Power maximization of a point absorber wave energy converter using improved model predictive control
Milani, Farideh; Moghaddam, Reihaneh Kardehi
2017-08-01
This paper considers controlling and maximizing the absorbed power of wave energy converters for irregular waves. With respect to physical constraints of the system, a model predictive control is applied. Irregular waves' behavior is predicted by Kalman filter method. Owing to the great influence of controller parameters on the absorbed power, these parameters are optimized by imperialist competitive algorithm. The results illustrate the method's efficiency in maximizing the extracted power in the presence of unknown excitation force which should be predicted by Kalman filter.
Wilmore, Jack H.; And Others
1986-01-01
Sixty-two subjects completed a four-stage submaximal cycle ergometer test to determine if estimates of maximal oxygen uptake could be improved by using ratings of perceived exertion singly or in combination with easily obtainable physiological measures. These procedures could be used to estimate the aerobic power of patients and athletes. (MT)
Sossan, Fabrizio; Kosek, Anna Magdalena; Martinenas, Sergejus
2013-01-01
to predict the future temperature of the water and it manages its state (on and off) according to the forecasted PV production, which are computed starting from forecast of the solar irradiance. Simulations for the proof of concept and for validating the proposed control strategy are proposed. Results......This paper presents a model predictive control (MPC) strategy for maximizing photo-voltaic (PV) selfconsumption in a household context exploiting the flexible demand of an electric water heater. The predictive controller uses a water heater model and forecast of the hot Water consumption in order...... of the control approach are compared with a traditional thermostatic controller using historical measurements of a 10 kW PV installation. Economic results based on the Italian self consumption tariffs are also reported. The model of the water heater complex is a mixed grey and white box and its parameters have...
Østerås, Sindre; Welde, Boye; Danielsen, Jørgen; van den Tillaar, Roland; Ettema, Gertjan; Sandbakk, Øyvind
2016-09-01
Østerås, S, Welde, B, Danielsen, J, van den Tillaar, R, Ettema, G, and Sandbakk, Ø. Contribution of upper-body strength, body composition, and maximal oxygen uptake to predict double poling power and overall performance in female cross-country skiers. J Strength Cond Res 30(9): 2557-2564, 2016-Maximal oxygen uptake (V[Combining Dot Above]O2max) is regarded as the most performance-differentiating physiological measure in cross-country (XC) skiing. In addition, upper-body strength and lean mass have been associated with double poling (DP) power in XC skiers. In this study, we tested upper-body maximal strength, lean mass, and V[Combining Dot Above]O2max's contributions to predict DP power production of different durations and the overall XC skiing performance level of elite female XC skiers. Thirteen skiers (V[Combining Dot Above]O2max: 64.9 ± 4.2 ml·kg·min) performed one 30-second and one 3-minute DP performance test using a ski ergometer. The International Ski Federation's (FIS) ranking points determined their overall XC skiing performance. The skiers performed three 1-repetition maximal strength tests in poling-specific exercises that isolated the elbow extension, shoulder extension, and trunk flexion movements. Body composition was determined by a DXA scan, and V[Combining Dot Above]O2max was tested in an incremental running test. Multiple regressions were used to predict power production in the 30-second and 3-minute tests and FIS points. The 2 best predictions of 30-second DP power were lean upper-body mass and maximal upper-body strength (with the 3 strength tests normalized and pooled together as one variable) (R = 0.84 and 0.81, p skiing performance (R = 0.43 and 0.40, p ≤ 0.05). Although the importance of upper-body strength and lean mass to predict DP power production and the overall XC skiing performance declines with the performance duration in female XC skiers, the importance of V[Combining Dot Above]O2max shows an opposite relationship.
Predicting Contextual Sequences via Submodular Function Maximization
Dey, Debadeepta; Hebert, Martial; Bagnell, J Andrew
2012-01-01
Sequence optimization, where the items in a list are ordered to maximize some reward has many applications such as web advertisement placement, search, and control libraries in robotics. Previous work in sequence optimization produces a static ordering that does not take any features of the item or context of the problem into account. In this work, we propose a general approach to order the items within the sequence based on the context (e.g., perceptual information, environment description, and goals). We take a simple, efficient, reduction-based approach where the choice and order of the items is established by repeatedly learning simple classifiers or regressors for each "slot" in the sequence. Our approach leverages recent work on submodular function maximization to provide a formal regret reduction from submodular sequence optimization to simple cost-sensitive prediction. We apply our contextual sequence prediction algorithm to optimize control libraries and demonstrate results on two robotics problems: ...
A cycle ergometer test of maximal aerobic power.
Myles, W S; Toft, R J
1982-01-01
An indirect test of maximal aerobic power (IMAP) was evaluated in 31 healthy male subjects by comparing it with a direct treadmill measurement of maximal aerobic power (VO2 max), with the prediction of VO2 max from heart rate during submaximal exercise on a cycle ergometer using Astrand's nomogram, with the British Army's Basic Fitness Test (BFT, a 2.4 km run performed in boots and trousers), and with a test of maximum anaerobic power. For the IMAP test, subjects pedalled on a cycle ergometer at 75 revs X min-1. The workload was 37.5 watts for the first minute, and was increased by 37.5 watts every minute until the subject could not continue. Time to exhaustion was recorded. Predicted VO2 max and times for BFT and IMAP correlated significantly (p less than 0.001) with the direct VO2 max: r = 0.70, r = 0.67 and r = 0.79 respectively. The correlation between direct VO2 max and the maximum anaerobic power test was significant (p less than 0.05) but lower, r = 0.44. Although lactate levels after direct VO2 max determination were significantly higher than those after the IMAP test, maximum heart rates were not significantly different. Submaximal VO2 values measured during the IMAP test yielded a regression equation relating VO2 and pedalling time. When individual values for direct and predicted VO2 max and times for BFT and IMAP were compared with equivalent standards, the percentages of subjects able to exceed the standard were 100, 65, 87, and 87 respectively. These data demonstrate that the IMAP test provides a valid estimate of VO2 max and indicate that it may be a practical test for establishing that an individual meets a minimum standard.
Maximally Flat Waveforms Operation of Class-F Power Amplifiers
V. Krizhanovski
2001-04-01
Full Text Available The requirements to output network's impedance on higher harmoniccomponents and appropriate input driving for formation maximally flatwaveforms of drain current and voltage were presented. Using suchwaveforms allows obtaining maximal efficiency and output powercapability of class-F power amplifiers.
Carnot cycle at finite power: attainability of maximal efficiency.
Allahverdyan, Armen E; Hovhannisyan, Karen V; Melkikh, Alexey V; Gevorkian, Sasun G
2013-08-01
We want to understand whether and to what extent the maximal (Carnot) efficiency for heat engines can be reached at a finite power. To this end we generalize the Carnot cycle so that it is not restricted to slow processes. We show that for realistic (i.e., not purposefully designed) engine-bath interactions, the work-optimal engine performing the generalized cycle close to the maximal efficiency has a long cycle time and hence vanishing power. This aspect is shown to relate to the theory of computational complexity. A physical manifestation of the same effect is Levinthal's paradox in the protein folding problem. The resolution of this paradox for realistic proteins allows to construct engines that can extract at a finite power 40% of the maximally possible work reaching 90% of the maximal efficiency. For purposefully designed engine-bath interactions, the Carnot efficiency is achievable at a large power.
LOAD THAT MAXIMIZES POWER OUTPUT IN COUNTERMOVEMENT JUMP
Pedro Jimenez-Reyes
2016-02-01
Full Text Available ABSTRACT Introduction: One of the main problems faced by strength and conditioning coaches is the issue of how to objectively quantify and monitor the actual training load undertaken by athletes in order to maximize performance. It is well known that performance of explosive sports activities is largely determined by mechanical power. Objective: This study analysed the height at which maximal power output is generated and the corresponding load with which is achieved in a group of male-trained track and field athletes in the test of countermovement jump (CMJ with extra loads (CMJEL. Methods: Fifty national level male athletes in sprinting and jumping performed a CMJ test with increasing loads up to a height of 16 cm. The relative load that maximized the mechanical power output (Pmax was determined using a force platform and lineal encoder synchronization and estimating the power by peak power, average power and flight time in CMJ. Results: The load at which the power output no longer existed was at a height of 19.9 ± 2.35, referring to a 99.1 ± 1% of the maximum power output. The load that maximizes power output in all cases has been the load with which an athlete jump a height of approximately 20 cm. Conclusion: These results highlight the importance of considering the height achieved in CMJ with extra load instead of power because maximum power is always attained with the same height. We advise for the preferential use of the height achieved in CMJEL test, since it seems to be a valid indicative of an individual's actual neuromuscular potential providing a valid information for coaches and trainers when assessing the performance status of our athletes and to quantify and monitor training loads, measuring only the height of the jump in the exercise of CMJEL.
Maximizing Statistical Power When Verifying Probabilistic Forecasts of Hydrometeorological Events
DeChant, C. M.; Moradkhani, H.
2014-12-01
Hydrometeorological events (i.e. floods, droughts, precipitation) are increasingly being forecasted probabilistically, owing to the uncertainties in the underlying causes of the phenomenon. In these forecasts, the probability of the event, over some lead time, is estimated based on some model simulations or predictive indicators. By issuing probabilistic forecasts, agencies may communicate the uncertainty in the event occurring. Assuming that the assigned probability of the event is correct, which is referred to as a reliable forecast, the end user may perform some risk management based on the potential damages resulting from the event. Alternatively, an unreliable forecast may give false impressions of the actual risk, leading to improper decision making when protecting resources from extreme events. Due to this requisite for reliable forecasts to perform effective risk management, this study takes a renewed look at reliability assessment in event forecasts. Illustrative experiments will be presented, showing deficiencies in the commonly available approaches (Brier Score, Reliability Diagram). Overall, it is shown that the conventional reliability assessment techniques do not maximize the ability to distinguish between a reliable and unreliable forecast. In this regard, a theoretical formulation of the probabilistic event forecast verification framework will be presented. From this analysis, hypothesis testing with the Poisson-Binomial distribution is the most exact model available for the verification framework, and therefore maximizes one's ability to distinguish between a reliable and unreliable forecast. Application of this verification system was also examined within a real forecasting case study, highlighting the additional statistical power provided with the use of the Poisson-Binomial distribution.
Levy, R.; Mcginness, H.
1976-01-01
Investigations were performed to predict the power available from the wind at the Goldstone, California, antenna site complex. The background for power prediction was derived from a statistical evaluation of available wind speed data records at this location and at nearby locations similarly situated within the Mojave desert. In addition to a model for power prediction over relatively long periods of time, an interim simulation model that produces sample wind speeds is described. The interim model furnishes uncorrelated sample speeds at hourly intervals that reproduce the statistical wind distribution at Goldstone. A stochastic simulation model to provide speed samples representative of both the statistical speed distributions and correlations is also discussed.
Maximal power output estimates the MLSS before and after aerobic training
Carolina Franco Wilke; Guilherme Passos Ramos; André Maia Lima; Christian Emmanuel Torres Cabido; Cristiano Lino Monteiro de Barros; Thiago Teixeira Mendes; Emerson Silami Garcia
2014-01-01
The purpose of this study is to present an equation to predict the maximal lactate steady state (MLSS) through a VO2peak incremental protocol. Twenty-six physically active men were divided in two groups (G1 and G2). They performed one maximal incremental test to determine their VO2peak and maximal power output (Wpeak), and also several constant intensity tests to determine MLSS intensity (MLSSw) on a cycle ergometer. Group G2 underwent six weeks of aerobic training at MLSSw. A regression equa...
Integral circulant graphs of prime power order with maximal energy
Sander, Jürgen W; 10.1016/j.laa.2011.05.039
2011-01-01
The energy of a graph is the sum of the moduli of the eigenvalues of its adjacency matrix. We study the energy of integral circulant graphs, also called gcd graphs, which can be characterized by their vertex count n and a set D of divisors of n in such a way that they have vertex set Zn and edge set {{a, b} : a, b in Zn; gcd(a - b, n) in D}. Using tools from convex optimization, we study the maximal energy among all integral circulant graphs of prime power order ps and varying divisor sets D. Our main result states that this maximal energy approximately lies between s(p - 1)p^(s-1) and twice this value. We construct suitable divisor sets for which the energy lies in this interval. We also characterize hyperenergetic integral circulant graphs of prime power order and exhibit an interesting topological property of their divisor sets.
Wind Power Prediction Investigation
Yuanlong Liu
2013-02-01
Full Text Available Daily and real-time forecast data of wind power is predicted in this study using three methods, which are Kalman filter model, GARCH model and time-series-based BP neural network model. Then, owing to evaluation to the calculation of accuracy and qualification rate, the best method, the time-series-based BP neural network model, was selected for its highest accuracy. Moreover, the prediction error influence due to convergence of wind turbine is on consideration according to the evaluation. Finally, suggestions of improving the prediction accuracy were put forward based on the discussion of accuracy-obstacle factors.
Discussion on: "Profit maximization of a power plant"
Boomsma, Trine Krogh; Fleten, Stein-Erik
2012-01-01
Kragelund et al. provides an interesting contribution to operations scheduling in liberalized electricity markets. They address the problem of profit maximization for a power plant participating in the electricity market. In particular, given that the plant has already been dispatched in a day......-ahead market, the aim is to schedule production throughout an operation day while complying with the day-ahead commitments, referred to in the paper as tracking a predefined production reference. The authors refer to Fig. 2 for an example of a production reference plan for a power plant of DONG Energy. A minor...... with the balancing mechanisms in most electricity markets, since no (or only very small) deviations are acceptable....
Prediction of Maximal Heart Rate in Children and Adolescents.
Gelbart, Miri; Ziv-Baran, Tomer; Williams, Craig A; Yarom, Yoni; Dubnov-Raz, Gal
2017-03-01
To identify a method to predict the maximal heart rate (MHR) in children and adolescents, as available prediction equations developed for adults have a low accuracy in children. We hypothesized that MHR may be influenced by resting heart rate, anthropometric factors, or fitness level. Cross-sectional study. Sports medicine center in primary care. Data from 627 treadmill maximal exercise tests performed by 433 pediatric athletes (age 13.7 ± 2.1 years, 70% males) were analyzed. Age, sex, sport type, stature, body mass, BMI, body fat, fitness level, resting, and MHR were recorded. To develop a prediction equation for MHR in youth, using stepwise multivariate linear regression and linear mixed model. To determine correlations between existing prediction equations and pediatric MHR. Observed MHR was 197 ± 8.6 b·min. Regression analysis revealed that resting heart rate, fitness, body mass, and fat percent were predictors of MHR (R = 0.25, P MHR variance, body mass added 5.7%, fat percent added 2.4%, and fitness added 1.2%. Existing adult equations had low correlations with observed MHR in children and adolescents (r = -0.03-0.34). A new equation to predict MHR in children and adolescents was developed, but was found to have low predictive ability, a finding similar to adult equations applied to children. Considering the narrow range of MHR in youth, we propose using 197 b·min as the mean MHR in children and adolescents, with 180 b·min the minimal threshold value (-2 standard deviations).
Partial AUC maximization for essential gene prediction using genetic algorithms.
Hwang, Kyu-Baek; Ha, Beom-Yong; Ju, Sanghun; Kim, Sangsoo
2013-01-01
Identifying genes indispensable for an organism's life and their characteristics is one of the central questions in current biological research, and hence it would be helpful to develop computational approaches towards the prediction of essential genes. The performance of a predictor is usually measured by the area under the receiver operating characteristic curve (AUC). We propose a novel method by implementing genetic algorithms to maximize the partial AUC that is restricted to a specific interval of lower false positive rate (FPR), the region relevant to follow-up experimental validation. Our predictor uses various features based on sequence information, protein-protein interaction network topology, and gene expression profiles. A feature selection wrapper was developed to alleviate the over-fitting problem and to weigh each feature's relevance to prediction. We evaluated our method using the proteome of budding yeast. Our implementation of genetic algorithms maximizing the partial AUC below 0.05 or 0.10 of FPR outperformed other popular classification methods.
Does power indicate capacity? 30-s Wingate anaerobic test vs. maximal accumulated O2 deficit.
Minahan, C; Chia, M; Inbar, O
2007-10-01
The purpose of this study was to evaluate the relationship between anaerobic power and capacity. Seven men and seven women performed a 30-s Wingate Anaerobic Test on a cycle ergometer to determine peak power, mean power, and the fatigue index. Subjects also cycled at a work rate predicted to elicit 120 % of peak oxygen uptake to exhaustion to determine the maximal accumulated O (2) deficit. Peak power and the maximal accumulated O (2) deficit were significantly correlated (r = 0.782, p = 0.001). However, when the absolute difference in exercise values between groups (men and women) was held constant using a partial correlation, the relationship diminished (r = 0.531, p = 0.062). In contrast, we observed a significant correlation between fatigue index and the maximal accumulated O (2) deficit when controlling for gender (r = - 0.597, p = 0.024) and the relationship remained significant when values were expressed relative to active muscle mass. A higher anaerobic power does not indicate a greater anaerobic capacity. Furthermore, we suggest that the ability to maintain power output during a 30-s cycle sprint is related to anaerobic capacity.
Hyuck-Min Kweon
2014-12-01
Full Text Available To maximize electric power production using wave energy extractions from resonance power buoys, the maximum motion displacement spectra of the buoys can primarily be obtained under a given wave condition. In this study, wave spectra observed in shoaling water were formulated. Target resonance frequencies were established from the arithmetic means of modal frequency bands and the peak frequencies. The motion characteristics of the circular cylindrical power buoys with corresponding drafts were then calculated using numerical models without considering PTO damping force. Results showed that the heave motions of the power buoys in shoaling waters with insufficient drafts produced greater amplification effects than those in deep seas with sufficient drafts.
Yang, Guangye; Jia, Suotang; Mihalache, Dumitru
2013-01-01
We address the possibility to control high power pulses extracted from the maximally compressed pulse in a nonlinear optical fiber by adjusting the initial excitation parameters. The numerical results show that the power, location and splitting order number of the maximally compressed pulse and the transmission features of high power pulses extracted from the maximally compressed pulse can be manipulated through adjusting the modulation amplitude, width, and phase of the initial Gaussian-type perturbation pulse on a continuous wave background.
A new approach to assessing maximal aerobic power in children: the Odense School Child Study.
Hansen, H S; Froberg, K; Nielsen, J R; Hyldebrandt, N
1989-01-01
In two experiments maximal aerobic power (VO2max) calculated from maximal mechanical power (Wmax) was evaluated in 39 children aged 9-11 years. A maximal multi-stage cycle ergometer exercise test was used with an increase in work load every 3 min. In the first experiment oxygen consumption was measured in 18 children during each of the prescribed work loads and a correction factor was calculated to estimate VO2max using the equation VO2max = 12.Wmax + 5.weight. An appropriate increase in work rate based on height was determined for boys (0.16 W.cm-1) and girls (0.15 W.cm-1) respectively. In the second experiment 21 children performed a maximal cycle ergometer exercise test twice. In addition to the procedure in the first experiment a similar exercise test was performed, but without measurement of oxygen uptake. Calculated VO2max correlated significantly (p less than 0.01) with those values measured in both boys (r = 0.90) and girls (r = 0.95) respectively, and the standard error of estimation for VO2max (calculated) on VO2max (measured) was less than 3.2%. Two expressions of relative work load (%VO2max and %Wmax) were established and found to be closely correlated. The relative work load in %VO2max could be predicted from the relative work load in %Wmax with an average standard error of 3.8%. The data demonstrate that calculated VO2max based on a maximal multi-stage exercise test provides an accurate and valid estimate of VO2max.
Time of day has no effect on maximal aerobic and peak power
Sesboüé B
2011-08-01
Full Text Available N Bessot1,3, S Moussay1,2, B Dufour1,2, D Davenne1,2, B Sesboüé1,3, A Gauthier1,21Inserm, ERI27, Caen, France; 2University Caen, Caen, France; 3CHRU Caen, Explorations Fonctionnelles, Caen, FranceBackground: The aim of this study was to explore the effect of time of day on peak power reached during an exercise test and maximal aerobic power achieved when the subject reached maximal oxygen uptake.Methods: Fifteen male competitive endurance cyclists performed a standardized maximal incremental exercise test at 06:00 hours and 18:00 hours. The test began with a 5-minute warmup period at a workload of 150 W. The work rate was then increased by incremental steps of 30 W per minute until the respiratory exchange ratio reached 1.00. Thereafter, workload was increased in steps of 15 W per minute until exhaustion was reached.Results: No significant diurnal variation was detected in physiological parameters (maximal oxygen uptake and maximal heart rate or biomechanical parameters (maximal aerobic power, peak power.Conclusion: Circadian variations classically reported in competitive aerobic performances could be due to fluctuations in maximal aerobic endurance and/or improvement in gestural efficiency (pattern of muscle activity, effective force production, and kinematics.Keywords: chronobiology, maximal aerobic power, peak power, maximal oxygen uptake, maximal incremental test
Timmons, James A; Knudsen, Steen; Rankinen, Tuomo
2010-01-01
A low maximal oxygen consumption (VO2max) is a strong risk factor for premature mortality. Supervised endurance exercise training increases VO2max with a very wide range of effectiveness in humans. Discovering the DNA variants that contribute to this heterogeneity typically requires substantial s...... of genetic biomarkers, sufficiently discrete for diagnostic purposes, for a range of physiological and pharmacological phenotypes in humans.......A low maximal oxygen consumption (VO2max) is a strong risk factor for premature mortality. Supervised endurance exercise training increases VO2max with a very wide range of effectiveness in humans. Discovering the DNA variants that contribute to this heterogeneity typically requires substantial...... association analysis yields a strongly validated molecular predictor with meaningful explanatory power. VO2max responses to endurance training can be predicted by measuring a approximately 30-gene RNA expression signature in muscle prior to training. The general approach taken could accelerate the discovery...
Bianba, B; Berntsen, S; Andersen, Lars Bo
2010-01-01
Chinese children aged 9-10 years, living in Lhasa at 3700 meters above sea level, V.O2peak was measured directly using a portable oxygen analyzer, and predicted from maximal power output (Wmax) using a maximal cycle ergometer test. RESULTS: In multiple regression analyses with V.O2peak as dependent......AIM: The aims of the present study of Tibetan and Han Chinese children were to establish prediction equations for peak oxygen uptake (V.O2peak) using conventional power output measures, and to compare with prediction models based on data from sea level. METHODS: In 25 Tibetan children and 15 Han...... with the equations from the present study. None of the three could accurately predict the direct measured V.O2peak, and predictions differed in an unsystematic manner, including over- or underestimation and no differentiation between genders. CONCLUSION: Peak oxygen uptake could be estimated from Wmax and sex...
Maximizing MST's inductive capability with a Bp programmable power supply
Chapman, B. E.; Holly, D. J.; Jacobson, C. M.; McCollam, K. J.; Morin, J. C.; Sarff, J. S.; Squitieri, A.
2016-10-01
A major goal of the MST program is the advancement of inductive control for the development of both the RFP's fusion potential and, synergistically, the predictive capability of fusion science. This entails programmable power supplies (PPS's) for the Bt and Bp circuits. A Bt PPS is already in place, allowing advanced RFP operation and the production of tokamak plasmas, and a Bp PPS prototype is under construction. To explore some of the new capabilities to be provided by the Bp PPS, the existing Bt PPS has been temporarily connected to the Bp circuit. One key result is new-found access to very low Ip (20 kA) and very low Lundquist number, S (104). At this low S, simulation of RFP plasmas with the MHD code NIMROD is readily achievable, and work toward validation of extended MHD models using NIMROD is underway with direct comparisons to these MST plasmas. The full Bp PPS will also provide higher Ip and S than presently possible, allowing MST to produce plasmas with S spanning as much as five orders of magnitude, a dramatic extension of MST's capability. In these initial tests, the PPS has also increased five-fold MST's Ip flattop duration, to about 100 ms. This, coupled with the recently demonstrated PPS ability to drive large-amplitude sinusoidal oscillations in Ip, will allow tests of extended-duration oscillating field current drive, the goal of which is ac sustainment of a quasi-dc plasma current. Work supported by US DOE.
Mohsen Taherbaneh; A. H. Rezaie; H. Ghafoorifard; Rahimi, K; M. B. Menhaj
2010-01-01
In applications with low-energy conversion efficiency, maximizing the output power improves the efficiency. The maximum output power of a solar panel depends on the environmental conditions and load profile. In this paper, a method based on simultaneous use of two fuzzy controllers is developed in order to maximize the generated output power of a solar panel in a photovoltaic system: fuzzy-based sun tracking and maximum power point tracking. The sun tracking is performed by changing the solar...
Maximal power output estimates the MLSS before and after aerobic training
Carolina Franco Wilke
2014-06-01
Full Text Available The purpose of this study is to present an equation to predict the maximal lactate steady state (MLSS through a VO2peak incremental protocol. Twenty-six physically active men were divided in two groups (G1 and G2. They performed one maximal incremental test to determine their VO2peak and maximal power output (Wpeak, and also several constant intensity tests to determine MLSS intensity (MLSSw on a cycle ergometer. Group G2 underwent six weeks of aerobic training at MLSSw. A regression equation was created using G1 subjects Wpeak and MLSSw to estimate the MLSS intensity (MLSSweq before and after training for G2 (MLSSweq = 0.866 x Wpeak-41.734. The mean values were not different (150±27W vs 148±27W, before training / 171±26W vs 177±24W, after training and significant correlations were found between the measured and the estimated MLSSw before (r²=0.49 and after training (r²=0.62 in G2. The proposed equation was effective to estimate the MLSS intensity before and after aerobic training.
Abut F
2015-08-01
Full Text Available Fatih Abut, Mehmet Fatih AkayDepartment of Computer Engineering, Çukurova University, Adana, TurkeyAbstract: Maximal oxygen uptake (VO2max indicates how many milliliters of oxygen the body can consume in a state of intense exercise per minute. VO2max plays an important role in both sport and medical sciences for different purposes, such as indicating the endurance capacity of athletes or serving as a metric in estimating the disease risk of a person. In general, the direct measurement of VO2max provides the most accurate assessment of aerobic power. However, despite a high level of accuracy, practical limitations associated with the direct measurement of VO2max, such as the requirement of expensive and sophisticated laboratory equipment or trained staff, have led to the development of various regression models for predicting VO2max. Consequently, a lot of studies have been conducted in the last years to predict VO2max of various target audiences, ranging from soccer athletes, nonexpert swimmers, cross-country skiers to healthy-fit adults, teenagers, and children. Numerous prediction models have been developed using different sets of predictor variables and a variety of machine learning and statistical methods, including support vector machine, multilayer perceptron, general regression neural network, and multiple linear regression. The purpose of this study is to give a detailed overview about the data-driven modeling studies for the prediction of VO2max conducted in recent years and to compare the performance of various VO2max prediction models reported in related literature in terms of two well-known metrics, namely, multiple correlation coefficient (R and standard error of estimate. The survey results reveal that with respect to regression methods used to develop prediction models, support vector machine, in general, shows better performance than other methods, whereas multiple linear regression exhibits the worst performance
Maximally Flat Waveforms with Finite Number of Harmonics in Class-F Power Amplifiers
Anamarija Juhas
2013-01-01
Full Text Available In this paper general solution to the problem of finding maximally flat waveforms with finite number of harmonics (maximally flat trigonometric polynomials is provided. Waveform coefficients are expressed in closed form as functions of harmonic orders. Two special cases of maximally flat waveforms (so-called maximally flat even harmonic and maximally flat odd harmonic waveforms, which proved to play an important role in class-F and inverse class-F power amplifier (PA operations, are also considered. For these two special types of waveforms, coefficients are expressed as functions of two parameters only. Closed form expressions for efficiency and power output capability of class-F and inverse class-F PA operations with maximally flat waveforms are also provided as explicit functions of number of a harmonics.
Predicting Failures in Power Grids
Chertkov, Michael; Stepanov, Mikhail G
2010-01-01
Here we develop an approach to predict power grid weak points, and specifically to efficiently identify the most probable failure modes in load distribution for a given power network. This approach is applied to two examples: Guam's power system and also the IEEE RTS-96 system, both modeled within the static Direct Current power flow model. Our algorithm is a power network adaption of the worst configuration heuristics, originally developed to study low probability events in physics and failures in error-correction. One finding is that, if the normal operational mode of the grid is sufficiently healthy, the failure modes, also called instantons, are sufficiently sparse, i.e. the failures are caused by load fluctuations at only a few buses. The technique is useful for discovering weak links which are saturated at the instantons. It can also identify overutilized and underutilized generators, thus providing predictive capability for improving the reliability of any power network.
Norhisam Misron
2016-08-01
Full Text Available A new control estimator to maximize the power generated with a maximum power point estimator is introduced. The power mapping characteristics from the double-stator generator are modeled as a mathematical equation which is used to develop the estimator for maximum power tracking to maximize the generated power. The proposed estimator automatically traces the instantaneous maximum power at various load conditions. However, to stabilize the output voltage, a boost converter is used from the inverter side. The developed double-stator generator is tested with the new estimator for the maximizing power generation capability under laboratory conditions. The experimental results confirm that with the new estimator, the average power generation capability is increased by 12% and the peak value is increase by 22%.
Solo Power: How One-Person Librarians Maximize Their Influence.
St. Clair, Guy
1997-01-01
One person librarians or solo librarians are the information providers of the future. This article discusses the need for solo librarians to be concerned with power and influence; service to customers; and political awareness/shared vision/partnership with management. Sidebar contains the OPL (One-Person Library) Manifesto with fundamental…
Sliding Mode Control Strategy for Wind Turbine Power Maximization
Oscar Barambones
2012-07-01
Full Text Available The efficiency of the wind power conversions systems can be greatly improved using an appropriate control algorithm. In this work, a sliding mode control for variable speed wind turbine that incorporates a doubly fed induction generator is described. The electrical system incorporates a wound rotor induction machine with back-to-back three phase power converter bridges between its rotor and the grid. In the presented design the so-called vector control theory is applied, in order to simplify the electrical equations. The proposed control scheme uses stator flux-oriented vector control for the rotor side converter bridge control and grid voltage vector control for the grid side converter bridge control. The stability analysis of the proposed sliding mode controller under disturbances and parameter uncertainties is provided using the Lyapunov stability theory. Finally simulated results show, on the one hand, that the proposed controller provides high-performance dynamic characteristics, and on the other hand, that this scheme is robust with respect to the uncertainties that usually appear in the real systems.
Power maximization for pyroelectric, piezoelectric, and hybrid energy harvesting
Shaheen, Murtadha A.
The goal of this dissertation consists of improving the efficiency of energy harvesting using pyroelectric and piezoelectric materials in a system by the proper characterization of electrical parameters, widening frequency, and coupling of both effects with the appropriate parameters. A new simple stand-alone method of characterizing the impedance of a pyroelectric cell has been demonstrated. This method utilizes a Pyroelectric single pole low pass filter technique, PSLPF. Utilizing the properties of a PSLPF, where a known input voltage is applied and capacitance C p and resistance Rp can be calculated at a frequency of 1 mHz to 1 Hz. This method demonstrates that for pyroelectric materials the impedance depends on two major factors: average working temperature, and the heating rate. Design and implementation of a hybrid approach using multiple piezoelectric cantilevers is presented. This is done to achieve mechanical and electrical tuning, along with bandwidth widening. In addition, a hybrid tuning technique with an improved adjusting capacitor method was applied. An toroid inductor of 700 mH is shunted in to the load resistance and shunt capacitance. Results show an extended frequency range up to 12 resonance frequencies (300% improvement) with improved power up to 197%. Finally, a hybrid piezoelectric and pyroelectric system is designed and tested. Using a voltage doubler, circuit for rectifying and collecting pyroelectric and piezoelectric voltages individually is proposed. The investigation showed that the hybrid energy is possible using the voltage doubler circuit from two independent sources for pyroelectrictity and piezoelectricity due to marked differences of optimal performance.
