy of the proposed algorithm. The study in this paper is performed in some of the remote areas in Saudi Arabia and can be expanded to any similar regions around the world. Numerous valuable results are extracted from this study that could help researchers and decision makers.

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<![CDATA[Effects of Leading Edge Defect on the Aerodynamic and Flow Characteristics of an S809 Airfoil]]> https://www.researchpad.co/article/5989da45ab0ee8fa60b8b6f9

Background

Unexpected performance degradation occurs in wind turbine blades due to leading edge defect when suffering from continuous impacts with rain drops, hails, insects, or solid particles during its operation life. To assess this issue, this paper numerically investigates the steady and dynamic stall characteristics of an S809 airfoil with various leading edge defects. More leading edge defect sizes and much closer to practical parameters are investigated in the paper.

Methodology

Numerical computation is conducted using the SST k-ω turbulence model, and the method has been validated by comparison with existed published data. In order to ensure the calculation convergence, the residuals for the continuity equation are set to be less than 10−7 and 10−6 in steady state and dynamic stall cases. The simulations are conducted with the software ANSYS Fluent 13.0.

Results

It is found that the characteristics of aerodynamic coefficients and flow fields are sensitive to leading edge defect both in steady and dynamic conditions. For airfoils with the defect thickness of 6%tc, leading edge defect has a relative small influence on the aerodynamics of S809 airfoil. For other investigated defect thicknesses, leading edge defect has much greater influence on the flow field structures, pressure coefficients and aerodynamic characteristics of airfoil at relative small defect lengths. For example, the lift coefficients decrease and drag coefficients increase sharply after the appearance of leading edge defect. However, the aerodynamic characteristics could reach a constant value when the defect length is large enough. The flow field, pressure coefficient distribution and aerodynamic coefficients do not change a lot when the defect lengths reach to 0.5%c,1%c, 2%c and 3%c with defect thicknesses of 6%tc, 12%tc,18%tc and 25%tc, respectively. In addition, the results also show that the critical defect length/thickness ratio is 0.5, beyond which the aerodynamic characteristics nearly remain unchanged. In dynamic stall, leading edge defect imposes a greater influence on the aerodynamic characteristics of airfoil than steady conditions. By increasing in defect length, it is found that the separated area becomes more intense and moves forward along the suction surface.

Conclusions

Leading edge defect has significant influence on the aerodynamic and flow characteristics of the airfoil, which will reach a stable status with enough large defect size. The leading edge separation bubble, circulation in the defect cavity and intense tailing edge vortex are the main features of flow around defective airfoils.

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<![CDATA[Potential Impacts of Offshore Wind Farms on North Sea Stratification]]> https://www.researchpad.co/article/5989da85ab0ee8fa60b9befe

Advances in offshore wind farm (OWF) technology have recently led to their construction in coastal waters that are deep enough to be seasonally stratified. As tidal currents move past the OWF foundation structures they generate a turbulent wake that will contribute to a mixing of the stratified water column. In this study we show that the mixing generated in this way may have a significant impact on the large-scale stratification of the German Bight region of the North Sea. This region is chosen as the focus of this study since the planning of OWFs is particularly widespread. Using a combination of idealised modelling and in situ measurements, we provide order-of-magnitude estimates of two important time scales that are key to understanding the impacts of OWFs: (i) a mixing time scale, describing how long a complete mixing of the stratification takes, and (ii) an advective time scale, quantifying for how long a water parcel is expected to undergo enhanced wind farm mixing. The results are especially sensitive to both the drag coefficient and type of foundation structure, as well as the evolution of the pycnocline under enhanced mixing conditions—both of which are not well known. With these limitations in mind, the results show that OWFs could impact the large-scale stratification, but only when they occupy extensive shelf regions. They are expected to have very little impact on large-scale stratification at the current capacity in the North Sea, but the impact could be significant in future large-scale development scenarios.

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