Accounting for complementarity to maximize monitoring power for species management.
Tulloch, Ayesha I T; Chadès, Iadine; Possingham, Hugh P
2013-10-01
To choose among conservation actions that may benefit many species, managers need to monitor the consequences of those actions. Decisions about which species to monitor from a suite of different species being managed are hindered by natural variability in populations and uncertainty in several factors: the ability of the monitoring to detect a change, the likelihood of the management action being successful for a species, and how representative species are of one another. However, the literature provides little guidance about how to account for these uncertainties when deciding which species to monitor to determine whether the management actions are delivering outcomes. We devised an approach that applies decision science and selects the best complementary suite of species to monitor to meet specific conservation objectives. We created an index for indicator selection that accounts for the likelihood of successfully detecting a real trend due to a management action and whether that signal provides information about other species. We illustrated the benefit of our approach by analyzing a monitoring program for invasive predator management aimed at recovering 14 native Australian mammals of conservation concern. Our method selected the species that provided more monitoring power at lower cost relative to the current strategy and traditional approaches that consider only a subset of the important considerations. Our benefit function accounted for natural variability in species growth rates, uncertainty in the responses of species to the prescribed action, and how well species represent others. Monitoring programs that ignore uncertainty, likelihood of detecting change, and complementarity between species will be more costly and less efficient and may waste funding that could otherwise be used for management. © 2013 Society for Conservation Biology.
Power Utility Maximization in an Exponential Lévy Model Without a Risk-free Asset
Qing Zhou
2005-01-01
We consider the problem of maximizing the expected power utility from terminal wealth in a market where logarithmic securities prices follow a Levy process. By Girsanov's theorem, we give explicit solutions for power utility of undiscounted terminal wealth in terms of the Levy-Khintchine triplet.
Abut, Fatih; Akay, Mehmet Fatih
2015-01-01
Maximal oxygen uptake (VO2max) indicates how many milliliters of oxygen the body can consume in a state of intense exercise per minute. VO2max plays an important role in both sport and medical sciences for different purposes, such as indicating the endurance capacity of athletes or serving as a metric in estimating the disease risk of a person. In general, the direct measurement of VO2max provides the most accurate assessment of aerobic power. However, despite a high level of accuracy, practical limitations associated with the direct measurement of VO2max, such as the requirement of expensive and sophisticated laboratory equipment or trained staff, have led to the development of various regression models for predicting VO2max. Consequently, a lot of studies have been conducted in the last years to predict VO2max of various target audiences, ranging from soccer athletes, nonexpert swimmers, cross-country skiers to healthy-fit adults, teenagers, and children. Numerous prediction models have been developed using different sets of predictor variables and a variety of machine learning and statistical methods, including support vector machine, multilayer perceptron, general regression neural network, and multiple linear regression. The purpose of this study is to give a detailed overview about the data-driven modeling studies for the prediction of VO2max conducted in recent years and to compare the performance of various VO2max prediction models reported in related literature in terms of two well-known metrics, namely, multiple correlation coefficient (R) and standard error of estimate. The survey results reveal that with respect to regression methods used to develop prediction models, support vector machine, in general, shows better performance than other methods, whereas multiple linear regression exhibits the worst performance.
Can cycle power predict sprint running performance?
van Ingen Schenau, G J; Jacobs, R; de Koning, J J
1991-01-01
A major criticism of present models of the energetics and mechanics of sprint running concerns the application of estimates of parameters which seem to be adapted from measurements of running during actual competitions. This study presents a model which does not perpetuate this solecism. Using data obtained during supra-maximal cycle ergometer tests of highly trained athletes, the kinetics of the anaerobic and aerobic pathways were modelled. Internal power wasted in the acceleration and deceleration of body limbs and the power necessary to overcome air friction was calculated from data in the literature. Assuming a mechanical efficiency as found during submaximal cycling, a power equation was constructed which also included the power necessary to accelerate the body at the start of movement. The differential equation thus obtained was solved through simulation. The model appeared to predict realistic times at 100 m (10.47 s), 200 m (19.63 s) and 400 m (42.99 s) distances. By comparison with other methods it is argued that power equations of locomotion should include the concept of mechanical efficiency.
Rouis Majdi
2016-06-01
Full Text Available The aim of this study was to verify the impact of ethnicity on the maximal power-vertical jump relationship. Thirty-one healthy males, sixteen Caucasian (age: 26.3 ± 3.5 years; body height: 179.1 ± 5.5 cm; body mass: 78.1 ± 9.8 kg and fifteen Afro-Caribbean (age: 24.4 ±2.6 years; body height: 178.9 ± 5.5 cm; body mass: 77.1 ± 10.3 kg completed three sessions during which vertical jump height and maximal power of lower limbs were measured. The results showed that the values of vertical jump height and maximal power were higher for Afro-Caribbean participants (62.92 ± 6.7 cm and 14.70 ± 1.75 W∙kg-1 than for Caucasian ones (52.92 ± 4.4 cm and 12.75 ± 1.36 W∙kg-1. Moreover, very high reliability indices were obtained on vertical jump (e.g. 0.95 < ICC < 0.98 and maximal power performance (e.g. 0.75 < ICC < 0.97. However, multiple linear regression analysis showed that, for a given value of maximal power, the Afro-Caribbean participants jumped 8 cm higher than the Caucasians. Together, these results confirmed that ethnicity impacted the maximal power-vertical jump relationship over three sessions. In the current context of cultural diversity, the use of vertical jump performance as a predictor of muscular power should be considered with caution when dealing with populations of different ethnic origins.
Mohsen Taherbaneh
2010-01-01
Full Text Available In applications with low-energy conversion efficiency, maximizing the output power improves the efficiency. The maximum output power of a solar panel depends on the environmental conditions and load profile. In this paper, a method based on simultaneous use of two fuzzy controllers is developed in order to maximize the generated output power of a solar panel in a photovoltaic system: fuzzy-based sun tracking and maximum power point tracking. The sun tracking is performed by changing the solar panel orientation in horizontal and vertical directions by two DC motors properly designed. A DC-DC converter is employed to track the solar panel maximum power point. In addition, the proposed system has the capability of the extraction of solar panel I-V curves. Experimental results present that the proposed fuzzy techniques result in increasing of power delivery from the solar panel, causing a reduction in size, weight, and cost of solar panels in photovoltaic systems.
Bianba, B; Berntsen, S; Andersen, Lars Bo;
2010-01-01
in a progressive cycle ergometer test among children living at 3700 meters in Tibet. The estimate of V.O2peak is probably more valid using the present equations than prediction models based on data from sea level. The equations used for the prediction are: BianbaeqT: (l·min-1) = 0.5419 + (0.0096· Wmax) - (0...... Chinese children aged 9-10 years, living in Lhasa at 3700 meters above sea level, V.O2peak was measured directly using a portable oxygen analyzer, and predicted from maximal power output (Wmax) using a maximal cycle ergometer test. RESULTS: In multiple regression analyses with V.O2peak as dependent......AIM: The aims of the present study of Tibetan and Han Chinese children were to establish prediction equations for peak oxygen uptake (V.O2peak) using conventional power output measures, and to compare with prediction models based on data from sea level. METHODS: In 25 Tibetan children and 15 Han...
Using Maximal Isometric Force to Determine the Optimal Load for Measuring Dynamic Muscle Power
Spiering, Barry A.; Lee, Stuart M. C.; Mulavara, Ajitkumar P.; Bentley, Jason R.; Nash, Roxanne E.; Sinka, Joseph; Bloomberg, Jacob J.
2009-01-01
Maximal power output occurs when subjects perform ballistic exercises using loads of 30-50% of one-repetition maximum (1-RM). However, performing 1-RM testing prior to power measurement requires considerable time, especially when testing involves multiple exercises. Maximal isometric force (MIF), which requires substantially less time to measure than 1-RM, might be an acceptable alternative for determining the optimal load for power testing. PURPOSE: To determine the optimal load based on MIF for maximizing dynamic power output during leg press and bench press exercises. METHODS: Twenty healthy volunteers (12 men and 8 women; mean +/- SD age: 31+/-6 y; body mass: 72 +/- 15 kg) performed isometric leg press and bench press movements, during which MIF was measured using force plates. Subsequently, subjects performed ballistic leg press and bench press exercises using loads corresponding to 20%, 30%, 40%, 50%, and 60% of MIF presented in randomized order. Maximal instantaneous power was calculated during the ballistic exercise tests using force plates and position transducers. Repeated-measures ANOVA and Fisher LSD post hoc tests were used to determine the load(s) that elicited maximal power output. RESULTS: For the leg press power test, six subjects were unable to be tested at 20% and 30% MIF because these loads were less than the lightest possible load (i.e., the weight of the unloaded leg press sled assembly [31.4 kg]). For the bench press power test, five subjects were unable to be tested at 20% MIF because these loads were less than the weight of the unloaded aluminum bar (i.e., 11.4 kg). Therefore, these loads were excluded from analysis. A trend (p = 0.07) for a main effect of load existed for the leg press exercise, indicating that the 40% MIF load tended to elicit greater power output than the 60% MIF load (effect size = 0.38). A significant (p . 0.05) main effect of load existed for the bench press exercise; post hoc analysis indicated that the effect of
Souza, Kristopher Mendes; de Lucas, Ricardo Dantas; do Nascimento Salvador, Paulo Cesar; Guglielmo, Luiz Guilherme Antonacci; Caritá, Renato Aparecido Corrêa; Greco, Camila Coelho; Denadai, Benedito Sérgio
2015-09-01
The aim of this study was to investigate whether the maximal power output (Pmax) during an incremental test was dependent on the curvature constant (W') of the power-time relationship. Thirty healthy male subjects (maximal oxygen uptake = 3.58 ± 0.40 L·min(-1)) performed a ramp incremental cycling test to determine the maximal oxygen uptake and Pmax, and 4 constant work rate tests to exhaustion to estimate 2 parameters from the modeling of the power-time relationship (i.e., critical power (CP) and W'). Afterwards, the participants were ranked according to their magnitude of W'. The median third was excluded to form a high W' group (HIGH, n = 10), and a low W' group (LOW, n = 10). Maximal oxygen uptake (3.84 ± 0.50 vs. 3.49 ± 0.37 L·min(-1)) and CP (213 ± 22 vs. 200 ± 29 W) were not significantly different between HIGH and LOW, respectively. However, Pmax was significantly greater for the HIGH (337 ± 23 W) than for the LOW (299 ± 40 W). Thus, in physically active individuals with similar aerobic parameters, W' influences the Pmax during incremental testing.
Determination of the peak power output during maximal brief pedalling bouts.
Nakamura, Y; Mutoh, Y; Miyashita, M
1985-01-01
The purpose of this study was to propose an optimization procedure for determining power output during very brief maximal pedalling exercise. Twenty-six healthy male students (21-28 years) performed anaerobic tests on a Monark bicycle ergometer with maximal effort for less than 10 s at eight different loads ranging from 28.1 to 84.2 Nm in pedalling moment. The maximal pedalling rate was determined from the minimal time required for one rotation of the cycle wheel. Pedalling rate decreased linearly with the load. The relationship between load and pedalling rate was represented by two linear regression equations for each subject; one regression equation was determined from eight pairs of pedalling rates and loads (r less than -0.976) and the other from three pairs (at 28.1, 46.8, 65.5 Nm; r less than -0.969). The two regression coefficients of the respective regression equations were almost identical. Mean +/- S.D. of maximal power output (Pmax) which was determined for each subject based on the two linear regression equations for eight pairs and three pairs of pedalling rates and loads was 930 +/- 187 W (13.4 +/- 1.6 W kgBW-1) and 927 +/- 187 W (13.4 +/- 1.6 W kgBW-1), respectively. There was no statistically significant difference between the values of Pmax which were obtained from each equation. It was concluded that maximal anaerobic power could be simply determined by performing maximal cycling exercise at three different loads.
The Measurement of Maximal (Anaerobic Power Output on a Cycle Ergometer: A Critical Review
Tarak Driss
2013-01-01
Full Text Available The interests and limits of the different methods and protocols of maximal (anaerobic power ( assessment are reviewed: single all-out tests versus force-velocity tests, isokinetic ergometers versus friction-loaded ergometers, measure of during the acceleration phase or at peak velocity. The effects of training, athletic practice, diet and pharmacological substances upon the production of maximal mechanical power are not discussed in this review mainly focused on the technical (ergometer, crank length, toe clips, methodological (protocols and biological factors (muscle volume, muscle fiber type, age, gender, growth, temperature, chronobiology and fatigue limiting in cycling. Although the validity of the Wingate test is questionable, a large part of the review is dedicated to this test which is currently the all-out cycling test the most often used. The biomechanical characteristics specific of maximal and high speed cycling, the bioenergetics of the all-out cycling exercises and the influence of biochemical factors (acidosis and alkalosis, phosphate ions… are recalled at the beginning of the paper. The basic knowledge concerning the consequences of the force-velocity relationship upon power output, the biomechanics of sub-maximal cycling exercises and the study on the force-velocity relationship in cycling by Dickinson in 1928 are presented in Appendices.
In vivo muscle force and muscle power during near-maximal frog jumps.
Moo, Eng Kuan; Peterson, Daniel R; Leonard, Timothy R; Kaya, Motoshi; Herzog, Walter
2017-01-01
Frogs' outstanding jumping ability has been associated with a high power output from the leg extensor muscles. Two main theories have emerged to explain the high power output of the frog leg extensor muscles, either (i) the contractile conditions of all leg extensor muscles are optimized in terms of muscle length and speed of shortening, or (ii) maximal power is achieved through a dynamic catch mechanism that uncouples fibre shortening from the corresponding muscle-tendon unit shortening. As in vivo instantaneous power generation in frog hind limb muscles during jumping has never been measured directly, it is hard to distinguish between the two theories. In this study, we determined the instantaneous variable power output of the plantaris longus (PL) of Lithobates pipiens (also known as Rana pipiens), by directly measuring the in vivo force, length change, and speed of muscle and fibre shortening in near maximal jumps. Fifteen near maximal jumps (> 50cm in horizontal distance) were analyzed. High instantaneous peak power in PL (536 ± 47 W/kg) was achieved by optimizing the contractile conditions in terms of the force-length but not the force-velocity relationship, and by a dynamic catch mechanism that decouples fascicle shortening from muscle-tendon unit shortening. We also found that the extra-muscular free tendon likely amplifies the peak power output of the PL by modulating fascicle shortening length and shortening velocity for optimum power output, but not by releasing stored energy through recoiling as the tendon only started recoiling after peak PL power had been achieved.
In vivo muscle force and muscle power during near-maximal frog jumps
Leonard, Timothy R.; Kaya, Motoshi; Herzog, Walter
2017-01-01
Frogs’ outstanding jumping ability has been associated with a high power output from the leg extensor muscles. Two main theories have emerged to explain the high power output of the frog leg extensor muscles, either (i) the contractile conditions of all leg extensor muscles are optimized in terms of muscle length and speed of shortening, or (ii) maximal power is achieved through a dynamic catch mechanism that uncouples fibre shortening from the corresponding muscle-tendon unit shortening. As in vivo instantaneous power generation in frog hind limb muscles during jumping has never been measured directly, it is hard to distinguish between the two theories. In this study, we determined the instantaneous variable power output of the plantaris longus (PL) of Lithobates pipiens (also known as Rana pipiens), by directly measuring the in vivo force, length change, and speed of muscle and fibre shortening in near maximal jumps. Fifteen near maximal jumps (> 50cm in horizontal distance) were analyzed. High instantaneous peak power in PL (536 ± 47 W/kg) was achieved by optimizing the contractile conditions in terms of the force-length but not the force-velocity relationship, and by a dynamic catch mechanism that decouples fascicle shortening from muscle-tendon unit shortening. We also found that the extra-muscular free tendon likely amplifies the peak power output of the PL by modulating fascicle shortening length and shortening velocity for optimum power output, but not by releasing stored energy through recoiling as the tendon only started recoiling after peak PL power had been achieved. PMID:28282405
S. T. Jaya Christa
2006-06-01
Full Text Available This paper deals with the optimal location and parameters of Unified Power Flow Controllers (UPFCs in electrical power systems, using particle swarm optimization (PSO. The objective is to maximize the transmission system loadability subject to the transmission line capacity limits and specified bus voltage levels. Using the proposed method, the location of UPFCs and their parameters are optimized simultaneously. PSO is used to solve the above non-linear programming problem for better accuracy. The proposed approach is examined and tested on IEEE 30-bus system and IEEE 118-bus system. The results obtained are quite promising for the power system operation environment
San Martín, René; Appelbaum, Lawrence G; Pearson, John M; Huettel, Scott A; Woldorff, Marty G
2013-04-17
Success in many decision-making scenarios depends on the ability to maximize gains and minimize losses. Even if an agent knows which cues lead to gains and which lead to losses, that agent could still make choices yielding suboptimal rewards. Here, by analyzing event-related potentials (ERPs) recorded in humans during a probabilistic gambling task, we show that individuals' behavioral tendencies to maximize gains and to minimize losses are associated with their ERP responses to the receipt of those gains and losses, respectively. We focused our analyses on ERP signals that predict behavioral adjustment: the frontocentral feedback-related negativity (FRN) and two P300 (P3) subcomponents, the frontocentral P3a and the parietal P3b. We found that, across participants, gain maximization was predicted by differences in amplitude of the P3b for suboptimal versus optimal gains (i.e., P3b amplitude difference between the least good and the best gains). Conversely, loss minimization was predicted by differences in the P3b amplitude to suboptimal versus optimal losses (i.e., difference between the worst and the least bad losses). Finally, we observed that the P3a and P3b, but not the FRN, predicted behavioral adjustment on subsequent trials, suggesting a specific adaptive mechanism by which prior experience may alter ensuing behavior. These findings indicate that individual differences in gain maximization and loss minimization are linked to individual differences in rapid neural responses to monetary outcomes.
Jalil Ataee
2014-06-01
Full Text Available Accommodation resistance is a training technique that may improve strength and power gains beyond those achieved by traditional free weights. In this method, chains are either added on a free-weight bar and combined with traditional plates or added to the bar as the entire load. Purpose. The aim of the current study was to compare the effectiveness of accommodation and constant resistance training methods during a four-week period on maximal strength and power in trained athletes. Methods. This study was comprised of 24 trained athletes, including 16 trained males [8 Wushu athletes (Kung-Fu and 8 wrestlers, age: 20.5 ± 2.00 yrs. old]. Participants were initially tested on weight, body circumference, fat percent, upper and lower body maximal strength, determined by the 1-repetition maximum (1RM test, which determines the greatest amount of weight a person can successfully lift, and upper and lower body power. Participants were equally randomized to either accommodation or constant resistance training groups. Both groups underwent resistance training for a four-week period that consisted of three sessions per week. Multivariate repeated-measures analyses of variance of the data were used to verify significant differences in strength and power between groups. The modified Bonferroni post hoc test was used to compare the obtained results in pre-, mid-, and post test. Results. In the accommodation resistance group, there was a significant difference in lower body maximal strength compared to the constant group (163.12 ± 18.82 kg in the accommodation group vs. 142.25 ± 20.04 kg in the constant group, P = 0.04. No significant differences were found in upper body power, lower body power, and upper body maximal strength between the two groups (P > 0.05. Conclusion. Although there was only a significant difference in lower body maximal strength between groups, accommodation resistance training may induce a physiological training response by improving
Morimoto, Shigeo; Nakamura, Tomohiko; Takeda, Yoji
This paper proposes the sensorless output power maximization control of the wind generation system. A permanent magnet synchronous generator (PMSG) is used as a variable speed generator in the proposed system. The generator torque is suitably controlled according to the generator speed and thus the power from a wind turbine settles down on the maximum power point by the proposed MPPT control method, where the information of wind velocity is not required. Moreover, the maximum available generated power is obtained by the optimum current vector control. The current vector of PMSG is optimally controlled according to the generator speed and the required torque in order to minimize the losses of PMSG considering the voltage and current constraints. The proposed wind power generation system can be achieved without mechanical sensors such as a wind velocity detector and a position sensor. Several experimental results show the effectiveness of the proposed control method.
Optimal design parameters of the bicycle-rider system for maximal muscle power output.
Yoshihuku, Y; Herzog, W
1990-01-01
The purpose of this study was to find the optimal values of design parameters for a bicycle-rider system (crank length, pelvic inclination, seat height, and rate of crank rotation) which maximize the power output from muscles of the human lower limb during bicycling. The human lower limb was modelled as a planar system of five rigid bodies connected by four smooth pin joints and driven by seven functional muscle groups. The muscles were assumed to behave according to an adapted form of Hill's equation. The dependence of the average power on the design parameters was examined. The instantaneous power of each muscle group was studied and simultaneous activity of two seemingly antagonistic muscle groups was analyzed. Average peak power for one full pedal revolution was found to be around 1100 W. The upper body position corresponding to this peak power output was slightly reclined, and the pedalling rate was 155 rpm for a nominal crank length of 170 mm.
Maximal aerobic capacity in ageing subjects: actual measurements versus predicted values
Cristina Pistea; Evelyne Lonsdorfer; Stéphane Doutreleau; Monique Oswald; Irina Enache; Anne Charloux
2016-01-01
We evaluated the impact of selection of reference values on the categorisation of measured maximal oxygen consumption (V′O2 peak) as “normal” or “abnormal” in an ageing population. We compared measured V′O2 peak with predicted values and the lower limit of normal (LLN) calculated with five equations. 99 (58 males and 41 females) disease-free subjects aged ≥70 years completed an incremental maximal exercise test on a cycle ergometer. Mean V′O2 peak was 1.88 L·min−1 in men and 1.26 L·min−1 in w...
Lithium-thionyl chloride battery design concepts for maximized power applications
Kane, P.; Marincic, N.
The need for primary batteries configured to deliver maximized power has been asserted by many different procuring activities. Battery Engineering Inc. has developed some specific design concepts and mastered some specialized techniques utilized in the production of this type of power source. The batteries have been successfully bench tested during the course of virtually all of these programs, with ultimate success coming in the form of two successful test launches under the USAF Plasma Effects Decoy Program. This paper briefly discusses some of these design concepts and the rationale behind them.
Wind tunnel testing of a closed-loop wake deflection controller for wind farm power maximization
Campagnolo, Filippo; Petrović, Vlaho; Schreiber, Johannes; Nanos, Emmanouil M.; Croce, Alessandro; Bottasso, Carlo L.
2016-09-01
This paper presents results from wind tunnel tests aimed at evaluating a closed- loop wind farm controller for wind farm power maximization by wake deflection. Experiments are conducted in a large boundary layer wind tunnel, using three servo-actuated and sensorized wind turbine scaled models. First, we characterize the impact on steady-state power output of wake deflection, achieved by yawing the upstream wind turbines. Next, we illustrate the capability of the proposed wind farm controller to dynamically driving the upstream wind turbines to the optimal yaw misalignment setting.
Maximal heart rate prediction in adults that are overweight or obese.
Franckowiak, Shawn C; Dobrosielski, Devon A; Reilley, Suzanne M; Walston, Jeremy D; Andersen, Ross E
2011-05-01
An accurate predictor of maximal heart rate (MHR) is necessary to prescribe safe and effective exercise in those considered overweight and obese when actual measurement of MHR is unavailable or contraindicated. To date, accuracy of MHR prediction equations in individuals that are overweight or obese has not been well established. The purpose of this study was to examine the accuracy of 3 equations for predicting MHR in adults that are overweight or obese. One hundred seventy-three sedentary adults that were overweight or obese enrolled in weight-loss study and performed a VO₂peak treadmill test before the start of the weight loss treatment. A total of 132 of the 173 participants met conditions for achieving maximal exercise testing criteria and were included in this study. Maximal heart rate values determined from VO₂peak treadmill tests were compared across gender, age, and weight status with the following prediction equations: (a) 220 - age, (b) 208 - 0.7 × age, and (c) 200 - 0.48 × age. Among 20- to 40-year-old participants, actual MHR averaged 180 ± 9 b·min⁻¹ and was overestimated (p MHR to be 178 ± 4 b·min⁻¹, which was greater than the actual value (175 ± 12, p = 0.005). Prediction equations showed close agreement to actual MHR, with 208 - 0.7 × age being the most accurate.
Squat jump training at maximal power loads vs. heavy loads: effect on sprint ability.
Harris, Nigel K; Cronin, John B; Hopkins, Will G; Hansen, Keir T
2008-11-01
Training at a load maximizing power output (Pmax) is an intuitively appealing strategy for enhancement of performance that has received little research attention. In this study we identified each subject's Pmax for an isoinertial resistance training exercise used for testing and training, and then we related the changes in strength to changes in sprint performance. The subjects were 18 well-trained rugby league players randomized to two equal-volume training groups for a 7-week period of squat jump training with heavy loads (80% 1RM) or with individually determined Pmax loads (20.0-43.5% 1RM). Performance measures were 1RM strength, maximal power at 55% of pretraining 1RM, and sprint times for 10 and 30 m. Percent changes were standardized to make magnitude-based inferences. Relationships between changes in these variables were expressed as correlations. Sprint times for 10 m showed improvements in the 80% 1RM group (-2.9 +/- 3.2%) and Pmax group (-1.3 +/- 2.2%), and there were similar improvements in 30-m sprint time (-1.9 +/- 2.8 and -1.2 +/- 2.0%, respectively). Differences in the improvements in sprint time between groups were unclear, but improvement in 1RM strength in the 80% 1RM group (15 +/- 9%) was possibly substantially greater than in the Pmax group (11 +/- 8%). Small-moderate negative correlations between change in 1RM and change in sprint time (r approximately -0.30) in the combined groups provided the only evidence of adaptive associations between strength and power outputs, and sprint performance. In conclusion, it seems that training at the load that maximizes individual peak power output for this exercise with a sample of professional team sport athletes was no more effective for improving sprint ability than training at heavy loads, and the changes in power output were not usefully related to changes in sprint ability.
Energy Efficiency Maximization for WSNs with Simultaneous Wireless Information and Power Transfer.
Yu, Hongyan; Zhang, Yongqiang; Guo, Songtao; Yang, Yuanyuan; Ji, Luyue
2017-08-18
Recently, the simultaneous wireless information and power transfer (SWIPT) technique has been regarded as a promising approach to enhance performance of wireless sensor networks with limited energy supply. However, from a green communication perspective, energy efficiency optimization for SWIPT system design has not been investigated in Wireless Rechargeable Sensor Networks (WRSNs). In this paper, we consider the tradeoffs between energy efficiency and three factors including spectral efficiency, the transmit power and outage target rate for two different modes, i.e., power splitting (PS) and time switching modes (TS), at the receiver. Moreover, we formulate the energy efficiency maximization problem subject to the constraints of minimum Quality of Service (QoS), minimum harvested energy and maximum transmission power as non-convex optimization problem. In particular, we focus on optimizing power control and power allocation policy in PS and TS modes to maximize energy efficiency of data transmission. For PS and TS modes, we propose the corresponding algorithm to characterize a non-convex optimization problem that takes into account the circuit power consumption and the harvested energy. By exploiting nonlinear fractional programming and Lagrangian dual decomposition, we propose suboptimal iterative algorithms to obtain the solutions of non-convex optimization problems. Furthermore, we derive the outage probability and effective throughput from the scenarios that the transmitter does not or partially know the channel state information (CSI) of the receiver. Simulation results illustrate that the proposed optimal iterative algorithm can achieve optimal solutions within a small number of iterations and various tradeoffs between energy efficiency and spectral efficiency, transmit power and outage target rate, respectively.
Lee, Joong Seok; Lee, Il Kyu; Seung, Hong Min; Lee, Jun Kyu; Kim, Yoon Young
2017-03-01
Joints with slowly varying tapered shapes, such as linear or exponential profiles, are known to transmit incident wave power efficiently between two waveguides with dissimilar impedances. This statement is valid only when the considered joint length is longer than the wavelengths of the incident waves. When the joint length is shorter than the wavelengths, however, appropriate shapes of such subwavelength joints for efficient power transmission have not been explored much. In this work, considering one-dimensional torsional wave motion in a cylindrical elastic waveguide system, optimal shapes or radial profiles of a subwavelength joint maximizing the power transmission coefficient are designed by a gradient-based optimization formulation. The joint is divided into a number of thin disk elements using the transfer matrix approach and optimal radii of the disks are determined by iterative shape optimization processes for several single or bands of wavenumbers. Due to the subwavelength constraint, the optimized joint profiles were found to be considerably different from the slowly varying tapered shapes. Specifically, for bands of wavenumbers, peculiar gourd-like shapes were obtained as optimal shapes to maximize the power transmission coefficient. Numerical results from the proposed optimization formulation were also experimentally realized to verify the validity of the present designs.
Du, Sijun; Jia, Yu; Seshia, Ashwin
2015-12-01
A resonant vibration energy harvester typically comprises of a clamped anchor and a vibrating shuttle with a proof mass. Piezoelectric materials are embedded in locations of high strain in order to transduce mechanical deformation into electric charge. Conventional design for piezoelectric vibration energy harvesters (PVEH) usually utilizes piezoelectric material and metal electrode layers covering the entire surface area of the cantilever with no consideration provided to examining the trade-off involved with respect to maximizing output power. This paper reports on the theory and experimental verification underpinning optimization of the active electrode area of a cantilevered PVEH in order to maximize output power. The analytical formulation utilizes Euler-Bernoulli beam theory to model the mechanical response of the cantilever. The expression for output power is reduced to a fifth order polynomial expression as a function of the electrode area. The maximum output power corresponds to the case when 44% area of the cantilever is covered by electrode metal. Experimental results are also provided to verify the theory.
Maximal Sprint Power in Road Cyclists After Variable and Nonvariable High-Intensity Exercise.
Menaspà, Paolo; Martin, David T; Victor, James; Abbiss, Chris R
2015-11-01
This study compared the sprint performance of professional cyclists after 10 minutes of variable (VAR) or nonvariable (N-VAR) high-intensity cycling with sprint performance in a rested state. Ten internationally competitive male cyclists (mean ± SD: age, 20.1 ± 1.3 years; stature, 1.81 ± 0.07 m; body weight, 69.5 ± 4.9 kg; and V[Combining Dot Above]O2peak, 72.5 ± 4.4 ml·kg·min) performed a 12-second maximal sprint in 3 conditions: (a) a rested state, (b) after 10 minutes of N-VAR cycling, and (c) after 10 minutes of VAR cycling. The intensity during the 10-minute efforts gradually increased to replicate power output observed in the final section of cycling road races. During the VAR cycling, participants performed short (2 seconds) accelerations at 80% of their sprint peak power, every 30 seconds. Average power output, cadence, and maximal heart rate (HR) during the 10-minute efforts were similar between conditions (5.3 ± 0.2 W·kg, 102 ± 1 rpm, and 93 ± 3% HRmax). Postexercise blood lactate concentration and sessional perceived exertion were also similar (8.3 ± 1.6 mmol·L, 15.4 ± 1.3 [6-20 scale]). Peak and average power output and cadence during the subsequent maximal sprint were not different between the 3 experimental conditions (p > 0.05). In conclusion, this study showed that neither the VAR nor the N-VAR 10-minute efforts ridden in this study impaired sprint performance in elite competitive cyclists.
McNamara, John M; Stearne, David J
2013-06-01
Although there is considerable research on concurrent training, none has integrated flexible nonlinear periodization and maximal-effort cycling in the same design. The purpose of this investigation was to test outcome measures of strength and power using a pretest-posttest randomized groups design. A strength and endurance (SE) group was compared with a strength, endurance, and maximal-effort cycling (SEC) group. Both groups used a flexible nonlinear periodization design. Thirteen male and 7 female students (mean ± SD: age, 22.5 ± 4.1 years; height, 173.5 ± 12.4 cm; weight, 79.4 ± 20.2 kg; strength training experience, 2.4 ± 2.2 years) participated in this study. Groups were not matched for age, height, weight, strength training experience, or sex, but were randomly assigned to an SE (n = 10) or SEC (n = 10) group. All training was completed within 45 minutes, twice per week (Monday and Wednesday), over 12 consecutive weeks. Both groups were assigned 6.75 total hours of aerobic conditioning, and 13.5 hours of free weight and machine exercises totaling 3,188 repetitions ranging from 5 to 20 repetition maximums. The SEC group performed 2 cycling intervals per workout ranging from 10 to 45 seconds. Pretest and posttest measures included chest press and standing broad jump. Analysis of variance showed that there were no significant differences between the SE and SEC groups on measures of chest press or standing broad jump performance (p, not significant). Paired sample t-tests (p = 0.05) showed significant improvement in strength and power in all groups (pretest to posttest), except for SE jump performance (p, not significant). In conclusion, adding maximal-effort cycling does not provide additional strength or power benefits to a concurrent flexible nonlinear training program. However, an exercise professional can take confidence that a concurrent flexible nonlinear training program can increase strength and power in healthy individuals.
Suresh Chintalapudi Venkata
2015-09-01
Full Text Available In this paper a novel non-linear optimization problem is formulated to maximize the social welfare in restructured environment with generalized unified power flow controller (GUPFC. This paper presents a methodology to optimally allocate the reactive power by minimizing voltage deviation at load buses and total transmission power losses so as to maximize the social welfare. The conventional active power generation cost function is modified by combining costs of reactive power generated by the generators, shunt capacitors and total power losses to it. The formulated objectives are optimized individually and simultaneously as multi-objective optimization problem, while satisfying equality, in-equality, practical and device operational constraints. A new optimization method, based on two stage initialization and random distribution processes is proposed to test the effectiveness of the proposed approach on IEEE-30 bus system, and the detailed analysis is carried out.
Fairbarn, M S; Blackie, S P; McElvaney, N G; Wiggs, B R; Paré, P D; Pardy, R L
1994-05-01
Measurement of heart rate and oxygen uptake during incremental exercise and at maximal exercise is useful in evaluating mechanisms responsible for exercise limitation in patients with cardiopulmonary disease. Presently used prediction equations are based on relatively small groups of subjects in whom there was an uneven distribution of subjects with regard to age and sex or based on equations that were from extrapolated data. Our prediction equations are based on data from 231 men and women equally divided within decades between 20 and 80 years. Patients exercised to a symptom-limited maximum on a cycle ergometer while measurements of heart rate and oxygen uptake were recorded. The relationship between heart rate and oxygen uptake throughout exercise (HR:VO2) was determined using a statistical technique that included each data point from each subject. The HR:VO2 throughout incremental exercise was best described by separate equations for women younger than 50 years and older than 50 years and for men younger than 70 years and older than 70 years. Prediction equations for maximal heart rate (HRmax) and maximal oxygen uptake (VO2max) were developed by linear regression and were selected from all possible combinations of parameters. The HRmax was most accurately predicted by age alone for both sexes. Unlike the HR:VO2 relationship, the slope of the line relating heart rate to age was not different for the older women compared with the younger women so that a single equation was derived to predict HRmax. A single equation for the men was also sufficient since the slope of heart rate to age was the same for all ages. To most accurately predict VO2max, a separate equation was required for both the women and men that included age, height, and weight.
Reliability of Maximal Back Squat and Power Clean Performances in Inexperienced Athletes.
Comfort, Paul; McMahon, John J
2015-11-01
The aim of the study was to determine between-session reliability of maximal weight lifted during the back squat and power clean, in inexperienced athletes, and to identify the smallest detectable difference between sessions. Forty-four collegiate athletes (men: n = 32; age: 21.5 ± 2.0 years; height: 180.0 ± 6.1 cm; body mass: 81.01 ± 7.42 kg; women: n = 12; age: 21.0 ± 1.9 years; height: 169.0 ± 5.2 cm; body mass: 62.90 ± 7.46 kg) participated in this study. One repetition maximum (1RM) back squat and power cleans were each performed twice on separate days, 3-5 days apart. Paired samples' t tests revealed no significant differences between trial 1 and trial 2 of the power clean (70.55 ± 24.24 kg, 71.22 ± 23.87 kg, p > 0.05, power = 0.99) and the back squat (130.32 ± 34.05 kg, 129.82 ± 34.07 kg, p > 0.05, power = 1.0). No differences in reliability or measurement error were observed between men and women. Intraclass correlation coefficients (ICCs) demonstrated a high reliability (ICC = 0.997, p clean with an R of 0.987; similarly, high reliability was observed for between-session back squat performances (ICC = 0.994, p 5% to identify a meaningful change in both maximal back squat and power clean performance.
Maximizing photovoltaic power generation of a space-dart configured satellite
Lee, Dae Young; Cutler, James W.; Mancewicz, Joe; Ridley, Aaron J.
2015-06-01
Many small satellites are power constrained due to their minimal solar panel area and the eclipse environment of low-Earth orbit. As with larger satellites, these small satellites, including CubeSats, use deployable power arrays to increase power production. This presents a design opportunity to develop various objective functions related to energy management and methods for optimizing these functions over a satellite design. A novel power generation model was created, and a simulation system was developed to evaluate various objective functions describing energy management for complex satellite designs. The model uses a spacecraft-body-fixed spherical coordinate system to analyze the complex geometry of a satellite's self-induced shadowing with computation provided by the Open Graphics Library. As an example design problem, a CubeSat configured as a space-dart with four deployable panels is optimized. Due to the fast computation speed of the solution, an exhaustive search over the design space is used to find the solar panel deployment angles which maximize total power generation. Simulation results are presented for a variety of orbit scenarios. The method is extendable to a variety of complex satellite geometries and power generation systems.
Optimal Operation of Network-Connected Combined Heat and Powers for Customer Profit Maximization
Da Xie
2016-06-01
Full Text Available Network-connected combined heat and powers (CHPs, owned by a community, can export surplus heat and electricity to corresponding heat and electric networks after community loads are satisfied. This paper proposes a new optimization model for network-connected CHP operation. Both CHPs’ overall efficiency and heat to electricity ratio (HTER are assumed to vary with loading levels. Based on different energy flow scenarios where heat and electricity are exported to the network from the community or imported, four profit models are established accordingly. They reflect the different relationships between CHP energy supply and community load demand across time. A discrete optimization model is then developed to maximize the profit for the community. The models are derived from the intervals determined by the daily operation modes of CHP and real-time buying and selling prices of heat, electricity and natural gas. By demonstrating the proposed models on a 1 MW network-connected CHP, results show that the community profits are maximized in energy markets. Thus, the proposed optimization approach can help customers to devise optimal CHP operating strategies for maximizing benefits.
Maximal aerobic capacity in ageing subjects: actual measurements versus predicted values.
Pistea, Cristina; Lonsdorfer, Evelyne; Doutreleau, Stéphane; Oswald, Monique; Enache, Irina; Charloux, Anne
2016-01-01
We evaluated the impact of selection of reference values on the categorisation of measured maximal oxygen consumption (V'O2peak) as "normal" or "abnormal" in an ageing population. We compared measured V'O2peak with predicted values and the lower limit of normal (LLN) calculated with five equations. 99 (58 males and 41 females) disease-free subjects aged ≥70 years completed an incremental maximal exercise test on a cycle ergometer. Mean V'O2peak was 1.88 L·min(-1) in men and 1.26 L·min(-1) in women. V'O2peak ranged from 89% to 108% of predicted in men, and from 88% to 164% of predicted in women, depending on the reference equation used. The proportion of subjects below the LLN ranged from 5% to 14% in men and 0-22% in women, depending on the reference equation. The LLN was lacking in one study, and was unsuitable for women in another. Most LLNs ranged between 53% and 73% of predicted. Therefore, choosing an 80% cut-off leads to overestimation of the proportion of "abnormal" subjects. To conclude, the proportion of subjects aged ≥70 years with a "low" V'O2peak differs markedly according to the chosen reference equations. In clinical practice, it is still relevant to test a sample of healthy volunteers and select the reference equations that better characterise this sample.
Oliver, Jonathan M.; Almada, Anthony L.; Van Eck, Leighsa E.; Shah, Meena; Mitchell, Joel B.; Jones, Margaret T.; Jagim, Andrew R.; Rowlands, David S.
2016-01-01
Athletes in sports demanding repeat maximal work outputs frequently train concurrently utilizing sequential bouts of intense endurance and resistance training sessions. On a daily basis, maximal work within subsequent bouts may be limited by muscle glycogen availability. Recently, the ingestion of a unique high molecular weight (HMW) carbohydrate was found to increase glycogen re-synthesis rate and enhance work output during subsequent endurance exercise, relative to low molecular weight (LMW) carbohydrate ingestion. The effect of the HMW carbohydrate, however, on the performance of intense resistance exercise following prolonged-intense endurance training is unknown. Sixteen resistance trained men (23±3 years; 176.7±9.8 cm; 88.2±8.6 kg) participated in a double-blind, placebo-controlled, randomized 3-way crossover design comprising a muscle-glycogen depleting cycling exercise followed by ingestion of placebo (PLA), or 1.2 g•kg•bw-1 of LMW or HMW carbohydrate solution (10%) with blood sampling for 2-h post-ingestion. Thereafter, participants performed 5 sets of 10 maximal explosive repetitions of back squat (75% of 1RM). Compared to PLA, ingestion of HMW (4.9%, 90%CI 3.8%, 5.9%) and LMW (1.9%, 90%CI 0.8%, 3.0%) carbohydrate solutions substantially increased power output during resistance exercise, with the 3.1% (90% CI 4.3, 2.0%) almost certain additional gain in power after HMW-LMW ingestion attributed to higher movement velocity after force kinematic analysis (HMW-LMW 2.5%, 90%CI 1.4, 3.7%). Both carbohydrate solutions increased post-exercise plasma glucose, glucoregulatory and gut hormones compared to PLA, but differences between carbohydrates were unclear; thus, the underlying mechanism remains to be elucidated. Ingestion of a HMW carbohydrate following prolonged intense endurance exercise provides superior benefits to movement velocity and power output during subsequent repeated maximal explosive resistance exercise. This study was registered with
Expected Power-Utility Maximization Under Incomplete Information and with Cox-Process Observations
Fujimoto, Kazufumi, E-mail: m_fuji@kvj.biglobe.ne.jp [Bank of Tokyo-Mitsubishi UFJ, Ltd., Corporate Risk Management Division (Japan); Nagai, Hideo, E-mail: nagai@sigmath.es.osaka-u.ac.jp [Osaka University, Division of Mathematical Science for Social Systems, Graduate School of Engineering Science (Japan); Runggaldier, Wolfgang J., E-mail: runggal@math.unipd.it [Universita di Padova, Dipartimento di Matematica Pura ed Applicata (Italy)
2013-02-15
We consider the problem of maximization of expected terminal power utility (risk sensitive criterion). The underlying market model is a regime-switching diffusion model where the regime is determined by an unobservable factor process forming a finite state Markov process. The main novelty is due to the fact that prices are observed and the portfolio is rebalanced only at random times corresponding to a Cox process where the intensity is driven by the unobserved Markovian factor process as well. This leads to a more realistic modeling for many practical situations, like in markets with liquidity restrictions; on the other hand it considerably complicates the problem to the point that traditional methodologies cannot be directly applied. The approach presented here is specific to the power-utility. For log-utilities a different approach is presented in Fujimoto et al. (Preprint, 2012).
An effective control strategy to maximize power extraction from wind turbines
Mouhadjer, Samir; Benmedjahed, Miloud; Neçaïbia, Ammar
2016-07-01
Among the various identifiable renewable energies sources, one holds the attention in this study for its important potential in the world; it's about wind energy. Our objective in this present work is to contribute a share to the research solution to the problems of coupling between this energy source and the load; it's about the transfer of the maximum power to the latter which often suffers from a bad matching. In order to maximize the wind power extraction, this work describes design of a PWM rectifier controller for wind turbines. Generic PWM rectifier is used and PICl6F876 Microcontroller is proposed. The goal of the controller is to keep operating point as close to the maximum efficiency as possible.
Maximizing the Social Welfare of Virtual Power Players Operation in Case of Excessive Wind Power
Faria, Pedro; Vale, Zita; Morais, Hugo
2013-01-01
that aggregates and manages the available energy resources. When facing a situation of excessive non-dispatchable generation, including wind power, real time pricing is applied in order to induce the increase of consumption so that wind curtailment is minimized. This method is especially useful when actual...... and day-ahead resources forecast differ significantly. The distribution network characteristics and concerns are addressed by including the network constraints in the optimization model. The proposed methodology has been implemented in GAMS optimization tool and its application is illustrated...
Koninckx, Erwin; Van Leemputte, Marc; Hespel, Peter
2010-07-01
The aim of this study was to compare the effects of a weight training program for the leg extensors with isokinetic cycling training (80 rpm) on maximal power output and endurance performance. Both strength training interventions were incorporated twice a week in a similar endurance training program of 12 weeks. Eighteen trained male cyclists (VO(2peak) 60 +/- 1 ml kg(-1) min(-1)) were grouped into the weight training (WT n = 9) or the isokinetic training group (IT n = 9) matched for training background and sprint power (P (max)), assessed from five maximal sprints (5 s) on an isokinetic bicycle ergometer at cadences between 40 and 120 rpm. Crank torque was measured (1 kHz) to determine the torque distribution during pedaling. Endurance performance was evaluated by measuring power, heart rate and lactate during a graded exercise test to exhaustion and a 30-min performance test. All tests were performed on subjects' individual race bicycle. Knee extension torque was evaluated isometrically at 115 degrees knee angle and dynamically at 200 degrees s(-1) using an isokinetic dynamometer. P (max) at 40 rpm increased in both the groups (~15%; P < 0.05). At 120 rpm, no improvement of P (max) was found in the IT training group, which was possibly related to an observed change in crank torque at high cadences (P < 0.05). Both groups improved their power output in the 30-min performance test (P < 0.05). Isometric knee extension torque increased only in WT (P < 0.05). In conclusion, at low cadences, P (max) improved in both training groups. However, in the IT training group, a disturbed pedaling technique compromises an improvement of P (max) at high cadences.
Cross-Validation of Age-Predicted Maximal Heart Rate Equations Among Female Collegiate Athletes.
Esco, Michael R; Chamberlain, Nik; Flatt, Andrew A; Snarr, Ronald L; Bishop, Phillip A; Williford, Henry N
2015-11-01
The purpose of this study was to determine the accuracy of 3 general and 2 female-specific age-predicted maximal heart rate (HRmax) prediction equations in female collegiate athletes. Thirty female collegiate athletes (age = 21.5 ± 1.9 years, height = 164.7 ± 6.6 cm, weight = 61.3 ± 8.2 kg) participated. HRmax was determined with a maximal graded exercise test and predicted with 3 general equations (Fox et al., Astrand, and Tanaka et al.) and 2 female-specific equations (Fairbarn et al. and Gulati et al.). There was no significant difference between observed HRmax (185.9 ± 5.0 b·min) and the Fairbarn (187.5 ± 1.2 b·min) and Gulati (187.1 ± 1.7 b·min) equations (p = 0.11 and 0.23, respectively). The Fox (198.5 ± 1.9 b·min), Astrand (198.1 ± 1.6 b·min), and Tanaka (193.0 ± 1.4 b·min) equations provided significantly higher estimates compared with observed HRmax (p < 0.001 for each). The standard error of the estimate was similar for all the prediction equations (between 5.0 and 5.4 b·min), but the total error was smallest for Fairbarn and Gulati (5.3 b·min for each) and largest for Fox and Astrand (13.9 and 13.3 b·min, respectively). The 95% limits of agreement of the mean error were similar for all of the prediction equations, with values varying between 9.9 and 10.5 b·min. Because of the wide limits of agreement displayed by each equation, the use of age-predicted methods for estimating HRmax in collegiate female athletes should be performed only with caution.
Cardenas-Valencia, Andres M.; Short, R. Timothy; Adornato, Lori; Langebrake, Larry
2010-04-01
Use of sensor systems in water bodies has applications that range from environmental and oceanographic research to port and homeland security. Power sources are often the limiting component for further reduction of sensor system size and weight. We present recent investigations of metal-anode water-activated galvanic cells, specifically water-activated Alcells using inorganic alkali peroxides and solid organic oxidizers (heterocyclic halamines), in a semi-fuel cell configuration (i.e., with cathode species generated in situ and flow-through cells). The oxidizers utilized are inexpensive solid materials that are generally (1) safer to handle than liquid solutions or gases, (2) have inherently higher current and energy capacity (as they are not dissolved), and, (3) if appropriately packaged, will not degrade over time. The specific energy (S.E.) of Al-alkali peroxide was found to be 230 Wh/kg (460 Wh/kg, considering only active materials) in a seven-gram cell. Interestingly, when the cell size was increased (making more area of the catalytic cathode electrode available), the results from a single addition of water in an Al-organic oxidizer cell (weighing ~18 grams) showed an S.E. of about 200 Wh/kg. This scalability characteristic suggests that values in excess of 400 Wh/kg could be obtained in a semi-fuel-cell-like system. In this paper, we also present design considerations that take into account the energy requirements of the pumping devices and show that the proposed oxidizers, and the possible control of the chemical equilibrium of these cathodes in solution, may help reduce this power requirement and hence enhance the overall energetic balance.
Bo LI; Sung-kwon PARK
2016-01-01
In the IEEE 802.16e/m standard, three power saving classes (PSCs) are defined to save the energy of a mobile sub-scriber station (MSS). However, how to set the parameters of PSCs to maximize the power saving and guarantee the quality of service is not specified in the standard. Thus, many algorithms were proposed to set the PSCs in IEEE 802.16 networks. However, most of the proposed algorithms consider only the power saving for a single MSS. In the algorithms designed for multiple MSSs, the sleep state, which is set for activation of state transition overhead power, is not considered. The PSC setting for real-time connections in multiple MSSs with consideration of the state transition overhead is studied. The problem is non-deterministic polynomial time hard (NP-hard), and a suboptimal algorithm for the problem is proposed. Simulation results demonstrate that the energy saving of the proposed algorithm is higher than that of state-of-the-art algorithms and approaches the optimum limit.
The effect of ephedra and caffeine on maximal strength and power in resistance-trained athletes.
Williams, Andrew D; Cribb, Paul J; Cooke, Matthew B; Hayes, Alan
2008-03-01
Caffeine and ephedrine-related alkaloids recently have been removed from International Olympic Committee banned substances lists, whereas ephedrine itself is now permissible at urinary concentrations less than 10 mug.mL. The changes to the list may contribute to an increased use of caffeine and ephedra as ergogenic aids by athletes. Consequently, we sought to investigate the effects of ingesting caffeine (C) or a combination of ephedra and caffeine (C + E) on muscular strength and anaerobic power using a double-blind, crossover design. Forty-five minutes after ingesting a glucose placebo (P: 300 mg), C (300 mg) or C + E (300 mg + 60 mg), 9 resistance-trained male participants were tested for maximal strength by bench press [BP; 1 repetition maximum (1RM)] and latissimus dorsi pull down (LP; 1RM). Subjects also performed repeated repetitions at 80% of 1RM on both BP and LP until exhaustion. After this test, subjects underwent a 30-second Wingate test to determine peak anaerobic cycling power, mean power, and fatigue index. Although subjects reported increased alertness and enhanced mood after supplementation with caffeine and ephedra, there were no significant differences between any of the treatments in muscle strength, muscle endurance, or peak anaerobic power. Our results do not support the contention that supplementation with ephedra or caffeine will enhance either muscle strength or anaerobic exercise performance.
Composable and Predictable Power Management
Nelson, A.T.
2014-01-01
The functionality of embedded systems is ever growing. The computational power of embedded systems is growing to match this demand, with embedded multiprocessor systems becoming more common. The limitations of embedded systems are not always related to chip size but are commonly due to energy and/or
Maximal aerobic capacity in ageing subjects: actual measurements versus predicted values
Cristina Pistea
2016-03-01
Full Text Available We evaluated the impact of selection of reference values on the categorisation of measured maximal oxygen consumption (V′O2peak as “normal” or “abnormal” in an ageing population. We compared measured V′O2peak with predicted values and the lower limit of normal (LLN calculated with five equations. 99 (58 males and 41 females disease-free subjects aged ≥70 years completed an incremental maximal exercise test on a cycle ergometer. Mean V′O2peak was 1.88 L·min−1 in men and 1.26 L·min−1 in women. V′O2peak ranged from 89% to 108% of predicted in men, and from 88% to 164% of predicted in women, depending on the reference equation used. The proportion of subjects below the LLN ranged from 5% to 14% in men and 0–22% in women, depending on the reference equation. The LLN was lacking in one study, and was unsuitable for women in another. Most LLNs ranged between 53% and 73% of predicted. Therefore, choosing an 80% cut-off leads to overestimation of the proportion of “abnormal” subjects. To conclude, the proportion of subjects aged ≥70 years with a “low” V′O2peak differs markedly according to the chosen reference equations. In clinical practice, it is still relevant to test a sample of healthy volunteers and select the reference equations that better characterise this sample.
Effects of temperature on the maximal instantaneous muscle power of humans.
Ferretti, G; Ishii, M; Moia, C; Cerretelli, P
1992-01-01
The maximal instantaneous muscle power (wi,max) probably reflects the maximal rate of adenosine 5'-triphosphate (ATP) hydrolysis (ATPmax), a temperature-dependent variable, which gives rise to the hypothesis that temperature, by affecting ATPmax, may also influence wi,max. This hypothesis was tested on six subjects, whose vastus lateralis muscle temperature (Tmuscle) was monitored by a thermocouple inserted approximately 3 cm below the skin surface. The Wi,max was determined during a series of high jumps off both feet on a force platform before and after immersion up to the abdomen for 90 min in a temperature controlled (T = 20 +/- 0.1 degrees C) water bath. Control Tmuscle was 35.8 +/- 0.7 degrees C, with control Wi,max being 51.6 (SD 8.7) W.kg-1. After cold exposure, Tmuscle decreased by about 8 degrees C, whereas wi,max 27% lower. The temperature dependence of Wi,max was found to be less (Q10 less than 1.5, where Q10 is the temperature coefficient as calculated in other studies) than reported in the literature for ATPmax. Such a low Q10 may reflect an increase in the mechanical equivalent of ATP splitting, as a consequence of the reduced velocity of muscle contraction occurring at low Tmuscle.
The exact maximal energy of integral circulant graphs with prime power order
Sander, J W
2011-01-01
The energy of a graph was introduced by {\\sc Gutman} in 1978 as the sum of the absolute values of the eigenvalues of its adjacency matrix. We study the energy of integral circulant graphs, also called gcd graphs, which can be characterized by their vertex count $n$ and a set $\\cal D$ of divisors of $n$ in such a way that they have vertex set $\\mathbb{Z}/n\\mathbb{Z}$ and edge set $\\{\\{a,b\\}:\\, a,b\\in\\mathbb{Z}/n\\mathbb{Z},\\, \\gcd(a-b,n)\\in {\\cal D}\\}$. Given an arbitrary prime power $p^s$, we determine all divisor sets maximising the energy of an integral circulant graph of order $p^s$. This enables us to compute the maximal energy $\\Emax{p^s}$ among all integral circulant graphs of order $p^s$.
The relationship of maximal alactacid anaerobic power to somatotype in trained subjects.
Ergen, E; Sardella, F; Dal Monte, A
1985-12-01
The purpose of the present study was to investigate the relationship between somatotype components and maximal alactacid anaerobic power (MAAP) in trained subjects. The somatotype components (endomorphy: means = 2.66, S.D. = +/- 0.78; mesomorphy: means = 5.45, S.D. = +/- 1.12; ectomorphy: means = 2.46, S.D. = +/- 0.88) and total MAAP were measured in 40 male fencers (aged, means 21.79, S.D. = +/- 3.97) in order to determine the correlations. The results did not show any correlations between the parameters. It can be concluded that the MAAP of an individual does not depend on the somatotype; but it may also be assumed that MAAP show changes with the percentage of fibre type, enzymatic activity in these fibres involved by large muscle groups which are relatively related to musculo-skeletal development (second component of somatotype) and neuro-muscular properties of the subjects, all having a genetic basis.
Wind Power Prediction using Ensembles
Giebel, Gregor; Badger, Jake; Landberg, Lars
2005-01-01
offshore wind farm and the whole Jutland/Funen area. The utilities used these forecasts for maintenance planning, fuel consumption estimates and over-the-weekend trading on the Leipzig power exchange. Othernotable scientific results include the better accuracy of forecasts made up from a simple...... superposition of two NWP provider (in our case, DMI and DWD), an investigation of the merits of a parameterisation of the turbulent kinetic energy within thedelivered wind speed forecasts, and the finding that a “naïve” downscaling of each of the coarse ECMWF ensemble members with higher resolution HIRLAM did...
Conditional prediction intervals of wind power generation
Pinson, Pierre; Kariniotakis, Georges
2010-01-01
A generic method for the providing of prediction intervals of wind power generation is described. Prediction intervals complement the more common wind power point forecasts, by giving a range of potential outcomes for a given probability, their so-called nominal coverage rate. Ideally they inform of the situation-specific uncertainty of point forecasts. In order to avoid a restrictive assumption on the shape of forecast error distributions, focus is given to an empirical and nonparametric app...
Dalton, Brian H; Power, Geoffrey A; Paturel, Justin R; Rice, Charles L
2015-06-01
The underlying factors related to the divergent findings of age-related fatigue for dynamic tasks are not well understood. The purpose here was to investigate age-related fatigability and recovery between a repeated constrained (isokinetic) and an unconstrained velocity (isotonic) task, in which participants performed fatiguing contractions at the velocity (isokinetic) or resistance (isotonic) corresponding with maximal power. To compare between tasks, isotonic torque-power relationships were constructed prior to and following both fatiguing tasks and during short-term recovery. Contractile properties were recorded from 9 old (~75 years) and 11 young (~25 years) men during three testing sessions. In the first session, maximal power was assessed, and sessions 2 and 3 involved an isokinetic or an isotonic concentric fatigue task performed until maximal power was reduced by 40 %. Compared with young, the older men performed the same number of contractions to task failure for the isokinetic task (~45 contractions), but 20 % fewer for the isotonic task (p contraction strength, angular velocity, and power were reduced by ~30, ~13, and ~25 %, respectively, immediately following task failure, and only isometric torque was not recovered fully by 10 min. In conclusion, older men are more fatigable than the young when performing a repetitive maximal dynamic task at a relative resistance (isotonic) but not an absolute velocity (isokinetic), corresponding to maximal power.
Optimal prediction intervals of wind power generation
Wan, Can; Wu, Zhao; Pinson, Pierre; Dong, Zhao Yang; Wong, Kit Po
2014-01-01
Accurate and reliable wind power forecasting is essential to power system operation. Given significant uncertainties involved in wind generation, probabilistic interval forecasting provides a unique solution to estimate and quantify the potential impacts and risks facing system operation with wind penetration beforehand. This paper proposes a novel hybrid intelligent algorithm approach to directly formulate optimal prediction intervals of wind power generation based on extreme learning machin...
Villadsen, Allan; Roos, Ewa M.; Overgaard, Søren
Abstract : Purpose To evaluate the reliability of single-joint and multi-joint maximal leg muscle power and functional performance measures in patients with severe OA. Background Muscle power, taking both strength and velocity into account, is a more functional measure of lower extremity muscle a...
Roger S Seymour
Full Text Available Inertial homeothermy, the maintenance of a relatively constant body temperature that occurs simply because of large size, is often applied to large dinosaurs. Moreover, biophysical modelling and actual measurements show that large crocodiles can behaviourally achieve body temperatures above 30°C. Therefore it is possible that some dinosaurs could achieve high and stable body temperatures without the high energy cost of typical endotherms. However it is not known whether an ectothermic dinosaur could produce the equivalent amount of muscular power as an endothermic one. To address this question, this study analyses maximal power output from measured aerobic and anaerobic metabolism in burst exercising estuarine crocodiles, Crocodylusporosus, weighing up to 200 kg. These results are compared with similar data from endothermic mammals. A 1 kg crocodile at 30°C produces about 16 watts from aerobic and anaerobic energy sources during the first 10% of exhaustive activity, which is 57% of that expected for a similarly sized mammal. A 200 kg crocodile produces about 400 watts, or only 14% of that for a mammal. Phosphocreatine is a minor energy source, used only in the first seconds of exercise and of similar concentrations in reptiles and mammals. Ectothermic crocodiles lack not only the absolute power for exercise, but also the endurance, that are evident in endothermic mammals. Despite the ability to achieve high and fairly constant body temperatures, therefore, large, ectothermic, crocodile-like dinosaurs would have been competitively inferior to endothermic, mammal-like dinosaurs with high aerobic power. Endothermy in dinosaurs is likely to explain their dominance over mammals in terrestrial ecosystems throughout the Mesozoic.
Seymour, Roger S
2013-01-01
Inertial homeothermy, the maintenance of a relatively constant body temperature that occurs simply because of large size, is often applied to large dinosaurs. Moreover, biophysical modelling and actual measurements show that large crocodiles can behaviourally achieve body temperatures above 30°C. Therefore it is possible that some dinosaurs could achieve high and stable body temperatures without the high energy cost of typical endotherms. However it is not known whether an ectothermic dinosaur could produce the equivalent amount of muscular power as an endothermic one. To address this question, this study analyses maximal power output from measured aerobic and anaerobic metabolism in burst exercising estuarine crocodiles, Crocodylusporosus, weighing up to 200 kg. These results are compared with similar data from endothermic mammals. A 1 kg crocodile at 30°C produces about 16 watts from aerobic and anaerobic energy sources during the first 10% of exhaustive activity, which is 57% of that expected for a similarly sized mammal. A 200 kg crocodile produces about 400 watts, or only 14% of that for a mammal. Phosphocreatine is a minor energy source, used only in the first seconds of exercise and of similar concentrations in reptiles and mammals. Ectothermic crocodiles lack not only the absolute power for exercise, but also the endurance, that are evident in endothermic mammals. Despite the ability to achieve high and fairly constant body temperatures, therefore, large, ectothermic, crocodile-like dinosaurs would have been competitively inferior to endothermic, mammal-like dinosaurs with high aerobic power. Endothermy in dinosaurs is likely to explain their dominance over mammals in terrestrial ecosystems throughout the Mesozoic.
Simulators predict power plant operation
Peltier, R.
2002-07-01
Mix the complexity of a new construction or major retrofit project with today's 'do more with less', a pinch of 'personnel inexperience,' and a dash of 'unintended consequences', and you have got a recipe for insomnia. Advanced simulation tools, however, can help you wring out your design train your operators before the first wire is terminated and just may be get a good night's rest. The article describes several examples of uses of simulation tools. Esscor recently completed a simulation project for a major US utility exploring the potential for furnace/duct implosion that could result from adding higher volumetric flow induced-draft fans and selective catalytic reduction to a 650-MW coal-fired plant. CAF Electronics Inc. provided a full-scope simulator for Alstom's KA24-1 combined-cycle power plant in Paris, France. Computational fluid dynamics (CFD) tools are being used by the Gas Technology Institute to simulate the performance of the next generation of pulverized coal combustors. 5 figs.
Hody, S; Rogister, B; Leprince, P; Wang, F; Croisier, J-L
2013-08-01
Unaccustomed eccentric exercise may cause skeletal muscle damage with an increase in plasma creatine kinase (CK) activity. Although the wide variability among individuals in CK response to standardized lengthening contractions has been well described, the reasons underlying this phenomenon have not yet been understood. Therefore, this study investigated a possible correlation of the changes in muscle damage indirect markers after an eccentric exercise with the decline in muscle performance during the exercise. Twenty-seven healthy untrained male subjects performed three sets of 30 maximal isokinetic eccentric contractions of the knee extensors. The muscular work was recorded using an isokinetic dynamometer to assess muscle fatigue by means of various fatigue indices. Plasma CK activity, muscle soreness, and stiffness were measured before (pre) and one day after (post) exercise. The eccentric exercise bout induced significant changes of the three muscle damage indirect markers. Large inter-subject variability was observed for all criteria measured. More interestingly, the log (CK(post) /CK(pre)) and muscle stiffness appeared to be closely correlated with the relative work decrease (r = 0.84, r(2) = 0.70 and r = 0.75, r(2) = 0.56, respectively). This is the first study to propose that the muscle fatigue profile during maximal eccentric protocol could predict the magnitude of the symptoms associated with muscle damage in humans.
How reliable are the equations for predicting maximal heart rate values in military personnel?
Sporis, Goran; Vucetic, Vlatko; Jukic, Igor; Omrcen, Darija; Bok, Daniel; Custonja, Zrinko
2011-03-01
The purpose of this study was to evaluate the validity and reliability of equations for predicting maximal values of heart rate (HR) in military personnel. Five hundred and nine members of the Croatian Armed Forces (age 29.1 +/- 5.5 years; height 180.1 +/- 6.6 cm; body mass 83.4 +/- 11.3 kg; maximal oxygen uptake [VO2(max)] 49.7 +/- 6.9 mL O2/kg/min) were tested. The graded exercise test with gas exchange measurements was used to determine VO2(max) and maximum HR (HR(max)). The analysis of variance was used to determine the differences between the equations to calculate HR(max). The analysis of variance yielded statistically significant differences between seven HR equations (p max) = 205 - [age/2]) and Fox and Haskell's (HR(max) = 220 - age) equations had the highest correlation with the HRmax obtained by the graded exercise test. The authors recommend using the HR(max) values from the Stevens Creek and the Fox and Haskell equations for the purpose of training, testing, and daily exercise routine in military personnel.
A Novel Method for Prediction of Protein Domain Using Distance-Based Maximal Entropy
Shu-xue Zou; Yan-xin Huang; Yan Wang; Chun-guang Zhou
2008-01-01
Detecting the boundaries of protein domains is an important and challenging task in both experimental and computational structural biology. In this paper, a promising method for detecting the domain structure of a protein from sequence information alone is presented. The method is based on analyzing multiple sequence alignments derived from a database search. Multiple measures are defined to quantify the domain information content of each position along the sequence. Then they are combined into a single predictor using support vector machine. What is more important, the domain detection is first taken as an imbalanted data learning problem. A novel undersampling method is proposed on distance-based maximal entropy in the feature space of Support Vector Machine (SVM). The overall precision is about 80%. Simulation results demonstrate that the method can help not only in predicting the complete 3D structure of a protein but also in the machine learning system on general imbalanced datasets.
Crossfit-based high-intensity power training improves maximal aerobic fitness and body composition.
Smith, Michael M; Sommer, Allan J; Starkoff, Brooke E; Devor, Steven T
2013-11-01
The purpose of this study was to examine the effects of a crossfit-based high-intensity power training (HIPT) program on aerobic fitness and body composition. Healthy subjects of both genders (23 men, 20 women) spanning all levels of aerobic fitness and body composition completed 10 weeks of HIPT consisting of lifts such as the squat, deadlift, clean, snatch, and overhead press performed as quickly as possible. Additionally, this crossfit-based HIPT program included skill work for the improvement of traditional Olympic lifts and selected gymnastic exercises. Body fat percentage was estimated using whole-body plethysmography, and maximal aerobic capacity (VO2max) was measured by analyzing expired gasses during a Bruce protocol maximal graded treadmill test. These variables were measured again after 10 weeks of training and compared for significant changes using a paired t-test. Results showed significant (p < 0.05) improvements of VO2max in men (43.10 ± 1.40 to 48.96 ± 1.42 ml · kg · min) and women (35.98 ± 1.60 to 40.22 ± 1.62 ml · kg · min) and decreased body fat percentage in men (22.2 ± 1.3 to 18.0 ± 1.3) and women (26.6 ± 2.0 to 23.2 ± 2.0). These improvements were significant across all levels of initial fitness. Significant correlations between absolute oxygen consumption and oxygen consumption relative to body weight was found in both men (r = 0.83, p < 0.001) and women (r = 0.94, p < 0.001), indicating that HIPT improved VO2max scaled to body weight independent of changes to body composition. Our data show that HIPT significantly improves VO2max and body composition in subjects of both genders across all levels of fitness.
Lillo, F
2006-01-01
I consider the problem of the optimal limit order price of a financial asset in the framework of the maximization of the utility function of the investor. The analytical solution of the problem gives insight on the origin of the recently empirically observed power law distribution of limit order prices. In the framework of the model, the most likely proximate cause of this power law is a power law heterogeneity of traders' investment time horizons .
Predicting maximal exercise ventilation in patients with chronic obstructive pulmonary disease.
Carter, R; Peavler, M; Zinkgraf, S; Williams, J; Fields, S
1987-08-01
Shortness of breath is a chief complaint of many individuals with cardiopulmonary diseases. Exercise testing is often used to help differentiate cardiac from pulmonary involvement. In assessing pulmonary dysfunction during exercise it is essential to know the point at which ventilatory limitation will occur. Numerous authors have presented regression equations based on the FEV1 for predicting either MVV or VEmax. Resting pulmonary function studies were obtained from 53 patients with COPD. Symptom-limited maximal exercise testing was completed on a cycle ergometer using increments of 10 watts/min. Each regression equation for predicting MVV or VEmax was then applied to the data set. Results showed that the FEV1 correlated with the measured VEmax (r = .81) as did PEF (r = .81), MVV (r = .78), IC (r = .78), DCO (r = .68), VA (r = .67), VE (r = .65) and FVC (r = .64). Single post-bronchodilator FEV1 measurements ranged from 0.56 to 1.64 L (mean 1.0 L) while VEmax ranged from 16 to 78 L/min (mean 37.69 L/min). The equation VEmax = 37.5 X FEV1 was the most robust equation found in the literature for predicting VEmax in this sample. This equation was not statistically different from the line of identity when predicted VEmax was plotted against the measured VEmax. The intercept was 0.91 with a slope of 0.98. In addition, this equation had a smaller mean square error in predicting VEmax than those of the other equations investigated.
Quantification of hand and forearm muscle forces during a maximal power grip task.
Goislard de Monsabert, Benjamin; Rossi, Jérémy; Berton, Eric; Vigouroux, Laurent
2012-10-01
The aim of this study was to estimate muscle and joint forces during a power grip task. Considering the actual lack of quantification of such internal variables, this information would be essential for sports sciences, medicine, and ergonomics. This study also contributed to the advancement of scientific knowledge concerning hand control during power grip. A specially designed apparatus combining both an instrumented handle and a pressure map was used to record the forces at the hand/handle interface during maximal exertions. Data were processed such that the forces exerted on 25 hand anatomical areas were determined. Joint angles of the five fingers and the wrist were also computed from synchronized kinematic measurements. These processed data were used as input of a hand/wrist biomechanical model, which includes 23 degrees of freedom and 42 muscles to estimate muscle and joint forces. Greater forces were applied on the distal phalanges of the long fingers compared with the middle and the proximal ones. Concomitantly, high solicitations were observed for FDP muscles. A large cocontraction level of extensor muscles was also estimated by the model and confirmed previously reported activities and injuries of extensor muscles related to the power grip. Quantifying hand internal loadings also resulted in new insights into the thumb and the wrist biomechanics. Output muscle tension ratios were all in smaller ranges than the ones reported in the literature. Including wrist and finger interactions in this hand model provided new quantification of muscle load sharing, cocontraction level, and biomechanics of the hand. Such information could complete future investigations concerning handle ergonomics or pathomechanisms of hand musculoskeletal disorders.
Conditional prediction intervals of wind power generation
Pinson, Pierre; Kariniotakis, Georges
2010-01-01
A generic method for the providing of prediction intervals of wind power generation is described. Prediction intervals complement the more common wind power point forecasts, by giving a range of potential outcomes for a given probability, their so-called nominal coverage rate. Ideally they inform...... on the characteristics of prediction errors for providing conditional interval forecasts. By simultaneously generating prediction intervals with various nominal coverage rates, one obtains full predictive distributions of wind generation. Adapted resampling is applied here to the case of an onshore Danish wind farm......, for which three point forecasting methods are considered as input. The probabilistic forecasts generated are evaluated based on their reliability and sharpness, while compared to forecasts based on quantile regression and the climatology benchmark. The operational application of adapted resampling...
Model predictive control for wind power gradients
Hovgaard, Tobias Gybel; Boyd, Stephen; Jørgensen, John Bagterp
2015-01-01
ranges. The system dynamics are quite non-linear, and the constraints and objectives are not convex functions of the control inputs, so the resulting optimal control problem is difficult to solve globally. In this paper, we show that by a novel change of variables, which focuses on power flows, we can......We consider the operation of a wind turbine and a connected local battery or other electrical storage device, taking into account varying wind speed, with the goal of maximizing the total energy generated while respecting limits on the time derivative (gradient) of power delivered to the grid. We...... transform the problem to one with linear dynamics and convex constraints. Thus, the problem can be globally solved, using robust, fast solvers tailored for embedded control applications. We implement the optimal control problem in a receding horizon manner and provide extensive closed-loop tests with real...
Optimal prediction intervals of wind power generation
Wan, Can; Wu, Zhao; Pinson, Pierre
2014-01-01
Accurate and reliable wind power forecasting is essential to power system operation. Given significant uncertainties involved in wind generation, probabilistic interval forecasting provides a unique solution to estimate and quantify the potential impacts and risks facing system operation with wind...... penetration beforehand. This paper proposes a novel hybrid intelligent algorithm approach to directly formulate optimal prediction intervals of wind power generation based on extreme learning machine and particle swarm optimization. Prediction intervals with Associated confidence levels are generated through...... conducted. Comparing with benchmarks applied, experimental results demonstrate the high efficiency and reliability of the developed approach. It is therefore convinced that the proposed method provides a new generalized framework for probabilistic wind power forecasting with high reliability and flexibility...
Kendall, Kristina L; Fukuda, David H; Smith, Abbie E; Cramer, Joel T; Stout, Jeffrey R
2012-03-01
The objective of this study was to examine the relationship between the critical velocity (CV) test and maximal oxygen consumption (VO2max) and develop a regression equation to predict VO2max based on the CV test in female collegiate rowers. Thirty-five female (mean ± SD; age, 19.38 ± 1.3 years; height, 170.27 ± 6.07 cm; body mass, 69.58 ± 0.3 1 kg) collegiate rowers performed 2 incremental VO2max tests to volitional exhaustion on a Concept II Model D rowing ergometer to determine VO2max. After a 72-hour rest period, each rower completed 4 time trials at varying distances for the determination of CV and anaerobic rowing capacity (ARC). A positive correlation was observed between CV and absolute VO2max (r = 0.775, p < 0.001) and ARC and absolute VO2max (r = 0.414, p = 0.040). Based on the significant correlation analysis, a linear regression equation was developed to predict the absolute VO2max from CV and ARC (absolute VO2max = 1.579[CV] + 0.008[ARC] - 3.838; standard error of the estimate [SEE] = 0.192 L·min(-1)). Cross validation analyses were performed using an independent sample of 10 rowers. There was no significant difference between the mean predicted VO2max (3.02 L·min(-1)) and the observed VO2max (3.10 L·min(-1)). The constant error, SEE and validity coefficient (r) were 0.076 L·min(-1), 0.144 L·min(-1), and 0.72, respectively. The total error value was 0.155 L·min(-1). The positive relationship between CV, ARC, and VO2max suggests that the CV test may be a practical alternative to measuring the maximal oxygen uptake in the absence of a metabolic cart. Additional studies are needed to validate the regression equation using a larger sample size and different populations (junior- and senior-level female rowers) and to determine the accuracy of the equation in tracking changes after a training intervention.
Brian H. Dalton; Geoffrey A Power; Paturel, Justin R.; Rice, Charles L.
2015-01-01
The underlying factors related to the divergent findings of age-related fatigue for dynamic tasks are not well understood. The purpose here was to investigate age-related fatigability and recovery between a repeated constrained (isokinetic) and an unconstrained velocity (isotonic) task, in which participants performed fatiguing contractions at the velocity (isokinetic) or resistance (isotonic) corresponding with maximal power. To compare between tasks, isotonic torque–power relationships were...
Short-term wind power prediction
Joensen, Alfred K.
2003-01-01
The present thesis consists of 10 research papers published during the period 1997-2002 together with a summary report. The objective of the work described in the thesis is to develop models and methods for calculation of high accuracy predictions of wind power generated electricity......, and to implement these models and methods in an on-line software application. The economical value of having predictions available is also briefly considered. The summary report outlines the background and motivation for developing wind power prediction models. The meteorological theory which is relevant...... for the thesis is outlined and the background for the models and methods which are proposed in the various papers is described. The software system, Zephyr, which has been developed is also described in the summary report. The main part of the papers have been written in conjunction with two research projects...
Maximal loads acting on legs of powered roof support unit in longwalls with bumping hazards
StanislawSzweda
2001-01-01
In the article the results of measurements of the resultant force in the legs of a powered roof support unit, caused by a dynamic interaction bf the rock mass, are discussed. The measurements have been taken in the Iongwalls mined with a roof fall, characterized by the highest degree of bumping hazard. It has been stated that the maximal force in the legs Fro, recorded during a dynamic interaction of the rock mass, is proportional to the initial static force in the legs Fst.p Therefore a need for a careful selection of the initial load of the powered roof support, according to the local mining and geological conditions, results from such a statement. Setting the legs with the supporting load exceeding the indispensable value for keeping the direct roof solids in balance, deteriorating the operational parameters of a Iongwall system also has a disadvantageous influence on the value of the force in the legs and the rate of its increase, caused by a dynamic interaction of the rock mass. A correct selection of the initial load causes a decrease in the intensity of a dynamic interaction of the rock mass on powered roof supports, which also has an advanta igeous influence on their life, Simultaneously with the measurements of the resultant force in the legs, the vertical acceleration of the canopy was also recorded. It has enabled to prove that the external dynamic forces may act on the unit both from the roof as well as from the floor. The changes of the force in the legs caused by dynamic phenomena intrinsically created in the roof and changes of the force in the legs caused by blasting explosives in the roof of the working, have been analyzed separately. It has been stated that an increase in the loads of legs, caused by intrinsic phenomena is significantly higher than a force increase in the legs caused by blasting. It means that powered roof supports, to be operated in the workings, where the bumping hazard occurs, will also transmit the loads acting on a unit
Furrer, Regula; Jaspers, Richard T.; Baggerman, Hein L.; Bravenboer, Nathalie; Lips, Paul; de Haan, Arnold
2013-01-01
Improvement of muscle peak power and oxidative capacity are generally presumed to be mutually exclusive. However, this may not be valid by using fibre type-specific recruitment. Since rat medial gastrocnemius muscle (GM) is composed of high and low oxidative compartments which are recruited task specifically, we hypothesised that the adaptive responses to peak power training were unaffected by additional endurance training. Thirty rats were subjected to either no training (control), peak power training (PT), or both peak power and endurance training (PET), which was performed on a treadmill 5 days per week for 6 weeks. Maximal running velocity increased 13.5% throughout the training and was similar in both training groups. Only after PT, GM maximal force was 10% higher than that of the control group. In the low oxidative compartment, mRNA levels of myostatin and MuRF-1 were higher after PT as compared to those of control and PET groups, respectively. Phospho-S6 ribosomal protein levels remained unchanged, suggesting that the elevated myostatin levels after PT did not inhibit mTOR signalling. In conclusion, even by using task-specific recruitment of the compartmentalized rat GM, additional endurance training interfered with the adaptive response of peak power training and attenuated the increase in maximal force after power training. PMID:23509812
Regula Furrer
2013-01-01
Full Text Available Improvement of muscle peak power and oxidative capacity are generally presumed to be mutually exclusive. However, this may not be valid by using fibre type-specific recruitment. Since rat medial gastrocnemius muscle (GM is composed of high and low oxidative compartments which are recruited task specifically, we hypothesised that the adaptive responses to peak power training were unaffected by additional endurance training. Thirty rats were subjected to either no training (control, peak power training (PT, or both peak power and endurance training (PET, which was performed on a treadmill 5 days per week for 6 weeks. Maximal running velocity increased 13.5% throughout the training and was similar in both training groups. Only after PT, GM maximal force was 10% higher than that of the control group. In the low oxidative compartment, mRNA levels of myostatin and MuRF-1 were higher after PT as compared to those of control and PET groups, respectively. Phospho-S6 ribosomal protein levels remained unchanged, suggesting that the elevated myostatin levels after PT did not inhibit mTOR signalling. In conclusion, even by using task-specific recruitment of the compartmentalized rat GM, additional endurance training interfered with the adaptive response of peak power training and attenuated the increase in maximal force after power training.
Farquhar, Sara J; Chmielewski, Terese L; Snyder-Mackler, Lynn
2005-10-01
Weakness and failure of voluntary activation of the quadriceps femoris muscles often occur after anterior cruciate ligament (ACL) rupture. Side-to-side strength comparisons are used as a measure of progress, and are inaccurate if the quadriceps has activation failure. Burst superimposition testing is commonly used to assess quadriceps strength and activation during a maximal volitional isometric contraction (MVIC), using the central activation ratio (CAR) calculation. A recently developed mathematical model predicts the MVIC from submaximal efforts. The purpose of this study was to compare the CAR calculation to the mathematical model. We hypothesized that the model would be a more accurate predictor of strength than the CAR calculation when voluntary activation failure is present. Data from the involved and uninvolved quadriceps muscles of 100 consecutive subjects with complete, isolated ACL rupture were retrospectively evaluated. Subjects who required multiple trials to produce an MVIC with full activation (true MVIC) were used to compare the CAR calculation, the mathematical model, and this true MVIC. Subjects unable to produce a true MVIC with multiple trials were used to compare the mathematical model to the CAR calculation. Results demonstrate that both methods reliably and accurately estimate the quadriceps weakness associated with ACL rupture. We recommend use of the CAR calculation to provide estimations of true quadriceps strength to facilitate clinical decisions about progress in rehabilitation after ACL rupture.
Moduli dynamics as a predictive tool for thermal maximally supersymmetric Yang-Mills at large N
Morita, Takeshi; Shiba, Shotaro; Wiseman, Toby; Withers, Benjamin
2015-07-01
Maximally supersymmetric ( p + 1)-dimensional Yang-Mills theory at large N and finite temperature, with possibly compact spatial directions, has a rich phase structure. Strongly coupled phases may have holographic descriptions as black branes in various string duality frames, or there may be no gravity dual. In this paper we provide tools in the gauge theory which give a simple and unified picture of the various strongly coupled phases, and transitions between them. Building on our previous work we consider the effective theory describing the moduli of the gauge theory, which can be computed precisely when it is weakly coupled far out on the Coulomb branch. Whilst for perturbation theory naive extrapolation from weak coupling to strong gives little information, for this moduli theory naive extrapolation from its weakly to its strongly coupled regime appears to encode a surprising amount of information about the various strongly coupled phases. We argue it encodes not only the parametric form of thermodynamic quantities for these strongly coupled phases, but also certain transcendental factors with a geometric origin, and allows one to deduce transitions between the phases. We emphasise it also gives predictions for the behaviour of other observables in these phases.
Abbas, Nikhar; Tom, Nathan
2017-09-01
Wave energy converter (WEC) control strategies have been primarily focused on maximizing power absorption. The use of model predictive control strategies allows for a finite-horizon, multiterm objective function to be solved. This work utilizes a multiterm objective function to maximize power absorption while minimizing the structural loads on the WEC system. Furthermore, a Kalman filter and autoregressive model were used to estimate and forecast the wave exciting force and predict the future dynamics of the WEC. The WEC's power-take-off time-averaged power and structural loads under a perfect forecast assumption in irregular waves were compared against results obtained from the Kalman filter and autoregressive model to evaluate model predictive control performance.
Guo, Yi; Jiang, John N; Tang, Choon Yik; Ramakumar, Rama G
2010-01-01
This paper addresses the problem of controlling a variable-speed wind turbine with a Doubly Fed Induction Generator (DFIG), modeled as an electromechanically-coupled nonlinear system with rotor voltages and blade pitch angle as its inputs, active and reactive powers as its outputs, and most of the aerodynamic and mechanical parameters as its uncertainties. Using a blend of linear and nonlinear control strategies (including feedback linearization, pole placement, uncertainty estimation, and gradient-based potential function minimization) as well as time-scale separation in the dynamics, we develop a controller that is capable of maximizing the active power in the Maximum Power Tracking (MPT) mode, regulating the active power in the Power Regulation (PR) mode, seamlessly switching between the two modes, and simultaneously adjusting the reactive power to achieve a desired power factor. The controller consists of four cascaded components, uses realistic feedback signals, and operates without knowledge of the C_p-...
Precision Prediction of the Log Power Spectrum
Repp, Andrew
2016-01-01
At translinear scales, the log power spectrum captures significantly more cosmological information than the standard power spectrum. At high wavenumbers $k$, the cosmological information in the standard power spectrum $P(k)$ fails to increase in proportion to $k$ due to correlations between large- and small-scale modes. As a result, $P(k)$ suffers from an information plateau on these translinear scales, so that analysis with the standard power spectrum cannot access the information contained in these small-scale modes. The log power spectrum $P_A(k)$, on the other hand, captures the majority of this otherwise lost information. Until now there has been no means of predicting the amplitude of the log power spectrum apart from cataloging the results of simulations. We here present a cosmology-independent prescription for the log power spectrum, and we find this prescription to display accuracy comparable to that of Smith et al. (2003), over a range of redshifts and smoothing scales, and for wavenumbers up to $1....
Peak power prediction of a vanadium redox flow battery
Yu, V. K.; Chen, D.
2014-12-01
The vanadium redox flow battery (VRFB) is a promising grid-scale energy storage technology, but future widespread commercialization requires a considerable reduction in capital costs. Determining the appropriate battery size for the intended power range can help minimize the amount of materials needed, thereby reducing capital costs. A physics-based model is an essential tool for predicting the power range of large scale VRFB systems to aid in the design optimization process. This paper presents a modeling framework that accounts for the effects of flow rate on the pumping losses, local mass transfer rate, and nonuniform vanadium concentration in the cell. The resulting low-order model captures battery performance accurately even at high power densities and remains computationally practical for stack-level optimization and control purposes. We first use the model to devise an optimal control strategy that maximizes battery life during discharge. Assuming optimal control is implemented, we then determine the upper efficiency limits of a given VRFB system and compare the net power and associated overpotential and pumping losses at different operating points. We also investigate the effects of varying the electrode porosity, stack temperature, and total vanadium concentration on the peak power.
Coggan, Andrew R; Leibowitz, Joshua L; Kadkhodayan, Ana; Thomas, Deepak P; Ramamurthy, Sujata; Spearie, Catherine Anderson; Waller, Suzanne; Farmer, Marsha; Peterson, Linda R
2015-08-01
Nitric oxide (NO) has been demonstrated to enhance the maximal shortening velocity and maximal power of rodent muscle. Dietary nitrate (NO3(-)) intake has been demonstrated to increase NO bioavailability in humans. We therefore hypothesized that acute dietary NO3(-) intake (in the form of a concentrated beetroot juice (BRJ) supplement) would improve muscle speed and power in humans. To test this hypothesis, healthy men and women (n = 12; age = 22-50 y) were studied using a randomized, double-blind, placebo-controlled crossover design. After an overnight fast, subjects ingested 140 mL of BRJ either containing or devoid of 11.2 mmol of NO3(-). After 2 h, knee extensor contractile function was assessed using a Biodex 4 isokinetic dynamometer. Breath NO levels were also measured periodically using a Niox Mino analyzer as a biomarker of whole-body NO production. No significant changes in breath NO were observed in the placebo trial, whereas breath NO rose by 61% (P power at the highest angular velocity tested (i.e., 6.28 rad/s). Calculated maximal knee extensor power was therefore greater (i.e., 7.90 ± 0.59 vs. 7.44 ± 0.53 W/kg; P power in healthy men and women.
Ro, Kyoungsoo
The study started with the requirement that a photovoltaic (PV) power source should be integrated with other supplementary power sources whether it operates in a stand-alone or grid-connected mode. First, fuel cells for a backup of varying PV power were compared in detail with batteries and were found to have more operational benefits. Next, maximizing performance of a grid-connected PV-fuel cell hybrid system by use of a two-loop controller was discussed. One loop is a neural network controller for maximum power point tracking, which extracts maximum available solar power from PV arrays under varying conditions of insolation, temperature, and system load. A real/reactive power controller (RRPC) is the other loop. The RRPC meets the system's requirement for real and reactive powers by controlling incoming fuel to fuel cell stacks as well as switching control signals to a power conditioning subsystem. The RRPC is able to achieve more versatile control of real/reactive powers than the conventional power sources since the hybrid power plant does not contain any rotating mass. Results of time-domain simulations prove not only effectiveness of the proposed computer models of the two-loop controller, but also their applicability for use in transient stability analysis of the hybrid power plant. Finally, environmental evaluation of the proposed hybrid plant was made in terms of plant's land requirement and lifetime COsb2 emissions, and then compared with that of the conventional fossil-fuel power generating forms.
Uncertainties in predicting solar panel power output
Anspaugh, B.
1974-01-01
The problem of calculating solar panel power output at launch and during a space mission is considered. The major sources of uncertainty and error in predicting the post launch electrical performance of the panel are considered. A general discussion of error analysis is given. Examples of uncertainty calculations are included. A general method of calculating the effect on the panel of various degrading environments is presented, with references supplied for specific methods. A technique for sizing a solar panel for a required mission power profile is developed.
Gebraad, Pieter [National Renewable Energy Laboratory, Golden CO USA; Thomas, Jared J. [Brigham Young University, Provo UT USA; Ning, Andrew [Brigham Young University, Provo UT USA; Fleming, Paul [National Renewable Energy Laboratory, Golden CO USA; Dykes, Katherine [National Renewable Energy Laboratory, Golden CO USA
2016-05-24
This paper presents a wind plant modeling and optimization tool that enables the maximization of wind plant annual energy production (AEP) using yaw-based wake steering control and layout changes. The tool is an extension of a wake engineering model describing the steady-state effects of yaw on wake velocity profiles and power productions of wind turbines in a wind plant. To make predictions of a wind plant's AEP, necessary extensions of the original wake model include coupling it with a detailed rotor model and a control policy for turbine blade pitch and rotor speed. This enables the prediction of power production with wake effects throughout a range of wind speeds. We use the tool to perform an example optimization study on a wind plant based on the Princess Amalia Wind Park. In this case study, combined optimization of layout and wake steering control increases AEP by 5%. The power gains from wake steering control are highest for region 1.5 inflow wind speeds, and they continue to be present to some extent for the above-rated inflow wind speeds. The results show that layout optimization and wake steering are complementary because significant AEP improvements can be achieved with wake steering in a wind plant layout that is already optimized to reduce wake losses.
Maximal loads acting on legs of powered roof support unit in longwalls with bumping hazards
Stanislaw Szweda
2001-01-01
In the article the results of measurements of the resultant force in th e legs of a powered roof support unit, caused by a dynamic interaction of the ro ck mass, are discussed. The measurements have been taken in the longwalls mined with a roof fall, characterized by the highest degree of bumping hazard. It has been stated that the maximal force in the legs Fm, recorded during a dynam ic interaction of the rock mass, is proportional to the initial static force in the legs Fst,p. Th erefore a need for a careful selection of the initial load of the powered roof s upport, according to the local mining and geological conditions, results from su ch a statement. Setting the legs with the supporting load exceeding the indispen sable value for keeping the direct roof solids in balance, deteriorating the ope rational parameters of a longwall system also has a disadvantageous influence on the value of the force in the legs and the rate of its increase, caused by a dy namic interaction of the rock mass. A correct selection of the initial load caus es a decrease in the intensity of a dynamic interaction of the rock mass on powe red roof supports, which also has an advantageous influence on their life. Simultaneously with the measurements of the resultant force in the legs, the vertical acceleration of the canopy was also recorded. It has enabled to prove that the exte rnal dynamic forces may act on the unit both from the roof as well as from the f loor. The changes of the force in the legs caused by dynamic phenomena intrinsic ally created in the roof and changes of the force in the legs caused by blasting explosives in the roof of the working, have been analyzed separately. It has been stated that an increase in the loads of legs, caused by intrinsi c phenomena is significantly higher than a force increase in the legs caused by blasting. It means that powered roof supports, to be operated in the workings, w here the bumping hazard occurs, will also transmit the loads
Maximization of ICRF power by SOL density tailoring with local gas injection
Jacquet, P.; Goniche, M.; Bobkov, V.; Lerche, E.; Pinsker, R. I.; Pitts, R. A.; Zhang, W.; Colas, L.; Hosea, J.; Moriyama, S.; Wang, S.-J.; Wukitch, S.; Zhang, X.; Bilato, R.; Bufferand, H.; Guimarais, L.; Faugel, H.; Hanson, G. R.; Kocan, M.; Monakhov, I.; Noterdaeme, J.-M.; Petrzilka, V.; Shaw, A.; Stepanov, I.; Sips, A. C. C.; Van Eester, D.; Wauters, T.; JET contributors, the; the ASDEX Upgrade Team; the DIII-D Team; ITPA ‘Integrated Operation Scenarios' members, the; experts
2016-04-01
Experiments have been performed under the coordination of the International Tokamak Physics Activity (ITPA) on several tokamaks, including ASDEX Upgrade (AUG), JET and DIII-D, to characterize the increased Ion cyclotron range of frequency (ICRF) antenna loading achieved by optimizing the position of gas injection relative to the RF antennas. On DIII-D, AUG and JET (with the ITER-Like Wall) a 50% increase in the antenna loading was observed when injecting deuterium in ELMy H-mode plasmas using mid-plane inlets close to the powered antennas instead of divertor injection and, with smaller improvement when using gas inlets located at the top of the machine. The gas injection rate required for such improvements (~0.7 × 1022 el s-1 in AUG, ~1.0 × 1022 el s-1 in JET) is compatible with the use of this technique to optimize ICRF heating during the development of plasma scenarios and no degradation of confinement was observed when using the mid-plane or top inlets compared with divertor valves. An increase in the scrape-off layer (SOL) density was measured when switching gas injection from divertor to outer mid-plane or top. On JET and DIII-D, the measured SOL density increase when using main chamber puffing is consistent with the antenna coupling resistance increase provided that the distance between the measurement lines of sight and the injection location is taken into account. Optimized gas injection was also found to be beneficial for reducing tungsten (W) sputtering at the AUG antenna limiters, and also to reduce slightly the W and nickel (Ni) content in JET plasmas. Modeling the specific effects of divertor/top/mid-plane injection on the outer mid-plane density was carried out using both the EDGE2D-EIRENE and EMC3-EIRENE plasma boundary code packages; simulations indeed indicate that outer mid-plane gas injection maximizes the density in the mid-plane close to the injection point with qualitative agreement with the AUG SOL density measurements
Ambach, Daniel; Croonenbroeck, Carsten
2014-01-01
The Wind Power Prediction Tool (WPPT) has successfully been used for accurate wind power forecasts in the short to medium term scenario (up to 12 hours ahead). Since its development about a decade ago, a lot of additional stochastic modeling has been applied to the interdependency of wind power and wind speed. We improve the model in three ways: First, we replace the rather simple Fourier series of the basic model by more general and flexible periodic Basis splines (Bsplines). Second, we mode...
Driss, Tarak; Lambertz, Daniel; Rouis, Majdi; Vandewalle, Henry
2012-11-01
The importance of maximal voluntary torque (T (MVC)), maximal rate of torque development (MRTD) and musculo-tendinous stiffness of the triceps surae for maximal power output on a cycle ergometre (Pmax) was studied in 21 healthy subjects by studying the relationships between maximal cycling power related to body mass (Pmax BM(-1)) with T (MVC), MRTD and different indices of musculo-tendinous stiffness of the ankle flexor. Pmax BM(-1) was calculated from the data of an all-out force-velocity test on a Monark cycle ergometre. T (MVC) and MRTD were measured on a specific ankle ergometre. Musculo-tendinous stiffness was estimated by means of quick releases at 20, 40, 60 and 80% T (MVC) on the same ankle ergometre. Pmax BM(-1) was significantly and positively correlated with MRTD related to body mass but the positive correlation between Pmax BM(-1) and T (MVC) did not reach the significance level (0.05). Pmax BM(-1) was significantly and positively correlated with the estimation of stiffness at 40% T (MVC) (S(0.4)), but not with stiffness at 20, 60 and 80% T (MVC). The results of the present study suggest that maximal power output during cycling is significantly correlated with the level of musculo-tendinous stiffness which corresponds to torque range around peak torque at optimal pedal rate. However, the low coefficient of determination (r2 = 0.203) between Pmax BM(-1) and S (0.4) BM(-1) suggested that Pmax BM(-1) largely depended on other factors than the musculo-tendinous stiffness of the only plantar flexors.
Experiences with Statistical Methods for Wind Power Prediction
Nielsen, Torben Skov; Madsen, Henrik; Tofting, John
1999-01-01
This paper describes a tool for predicting the power procution from wind turbines in an area / the Wind Power Prediction Tool (WPPT). The predictions are based on on-line measuremets of power production for a selected set of reference wind farms i the area as well as numerical weather predictions...
Maximization of revenues for power sales from a solid waste resources recovery facility
1991-12-01
The report discusses the actual implementation of the best alternative in selling electrical power generated by an existing waste-to-energy facility, the Metro-Dade County Resources Recovery Plant. After the plant processes and extracts various products out of the municipal solid waste, it burns it to produce electrical power. The price for buying power to satisfy the internal needs of our Resources Recovery Facility (RRF) is substantially higher than the power price for selling electricity to any other entity. Therefore, without any further analysis, it was decided to first satisfy those internal needs and then export the excess power. Various alternatives were thoroughly explored as to what to do with the excess power. Selling power to the power utilities or utilizing the power in other facilities were the primary options.
Luthy, Sarah K; Marinkovic, Aleksandar; Weiner, Daniel J
2011-06-01
High-frequency chest compression (HFCC) is a therapy for cystic fibrosis (CF). We hypothesized that the resonant frequency (f(res)), as measured by impulse oscillometry, could be used to determine what HFCC vest settings produce maximal airflow or volume in pediatric CF patients. In 45 subjects, we studied: f(res), HFCC vest frequencies that subjects used (f(used)), and the HFCC vest frequencies that generated the greatest volume (f(vol)) and airflow (f(flow)) changes as measured by pneumotachometer. Median f(used) for 32 subjects was 14 Hz (range, 6-30). The rank order of the three most common f(used) was 15 Hz (28%) and 12 Hz (21%); three frequencies tied for third: 10, 11, and 14 Hz (5% each). Median f(res) for 43 subjects was 20.30 Hz (range, 7.85-33.65). Nineteen subjects underwent vest-tuning to determine f(vol) and f(flow). Median f(vol) was 8 Hz (range, 6-30). The rank order of the three most common f(vol) was: 8 Hz (42%), 6 Hz (32%), and 10 Hz (21%). Median f(flow) was 26 Hz (range, 8-30). The rank order of the three most common f(flow) was: 30 Hz (26%) and 28 Hz (21%); three frequencies tied for third: 8, 14, and 18 Hz (11% each). There was no correlation between f(used) and f(flow) (r(2) = -0.12) or f(vol) (r(2) = 0.031). There was no correlation between f(res) and f(flow) (r(2) = 0.19) or f(vol) (r(2) = 0.023). Multivariable analysis showed no independent variables were predictive of f(flow) or f(vol). Vest-tuning may be required to optimize clinical utility of HFCC. Multiple HFCC frequencies may need to be used to incorporate f(flow) and f(vol).
Vandewalle, H; Peres, G; Heller, J; Panel, J; Monod, H
1987-01-01
The force-velocity relationship on a Monark ergometer and the vertical jump height have been studied in 152 subjects practicing different athletic activities (sprint and endurance running, cycling on track and/or road, soccer, rugby, tennis and hockey) at an average or an elite level. There was an approximately linear relationship between braking force and peak velocity for velocities between 100 and 200 rev.min-1. The highest indices of force P0, velocity V0 and maximal anaerobic power (Wmax) were observed in the power athletes. There was a significant relationship between vertical jump height and Wmax related to body mass.
Prediction control of active power filters
王莉娜; 罗安
2003-01-01
A prediction method to obtain harmonic reference for active power filter is presented. It is a new use ofthe adaptive predictive filter based on FIR. The delay inherent in digital controller is successfully compensated by u-sing the proposed method, and the computing load is not very large compared with the conventional method. Moreo-ver, no additional hardware is needed. Its DSP-based realization is also presented, which is characterized by time-va-riant rate sampling, quasi synchronous sampling, and synchronous operation among the line frequency, PWM gener-ating and sampling in A/D unit. Synchronous operation releases the limitation on PWM modulation ratio and guar-antees that the electrical noises resulting from the switching operation of IGBTs do not interfere with the sampledcurrent. The simulation and experimental results verify the satisfactory performance of the proposed method.
Overall, Nickola C; Hammond, Matthew D; McNulty, James K; Finkel, Eli J
2016-08-01
When does power in intimate relationships shape important interpersonal behaviors, such as psychological aggression? Five studies tested whether possessing low relationship power was associated with aggressive responses, but (a) only within power-relevant relationship interactions when situational power was low, and (b) only by men because masculinity (but not femininity) involves the possession and demonstration of power. In Studies 1 and 2, men lower in relationship power exhibited greater aggressive communication during couples' observed conflict discussions, but only when they experienced low situational power because they were unable to influence their partner. In Study 3, men lower in relationship power reported greater daily aggressive responses toward their partner, but only on days when they experienced low situational power because they were either (a) unable to influence their partner or (b) dependent on their partner for support. In Study 4, men who possessed lower relationship power exhibited greater aggressive responses during couples' support-relevant discussions, but only when they had low situational power because they needed high levels of support. Study 5 provided evidence for the theoretical mechanism underlying men's aggressive responses to low relationship power. Men who possessed lower relationship power felt less manly on days they faced low situational power because their partner was unwilling to change to resolve relationship problems, which in turn predicted greater aggressive behavior toward their partner. These results demonstrate that fully understanding when and why power is associated with interpersonal behavior requires differentiating between relationship and situational power. (PsycINFO Database Record
An Optimization Problem for Predicting the Maximal Effect of Degradation of Mechanical Structures
Achtziger, W.; Bendsøe, Martin P.; Taylor, J. E.
2000-01-01
matrices, b is a vector, and x, y are the vectors of unknowns. The linear objective function to be maximized is (x, y) bar right arrow b(T)x. In a first step we investigate the problem properties such as existence of solutions and the differentiability of related marginal functions. As a by-product...
Prediction of maximal lactate steady state velocity based on performance in a 5km cycling test
Florentino Assenço
2007-09-01
Full Text Available Stationary cycling tests were used to analyze the validity of methods for estimating the Maximal Lactate Steady State (MLSS and the velocity and heart rate (HR that are sustainable during a 40-km time trial. Methods: 11 cyclists (23.9±4.1 years; 178±6.8 cm tall; 68.8±5.4 kg performed the following tests on a cyclosimulator, using their own bicycles: 1 Determination of the mean velocity and HR achieved during a 5-km (5kmVel and HR5km and a 40-km time trial (40kmVel and HR40km. 2 2-3 endurance tests to determine MLSSV with blood lactate ([lac] measurements. The relationship between MLSSV and 5kmVel in data from Harnish et al. (2001 was also used to calculate predicted MLSSV (km•h-1: [MLSSVp = 0.8809 x 5kmVel + 1.6365]. The HR corresponding to MLSSV (MLSSHR was estimated by taking 88% of HR5km (maximal- HR (Swensen et al. 1999. Results: The 5kmVel, 40kmVel, MLSSV and MLSSVp were 50.07±2.03, 45.57±1.97, 45.64±2.0 and 45.77±1.77km•h-1 respectively. No differences were found between 40kmVel, MLSSV and MLSSVp. Neither did [lac] or HR corresponding to MLSSV/40kmVel exhibit differences 4.5±0.6/4.2±0.3mM and 175.1±3.0/176.8±3.1 bpm. The MLSSV was 90.9±0.5% of 5kmVel and MLSSHR was 93.6±0.5% of HR5km. Conclusion: The equation proposed is valid for estimating both MLSSV and 40kmVel on a stationary cyclosimulator. ABSTRACT A validade de se estimar a velocidade e a frequência cardíaca (FC correspondentes ao máximo estado estável de lactato sanguíneo (MEEL, bem como a velocidade e FC que poderiam ser mantidas durante uma prova simulada de 40-km foram estudados em ciclismo estacionário. Métodos: 11 ciclistas (23,9±4,1anos; 178±6,8cm altura; 68,8±5,4kg realizaram os seguintes testes em ciclo-simulador, utilizando suas próprias bicicletas: 1 Determinação da velocidade média e a FC correspondentes aos testes de 5-km (5kmVel e FC5km e 40-km (40kmVel e FC40km. 2 2-3 testes de longa duração com dosagem de lactato sanguíneo [lac] para
Yasuhiro Tsubo
Full Text Available The brain is considered to use a relatively small amount of energy for its efficient information processing. Under a severe restriction on the energy consumption, the maximization of mutual information (MMI, which is adequate for designing artificial processing machines, may not suit for the brain. The MMI attempts to send information as accurate as possible and this usually requires a sufficient energy supply for establishing clearly discretized communication bands. Here, we derive an alternative hypothesis for neural code from the neuronal activities recorded juxtacellularly in the sensorimotor cortex of behaving rats. Our hypothesis states that in vivo cortical neurons maximize the entropy of neuronal firing under two constraints, one limiting the energy consumption (as assumed previously and one restricting the uncertainty in output spike sequences at given firing rate. Thus, the conditional maximization of firing-rate entropy (CMFE solves a tradeoff between the energy cost and noise in neuronal response. In short, the CMFE sends a rich variety of information through broader communication bands (i.e., widely distributed firing rates at the cost of accuracy. We demonstrate that the CMFE is reflected in the long-tailed, typically power law, distributions of inter-spike intervals obtained for the majority of recorded neurons. In other words, the power-law tails are more consistent with the CMFE rather than the MMI. Thus, we propose the mathematical principle by which cortical neurons may represent information about synaptic input into their output spike trains.
Using Predictive Analytics to Predict Power Outages from Severe Weather
Wanik, D. W.; Anagnostou, E. N.; Hartman, B.; Frediani, M. E.; Astitha, M.
2015-12-01
The distribution of reliable power is essential to businesses, public services, and our daily lives. With the growing abundance of data being collected and created by industry (i.e. outage data), government agencies (i.e. land cover), and academia (i.e. weather forecasts), we can begin to tackle problems that previously seemed too complex to solve. In this session, we will present newly developed tools to aid decision-support challenges at electric distribution utilities that must mitigate, prepare for, respond to and recover from severe weather. We will show a performance evaluation of outage predictive models built for Eversource Energy (formerly Connecticut Light & Power) for storms of all types (i.e. blizzards, thunderstorms and hurricanes) and magnitudes (from 20 to >15,000 outages). High resolution weather simulations (simulated with the Weather and Research Forecast Model) were joined with utility outage data to calibrate four types of models: a decision tree (DT), random forest (RF), boosted gradient tree (BT) and an ensemble (ENS) decision tree regression that combined predictions from DT, RF and BT. The study shows that the ENS model forced with weather, infrastructure and land cover data was superior to the other models we evaluated, especially in terms of predicting the spatial distribution of outages. This research has the potential to be used for other critical infrastructure systems (such as telecommunications, drinking water and gas distribution networks), and can be readily expanded to the entire New England region to facilitate better planning and coordination among decision-makers when severe weather strikes.
Zhang, Baohua; Hu, Weihao; Hou, Peng;
2016-01-01
The energy loss in a wind farm (WF) caused by wake interaction between wind turbines (WTs) is quite high, which can be reduced by proper active power dispatch. The electrical loss inside a WF by improper active power and reactive power dispatch is also considerable. In this paper, a coordinated a...
Kochanowicz Andrzej
2016-12-01
Full Text Available The aim of the study was to define the relationship between maximal power of lower limbs, the biomechanics of the forward handspring vault and the score received during a gymnastics competition. The research involved 42 gymnasts aged 9-11 years competing in the Poland’s Junior Championships. The study consisted of three stages: first -estimating the level of indicators of maximal power of lower limbs tested on a force plate during the countermovement jump; second - estimating the level of biomechanical indicators of the front handspring vault. For both mentioned groups of indicators and the score received by gymnasts during the vault, linear correlation analyses were made. The last stage consisted of conducting multiple regression analysis in order to predict the performance level of the front handspring vault. Results showed a positive correlation (0.401, p < 0.05 of lower limbs’ maximal power (1400 ± 502 W with the judges’ score for the front handstand vault (13.38 ± 1.02 points. However, the highest significant (p < 0.001 correlation with the judges’ score was revealed in the angle of the hip joint in the second phase of the flight (196.00 ± 16.64° and the contact time of hands with the vault surface (0.264 ± 0.118 s, where correlation coefficients were: -0.671 and -0.634, respectively. In conclusion, the angles of the hip joint in the second phase of the flight and when the hands touched the vault surface proved to be the most important indicators for the received score.
Kazemi, A.; Hosseinipoor, N.A. [Iran Univ. of Science and Technology, Tehran (Iran, Islamic Republic of)
2010-07-01
A series FACTS device such as a thyristor controlled series compensator (TCSC) has the ability to directly control the power flow and can be effective in improving the operation of a transmission network. This paper examined the optimal locating and sizing of a TCSC, for congestion management in competitive power markets. It proposed an algorithm for congestion management based on an optimal power flow (OPF) framework. The paper discussed the TCSC model and described the proposed method and formulation of an OPF framework. It was solved with the objective function of maximizing the social welfare by using a genetic algorithm for optimal fine-tuning generation and loads schedule and location-sizing of one unit TCSC. The simulation results were tested on the IEEE 14-bus and IEEE 30-bus system. It was validated through comparison of obtained social welfare with and without TCSC. It was concluded that this device was appropriate for long-term congestion management. 12 refs., 5 tabs.
Effective soil hydraulic conductivity predicted with the maximum power principle
Westhoff, Martijn; Erpicum, Sébastien; Archambeau, Pierre; Pirotton, Michel; Zehe, Erwin; Dewals, Benjamin
2016-04-01
Drainage of water in soils happens for a large extent through preferential flowpaths, but these subsurface flowpaths are extremely difficult to observe or parameterize in hydrological models. To potentially overcome this problem, thermodynamic optimality principles have been suggested to predict effective parametrization of these (sub-grid) structures, such as the maximum entropy production principle or the equivalent maximum power principle. These principles have been successfully applied to predict heat transfer from the Equator to the Poles, or turbulent heat fluxes between the surface and the atmosphere. In these examples, the effective flux adapts itself to its boundary condition by adapting its effective conductance through the creation of e.g. convection cells. However, flow through porous media, such as soils, can only quickly adapt its effective flow conductance by creation of preferential flowpaths, but it is unknown if this is guided by the aim to create maximum power. Here we show experimentally that this is indeed the case: In the lab, we created a hydrological analogue to the atmospheric model dealing with heat transport between Equator and poles. The experimental setup consists of two freely draining reservoirs connected with each other by a confined aquifer. By adding water to only one reservoir, a potential difference will build up until a steady state is reached. From the steady state potential difference and the observed flow through the aquifer, and effective hydraulic conductance can be determined. This observed conductance does correspond to the one maximizing power of the flux through the confined aquifer. Although this experiment is done in an idealized setting, it opens doors for better parameterizing hydrological models. Furthermore, it shows that hydraulic properties of soils are not static, but they change with changing boundary conditions. A potential limitation to the principle is that it only applies to steady state conditions
da Silva, Bruno Victor C; Simim, Mário A de Moura; Marocolo, Moacir; Franchini, Emerson; da Mota, Gustavo R
2015-06-01
We determined the optimal load for the peak power output (PPO) during the bench press throw (BPT) in Brazilian Jiu-Jitsu (BJJ) athletes and compared the PPO and maximal strength between advanced (AD) and nonadvanced (NA) athletes. Twenty-eight BJJ athletes (24.8 ± 5.7 years) performed the BPT at loads of 30, 40, 50, and 60% of their 1 repetition maximum (RM) in a randomized order (5-minute rest between BPTs). The PPO was determined by measuring the barbell displacement by an accelerometer (Myotest). The absolute (F = 7.25; p 0.05) in the PPO (30-60% 1RM). A polynomial adjustment indicated that the optimal load was ∼42% of 1RM for all groups and subgroups (R from 0.82 to 0.99). Our results suggest that there can be (1RM) differences between AD and NA BJJ athletes; however, there is no difference in the muscle power between the AD and NA groups. Additionally, ∼42% of 1RM seems to be the optimal load for developing maximal power using the BPT for the BJJ athletes.
Abut F; Akay MF
2015-01-01
Fatih Abut, Mehmet Fatih AkayDepartment of Computer Engineering, Çukurova University, Adana, TurkeyAbstract: Maximal oxygen uptake (VO2max) indicates how many milliliters of oxygen the body can consume in a state of intense exercise per minute. VO2max plays an important role in both sport and medical sciences for different purposes, such as indicating the endurance capacity of athletes or serving as a metric in estimating the disease risk of a person. In general, the direct measure...
Experiences with Statistical Methods for Wind Power Prediction
Nielsen, Torben Skov; Madsen, Henrik; Tofting, John
1999-01-01
This paper describes a tool for predicting the power procution from wind turbines in an area / the Wind Power Prediction Tool (WPPT). The predictions are based on on-line measuremets of power production for a selected set of reference wind farms i the area as well as numerical weather predictions...... covering the locations of the reference wind farms. WPPT is in operational use in the Western part of Denmark and the utililties experiences with the tool is presented....
Maximizing the power density of aqueous electrochemical flow cells with in operando deposition
Goulet, Marc-Antoni; Ibrahim, Omar A.; Kim, Will H. J.; Kjeang, Erik
2017-01-01
To transition toward sustainable energy systems, next generation power sources must provide high power density at minimum cost. Using inexpensive and environmentally friendly fabrication methods, this work describes a room temperature electrochemical flow cell with a maximum power density of 2.01 W cm-2 or 13.4 W cm-3. In part, this is achieved by minimizing ohmic resistance through decreased electrode spacing, implementation of current collectors and improvement of electrolyte conductivity. The majority of the performance gain is provided by a novel in operando dynamic flowing deposition method for which the cell design has been optimized. Carbon nanotubes (CNTs) are deposited dynamically at the entrance of and within the carbon paper electrodes during operation of the cell. A natural equilibrium is reached between deposition and detachment of CNTs at which the electrochemical surface area and pore size distribution of the flow-through porous electrodes are greatly enhanced. In this way, the novel deposition method more than doubles the power density of the cell and sets a new performance benchmark for what is practically attainable with aqueous electrochemical flow cells. Overall, it is expected that the design and operation methods illustrated here will enable a wide range of electrochemical flow cell technologies to achieve optimal performance.
Habibi, Hamed; Rahimi Nohooji, Hamed; Howard, Ian
2017-09-01
Power maximization has always been a practical consideration in wind turbines. The question of how to address optimal power capture, especially when the system dynamics are nonlinear and the actuators are subject to unknown faults, is significant. This paper studies the control methodology for variable-speed variable-pitch wind turbines including the effects of uncertain nonlinear dynamics, system fault uncertainties, and unknown external disturbances. The nonlinear model of the wind turbine is presented, and the problem of maximizing extracted energy is formulated by designing the optimal desired states. With the known system, a model-based nonlinear controller is designed; then, to handle uncertainties, the unknown nonlinearities of the wind turbine are estimated by utilizing radial basis function neural networks. The adaptive neural fault tolerant control is designed passively to be robust on model uncertainties, disturbances including wind speed and model noises, and completely unknown actuator faults including generator torque and pitch actuator torque. The Lyapunov direct method is employed to prove that the closed-loop system is uniformly bounded. Simulation studies are performed to verify the effectiveness of the proposed method.
Habibi, Hamed; Rahimi Nohooji, Hamed; Howard, Ian
2017-04-01
Power maximization has always been a practical consideration in wind turbines. The question of how to address optimal power capture, especially when the system dynamics are nonlinear and the actuators are subject to unknown faults, is significant. This paper studies the control methodology for variable-speed variable-pitch wind turbines including the effects of uncertain nonlinear dynamics, system fault uncertainties, and unknown external disturbances. The nonlinear model of the wind turbine is presented, and the problem of maximizing extracted energy is formulated by designing the optimal desired states. With the known system, a model-based nonlinear controller is designed; then, to handle uncertainties, the unknown nonlinearities of the wind turbine are estimated by utilizing radial basis function neural networks. The adaptive neural fault tolerant control is designed passively to be robust on model uncertainties, disturbances including wind speed and model noises, and completely unknown actuator faults including generator torque and pitch actuator torque. The Lyapunov direct method is employed to prove that the closed-loop system is uniformly bounded. Simulation studies are performed to verify the effectiveness of the proposed method.
Moduli dynamics as a predictive tool for thermal maximally supersymmetric Yang-Mills at large N
Morita, Takeshi; Wiseman, Toby; Withers, Benjamin
2014-01-01
Maximally supersymmetric (p+1)-dimensional Yang-Mills theory at large N and finite temperature, with possibly compact spatial directions, has a rich phase structure. Strongly coupled phases may have holographic descriptions as black branes in various string duality frames, or there may be no gravity dual. In this paper we provide tools in the gauge theory which give a simple and unified picture of the various strongly coupled phases, and transitions between them. Building on our previous work we consider the effective theory describing the moduli of the gauge theory, which can be computed precisely when it is weakly coupled far out on the Coulomb branch. Whilst for perturbation theory naive extrapolation from weak coupling to strong gives little information, for this moduli theory naive extrapolation from its weakly to its strongly coupled regime appears to encode a surprising amount of information about the various strongly coupled phases. We argue it encodes not only the parametric form of thermodynamic qua...
Self-suspended vibration-driven energy harvesting chip for power density maximization
Murillo, Gonzalo; Agustí, Jordi; Abadal, Gabriel
2015-11-01
This work introduces a new concept to integrate energy-harvesting devices with the aim of improving their throughput, mainly in terms of scavenged energy density and frequency tunability. This concept, named energy harvester in package (EHiP), is focused on the heterogeneous integration of a MEMS die, dedicated to scavenging energy, with an auxiliary chip, which can include the control and power management circuitry, sensors and RF transmission capabilities. The main advantages are that the whole die can be used as an inertial mass and the chip area usage is optimized. Based on this concept, in this paper we describe the development and characterization of a MEMS die fully dedicated to harvesting mechanical energy from ambient vibrations through an electrostatic transduction. A test PCB has been fabricated to perform the assembly that allows measurement of the resonance motion of the whole system at 289 Hz. An estimated maximum generated power of around 11 μW has been obtained for an input vibration acceleration of ˜10 m s-2 when the energy harvester operates in a constant-charge cycle for the best-case scenario. Therefore, a maximum scavenged power density of 0.85 mW cm-3 is theoretically expected for the assembled system. These results demonstrate that the generated power density of any vibration-based energy harvester can be significantly increased by applying the EHiP concept, which could become an industrial standard for manufacturing this kind of system, independently of the transduction type, fabrication technology or application.
Evans, Harrison J L; Ferrar, Katia E; Smith, Ashleigh E; Parfitt, Gaynor; Eston, Roger G
2015-03-01
This systematic review aimed to (i) report the accuracy of submaximal exercise-based predictive equations that incorporate oxygen uptake (measured via open circuit spirometry) to predict maximal oxygen uptake (VO₂max) and (ii) provide a critical reflection of the data to inform health professionals and researchers when selecting a prediction equation. Systematic review. A systematic search of MEDLINE, EMBASE (via OvidSP), CINAHL, SPORTDiscus (via EBSCO Host) and Scopus databases was undertaken in February 2013. Studies were required to report data on healthy participants aged 18-65y. Following tabulation of extracted data, a narrative synthesis was conducted. From a total of 7597 articles screened, 19 studies were included, from which a total of 43 prediction equations were extracted. No significant difference was reported between the measured and predicted VO₂max in 28 equations. Pearson's correlation coefficient between the predicted and measured VO₂max ranged from r=0.92 to r=0.57. The variables most commonly used in predictive equations were heart rate (n=19) and rating of perceived exertion (n=24). Overall, submaximal exercise-based equations using open circuit spirometry to predict VO₂max are moderately to highly accurate. The heart rate and rating of perceived exertion methods of predicting VO₂max were of similar accuracy. Important factors to consider when selecting a predictive equation include: the level of exertion required; participant medical conditions or medications; the validation population; mode of ergometry; time and resources available for familiarisation trials; and the level of bias of the study from which equations are derived. Copyright © 2014 Sports Medicine Australia. Published by Elsevier Ltd. All rights reserved.
Zhang, Baohua; Hu, Weihao; Hou, Peng
2015-01-01
Inclusion of the wake effect in the wind farm control design (WF) can increase the total captured power by wind turbines (WTs), which is usually implemented by derating upwind WTs. However, derating the WT without a proper control strategy will increase the structural loads, caused by operation i...
Maximal Force Characteristics of the Ca2+-Powered Actuator of Vorticella convallaria
Ryu, Sangjin; Lang, Matthew J.; Matsudaira, Paul
2012-01-01
The millisecond stalk contraction of the sessile ciliate Vorticella convallaria is powered by energy from Ca2+ binding to generate contractile forces of ∼10 nN. Its contractile organelle, the spasmoneme, generates higher contractile force under increased stall resistances. By applying viscous drag force to contracting V. convallaria in a microfluidic channel, we observed that the mechanical force and work of the spasmoneme depended on the stalk length, i.e., the maximum tension (150–350 nN) a...
Least cost addition of power from hydroelectrical developments: Maximizing existing assets
Felix, Lafontant; Briand, Marie-Helene; Veilleux, Rheaume
2010-09-15
Hydroelectric developments built in the early 1900's are nearing their useful lifespan and require significant rehabilitation in order to meet modern safety and performance criteria. Also, global increasing energy costs represent a strong incentive for operators to find low-cost, environment-friendly solutions while increasing energy generation at existing facilities. Projects promoting innovative ways of recycling existing developments are great examples of sustainable development and represent win-win solutions for population and hydropower industry alike. The proposed presentation describes successful projects consisting in the rehabilitation or addition of power to existing hydroelectric. These recycling projects are very attractive from both economic and environmental.
Maximizing lipocalin prediction through balanced and diversified training set and decision fusion.
Nath, Abhigyan; Subbiah, Karthikeyan
2015-12-01
Lipocalins are short in sequence length and perform several important biological functions. These proteins are having less than 20% sequence similarity among paralogs. Experimentally identifying them is an expensive and time consuming process. The computational methods based on the sequence similarity for allocating putative members to this family are also far elusive due to the low sequence similarity existing among the members of this family. Consequently, the machine learning methods become a viable alternative for their prediction by using the underlying sequence/structurally derived features as the input. Ideally, any machine learning based prediction method must be trained with all possible variations in the input feature vector (all the sub-class input patterns) to achieve perfect learning. A near perfect learning can be achieved by training the model with diverse types of input instances belonging to the different regions of the entire input space. Furthermore, the prediction performance can be improved through balancing the training set as the imbalanced data sets will tend to produce the prediction bias towards majority class and its sub-classes. This paper is aimed to achieve (i) the high generalization ability without any classification bias through the diversified and balanced training sets as well as (ii) enhanced the prediction accuracy by combining the results of individual classifiers with an appropriate fusion scheme. Instead of creating the training set randomly, we have first used the unsupervised Kmeans clustering algorithm to create diversified clusters of input patterns and created the diversified and balanced training set by selecting an equal number of patterns from each of these clusters. Finally, probability based classifier fusion scheme was applied on boosted random forest algorithm (which produced greater sensitivity) and K nearest neighbour algorithm (which produced greater specificity) to achieve the enhanced predictive performance
2012-12-01
portable devices where system size and efficiency are the primary design factors. Size and efficiency also govern the use of multiple MPPTs at the sub... mechanisms responsible for the energy losses in a switch-mode converter are the same. They include the components responsible for conduction, capacitor...designed to directly power a load as done in this test. The SPV-1020 may require an appropriate battery charger such as the STEVAL SEA05 battery
Greenisen, Michael C.; Fortney, Suzanne M.; Lee, Stuart M. C.; Moore, Alan D.; Barrows, Linda H.
1993-01-01
Several investigations within the Exercise Countermeasures Project at the NASA Johnson Space Center focused on the assessment of maximum oxygen consumption (VO2(sub max)) within the Astronaut Corps pre- and postspace flight. Investigations during the Apollo era suggested that there was a significant decrease in postflight VO2(sub max) when compared to preflight values, and current studies have documented that this trend continues in the Space Shuttle era. It is generally accepted and was confirmed in our laboratory that VO2(sub max) can be predicted from submaximal measures taken during graded exercise tests on the cycle ergometer with respect to populations. However, previous work had not examined the effect of day-to-day variations in the physiologic responses that might alter these predictions for individuals. Stability of individual submaximal data over serial tests is important so that predicted changes in VO2(sub max) are reflective of actual VO2(sub max) changes. Therefore, the purpose of this investigation was to determine which of the accepted equations to predict VO2(sub max) would be less affected by normal daily physiologic changes.
Maximal force characteristics of the Ca(2+)-powered actuator of Vorticella convallaria.
Ryu, Sangjin; Lang, Matthew J; Matsudaira, Paul
2012-09-05
The millisecond stalk contraction of the sessile ciliate Vorticella convallaria is powered by energy from Ca(2+) binding to generate contractile forces of ∼10 nN. Its contractile organelle, the spasmoneme, generates higher contractile force under increased stall resistances. By applying viscous drag force to contracting V. convallaria in a microfluidic channel, we observed that the mechanical force and work of the spasmoneme depended on the stalk length, i.e., the maximum tension (150-350 nN) and work linearly depended on the stalk length (∼2.5 nN and ∼30 fJ per 1 μm of the stalk). This stalk-length dependency suggests that motor units of the spasmoneme may be organized in such a way that the mechanical force and work of each unit cumulate in series along the spasmoneme.
Effect of Carbohydrate Intake on Maximal Power Output and Cognitive Performances
Laura Pomportes
2016-10-01
Full Text Available The present study aimed to assess the beneficial effect of acute carbohydrate (7% CHO intake on muscular and cognitive performances. Seventeen high levels athletes in explosive sports (fencing and squash participated in a randomized, double-blind study consisting in series of 6 sprints (5s with a passive recovery (25s followed by 15 min submaximal cycling after either maltodextrine and fructose (CHO or placebo (Pl intake. Cognitive performances were assessed before and after sprint exercise using a simple reaction time (SRT task at rest, a visual scanning task (VS and a Go/Nogo task (GNG during a submaximal cycling exercise. Results showed a beneficial effect of exercise on VS task on both conditions (Pl: −283 ms; CHO: −423 ms and on SRT only during CHO condition (−26 ms. In the CHO condition, SRT was faster after exercise whereas no effect of exercise was observed in the Pl condition. According to a qualitative statistical method, a most likely and likely positive effect of CHO was respectively observed on peak power (+4% and tiredness (−23% when compared to Pl. Furthermore, a very likely positive effect of CHO was observed on SRT (−8% and a likely positive effect on visual scanning (−6% and Go/Nogo tasks (−4% without any change in accuracy. In conclusion acute ingestion of 250 mL of CHO, 60 min and 30 min before exercise, improve peak power output, decrease muscular tiredness and speed up information processing and visual detection without changing accuracy.
Garbouj, H; Selmi, M A; Sassi, R Haj; Yahmed, M Haj; Chamari, K; Chaouachi, A
2016-12-01
The Special Judo Fitness Test (SJFT) has become the test most widely used by coaches and physical trainers for assessment of competitors' judo-specific physical aptitude and training programme prescription. The aim of this study was to investigate the relationship between the SJFT performance indices and both maximal aerobic power and the level of blood lactate concentrations in female judo athletes. Seventeen female judokas (age: 21.9±1.6 years, body mass: 74.6±27.4 kg, height: 164.5±8.6 cm; BMI: 27.1±8.0 kg · m(-2)) took part in this study. All participants performed the SJFT, 20 m multi-stage shuttle run test (MSRT), and 30 m straight sprint test (SST), from which we calculated both acceleration (10 m) and the maximal anaerobic speed (MAnS: flying 20 m sprint). A blood sample was taken 3 min after the SJFT. The number of throws was significantly correlated with estimated VO2max (r=0.795, p=0.0001) and both acceleration (r=0.63, p =0.006) and MAnS (r=0.76, p=0.0004). Peak blood lactate recorded after the SJFT was 13.90±1.39 mmol · l(-1). No significant correlation was found between blood lactate concentration and the SJFT performance indices. The lack of significant correlation between blood lactate and SJFT performance suggests that lactic anaerobic metabolism has no effect on this type of judo-specific supra-maximal exercise. The observed results can provide coaches and strength and conditioning professionals with relevant information for the interpretation of SJFT performance and the prescription of specific training programmes for female judo athletes.
Mahdi M. M. El-Arini
2013-01-01
Full Text Available In recent years, the solar energy has become one of the most important alternative sources of electric energy, so it is important to operate photovoltaic (PV panel at the optimal point to obtain the possible maximum efficiency. This paper presents a new optimization approach to maximize the electrical power of a PV panel. The technique which is based on objective function represents the output power of the PV panel and constraints, equality and inequality. First the dummy variables that have effect on the output power are classified into two categories: dependent and independent. The proposed approach is a multistage one as the genetic algorithm, GA, is used to obtain the best initial population at optimal solution and this initial population is fed to Lagrange multiplier algorithm (LM, then a comparison between the two algorithms, GA and LM, is performed. The proposed technique is applied to solar radiation measured at Helwan city at latitude 29.87°, Egypt. The results showed that the proposed technique is applicable.
Singh, Brijesh; Mahanty, Ranjit; Singh, S. P.
2013-05-01
This paper presents a framework to achieve an optimal power flow solution in a decentralized bilateral multitransaction-based market. An independent optimal dispatch solution has been used for each market. The interior point (IP)-based optimization technique has been used for finding a global economic optimal solution of the whole system. In this method, all the participants try to maximize their own profits with the help of system information announced by the operator. In the present work, a parallel algorithm has been used to find out a global optimum solution in decentralized market model. The study has been carried out on a modified IEEE-30 bus system. The results show that the suggested decentralized approach can provide a better optimal solution. The obtained results show the effectiveness of IP optimization-based optimal generator schedule and congestion management in the decentralized market.
Power Admission Control with Predictive Thermal Management in Smart Buildings
Yao, Jianguo; Costanzo, Giuseppe Tommaso; Zhu, Guchuan
2015-01-01
This paper presents a control scheme for thermal management in smart buildings based on predictive power admission control. This approach combines model predictive control with budget-schedulability analysis in order to reduce peak power consumption as well as ensure thermal comfort. First...
The power profile predicts road cycling MMP.
Quod, M J; Martin, D T; Martin, J C; Laursen, P B
2010-06-01
Laboratory tests of fitness variables have previously been shown to be valid predictors of cycling time-trial performance. However, due to the influence of drafting, tactics and the variability of power output in mass-start road races, comparisons between laboratory tests and competition performance are limited. The purpose of this study was to compare the power produced in the laboratory Power Profile (PP) test and Maximum Mean Power (MMP) analysis of competition data. Ten male cyclists (mean+/-SD: 20.8+/-1.5 y, 67.3+/-5.5 kg, V O (2 max) 72.7+/-5.1 mL x kg (-1) x min (-1)) completed a PP test within 14 days of competing in a series of road races. No differences were found between PP results and MMP analysis of competition data for durations of 60-600 s, total work or estimates of critical power and the fixed amount of work that can be completed above critical power (W'). Self-selected cadence was 15+/-7 rpm higher in the lab. These results indicate that the PP test is an ecologically valid assessment of power producing capacity over cycling specific durations. In combination with MMP analysis, this may be a useful tool for quantifying elements of cycling specific performance in competitive cyclists.
Introducing Model Predictive Control for Improving Power Plant Portfolio Performance
Edlund, Kristian Skjoldborg; Bendtsen, Jan Dimon; Børresen, Simon
2008-01-01
This paper introduces a model predictive control (MPC) approach for construction of a controller for balancing the power generation against consumption in a power system. The objective of the controller is to coordinate a portfolio consisting of multiple power plant units in the effort to perform...
Model Predictive Load Scheduling Using Solar Power Forecasting
Habib, Abdulelah H.; Kleissl, Jan; de Callafon, Raymond A.
2016-01-01
In this paper a model is developed to solve the on/off scheduling of (non-linear) dynamic electric loads based on predictions of the power delivery of a (standalone) solar power source. Knowledge of variations in the solar power output is used to optimally select the timing and the combinations of a set of given electric loads, where each load has a desired dynamic power profile. The optimization exploits the desired power profiles of the electric loads in terms of dynamic power ramp up/down ...
VT Predicted Mean Wind Power - 50 meter height
Vermont Center for Geographic Information — (Link to Metadata) Wind power predictions at 50m are generated by a numerical model that simulates weather conditions over a 15-year period, taking into account...
The predictive power of local properties of financial networks
Caraiani, Petre
2017-01-01
The literature on analyzing the dynamics of financial networks has focused so far on the predictive power of global measures of networks like entropy or index cohesive force. In this paper, I show that the local network properties have similar predictive power. I focus on key network measures like average path length, average degree or cluster coefficient, and also consider the diameter and the s-metric. Using Granger causality tests, I show that some of these measures have statistically significant prediction power with respect to the dynamics of aggregate stock market. Average path length is most robust relative to the frequency of data used or specification (index or growth rate). Most measures are found to have predictive power only for monthly frequency. Further evidences that support this view are provided through a simple regression model.
Lemmink, K.A.P.M.; Verheijen, R.; Visscher, C.
2004-01-01
AIM: The purpose of this study was to examine the discriminative power of the recently developed Interval Shuttle Run Test (ISRT) and the widely used Maximal Multistage 20 m Shuttle Run Test (MMSRT) for soccer players at different levels of competition. The main difference between the tests is that
Wind Power Plant Prediction by Using Neural Networks: Preprint
Liu, Z.; Gao, W.; Wan, Y. H.; Muljadi, E.
2012-08-01
This paper introduces a method of short-term wind power prediction for a wind power plant by training neural networks based on historical data of wind speed and wind direction. The model proposed is shown to achieve a high accuracy with respect to the measured data.
Application of Artificial Neural Networks for Predicting Generated Wind Power
Vijendra Singh
2016-01-01
This paper addresses design and development of an artificial neural network based system for prediction of wind energy produced by wind turbines. Now in the last decade, renewable energy emerged as an additional alternative source for electrical power generation. We need to assess wind power generation capacity by wind turbines because of its non-exhaustible nature. The power generation by electric wind turbines depends on the speed of wind, flow direction, fluctuations, density of air, gener...
Li, Chun; Yang, Yan; Fei, Wenchao; He, Ping-an; Yu, Xiaoqing; Zhang, Defu; Yi, Shumin; Li, Xuepeng; Zhu, Jin; Wang, Changzhong; Wang, Zhifu
2015-03-21
Polymerase chain reaction (PCR) is hailed as one of the monumental scientific techniques of the twentieth century, and has become a common and often indispensable technique in many areas. However, researchers still frequently find some DNA templates very hard to amplify with PCR, although many kinds of endeavors were introduced to optimize the amplification. In fact, during the past decades, the experimental procedure of PCR was always the focus of attention, while the analysis of a DNA template, the PCR experimental subject itself, was almost neglected. Up to now, nobody can certainly identify whether a fragment of DNA can be simply amplified using conventional Taq DNA polymerase-based PCR protocol. Characterizing a DNA template and then developing a reliable and efficient method to predict the success of PCR reactions is thus urgently needed. In this study, by means of the Markov maximal order model, we construct a 48-D feature vector to represent a DNA template. Support vector machine (SVM) is then employed to help evaluate PCR result. To examine the anticipated success rates of our predictor, jackknife cross-validation test is adopted. The overall accuracy of our approach arrives at 93.12%, with the sensitivity, specificity, and MCC of 94.68%, 91.58%, and 0.863%, respectively.
A new ensemble model for short term wind power prediction
Madsen, Henrik; Albu, Razvan-Daniel; Felea, Ioan
2012-01-01
As the objective of this study, a non-linear ensemble system is used to develop a new model for predicting wind speed in short-term time scale. Short-term wind power prediction becomes an extremely important field of research for the energy sector. Regardless of the recent advancements in the re-search...
Gutman, Boris A; Hua, Xue; Rajagopalan, Priya; Chou, Yi-Yu; Wang, Yalin; Yanovsky, Igor; Toga, Arthur W; Jack, Clifford R; Weiner, Michael W; Thompson, Paul M
2013-04-15
We propose a new method to maximize biomarker efficiency for detecting anatomical change over time in serial MRI. Drug trials using neuroimaging become prohibitively costly if vast numbers of subjects must be assessed, so it is vital to develop efficient measures of brain change. A popular measure of efficiency is the minimal sample size (n80) needed to detect 25% change in a biomarker, with 95% confidence and 80% power. For multivariate measures of brain change, we can directly optimize n80 based on a Linear Discriminant Analysis (LDA). Here we use a supervised learning framework to optimize n80, offering two alternative solutions. With a new medial surface modeling method, we track 3D dynamic changes in the lateral ventricles in 2065 ADNI scans. We apply our LDA-based weighting to the results. Our best average n80-in two-fold nested cross-validation-is 104 MCI subjects (95% CI: [94,139]) for a 1-year drug trial, and 75AD subjects [64,102]. This compares favorably with other MRI analysis methods. The standard "statistical ROI" approach applied to the same ventricular surfaces requires 165 MCI or 94AD subjects. At 2 years, the best LDA measure needs only 67 MCI and 52AD subjects, versus 119 MCI and 80AD subjects for the stat-ROI method. Our surface-based measures are unbiased: they give no artifactual additive atrophy over three time points. Our results suggest that statistical weighting may boost efficiency of drug trials that use brain maps.
Prediction of lacking control power in power plants using statistical models
Odgaard, Peter Fogh; Mataji, B.; Stoustrup, Jakob
2007-01-01
errors; the second uses operating point depending statistics of prediction errors. Using these methods on the previous mentioned case, it can be concluded that the second method can be used to predict the power plant performance, while the first method has problems predicting the uncertain performance...
Operational results from a physical power prediction model
Landberg, L. [Risoe National Lab., Meteorology and Wind Energy Dept., Roskilde (Denmark)
1999-03-01
This paper will describe a prediction system which predicts the expected power output of a number of wind farms. The system is automatic and operates on-line. The paper will quantify the accuracy of the predictions and will also give examples of the performance for specific storm events. An actual implementation of the system will be described and the robustness demonstrated. (au) 11 refs.
Potentiality Prediction of Electric Power Replacement Based on Power Market Development Strategy
Miao, Bo; Yang, Shuo; Liu, Qiang; Lin, Jingyi; Zhao, Le; Liu, Chang; Li, Bin
2017-05-01
The application of electric power replacement plays an important role in promoting the development of energy conservation and emission reduction in our country. To exploit the potentiality of regional electric power replacement, the regional GDP (gross domestic product) and energy consumption are taken as potentiality evaluation indicators. The principal component factors are extracted with PCA (principal component analysis), and the integral potentiality analysis is made to the potentiality of electric power replacement in the national various regions; a region is taken as a research object, and the potentiality of electric power replacement is defined and quantified. The analytical model for the potentiality of multi-scenario electric power replacement is developed, and prediction is made to the energy consumption with the grey prediction model. The relevant theoretical research is utilized to realize prediction analysis on the potentiality amount of multi-scenario electric power replacement.
Kalsen, Anders; Hostrup, Morten; Backer, Vibeke; Bangsbo, Jens
2016-06-01
The aim was to investigate the effect of the long-acting β2-adrenergic agonist formoterol on muscle strength and power output, muscle metabolism, and phosphorylation of CaMKII Thr(287) and FXYD1 during maximal sprinting. In a double-blind crossover study, 13 males [V̇o2 max: 45.0 ± 0.2 (means ± SE) ml·min(-1)·kg(-1)] performed a 30-s cycle ergometer sprint after inhalation of either 54 μg of formoterol (FOR) or placebo (PLA). Before and after the sprint, muscle biopsies were collected from vastus lateralis and maximal voluntary contraction (MVC), and contractile properties of quadriceps were measured. Oxygen uptake was measured during the sprint. During the sprint, peak power, mean power, and end power were 4.6 ± 0.8, 3.9 ± 1.1, and 9.5 ± 3.2% higher (P power output during maximal sprinting is associated with increased rates of glycogenolysis and glycolysis that may counteract development of fatigue. Copyright © 2016 the American Physiological Society.
Integrated Solid Oxide Fuel Cell Power System Characteristics Prediction
Marian GAICEANU
2009-07-01
Full Text Available The main objective of this paper is to deduce the specific characteristics of the CHP 100kWe Solid Oxide Fuel Cell (SOFC Power System from the steady state experimental data. From the experimental data, the authors have been developed and validated the steady state mathematical model. From the control room the steady state experimental data of the SOFC power conditioning are available and using the developed steady state mathematical model, the authors have been obtained the characteristic curves of the system performed by Siemens-Westinghouse Power Corporation. As a methodology the backward and forward power flow analysis has been employed. The backward power flow makes possible to obtain the SOFC power system operating point at different load levels, resulting as the load characteristic. By knowing the fuel cell output characteristic, the forward power flow analysis is used to predict the power system efficiency in different operating points, to choose the adequate control decision in order to obtain the high efficiency operation of the SOFC power system at different load levels. The CHP 100kWe power system is located at Gas Turbine Technologies Company (a Siemens Subsidiary, TurboCare brand in Turin, Italy. The work was carried out through the Energia da Ossidi Solidi (EOS Project. The SOFC stack delivers constant power permanently in order to supply the electric and thermal power both to the TurboCare Company and to the national grid.
Skill forecasting from ensemble predictions of wind power
Pinson, Pierre; Nielsen, Henrik Aalborg; Madsen, Henrik
2009-01-01
Optimal management and trading of wind generation calls for the providing of uncertainty estimates along with the commonly provided short-term wind power point predictions. Alternative approaches for the use of probabilistic forecasting are introduced. More precisely, focus is given to prediction...... risk indices aiming to give a comprehensive signal on the expected level of forecast uncertainty. Ensemble predictions of wind generation are used as input. A proposal for the definition of prediction risk indices is given. Such skill forecasts are based on the spread of ensemble forecasts (i.e. a set...
Application of Artificial Neural Networks for Predicting Generated Wind Power
Vijendra Singh
2016-03-01
Full Text Available This paper addresses design and development of an artificial neural network based system for prediction of wind energy produced by wind turbines. Now in the last decade, renewable energy emerged as an additional alternative source for electrical power generation. We need to assess wind power generation capacity by wind turbines because of its non-exhaustible nature. The power generation by electric wind turbines depends on the speed of wind, flow direction, fluctuations, density of air, generator hours, seasons of an area, and wind turbine position. During a particular season, wind power generation access can be increased. In such a case, wind energy generation prediction is crucial for transmission of generated wind energy to a power grid system. It is advisable for the wind power generation industry to predict wind power capacity to diagnose it. The present paper proposes an effort to apply artificial neural network technique for measurement of the wind energy generation capacity by wind farms in Harshnath, Sikar, Rajasthan, India.
Gradient dynamics and entropy production maximization
Janečka, Adam
2016-01-01
Gradient dynamics describes irreversible evolution by means of a dissipation potential, which leads to several advantageous features like Maxwell--Onsager relations, distinguishing between thermodynamic forces and fluxes or geometrical interpretation of the dynamics. Entropy production maximization is a powerful tool for predicting constitutive relations in engineering. In this paper, both approaches are compared and their shortcomings and advantages are discussed.
Caserotti, Paolo; Aagaard, Per; Simonsen, Erik Bruun
2001-01-01
Aging, muscle power, stretch-shortening cycle, eccentric muscle actions, concentric contractions......Aging, muscle power, stretch-shortening cycle, eccentric muscle actions, concentric contractions...
Thermal power prediction of nuclear power plant using neural network and parity space model
Roh Myung-Sub,; Cheon Se-Woo,; Chang Soon-Heung,
1991-04-01
This paper reports on a power prediction system developed using an artificial neural network paradigm that was combined with a parity space signal validation technique. The parity space signal validation algorithm for the input preprocessing and the backpropagation network algorithm for the network learning are used for the power prediction system. A number of case studies were performed with emphasis on the applicability of the network in a steady-state high power level. The studies reveal that these algorithms can precisely predict the thermal power in a nuclear power plant. It also shows that the error signals resulting from instrumentation problems, even when the signals comprising various patterns are noisy or incomplete, can be properly treated.
Wind power prediction based on genetic neural network
Zhang, Suhan
2017-04-01
The scale of grid connected wind farms keeps increasing. To ensure the stability of power system operation, make a reasonable scheduling scheme and improve the competitiveness of wind farm in the electricity generation market, it's important to accurately forecast the short-term wind power. To reduce the influence of the nonlinear relationship between the disturbance factor and the wind power, the improved prediction model based on genetic algorithm and neural network method is established. To overcome the shortcomings of long training time of BP neural network and easy to fall into local minimum and improve the accuracy of the neural network, genetic algorithm is adopted to optimize the parameters and topology of neural network. The historical data is used as input to predict short-term wind power. The effectiveness and feasibility of the method is verified by the actual data of a certain wind farm as an example.
SIMULATION STUDY OF GENERALIZED PREDICTIVE CONTROL FOR TURBINE POWER
Shi Xiaoping; Li Dongmei
2004-01-01
A GPC (generalized predictive control) law is developed to control the power of a turbine, after transforming the nonlinear mathematical model of the power regulation system into a CARIMA(controlled auto-regressive integrated moving average) form. The effect of the new control law is compared with a traditional PID (proportional, integral and differential) control law by numerical simulation. The simulation results verify the effectiveness, the correctness and the advantage of the new control scheme.
Using machine learning to predict wind turbine power output
Clifton, A.; Kilcher, L.; Lundquist, J. K.; Fleming, P.
2013-06-01
Wind turbine power output is known to be a strong function of wind speed, but is also affected by turbulence and shear. In this work, new aerostructural simulations of a generic 1.5 MW turbine are used to rank atmospheric influences on power output. Most significant is the hub height wind speed, followed by hub height turbulence intensity and then wind speed shear across the rotor disk. These simulation data are used to train regression trees that predict the turbine response for any combination of wind speed, turbulence intensity, and wind shear that might be expected at a turbine site. For a randomly selected atmospheric condition, the accuracy of the regression tree power predictions is three times higher than that from the traditional power curve methodology. The regression tree method can also be applied to turbine test data and used to predict turbine performance at a new site. No new data are required in comparison to the data that are usually collected for a wind resource assessment. Implementing the method requires turbine manufacturers to create a turbine regression tree model from test site data. Such an approach could significantly reduce bias in power predictions that arise because of the different turbulence and shear at the new site, compared to the test site.
Neural Network Predictive Control Based Power System Stabilizer
Ali Mohamed Yousef
2012-04-01
Full Text Available The present study investigates the power system stabilizer based on neural predictive control for improving power system dynamic performance over a wide range of operating conditions. In this study a design and application of the Neural Network Model Predictive Controller (NN-MPC on a simple power system composed of a synchronous generator connected to an infinite bus through a transmission line is proposed. The synchronous machine is represented in detail, taking into account the effect of the machine saliency and the damper winding. Neural network model predictive control combines reliable prediction of neural network model with excellent performance of model predictive control using nonlinear Levenberg-Marquardt optimization. This control system is used the rotor speed deviation as a feedback signal. Furthermore, the using performance system of the proposed controller is compared with the system performance using conventional one (PID controller through simulation studies. Digital simulation has been carried out in order to validate the effectiveness proposed NN-MPC power system stabilizer for achieving excellent performance. The results demonstrate that the effectiveness and superiority of the proposed controller in terms of fast response and small settling time.
Brendle, Joerg
2016-01-01
We show that, consistently, there can be maximal subtrees of P (omega) and P (omega) / fin of arbitrary regular uncountable size below the size of the continuum. We also show that there are no maximal subtrees of P (omega) / fin with countable levels. Our results answer several questions of Campero, Cancino, Hrusak, and Miranda.
Introducing Model Predictive Control for Improving Power Plant Portfolio Performance
Edlund, Kristian Skjoldborg; Bendtsen, Jan Dimon; Børresen, Simon
2008-01-01
This paper introduces a model predictive control (MPC) approach for construction of a controller for balancing the power generation against consumption in a power system. The objective of the controller is to coordinate a portfolio consisting of multiple power plant units in the effort to perform...... reference tracking and disturbance rejection in an economically optimal way. The performance function is chosen as a mixture of the `1-norm and a linear weighting to model the economics of the system. Simulations show a significant improvement of the performance of the MPC compared to the current...
Thermal Storage Power Balancing with Model Predictive Control
Halvgaard, Rasmus; Poulsen, Niels Kjølstad; Madsen, Henrik
2013-01-01
The method described in this paper balances power production and consumption with a large number of thermal loads. Linear controllers are used for the loads to track a temperature set point, while Model Predictive Control (MPC) and model estimation of the load behavior are used for coordination....... The total power consumption of all loads is controlled indirectly through a real-time price. The MPC incorporates forecasts of the power production and disturbances that influence the loads, e.g. time-varying weather forecasts, in order to react ahead of time. A simulation scenario demonstrates...
Akça Firat
2014-07-01
Full Text Available The aim of this research was to develop different regression models to predict 2000 m rowing ergometer performance with the use of anthropometric, anaerobic and strength variables and to determine how precisely the prediction models constituted by different variables predict performance, when conducted together in the same equation or individually. 38 male collegiate rowers (20.17 ± 1.22 years participated in this study. Anthropometric, strength, 2000 m maximal rowing ergometer and rowing anaerobic power tests were applied. Multiple linear regression procedures were employed in SPSS 16 to constitute five different regression formulas using a different group of variables. The reliability of the regression models was expressed by R2 and the standard error of estimate (SEE. Relationships of all parameters with performance were investigated through Pearson correlation coefficients. The prediction model using a combination of anaerobic, strength and anthropometric variables was found to be the most reliable equation to predict 2000 m rowing ergometer performance (R2 = 0.92, SEE= 3.11 s. Besides, the equation that used rowing anaerobic and strength test results also provided a reliable prediction (R2 = 0.85, SEE= 4.27 s. As a conclusion, it seems clear that physiological determinants which are affected by anaerobic energy pathways should also get involved in the processes and models used for performance prediction and talent identification in rowing.
A model to predict the power output from wind farms
Landberg, L. [Riso National Lab., Roskilde (Denmark)
1997-12-31
This paper will describe a model that can predict the power output from wind farms. To give examples of input the model is applied to a wind farm in Texas. The predictions are generated from forecasts from the NGM model of NCEP. These predictions are made valid at individual sites (wind farms) by applying a matrix calculated by the sub-models of WASP (Wind Atlas Application and Analysis Program). The actual wind farm production is calculated using the Riso PARK model. Because of the preliminary nature of the results, they will not be given. However, similar results from Europe will be given.
Model output statistics applied to wind power prediction
Joensen, A.; Giebel, G.; Landberg, L. [Risoe National Lab., Roskilde (Denmark); Madsen, H.; Nielsen, H.A. [The Technical Univ. of Denmark, Dept. of Mathematical Modelling, Lyngby (Denmark)
1999-03-01
Being able to predict the output of a wind farm online for a day or two in advance has significant advantages for utilities, such as better possibility to schedule fossil fuelled power plants and a better position on electricity spot markets. In this paper prediction methods based on Numerical Weather Prediction (NWP) models are considered. The spatial resolution used in NWP models implies that these predictions are not valid locally at a specific wind farm. Furthermore, due to the non-stationary nature and complexity of the processes in the atmosphere, and occasional changes of NWP models, the deviation between the predicted and the measured wind will be time dependent. If observational data is available, and if the deviation between the predictions and the observations exhibits systematic behavior, this should be corrected for; if statistical methods are used, this approaches is usually referred to as MOS (Model Output Statistics). The influence of atmospheric turbulence intensity, topography, prediction horizon length and auto-correlation of wind speed and power is considered, and to take the time-variations into account, adaptive estimation methods are applied. Three estimation techniques are considered and compared, Extended Kalman Filtering, recursive least squares and a new modified recursive least squares algorithm. (au) EU-JOULE-3. 11 refs.
For Tests That Are Predictively Powerful and without Social Prejudice
Soares, Joseph A.
2012-01-01
In Philip Pullman's dark matter sci-fi trilogy, there is a golden compass that in the hands of the right person is predictively powerful; the same was supposed to be true of the SAT/ACT--the statistically indistinguishable standardized tests for college admissions. They were intended to be reliable mechanisms for identifying future trajectories,…
Physical approach to short-term wind power prediction
Lange, Matthias
2006-01-01
Offers an approach to the ultimate goal of the short-term prediction of the power output of winds farms. This book addresses scientists and engineers working in wind energy related R and D and industry, as well as graduate students and nonspecialists researchers in the fields of atmospheric physics and meteorology.
A new ensemble model for short term wind power prediction
Madsen, Henrik; Albu, Razvan-Daniel; Felea, Ioan;
2012-01-01
As the objective of this study, a non-linear ensemble system is used to develop a new model for predicting wind speed in short-term time scale. Short-term wind power prediction becomes an extremely important field of research for the energy sector. Regardless of the recent advancements in the re......-search of prediction models, it was observed that different models have different capabilities and also no single model is suitable under all situations. The idea behind EPS (ensemble prediction systems) is to take advantage of the unique features of each subsystem to detain diverse patterns that exist in the dataset....... The conferred results show that the prediction errors can be decreased, while the computation time is reduced....
FGD Capacity Prediction of Thermal Power Plants in China
Zhu Fahua; Wang Sheng
2005-01-01
Through analyzing the proportion of SO2 emission from thermal power plants in the nationwide SO2 emission in USA, Japan etc. developed countries, and the developmental course of thermal power installed capacity and the FGD capacity in USA, the FGD capacity of thermal power plants in China is forecasted from two angles. One is to predict FGD capacity in accordance with the policy in force in China. The other is to predict FGD capacity based upon the emission right trading policy. As compared, it is held that FGD equipment should be mainly installed on the large size units burning high sulfur coal according to the emission right trading policy. Such a method of work not only can economize large amount of investments and operation costs, but also can realize the same environmental effect.
Effect of accuracy of wind power prediction on power system operator
Schlueter, R. A.; Sigari, G.; Costi, T.
1985-01-01
This research project proposed a modified unit commitment that schedules connection and disconnection of generating units in response to load. A modified generation control is also proposed that controls steam units under automatic generation control, fast responding diesels, gas turbines and hydro units under a feedforward control, and wind turbine array output under a closed loop array control. This modified generation control and unit commitment require prediction of trend wind power variation one hour ahead and the prediction of error in this trend wind power prediction one half hour ahead. An improved meter for predicting trend wind speed variation is developed. Methods for accurately simulating the wind array power from a limited number of wind speed prediction records was developed. Finally, two methods for predicting the error in the trend wind power prediction were developed. This research provides a foundation for testing and evaluating the modified unit commitment and generation control that was developed to maintain operating reliability at a greatly reduced overall production cost for utilities with wind generation capacity.
Model Predictive Control of Integrated Gasification Combined Cycle Power Plants
B. Wayne Bequette; Priyadarshi Mahapatra
2010-08-31
The primary project objectives were to understand how the process design of an integrated gasification combined cycle (IGCC) power plant affects the dynamic operability and controllability of the process. Steady-state and dynamic simulation models were developed to predict the process behavior during typical transients that occur in plant operation. Advanced control strategies were developed to improve the ability of the process to follow changes in the power load demand, and to improve performance during transitions between power levels. Another objective of the proposed work was to educate graduate and undergraduate students in the application of process systems and control to coal technology. Educational materials were developed for use in engineering courses to further broaden this exposure to many students. ASPENTECH software was used to perform steady-state and dynamic simulations of an IGCC power plant. Linear systems analysis techniques were used to assess the steady-state and dynamic operability of the power plant under various plant operating conditions. Model predictive control (MPC) strategies were developed to improve the dynamic operation of the power plants. MATLAB and SIMULINK software were used for systems analysis and control system design, and the SIMULINK functionality in ASPEN DYNAMICS was used to test the control strategies on the simulated process. Project funds were used to support a Ph.D. student to receive education and training in coal technology and the application of modeling and simulation techniques.
Hostrup, Morten; Kalsen, Anders; Onslev, Johan; Jessen, Søren; Haase, Christoffer; Habib, Sajad; Ørtenblad, Niels; Backer, Vibeke; Bangsbo, Jens
2015-09-01
The study was a randomized placebo-controlled trial investigating mechanisms by which chronic β2-adrenergic stimulation enhances muscle force and power output during maximal cycle ergometer exercise in young men. Eighteen trained men were assigned to an experimental group [oral terbutaline 5 mg/30 kg body weight (bw) twice daily (TER); n = 9] or a control group [placebo (PLA); n = 9] for a 4-wk intervention. No changes were observed with the intervention in PLA. Isometric muscle force of the quadriceps increased (P ≤ 0.01) by 97 ± 29 N (means ± SE) with the intervention in TER compared with PLA. Peak and mean power output during 30 s of maximal cycling increased (P ≤ 0.01) by 32 ± 8 and 25 ± 9 W, respectively, with the intervention in TER compared with PLA. Maximal oxygen consumption (V̇o2max) and time to fatigue during incremental cycling did not change with the intervention. Lean body mass increased by 1.95 ± 0.8 kg (P ≤ 0.05) with the intervention in TER compared with PLA. Change in single fiber cross-sectional area of myosin heavy chain (MHC) I (1,205 ± 558 μm(2); P ≤ 0.01) and MHC II fibers (1,277 ± 595 μm(2); P ≤ 0.05) of the vastus lateralis muscle was higher for TER than PLA with the intervention, whereas no changes were observed in MHC isoform distribution. Expression of muscle proteins involved in growth, ion handling, lactate production, and clearance increased (P ≤ 0.05) with the intervention in TER compared with PLA, with no change in oxidative enzymes. Our observations suggest that muscle hypertrophy is the primary mechanism underlying enhancements in muscle force and peak power during maximal cycling induced by chronic β2-adrenergic stimulation in humans.
Financial risk analysis and prediction of Chinese power industry
Jin, H.; An, C. [Hebei Univ. of Technology, Tianjin (China). School of Management; Zhang, C. [Nankai Univ., Tianjin (China). School of Business
2009-03-11
A study of 57 Shanghai and Shenzhen power industry companies was presented. The study considered financial ratios between companies in order to determine risk factors for financial crises. Financial data from the Shanghai and Shenzhen stock markets were used to investigate power company performance from 2006 to 2008. Data from the China Center for Economic Research (CCER) were also used. Results of the study indicated that the cash-to-current debt ratio, the return on equity (ROE), net asset growth ratio, and inventory turnover presented uncorrelated and significantly varying ratios for failed power companies. The study also showed that most power companies have a high proportion of liabilities, higher debt risk, low asset turnover ratios, and negative net working capital. Results of the analysis were used to design an early warning model that used logistic regression techniques to predict risk. 7 refs., 5 tabs.
Model predictive control power management strategies for HEVs: A review
Huang, Yanjun; Wang, Hong; Khajepour, Amir; He, Hongwen; Ji, Jie
2017-02-01
This paper presents a comprehensive review of power management strategy (PMS) utilized in hybrid electric vehicles (HEVs) with an emphasis on model predictive control (MPC) based strategies for the first time. Research on MPC-based power management systems for HEVs has intensified recently due to its many inherent merits. The categories of the existing PMSs are identified from the latest literature, and a brief study of each type is conducted. Then, the MPC approach is introduced and its advantages are discussed. Based on the acquisition method of driver behavior used for state prediction and the dynamic model used, the MPC is classified and elaborated. Factors that affect the performance of the MPC are put forward, including prediction accuracy, design parameters, and solvers. Finally, several important issues in the application of MPC-based power management strategies and latest developing trends are discussed. This paper not only provides a comprehensive analysis of MPC-based power management strategies for HEVs but also puts forward the future and emphasis of future study, which will promote the development of energy management controller with high performance and low cost for HEVs.
Prediction of Conducted Emissions in Satellite Power Buses
Giordano Spadacini
2015-01-01
Full Text Available This work reports a modeling methodology for the prediction of conducted emissions (CE in a wide frequency range (up to 100 MHz, which are generated by dc/dc converters and propagate along the power buses of satellites. In particular, the dc/dc converter seen as a source of CE is represented by a behavioral model, whose parameters can be identified by two unit-level experimental procedures performed in controlled test setups. A simplified multiconductor transmission-line (MTL model is developed to account for the propagation of CE in shielded bundles of twisted-wire pairs used as power cables. The whole power system is represented by the interconnection of the circuit models of dc/dc converters, cables, and Power Conditioning and Distribution Unit (PCDU. By solving the obtained network, frequency spectra of CE can be predicted. Experimental results are reported to substantiate the accuracy of the proposed unit-level dc/dc converter model and the MTL model of cables. Finally, a system-level test setup composed of three dc/dc converters connected to a PCDU is considered, and predicted CE are compared versus experimental measurements.
Suksan Tiyarachakun
2014-01-01
Full Text Available This paper presents a novel harmonic identification algorithm of shunt active power filter for balanced and unbalanced three-phase systems based on the instantaneous power theory called instantaneous power theory with Fourier. Moreover, the optimal design of predictive current controller using an artificial intelligence technique called adaptive Tabu search is also proposed in the paper. These enhancements of the identification and current control parts are the aim of the good performance for shunt active power filter. The good results for harmonic mitigation using the proposed ideas in the paper are confirmed by the intensive simulation using SPS in SIMULINK. The simulation results show that the enhanced shunt active power filter can provide the minimum %THD (Total Harmonic Distortion of source currents and unity power factor after compensation. In addition, the %THD also follows the IEEE Std.519-1992.
Empirical Information Metrics for Prediction Power and Experiment Planning
Christopher Lee
2011-01-01
Full Text Available In principle, information theory could provide useful metrics for statistical inference. In practice this is impeded by divergent assumptions: Information theory assumes the joint distribution of variables of interest is known, whereas in statistical inference it is hidden and is the goal of inference. To integrate these approaches we note a common theme they share, namely the measurement of prediction power. We generalize this concept as an information metric, subject to several requirements: Calculation of the metric must be objective or model-free; unbiased; convergent; probabilistically bounded; and low in computational complexity. Unfortunately, widely used model selection metrics such as Maximum Likelihood, the Akaike Information Criterion and Bayesian Information Criterion do not necessarily meet all these requirements. We define four distinct empirical information metrics measured via sampling, with explicit Law of Large Numbers convergence guarantees, which meet these requirements: Ie, the empirical information, a measure of average prediction power; Ib, the overfitting bias information, which measures selection bias in the modeling procedure; Ip, the potential information, which measures the total remaining information in the observations not yet discovered by the model; and Im, the model information, which measures the model’s extrapolation prediction power. Finally, we show that Ip + Ie, Ip + Im, and Ie — Im are fixed constants for a given observed dataset (i.e. prediction target, independent of the model, and thus represent a fundamental subdivision of the total information contained in the observations. We discuss the application of these metrics to modeling and experiment planning.
No extension of quantum theory can have improved predictive power.
Colbeck, Roger; Renner, Renato
2011-08-02
According to quantum theory, measurements generate random outcomes, in stark contrast with classical mechanics. This raises the question of whether there could exist an extension of the theory that removes this indeterminism, as suspected by Einstein, Podolsky and Rosen. Although this has been shown to be impossible, existing results do not imply that the current theory is maximally informative. Here we ask the more general question of whether any improved predictions can be achieved by any extension of quantum theory. Under the assumption that measurements can be chosen freely, we answer this question in the negative: no extension of quantum theory can give more information about the outcomes of future measurements than quantum theory itself. Our result has significance for the foundations of quantum mechanics, as well as applications to tasks that exploit the inherent randomness in quantum theory, such as quantum cryptography.
Chao Peng; Zhenzhen Zhang; Jia Wu
2015-01-01
A frequency control approach based on wind power and load power prediction information is proposed for wind-diesel-battery hybrid power system (WDBHPS). To maintain the frequency stability by wind power and diesel generation as much as possible, a fuzzy control theory based wind and diesel power control module is designed according to wind power and load prediction information. To compensate frequency fluctuation in real time and enhance system disturbance rejection ability, a battery energy ...
Andrew M. Parker
2007-12-01
Full Text Available Our previous research suggests that people reporting a stronger desire to maximize obtain worse life outcomes (Bruine de Bruin et al., 2007. Here, we examine whether this finding may be explained by the decision-making styles of self-reported maximizers. Expanding on Schwartz et al. (2002, we find that self-reported maximizers are more likely to show problematic decision-making styles, as evidenced by self-reports of less behavioral coping, greater dependence on others when making decisions, more avoidance of decision making, and greater tendency to experience regret. Contrary to predictions, self-reported maximizers were more likely to report spontaneous decision making. However, the relationship between self-reported maximizing and worse life outcomes is largely unaffected by controls for measures of other decision-making styles, decision-making competence, and demographic variables.
The critical power function is dependent on the duration of the predictive exercise tests chosen.
Bishop, D; Jenkins, D G; Howard, A
1998-02-01
The linear relationship between work accomplished (W(lim)) and time to exhaustion (t(lim)) can be described by the equation: W(lim) = a + CP x t(lim). Critical power (CP) is the slope of this line and is thought to represent a maximum rate of ATP synthesis without exhaustion, presumably an inherent characteristic of the aerobic energy system. The present investigation determined whether the choice of predictive tests would elicit significant differences in the estimated CP. Ten female physical education students completed, in random order and on consecutive days, five all-out predictive tests at preselected constant-power outputs. Predictive tests were performed on an electrically-braked cycle ergometer and power loadings were individually chosen so as to induce fatigue within approximately 1-10 mins. CP was derived by fitting the linear W(lim)-t(lim) regression and calculated three ways: 1) using the first, third and fifth W(lim)-t(lim) coordinates (I135), 2) using coordinates from the three highest power outputs (I123; mean t(lim) = 68-193 s) and 3) using coordinates from the lowest power outputs (I345; mean t(lim) = 193-485 s). Repeated measures ANOVA revealed that CPI123 (201.0+/-37.9W) > CPI135 (176.1+/-27.6W) > CPI345 (164.0+/-22.8W) (P<0.05). When the three sets of data were used to fit the hyperbolic Power-t(lim) regression, statistically significant differences between each CP were also found (P<0.05). The shorter the predictive trials, the greater the slope of the W(lim)-t(lim) regression; possibly because of the greater influence of 'aerobic inertia' on these trials. This may explain why CP has failed to represent a maximal, sustainable work rate. The present findings suggest that if CP is to represent the highest power output that an individual can maintain "for a very long time without fatigue" then CP should be calculated over a range of predictive tests in which the influence of aerobic inertia is minimised.
The power of operon rearrangements for predicting functional associations
Gabriel Moreno-Hagelsieb
2015-01-01
Full Text Available In this mini-review I aim to make the case that operons might be the most powerful source for predicted associations among gene products. Such associations can help identify potential processes where the products of unannotated genes might play a role. The power of the operon for providing insight into functional associations stems from four features: (1 on average, around 60% of the genes in prokaryotes are associated into operons; (2 the functional associations between genes in operons tend to be highly conserved; (3 operons can be predicted with high accuracy by conservation of gene order and by the distances between adjacent genes in the same DNA strand; and (4 operons frequently reorganize, providing further insight into functional associations that would not be evident without these reorganization events.
Predictive power of renormalisation group flows a comparison
Litim, Daniel F; Litim, Daniel F.; Pawlowski, Jan M.
2001-01-01
We study a proper-time renormalisation group, which is based on an operator cut-off regularisation of the one-loop effective action. The predictive power of this approach is constrained because the flow is not an exact one. We compare it to the Exact Renormalisation Group, which is based on a momentum regulator in the Wilsonian sense. In contrast to the former, the latter provides an exact flow. To leading order in a derivative expansion, an explicit map from the exact to the proper-time renormalisation group is established. The opposite map does not exist in general. We discuss various implications of these findings, in particular in view of the predictive power of the proper-time renormalisation group. As an application, we compute critical exponents for O(N)-symmetric scalar theories at the Wilson-Fisher fixed point in 3d from both formalisms.
Predicting and Preventing Flow Accelerated Corrosion in Nuclear Power Plant
Bryan Poulson
2014-01-01
Flow accelerated corrosion (FAC) of carbon steels in water has been a concern in nuclear power production for over 40 years. Many theoretical models or empirical approaches have been developed to predict the possible occurrence, position, and rate of FAC. There are a number of parameters, which need to be incorporated into any model. Firstly there is a measure defining the hydrodynamic severity of the flow; this is usually the mass transfer rate. The development of roughness due to FAC and it...
Characterizing and Predicting the Robustness of Power-law Networks
LaRocca, Sarah
2013-01-01
Power-law networks such as the Internet, terrorist cells, species relationships, and cellular metabolic interactions are susceptible to node failures, yet maintaining network connectivity is essential for network functionality. Disconnection of the network leads to fragmentation and, in some cases, collapse of the underlying system. However, the influences of the topology of networks on their ability to withstand node failures are poorly understood. Based on a study of the response of 2,000 power-law networks to node failures, we find that networks with higher nodal degree and clustering coefficient, lower betweenness centrality, and lower variability in path length and clustering coefficient maintain their cohesion better during such events. We also find that network robustness, i.e., the ability to withstand node failures, can be accurately predicted a priori for power-law networks across many fields. These results provide a basis for designing new, more robust networks, improving the robustness of existing...
Prediction of Chiller Power Consumption: An Entropy Generation Approach
Saththasivam, Jayaprakash
2016-06-21
Irreversibilities in each component of vapor compression chillers contribute to additional power consumption in chillers. In this study, chiller power consumption was predicted by computing the Carnot reversible work and entropy generated in every component of the chiller. Thermodynamic properties namely enthalpy and entropy of the entire refrigerant cycle were obtained by measuring the pressure and temperature at the inlet and outlet of each primary component of a 15kW R22 water cooled scroll chiller. Entropy generation of each component was then calculated using the First and Second Laws of Thermodynamics. Good correlation was found between the measured and computed chiller power consumption. This irreversibility analysis can be also effectively used as a performance monitoring tool in vapor compression chillers as higher entropy generation is anticipated during faulty operations.
K B Athreya
2009-09-01
It is shown that (i) every probability density is the unique maximizer of relative entropy in an appropriate class and (ii) in the class of all pdf that satisfy $\\int fh_id_=_i$ for $i=1,2,\\ldots,\\ldots k$ the maximizer of entropy is an $f_0$ that is proportional to $\\exp(\\sum c_i h_i)$ for some choice of $c_i$. An extension of this to a continuum of constraints and many examples are presented.
Ice Accretion Prediction on Wind Turbines and Consequent Power Losses
Yirtici, Ozcan; Tuncer, Ismail H.; Ozgen, Serkan
2016-09-01
Ice accretion on wind turbine blades modifies the sectional profiles and causes alteration in the aerodynamic characteristic of the blades. The objective of this study is to determine performance losses on wind turbines due to the formation of ice in cold climate regions and mountainous areas where wind energy resources are found. In this study, the Blade Element Momentum method is employed together with an ice accretion prediction tool in order to estimate the ice build-up on wind turbine blades and the energy production for iced and clean blades. The predicted ice shapes of the various airfoil profiles are validated with the experimental data and it is shown that the tool developed is promising to be used in the prediction of power production losses of wind turbines.
Honglu Zhu
2015-12-01
Full Text Available The power prediction for photovoltaic (PV power plants has significant importance for their grid connection. Due to PV power’s periodicity and non-stationary characteristics, traditional power prediction methods based on linear or time series models are no longer applicable. This paper presents a method combining the advantages of the wavelet decomposition (WD and artificial neural network (ANN to solve this problem. With the ability of ANN to address nonlinear relationships, theoretical solar irradiance and meteorological variables are chosen as the input of the hybrid model based on WD and ANN. The output power of the PV plant is decomposed using WD to separated useful information from disturbances. The ANNs are used to build the models of the decomposed PV output power. Finally, the outputs of the ANN models are reconstructed into the forecasted PV plant power. The presented method is compared with the traditional forecasting method based on ANN. The results shows that the method described in this paper needs less calculation time and has better forecasting precision.
Hostrup, Morten; Kalsen, Anders; Onslev, Johan
2015-01-01
of muscle proteins involved in growth, ion handling, lactate production and clearance increased (P≤0.05) with the intervention in TER compared to PLA, with no change in oxidative enzymes. Our observations suggest that muscle hypertrophy is the primary mechanism underlying enhancements in muscle force......The study was a randomized placebo-controlled trial investigating mechanisms by which chronic β2-adrenergic stimulation enhances muscle force and power output during maximal cycle ergometer exercise in young men. Eighteen trained men were assigned to an experimental group (oral terbutaline 5 mg∙30...... kgbw(-1) twice daily; TER, n=9) or a control group (placebo; PLA, n=9) for a four-week intervention. No changes were observed with the intervention in PLA. Isometric muscle force of the quadriceps increased (P≤0.01) by 97±29 N (mean±SE) with the intervention in TER compared to PLA. Peak and mean power...
Higgins, M F; Tallis, J; Price, M J; James, R S
2013-05-01
This study examined the effects of elevated buffer capacity [~32 mM HCO₃(-)] through administration of sodium bicarbonate (NaHCO₃) on maximally stimulated isolated mouse soleus (SOL) and extensor digitorum longus (EDL) muscles undergoing cyclical length changes at 37 °C. The elevated buffering capacity was of an equivalent level to that achieved in humans with acute oral supplementation. We evaluated the acute effects of elevated [HCO₃(-)] on (1) maximal acute power output (PO) and (2) time to fatigue to 60 % of maximum control PO (TLIM60), the level of decline in muscle PO observed in humans undertaking similar exercise, using the work loop technique. Acute PO was on average 7.0 ± 4.8 % greater for NaHCO₃-treated EDL muscles (P muscles (P muscle performance was variable, suggesting that there might be inter-individual differences in response to NaHCO₃ supplementation. These results present the best indication to date that NaHCO₃ has direct peripheral effects on mammalian skeletal muscle resulting in increased acute power output.
Prediction of heater power distribution in radiative cylindrical furnaces
Ravichandran, M.; Dilber, I.; Torok, D.
1999-07-01
In the design of long radiative cylindrical furnaces, it is important to control the temperature variation along the furnace walls and consequently the temperature distribution in the processed material by selectively adjusting the power input to heater rods located circumferentially around the furnace walls. The heaters are grouped in zones located at different axial locations. By adjusting the power to each zone a specified temperature distribution along the furnace can be attained. The radiative interchange between different axial zones of the furnace affects the temperature distribution; this interchange is also impacted by the shadowing caused by the presence of the load, i.e. the processed material. A desired temperature distribution can only be achieved by selectively changing the power input to the heaters. For an a priori assessment of the commercial viability of using process friendly temperature distributions, it is necessary to determine: (a) the maximum power demand from each zone; (b) if active cooling is inevitable and (c) the bounds on temperature distribution that can be achieved without active cooling. It is therefore extremely useful to be able to predict the input power distribution for achieving desired furnace temperature profiles. For a given power input, the temperature distribution inside the furnace could be obtained by using a general purpose Computational Fluid Dynamics (CFD) software, such as FIDAP. A new methodology is developed within the framework of FIDAP software to eliminate the manual trial and error method. The method is based on obtaining the sensitivity of the temperature at the desired locations of the furnace as a function of the power input to the heating elements. Using these sensitivity coefficients, an iterative scheme is designed to adjust the boundary conditions (power to the heating elements in this case) based on the discrepancy of the solution temperatures from the desired temperature distribution. For each of these
Mirolli, Marco; Santucci, Vieri G; Baldassarre, Gianluca
2013-03-01
An important issue of recent neuroscientific research is to understand the functional role of the phasic release of dopamine in the striatum, and in particular its relation to reinforcement learning. The literature is split between two alternative hypotheses: one considers phasic dopamine as a reward prediction error similar to the computational TD-error, whose function is to guide an animal to maximize future rewards; the other holds that phasic dopamine is a sensory prediction error signal that lets the animal discover and acquire novel actions. In this paper we propose an original hypothesis that integrates these two contrasting positions: according to our view phasic dopamine represents a TD-like reinforcement prediction error learning signal determined by both unexpected changes in the environment (temporary, intrinsic reinforcements) and biological rewards (permanent, extrinsic reinforcements). Accordingly, dopamine plays the functional role of driving both the discovery and acquisition of novel actions and the maximization of future rewards. To validate our hypothesis we perform a series of experiments with a simulated robotic system that has to learn different skills in order to get rewards. We compare different versions of the system in which we vary the composition of the learning signal. The results show that only the system reinforced by both extrinsic and intrinsic reinforcements is able to reach high performance in sufficiently complex conditions.
Saxena, Samveg
Homogeneous Charge Compression Ignition (HCCI) engines are one of the most promising engine technologies for the future of energy conversion from clean, efficient combustion. HCCI engines allow high efficiency and lower CO2 emission through the use of high compression ratios and the removal of intake throttle valves (like Diesel), and allow very low levels of urban pollutants like nitric oxide and soot (like Otto). These engines, however, are not without their challenges, such as low power density compared with other engine technologies, and a difficulty in controlling combustion timing. This dissertation first addresses the power output limits. The particular strategies for enabling high power output investigated in this dissertation focus on avoiding five critical limits that either damage an engine, drastically reduce efficiency, or drastically increase emissions: (1) ringing limits, (2) peak in-cylinder pressure limits, (3) misfire limits, (4) low intake temperature limits, and (5) excessive emissions limits. The research shows that the key factors that enable high power output, sufficient for passenger vehicles, while simultaneously avoiding the five limits defined above are the use of: (1) high intake air pressures allowing improved power output, (2) highly delayed combustion timing to avoid ringing limits, and (3) using the highest possible equivalence ratio before encountering ringing limits. These results are revealed by conducting extensive experiments spanning a wide range of operating conditions on a multi-cylinder HCCI engine. Second, this dissertation discusses strategies for effectively sensing combustion characteristics on a HCCI engine. For effective feedback control of HCCI combustion timing, a sensor is required to quantify when combustion occurs. Many laboratory engines use in-cylinder pressure sensors but these sensors are currently prohibitively expensive for wide-scale commercialization. Instead, ion sensors made from inexpensive sparkplugs
Using meteorological forecasts in on-line predictions of wind power
Nielsen, Torben Skov; Nielsen, Henrik Aalborg; Madsen, Henrik
1999-01-01
This report describes a model investigation into wind power prediction model as well as a tool for predicting the power production from wind turbines in an area - the Wind Power Prediction Tool (WPPT). The predictions are based on on-line measurements of power production for a selected set of ref...... of reference wind farms in the area as well as numerical weather predictions covering the locations of the reference wind farms. WPPT is in operational use in the Western part of Denmark and the utilities experiences with the tool is presented.......This report describes a model investigation into wind power prediction model as well as a tool for predicting the power production from wind turbines in an area - the Wind Power Prediction Tool (WPPT). The predictions are based on on-line measurements of power production for a selected set...
WANG Yu-xin
2013-09-01
Full Text Available In this paper, the traditional grid-connected PV perturbation method of disturbance near the maximum power point about the problems of shock，introduced a method based on single variable current control thought，established grid-connected PV maximum power tracking control system mathematical model, a novel single-variable current perturbation tracking method was put out, as long as the detected output current of the solar panel power generation system can achieve a stable variable maximum power tracking, through simulation and experimental study to verify the correctness of the model and the effectiveness of control methods.
Predicting Rediated Noise With Power Flow Finite Element Analysis
2007-02-01
vibratoire est traité d’une manière analogue au traitement du flux d’énergie thermique en régime stationnaire. RDDC a travaillé pendant plusieurs années à...previous phases of the PFFEA development, a hybrid energy method was developed for predicting high-frequency radiated sound power from a vibrating surface ...where the velocity on the surface of the radiating structure is known but the surface pressure is not. Fortunately, AVAST has algorithms appropriate
A mathematical look at a physical power prediction model
Landberg, L. [Riso National Lab., Roskilde (Denmark)
1997-12-31
This paper takes a mathematical look at a physical model used to predict the power produced from wind farms. The reason is to see whether simple mathematical expressions can replace the original equations, and to give guidelines as to where the simplifications can be made and where they can not. This paper shows that there is a linear dependence between the geostrophic wind and the wind at the surface, but also that great care must be taken in the selection of the models since physical dependencies play a very important role, e.g. through the dependence of the turning of the wind on the wind speed.
Model predictive control for Z-source power converter
Mo, W.; Loh, P.C.; Blaabjerg, Frede
2011-01-01
This paper presents Model Predictive Control (MPC) of impedance-source (commonly known as Z-source) power converter. Output voltage control and current control for Z-source inverter are analyzed and simulated. With MPC's ability of multi- system variables regulation, load current and voltage...... of variable switching frequency as well as robustness of transient response can be obtained at the same time with a formulated Z-source network model. Operating steady state and transient state simulation of MPC are going to be presented, which shows good reference tracking ability of this control method....
A mathematical look at a physical power prediction model
Landberg, L.
1998-01-01
This article takes a mathematical look at a physical model used to predict the power produced from wind farms. The reason is to see whether simple mathematical expressions can replace the original equations and to give guidelines as to where simplifications can be made and where they cannot....... The article shows that there is a linear dependence between the geostrophic wind and the local wind at the surface, but also that great care must be taken in the selection of the simple mathematical models, since physical dependences play a very important role, e.g. through the dependence of the turning...
Forecasting Electricity Spot Prices Accounting for Wind Power Predictions
Jónsson, Tryggvi; Pinson, Pierre; Nielsen, Henrik Aalborg
2013-01-01
-varying regression model. In a second step, time-series models, i.e., ARMA and Holt–Winters, are applied to account for residual autocorrelation and seasonal dynamics. Empirical results are presented for out-of-sample forecasts of day-ahead prices in the Western Danish price area of Nord Pool's Elspot, during a two......A two-step methodology for forecasting of electricity spot prices is introduced, with focus on the impact of predicted system load and wind power generation. The nonlinear and nonstationary influence of these explanatory variables is accommodated in a first step based on a nonparametric and time...
Sedliak, M; Finni, T; Cheng, S; Haikarainen, T; Häkkinen, K
2008-03-01
This study aimed to compare day-to-day repeatability of diurnal variation in strength and power. Thirty-two men were measured at four time points (07 : 00 - 08 : 00, 12 : 00 - 13 : 00, 17 : 00 - 18 : 00, and 20 : 30 - 21 : 30 h) throughout two consecutive days (day 1 and day 2). Power during loaded squat jumps, torque and EMG during maximal (MVC) and submaximal (MVC40) voluntary isometric knee extension contractions were measured. The EMG/torque ratio during MVC and MVC40 was calculated to evaluate neuromuscular efficiency. A significant time-of-day effect with repeatable diurnal patterns was found in power. In MVC, a significant time-of-day effect was present on day 2, whereas day 1 showed a typical but nonsignificant diurnal pattern. EMG and antagonist co-activation during MVC remained statistically unaltered, whereas neuromuscular efficiency improved from day 1 to day 2. A similar trend was observed in MVC40 neuromuscular efficiency with significant time-of-day and day-to-day effects. Unaltered agonist and antagonist activity during MVC suggests that modification at the muscular level was the primary source for the diurnal variation in peak torque. A learning effect seemed to affect data in MVC40. In conclusion, the second consecutive test day showed typical diurnal variation in both maximum strength and power with no day-to-day effect of cumulative fatigue.
Loturco, Irineu; Artioli, Guilherme Giannini; Kobal, Ronaldo; Gil, Saulo; Franchini, Emerson
2014-07-01
This study investigated the relationship between punching acceleration and selected strength and power variables in 19 professional karate athletes from the Brazilian National Team (9 men and 10 women; age, 23 ± 3 years; height, 1.71 ± 0.09 m; and body mass [BM], 67.34 ± 13.44 kg). Punching acceleration was assessed under 4 different conditions in a randomized order: (a) fixed distance aiming to attain maximum speed (FS), (b) fixed distance aiming to attain maximum impact (FI), (c) self-selected distance aiming to attain maximum speed, and (d) self-selected distance aiming to attain maximum impact. The selected strength and power variables were as follows: maximal dynamic strength in bench press and squat-machine, squat and countermovement jump height, mean propulsive power in bench throw and jump squat, and mean propulsive velocity in jump squat with 40% of BM. Upper- and lower-body power and maximal dynamic strength variables were positively correlated to punch acceleration in all conditions. Multiple regression analysis also revealed predictive variables: relative mean propulsive power in squat jump (W·kg-1), and maximal dynamic strength 1 repetition maximum in both bench press and squat-machine exercises. An impact-oriented instruction and a self-selected distance to start the movement seem to be crucial to reach the highest acceleration during punching execution. This investigation, while demonstrating strong correlations between punching acceleration and strength-power variables, also provides important information for coaches, especially for designing better training strategies to improve punching speed.
Obukhov, S. G.; Plotnikov, I. A.; Surzhikova, O. A.; Savkin, K. D.
2017-04-01
Solar photovoltaic technology is one of the most rapidly growing renewable sources of electricity that has practical application in various fields of human activity due to its high availability, huge potential and environmental compatibility. The original simulation model of the photovoltaic power plant has been developed to simulate and investigate the plant operating modes under actual operating conditions. The proposed model considers the impact of the external climatic factors on the solar panel energy characteristics that improves accuracy in the power output prediction. The data obtained through the photovoltaic power plant operation simulation enable a well-reasoned choice of the required capacity for storage devices and determination of the rational algorithms to control the energy complex.
Kraemer, William J; Boyd, Brittny M; Hooper, David R; Fragala, Maren S; Hatfield, Disa L; Dunn-Lewis, Courtenay; Comstock, Brett A; Szivak, Tunde K; Flanagan, Shawn D; Looney, David P; Newton, Robert U; Vingren, Jakob L; Häkkinen, Keijo; White, Mark T; Volek, Jeff S; Maresh, Carl M
2014-09-01
The optimal time of day for training has become an important question for many strength and conditioning specialists, and this study was designed to add some insights into this complex question. The primary purpose of this investigation was to examine physical performance within the temporal context of the relationship between physical performance, epinephrine, and melatonin concentrations in the early morning (0530 hours) and late (1500 hours) afternoon in elite collegiate male track and field athletes (jumpers and sprinters). Subjects had a mean (±SD) age, height, and body mass of 20.4 (±1.6) years, 185.8 (±9.4) cm, and 77.9 (±8.5) kg, respectively. Blood was obtained before each AM and PM testing session. Mean plasma melatonin concentrations were 34.9 ± 22.7 pg·ml and 4.8 ± 3.3 pg·ml for the AM vs. PM trials, respectively, demonstrating a significant (p ≤ 0.05) difference between time points. Mean resting plasma epinephrine concentrations for AM (171.7 ± 33.7 pmol·L) and PM (127.6 ± 47.8 pmol·L) also differed significantly between trails at the different times. In addition, significant differences were observed with respect to foot quickness in the AM (5.14 ± 1.06 seconds) and PM (4.39 ± 0.76 seconds). Mean peak power output for vertical jump power was 5,407.1 ± 1,272.9 W, 5,384.6 ± 888.3 W for AM vs. PM trials, respectively, which were not significantly different. The results of this investigation indicate that time of day did not negatively impact whole body physical performance in trained track athletes but did impact the quality of quickness. Thus in the morning, whole body power performances may be enhanced through adrenergic arousal when melatonin is elevated. However, this was not the case for movements requiring quickness and accuracy of movement. To compensate for the "sleepiness" associated with high concentrations of melatonin, being secreted from the pineal gland representing a continued "sleepiness" effect on the body, early
Balsalobre-Fernández, Carlos; Tejero-González, Carlos M; Del Campo-Vecino, Juan; Alonso-Curiel, Dionisio
2013-03-01
The aim of this study was to determine the effects of a power training cycle on maximum strength, maximum power, vertical jump height and acceleration in seven high-level 400-meter hurdlers subjected to a specific training program twice a week for 10 weeks. Each training session consisted of five sets of eight jump-squats with the load at which each athlete produced his maximum power. The repetition maximum in the half squat position (RM), maximum power in the jump-squat (W), a squat jump (SJ), countermovement jump (CSJ), and a 30-meter sprint from a standing position were measured before and after the training program using an accelerometer, an infra-red platform and photo-cells. The results indicated the following statistically significant improvements: a 7.9% increase in RM (Z=-2.03, p=0.021, δc=0.39), a 2.3% improvement in SJ (Z=-1.69, p=0.045, δc=0.29), a 1.43% decrease in the 30-meter sprint (Z=-1.70, p=0.044, δc=0.12), and, where maximum power was produced, a change in the RM percentage from 56 to 62% (Z=-1.75, p=0.039, δc=0.54). As such, it can be concluded that strength training with a maximum power load is an effective means of increasing strength and acceleration in high-level hurdlers.
Maryam Moazen
2016-09-01
Full Text Available In this paper, a predictive direct power control (PDPC method for the brushless doubly fed reluctance generator (BDFRG is proposed. Firstly, the BDFRG active and reactive power equations are derived and then the active and reactive power variations have been predicted within a fixed sampling period. The predicted power variations are used to calculate the required voltage of the secondary winding so that the power errors at the end of the following sampling period are eliminated. Switching pulses are produced using space vector pulse width modulation (SVPWM approach which causes to a fixed switching frequency. The BDFRG model and the proposed control method are simulated in MATLAB/Simulink software. Simulation results indicate the good performance of the control system in tracking of the active and reactive power references in both power step and speed variation conditions. In addition, fast dynamic response and lower output power ripple are other advantages of this control method.
Hansen, Dominique; Jacobs, Nele; Thijs, Herbert; Dendale, Paul; Claes, Neree
2016-09-01
Healthcare professionals with limited access to ergospirometry remain in need of valid and simple submaximal exercise tests to predict maximal oxygen uptake (VO2max ). Despite previous validation studies concerning fixed-rate step tests, accurate equations for the estimation of VO2max remain to be formulated from a large sample of healthy adults between age 18-75 years (n > 100). The aim of this study was to develop a valid equation to estimate VO2max from a fixed-rate step test in a larger sample of healthy adults. A maximal ergospirometry test, with assessment of cardiopulmonary parameters and VO2max , and a 5-min fixed-rate single-stage step test were executed in 112 healthy adults (age 18-75 years). During the step test and subsequent recovery, heart rate was monitored continuously. By linear regression analysis, an equation to predict VO2max from the step test was formulated. This equation was assessed for level of agreement by displaying Bland-Altman plots and calculation of intraclass correlations with measured VO2max . Validity further was assessed by employing a Jackknife procedure. The linear regression analysis generated the following equation to predict VO2max (l min(-1) ) from the step test: 0·054(BMI)+0·612(gender)+3·359(body height in m)+0·019(fitness index)-0·012(HRmax)-0·011(age)-3·475. This equation explained 78% of the variance in measured VO2max (F = 66·15, Pstep test equation has been developed to estimate VO2max in healthy adults. This tool could be employed by healthcare professionals with limited access to ergospirometry.
Model predictive control for Z-source power converter
Mo, W.; Loh, P.C.; Blaabjerg, Frede
2011-01-01
This paper presents Model Predictive Control (MPC) of impedance-source (commonly known as Z-source) power converter. Output voltage control and current control for Z-source inverter are analyzed and simulated. With MPC's ability of multi- system variables regulation, load current and voltage...... regulations, impedance network inductor current, capacitor voltage as well as switching frequency fixation, transient reservation and null state penalization are all regulated as subjecting to constraints of this control method. The quality of output waveform, stability of impedance-network, level constraint...... of variable switching frequency as well as robustness of transient response can be obtained at the same time with a formulated Z-source network model. Operating steady state and transient state simulation of MPC are going to be presented, which shows good reference tracking ability of this control method....
Predicting and Preventing Flow Accelerated Corrosion in Nuclear Power Plant
Bryan Poulson
2014-01-01
Full Text Available Flow accelerated corrosion (FAC of carbon steels in water has been a concern in nuclear power production for over 40 years. Many theoretical models or empirical approaches have been developed to predict the possible occurrence, position, and rate of FAC. There are a number of parameters, which need to be incorporated into any model. Firstly there is a measure defining the hydrodynamic severity of the flow; this is usually the mass transfer rate. The development of roughness due to FAC and its effect on mass transfer need to be considered. Then most critically there is the derived or assumed functional relationship between the chosen hydrodynamic parameter and the rate of FAC. Environmental parameters that are required, at the relevant temperature and pH, are the solubility of magnetite and the diffusion coefficient of the relevant iron species. The chromium content of the steel is the most important material factor.
Cosmic Emulation: Fast Predictions for the Galaxy Power Spectrum
Kwan, Juliana; Habib, Salman; Padmanabhan, Nikhil; Finkel, Hal; Frontiere, Nick; Pope, Adrian
2013-01-01
The halo occupation distribution (HOD) approach has proven to be an effective method for modeling galaxy clustering and bias. In this approach, galaxies of a given type are probabilistically assigned to individual halos in N-body simulations. In this paper, we present a fast emulator for predicting the fully nonlinear galaxy power spectrum over a range of freely specifiable HOD modeling parameters. The emulator is constructed using results from 100 HOD models run on a large LCDM N-body simulation, with Gaussian Process interpolation applied to a PCA-based representation of the galaxy power spectrum. The total error is currently ~3% (~2% in the simulation and ~1% in the emulation process) from z=1 to z=0, over the considered parameter range. We use the emulator to investigate parametric dependencies in the HOD model, as well as the behavior of galaxy bias as a function of HOD parameters. The emulator is publicly available at http://www.hep.anl.gov/cosmology/CosmicEmu/emu.html.
Power Prediction in Smart Grids with Evolutionary Local Kernel Regression
Kramer, Oliver; Satzger, Benjamin; Lässig, Jörg
Electric grids are moving from a centralized single supply chain towards a decentralized bidirectional grid of suppliers and consumers in an uncertain and dynamic scenario. Soon, the growing smart meter infrastructure will allow the collection of terabytes of detailed data about the grid condition, e.g., the state of renewable electric energy producers or the power consumption of millions of private customers, in very short time steps. For reliable prediction strong and fast regression methods are necessary that are able to cope with these challenges. In this paper we introduce a novel regression technique, i.e., evolutionary local kernel regression, a kernel regression variant based on local Nadaraya-Watson estimators with independent bandwidths distributed in data space. The model is regularized with the CMA-ES, a stochastic non-convex optimization method. We experimentally analyze the load forecast behavior on real power consumption data. The proposed method is easily parallelizable, and therefore well appropriate for large-scale scenarios in smart grids.
Power Relative to Body Mass Best Predicts Change in Core Temperature During Exercise-Heat Stress.
Gibson, Oliver R; Willmott, Ashley G B; James, Carl A; Hayes, Mark; Maxwell, Neil S
2017-02-01
Gibson, OR, Willmott, AGB, James, CA, Hayes, M, and Maxwell, NS. Power relative to body mass best predicts change in core temperature during exercise-heat stress. J Strength Cond Res 31(2): 403-414, 2017-Controlling internal temperature is crucial when prescribing exercise-heat stress, particularly during interventions designed to induce thermoregulatory adaptations. This study aimed to determine the relationship between the rate of rectal temperature (Trec) increase, and various methods for prescribing exercise-heat stress, to identify the most efficient method of prescribing isothermic heat acclimation (HA) training. Thirty-five men cycled in hot conditions (40° C, 39% R.H.) for 29 ± 2 minutes. Subjects exercised at 60 ± 9% V[Combining Dot Above]O2peak, with methods for prescribing exercise retrospectively observed for each participant. Pearson product moment correlations were calculated for each prescriptive variable against the rate of change in Trec (° C·h), with stepwise multiple regressions performed on statistically significant variables (p ≤ 0.05). Linear regression identified the predicted intensity required to increase Trec by 1.0-2.0° C between 20- and 45-minute periods and the duration taken to increase Trec by 1.5° C in response to incremental intensities to guide prescription. Significant (p ≤ 0.05) relationships with the rate of change in Trec were observed for prescriptions based on relative power (W·kg; r = 0.764), power (%Powermax; r = 0.679), rating of perceived exertion (RPE) (r = 0.577), V[Combining Dot Above]O2 (%V[Combining Dot Above]O2peak; r = 0.562), heart rate (HR) (%HRmax; r = 0.534), and thermal sensation (r = 0.311). Stepwise multiple regressions observed relative power and RPE as variables to improve the model (r = 0.791), with no improvement after inclusion of any anthropometric variable. Prescription of exercise under heat stress using power (W·kg or %Powermax) has the strongest relationship with the rate of change in
The Predictive Power of Financial Variables: New Evidence from Australia
Piyadasa Edirisuriya
2015-03-01
Full Text Available Many studies have attempted to examine the predictive power of financial variables for numerous countries, but rarely does such research focus on future economic activities with respect to Australia. Financial variables are used to predict future economic events primarily because these variables are the closest indicators of the expectations and activities of investors and other economic agents. The recent global financial crisis (GFC stemming from the subprime crisis shows that financial markets significantly influence global macroeconomic activities. In this study, we use major financial variables, such as the 90-day Treasury bill rate, 10-year Treasury bond rate, interest rate spread, and Australian stock index data. Similar to the housing prices in some other countries, those in Australia play a key role in future economic activities. In addition to financial variables, housing stock data is incorporated into our model for more realistic results, which are obtained by probit maximum likelihood estimation. We also use a general model for forecasting Australia’s GDP growth until the third quarter of 2012. The results support previous research findings, indicating that financial variables are a useful tool for forecasting future economic activities in Australia.
Wind turbine power curve prediction with consideration of rotational augmentation effects
Tang, X.; Huang, X.; Sun, S.; Peng, R.
2016-11-01
Wind turbine power curve expresses the relationship between the rotor power and the hub wind speed. Wind turbine power curve prediction is of vital importance for power control and wind energy management. To predict power curve, the Blade Element Moment (BEM) method is used in both academic and industrial communities. Due to the limited range of angles of attack measured in wind tunnel testing and the three-dimensional (3D) rotational augmentation effects in rotating turbines, wind turbine power curve prediction remains a challenge especially at high wind speeds. This paper presents an investigation of considering the rotational augmentation effects using characterized lift and drag coefficients from 3D computational fluid dynamics (CFD) simulations coupled in the BEM method. A Matlab code was developed to implement the numerical calculation. The predicted power outputs were compared with the NREL Phase VI wind turbine measurements. The results demonstrate that the coupled method improves the wind turbine power curve prediction.
Using meteorological forecasts in on-line predictions of wind power
Nielsen, Torben Skov; Nielsen, Henrik Aalborg; Madsen, Henrik;
1999-01-01
This report describes a model investigation into wind power prediction model as well as a tool for predicting the power production from wind turbines in an area - the Wind Power Prediction Tool (WPPT). The predictions are based on on-line measurements of power production for a selected set of ref...... of reference wind farms in the area as well as numerical weather predictions covering the locations of the reference wind farms. WPPT is in operational use in the Western part of Denmark and the utilities experiences with the tool is presented....
Social group utility maximization
Gong, Xiaowen; Yang, Lei; Zhang, Junshan
2014-01-01
This SpringerBrief explains how to leverage mobile users' social relationships to improve the interactions of mobile devices in mobile networks. It develops a social group utility maximization (SGUM) framework that captures diverse social ties of mobile users and diverse physical coupling of mobile devices. Key topics include random access control, power control, spectrum access, and location privacy.This brief also investigates SGUM-based power control game and random access control game, for which it establishes the socially-aware Nash equilibrium (SNE). It then examines the critical SGUM-b
Prediction of reserves using multivariate power-normal mixture distribution
Ling, Ang Siew; Hin, Pooi Ah
2016-10-01
Recently, in the area on stochastic loss reserving, there are a number of papers which analyze the individual claims data using the Position Dependent Marked Poisson Process. The present paper instead uses a different type of individual data. For the i-th (1≤i≤n) customer, these individual data include the sum insured si together with the amount paid yi j and the amount ai j reported but not yet paid in the j-th (1 ≤ j ≤ 6) development year. A technique based on multivariate power-normal mixture distribution is already available for predicting the future value (yi j + 1, ai j + 1) using the present year value (yi j, ai j) and the sum insured si. Presently the above technique is improved by the transformation of distribution which is defined on the whole real line to one which is non-negative and having approximately the same first four moments as the original distribution. It is found that, for the dataset considered in this paper, the improved method gives a better estimate for the reserve when compared with the chain ladder reserve estimate. Furthermore, the method is expected to provide a fairly reliable value for the Provision of Risk Margin for Adverse Deviation (PRAD).
Cherif, M; Chtourou, H; Souissi, N; Aouidet, A; Chamari, K
2016-12-01
This study was designed to assess the effect of strength and power training on throwing velocity and muscle strength in handball players according to their playing positions. Twenty-two male handball players were assigned to either an experimental group (n=11) or a control group (n=11) (age: 22.1 ± 3.0 years). They were asked to complete (i) the ball throwing velocity test and (ii) the one-repetition maximum (1-RM) tests for the half-back squat, the pull-over, the bench press, the developed neck, and the print exercises before and after 12 weeks of maximal power training. The training was designed to improve strength and power with an intensity of 85-95% of the 1RM. In addition to their usual routine handball training sessions, participants performed two sessions per week. During each session, they performed 3-5 sets of 3-8 repetitions with 3 min of rest in between. Then, they performed specific shots (i.e., 12 to 40). Ball-throwing velocity (p<0.001) was higher after the training period in rear line players (RL). The training programme resulted in an improvement of 1RM bench press (p<0.001), 1RM developed neck (p<0.001) and 1RM print (p<0.001) in both front line (FL) and RL. The control group showed a significant improvement only in ball-throwing velocity (p<0.01) and 1RM bench press (p<0.01) in RL. A significantly greater improvement was found in ball-throwing velocity (p<0.001), 1RM bench press (p<0.001), and 1RM half-back squat exercises in players of the central axis (CA) compared to the lateral axis (LA) (p<0.01). The power training programme induced significantly greater increases in ball-throwing velocity and muscle strength in FL than RL and in CA than LA axis players.
Kawahito, T. (Takamatsu National College of Technology, Kagawa (Japan)); Suzuki, T. (Tokushima University, Tokushima (Japan))
1994-03-20
This paper reports a method in a wind power generation system to control output current from a generator so that it fits automatically the wind turbine characteristics where the turbine characteristics are unknown and the generator characteristics are known. The paper details the following methods: a method that rotation speed of a wind turbine is observed to make the output current from the generator proportional to a square of the turbine rotation speed, and optimize the proportion coefficient so that the generator output at an equilibrium operation point of this system (wind turbine generated torque is in equilibrium with the generator driven torque) is maximized; and a method to derive an optimal proportion coefficient in discrete time control using a digital computer. The paper then describes the following matters: a simulation that assumes a pseudo natural wind velocity has verified the effectiveness of this control method; discovering an optimal proportion coefficient has required about ten minutes; and the way this control method handles fluctuation in wind velocity has a room of further improvement. 16 refs., 10 figs., 1 tab.
Gonzalo-Skok, Oliver; Tous-Fajardo, Julio; Arjol-Serrano, José Luis; Suarez-Arrones, Luis; Casajús, José Antonio; Mendez-Villanueva, Alberto
2016-05-01
To examine the effects of a low-volume repeated-power-ability (RPA) training program on repeated-sprint and change-of- direction (COD) ability and functional jumping performance. Twenty-two male elite young basketball players (age 16.2 ± 1.2 y, height 190.0 ± 10.0 cm, body mass 82.9 ± 10.1 kg) were randomly assigned either to an RPA-training group (n = 11) or a control group (n = 11). RPA training consisted of leg-press exercise, twice a week for 6 wk, of 1 or 2 blocks of 5 sets × 5 repetitions with 20 s of passive recovery between sets and 3 min between blocks with the load that maximized power output. Before and after training, performance was assessed by a repeated-sprint-ability (RSA) test, a repeated-COD-ability test, a hop for distance, and a drop jump followed by tests of a double unilateral hop with the right and left legs. Within-group and between-groups differences showed substantial improvements in slowest (RSAs) and mean time (RSAm) on RSA; best, slowest and mean time on repeated-COD ability; and unilateral right and left hop in the RPA group in comparison with control. While best time on RSA showed no improvement in any group, there was a large relationship (r = .68, 90% CI .43;.84) between the relative decrement in RSAm and RSAs, suggesting better sprint maintenance with RPA training. The relative improvements in best and mean repeated-COD ability were very largely correlated (r = .89, 90% CI .77;.94). Six weeks of lowvolume (4-14 min/wk) RPA training improved several physical-fitness tests in basketball players.
Lifetime prediction of high-power press-pack IGBTs in wind power applications
Busca, Cristian
developed for the studied open-capsule PP IGBT. First, a 3D FEM based clamping force distribution model which is able to translate mechanical clamping conditions into chip-level clamping forces is developed. Next, a 3D FEM based dynamic thermal model which is able to calculate the chip-level thermal...... impedances by taking into account chip-level clamping forces is developed. The chip-level power loss models are implemented in the form of look-up tables which take into consideration voltage, current and temperature. In order to predict the lifetime at chip-level the developed models are implemented...... data provided by IXYS WESTCODE UK for the chips used in the open-capsule PP IGBT. A test setup employing a stack with 2 PP IGBTs and 3 cooling plates is developed in order to validate to some extent the developed models. The clamping force distribution model is validated under ideal mechanical clamping...
Lifetime prediction modeling of airfoils for advanced power generation
Karaivanov, Ventzislav Gueorguiev
The use of gases produced from coal as a turbine fuel offers an attractive means for efficiently generating electric power from our Nation's most abundant fossil fuel resource. The oxy-fuel and hydrogen-fired turbine concepts promise increased efficiency and low emissions on the expense of increased turbine inlet temperature (TIT) and different working fluid. Developing the turbine technology and materials is critical to the creation of these near-zero emission power generation technologies. A computational methodology, based on three-dimensional finite element analysis (FEA) and damage mechanics is presented for predicting the evolution of creep and fatigue in airfoils. We took a first look at airfoil thermal distributions in these advanced turbine systems based on CFD analysis. The damage mechanics-based creep and fatigue models were implemented as user modified routine in commercial package ANSYS. This routine was used to visualize the creep and fatigue damage evolution over airfoils for hydrogen-fired and oxy-fuel turbines concepts, and regions most susceptible to failure were indentified. Model allows for interaction between creep and fatigue damage thus damage due to fatigue and creep processes acting separately in one cycle will affect both the fatigue and creep damage rates in the next cycle. Simulation results were presented for various thermal conductivity of the top coat. Surface maps were created on the airfoil showing the development of the TGO scale and the Al depletion of the bond coat. In conjunction with model development, laboratory-scale experimental validation was executed to evaluate the influence of operational compressive stress levels on the performance of the TBC system. TBC coated single crystal coupons were exposed isothermally in air at 900, 1000, 1100oC with and without compressive load. Exposed samples were cross-sectioned and evaluated with scanning electron microscope (SEM). Performance data was collected based on image analysis
A. M. Elaiw
2013-01-01
Full Text Available The purpose of this paper is to present a model predictive control (MPC approach for the periodic implementation of the optimal solutions of two optimal dynamic dispatch problems with emission and transmission line losses. The first problem is the dynamic economic emission dispatch (DEED which is a multiobjective optimization problem which minimizes both fuel cost and pollutants emission simultaneously under a set of constraints. The second one is the profit-based dynamic economic emission dispatch (PBDEED which is also a multi-objective optimization problem which maximizes the profit and minimizes the emission simultaneously under a set of constraints. Both the demand and energy price are assumed to be periodic and the total transmission loss is assumed to be a quadratic function of the generator power outputs. We assume that there are certain disturbances or uncertainties in the execution of the optimal controller and in the forecasted demand. The convergence and robustness of the MPC algorithm are demonstrated through the application of MPC to the DEED and PBDEED problems with five-unit and six-unit test systems, respectively.
Photovoltaic Power Prediction Based on Scene Simulation Knowledge Mining and Adaptive Neural Network
Dongxiao Niu
2013-01-01
Full Text Available Influenced by light, temperature, atmospheric pressure, and some other random factors, photovoltaic power has characteristics of volatility and intermittent. Accurately forecasting photovoltaic power can effectively improve security and stability of power grid system. The paper comprehensively analyzes influence of light intensity, day type, temperature, and season on photovoltaic power. According to the proposed scene simulation knowledge mining (SSKM technique, the influencing factors are clustered and fused into prediction model. Combining adaptive algorithm with neural network, adaptive neural network prediction model is established. Actual numerical example verifies the effectiveness and applicability of the proposed photovoltaic power prediction model based on scene simulation knowledge mining and adaptive neural network.
Paul, P.; Bhattacharyya, D.; Turton, R.; Zitney, S.
2012-01-01
Future integrated gasification combined cycle (IGCC) power plants with CO{sub 2} capture will face stricter operational and environmental constraints. Accurate values of relevant states/outputs/disturbances are needed to satisfy these constraints and to maximize the operational efficiency. Unfortunately, a number of these process variables cannot be measured while a number of them can be measured, but have low precision, reliability, or signal-to-noise ratio. In this work, a sensor placement (SP) algorithm is developed for optimal selection of sensor location, number, and type that can maximize the plant efficiency and result in a desired precision of the relevant measured/unmeasured states. In this work, an SP algorithm is developed for an selective, dual-stage Selexol-based acid gas removal (AGR) unit for an IGCC plant with pre-combustion CO{sub 2} capture. A comprehensive nonlinear dynamic model of the AGR unit is developed in Aspen Plus Dynamics® (APD) and used to generate a linear state-space model that is used in the SP algorithm. The SP algorithm is developed with the assumption that an optimal Kalman filter will be implemented in the plant for state and disturbance estimation. The algorithm is developed assuming steady-state Kalman filtering and steady-state operation of the plant. The control system is considered to operate based on the estimated states and thereby, captures the effects of the SP algorithm on the overall plant efficiency. The optimization problem is solved by Genetic Algorithm (GA) considering both linear and nonlinear equality and inequality constraints. Due to the very large number of candidate sets available for sensor placement and because of the long time that it takes to solve the constrained optimization problem that includes more than 1000 states, solution of this problem is computationally expensive. For reducing the computation time, parallel computing is performed using the Distributed Computing Server (DCS®) and the Parallel
Paul, P.; Bhattacharyya, D.; Turton, R.; Zitney, S.
2012-01-01
Future integrated gasification combined cycle (IGCC) power plants with CO{sub 2} capture will face stricter operational and environmental constraints. Accurate values of relevant states/outputs/disturbances are needed to satisfy these constraints and to maximize the operational efficiency. Unfortunately, a number of these process variables cannot be measured while a number of them can be measured, but have low precision, reliability, or signal-to-noise ratio. In this work, a sensor placement (SP) algorithm is developed for optimal selection of sensor location, number, and type that can maximize the plant efficiency and result in a desired precision of the relevant measured/unmeasured states. In this work, an SP algorithm is developed for an selective, dual-stage Selexol-based acid gas removal (AGR) unit for an IGCC plant with pre-combustion CO{sub 2} capture. A comprehensive nonlinear dynamic model of the AGR unit is developed in Aspen Plus Dynamics® (APD) and used to generate a linear state-space model that is used in the SP algorithm. The SP algorithm is developed with the assumption that an optimal Kalman filter will be implemented in the plant for state and disturbance estimation. The algorithm is developed assuming steady-state Kalman filtering and steady-state operation of the plant. The control system is considered to operate based on the estimated states and thereby, captures the effects of the SP algorithm on the overall plant efficiency. The optimization problem is solved by Genetic Algorithm (GA) considering both linear and nonlinear equality and inequality constraints. Due to the very large number of candidate sets available for sensor placement and because of the long time that it takes to solve the constrained optimization problem that includes more than 1000 states, solution of this problem is computationally expensive. For reducing the computation time, parallel computing is performed using the Distributed Computing Server (DCS®) and the Parallel
Chao Peng
2015-01-01
Full Text Available A frequency control approach based on wind power and load power prediction information is proposed for wind-diesel-battery hybrid power system (WDBHPS. To maintain the frequency stability by wind power and diesel generation as much as possible, a fuzzy control theory based wind and diesel power control module is designed according to wind power and load prediction information. To compensate frequency fluctuation in real time and enhance system disturbance rejection ability, a battery energy storage system real-time control module is designed based on ADRC (active disturbance rejection control. The simulation experiment results demonstrate that the proposed approach has a better disturbance rejection ability and frequency control performance compared with the traditional droop control approach.
Casillas, Jean-Marie; Joussain, Charles; Gremeaux, Vincent; Hannequin, Armelle; Rapin, Amandine; Laurent, Yves; Benaïm, Charles
2015-02-01
To develop a new predictive model of maximal heart rate based on two walking tests at different speeds (comfortable and brisk walking) as an alternative to a cardiopulmonary exercise test during cardiac rehabilitation. Evaluation of a clinical assessment tool. A Cardiac Rehabilitation Department in France. A total of 148 patients (133 men), mean age of 59 ±9 years, at the end of an outpatient cardiac rehabilitation programme. Patients successively performed a 6-minute walk test, a 200 m fast-walk test (200mFWT), and a cardiopulmonary exercise test, with measure of heart rate at the end of each test. An all-possible regression procedure was used to determine the best predictive regression models of maximal heart rate. The best model was compared with the Fox equation in term of predictive error of maximal heart rate using the paired t-test. Results of the two walking tests correlated significantly with maximal heart rate determined during the cardiopulmonary exercise test, whereas anthropometric parameters and resting heart rate did not. The simplified predictive model with the most acceptable mean error was: maximal heart rate = 130 - 0.6 × age + 0.3 × HR200mFWT (R(2) = 0.24). This model was superior to the Fox formula (R(2) = 0.138). The relationship between training target heart rate calculated from measured reserve heart rate and that established using this predictive model was statistically significant (r = 0.528, p heart rate measured during a safe simple fast walk test and age is more efficient than an equation only including age to predict maximal heart rate and training target heart rate. © The Author(s) 2014.
Short-Term Wind Power Prediction and Comprehensive Evaluation based on Multiple Methods
Zhaowei Wang
2013-12-01
Full Text Available Firstly, this study used prediction methods, including Kalman filter method, the GARCH (Generalized Autoregressive Conditional Heteroskedasticity model and the BP neural network model based on time sequence, to predict real-timely the wind power. And then, we construct indexes such as mean absolute error, root-mean-square error, accuracy rate and percent of pass to have error analysis on the predictive effect and get the best results of prediction effect that based on time sequence of the BP neural network model. Finally, we concluded the universal rule between the relative prediction error of single typhoon electric unit power of and the prediction relative error of total machine power by the analysis into lateral error indicators. And we analyze the influence on the error of the prediction result that resulting from the converge of wind generator power.
Reactive Power Impact on Lifetime Prediction of Two-level Wind Power Converter
Zhou, Dao; Blaabjerg, Frede; Lau, M.;
2013-01-01
The influence of reactive power injection on the dominating two-level wind power converter is investigated and compared in terms of power loss and thermal behavior. Then the lifetime of both the partial-scale and full-scale power converter is estimated based on the widely used Coffin-Manson model....... It is concluded that the injection of the reactive power could have serious impact on the power loss and thermal profile, especially at lower wind speed. Furthermore, the introduction of the reactive power could also shorten the lifetime of the wind power converter significantly....
Predictive Smart Grid Control with Exact Aggregated Power Constraints
Trangbæk, K; Petersen, Mette Højgaard; Bendtsen, Jan Dimon
2012-01-01
consumption, and on the other hand from natural variations in power production from e.g. wind turbines. The consumers represent energy-consuming units such as heat pumps, car batteries etc. These units obviously have limits on how much power and energy they can consume at any given time, which impose...
Gutman, Boris A.; Hua, Xue; Rajagopalan, Priya; Chou, Yi-Yu; Wang, Yalin; Yanovsky, Igor; Toga, Arthur W.; Jack, Clifford R.; Weiner, Michael W.; Thompson, Paul M.
2013-01-01
We propose a new method to maximize biomarker efficiency for detecting anatomical change over time in serial MRI. Drug trials using neuroimaging become prohibitively costly if vast numbers of subjects must be assessed, so it is vital to develop efficient measures of brain change. A popular measure of efficiency is the minimal sample size (n80) needed to detect 25% change in a biomarker, with 95% confidence and 80% power. For multivariate measures of brain change, we can directly optimize n80 based on a Linear Discriminant Analysis (LDA). Here we use a supervised learning framework to optimize n80, offering two alternative solutions. With a new medial surface modeling method, we track 3D dynamic changes in the lateral ventricles in 2065 ADNI scans. We apply our LDA-based weighting to the results. Our best average n80—in two-fold nested cross-validation—is 104 MCI subjects (95% CI: [94,139]) for a 1-year drug trial, and 75 AD subjects [64,102]. This compares favorably with other MRI analysis methods. The standard “statistical ROI” approach applied to the same ventricular surfaces requires 165 MCI or 94 AD subjects. At 2 years, the best LDA measure needs only 67 MCI and 52 AD subjects, versus 119 MCI and 80 AD subjects for the stat-ROI method. Our surface-based measures are unbiased: they give no artifactual additive atrophy over three time points. Our results suggest that statistical weighting may boost efficiency of drug trials that use brain maps. PMID:23296188
Reactive Power Impact on Lifetime Prediction of Two-level Wind Power Converter
Zhou, Dao; Blaabjerg, Frede; Lau, M.
2013-01-01
The influence of reactive power injection on the dominating two-level wind power converter is investigated and compared in terms of power loss and thermal behavior. Then the lifetime of both the partial-scale and full-scale power converter is estimated based on the widely used Coffin-Manson model...
Betavoltaic Power Prediction by using a Monte Carlo Simulation
Jung, H. K.; Lee, N. H.; Joo, Y. S.; Lee, C. W. [Korea Atomic Energy Research Institute, Taejon (Korea, Republic of)
2006-07-01
Semiconductor betavoltaic converters use energy from radioisotope sources to generate electricity for remote applications requiring a long life power. Radioisotope power sources can provide significant advantages of a high energy density and a longer life than chemical batteries. Micro-electromechanical Systems (MEMS) often require an on-board power source for a remote operation, especially in medical cases requiring an operation for more than 10 years. The betavoltaic effect shown in Figure 1 is the generation of a potential due to a net positive charge flow of an electron-induced electron-hole production (EHP). When EHP diffuse into the depletion region of the semiconductor PN-junction, the electrical field of the depletion region sweeps them across the depletion region. Because the resulting current is from an n-type to a p-type semiconductor, the net power can be extracted.
From entropy-maximization to equality-maximization: Gauss, Laplace, Pareto, and Subbotin
Eliazar, Iddo
2014-12-01
The entropy-maximization paradigm of statistical physics is well known to generate the omnipresent Gauss law. In this paper we establish an analogous socioeconomic model which maximizes social equality, rather than physical disorder, in the context of the distributions of income and wealth in human societies. We show that-on a logarithmic scale-the Laplace law is the socioeconomic equality-maximizing counterpart of the physical entropy-maximizing Gauss law, and that this law manifests an optimized balance between two opposing forces: (i) the rich and powerful, striving to amass ever more wealth, and thus to increase social inequality; and (ii) the masses, struggling to form more egalitarian societies, and thus to increase social equality. Our results lead from log-Gauss statistics to log-Laplace statistics, yield Paretian power-law tails of income and wealth distributions, and show how the emergence of a middle-class depends on the underlying levels of socioeconomic inequality and variability. Also, in the context of asset-prices with Laplace-distributed returns, our results imply that financial markets generate an optimized balance between risk and predictability.
Optimization of maintenance for power system equipment using a predictive health model
Bajracharya, G.; Koltunowicz, T.; Negenborn, R.R.; Papp, Z.; Djairam, D.; De Schutter, B.; Smit, J.J.
2009-01-01
In this paper, a model-predictive control based framework is proposed for modeling and optimization of the health state of power system equipment. In the framework, a predictive health model is proposed that predicts the health state of the equipment based on its usage and maintenance actions. Based
Prediction of Wind Energy Resources (PoWER) Users Guide
2016-01-01
used for fixed-site generators). PoWER is hosted on Apple iOS and Android (mobile device operating systems) based smartphones and tablets (referred...henceforth referred to as the “ app ”) provides information on the instantaneous electrical power and energy that can be generated by a wind generator...to from here on as the “device”). The functionality is identical between the iOS and Android device and the screen displays are similar between the 2
Modelling of physical properties - databases, uncertainties and predictive power
Gani, Rafiqul
Physical and thermodynamic property in the form of raw data or estimated values for pure compounds and mixtures are important pre-requisites for performing tasks such as, process design, simulation and optimization; computer aided molecular/mixture (product) design; and, product-process analysis...... connectivity approach. The development of these models requires measured property data and based on them, the regression of model parameters is performed. Although this class of models is empirical by nature, they do allow extrapolation from the regressed model parameters to predict properties of chemicals...... not included in the measured data-set. Therefore, they are also considered as predictive models. The paper will highlight different issues/challenges related to the role of the databases and the mathematical and thermodynamic consistency of the measured/estimated data, the predictive nature of the developed...
The predictive power of zero intelligence in financial markets
Doyne Farmer, J.; Patelli, Paolo; Zovko, Ilija I.
2005-02-01
Standard models in economics stress the role of intelligent agents who maximize utility. However, there may be situations where constraints imposed by market institutions dominate strategic agent behavior. We use data from the London Stock Exchange to test a simple model in which minimally intelligent agents place orders to trade at random. The model treats the statistical mechanics of order placement, price formation, and the accumulation of revealed supply and demand within the context of the continuous double auction and yields simple laws relating order-arrival rates to statistical properties of the market. We test the validity of these laws in explaining cross-sectional variation for 11 stocks. The model explains 96% of the variance of the gap between the best buying and selling prices (the spread) and 76% of the variance of the price diffusion rate, with only one free parameter. We also study the market impact function, describing the response of quoted prices to the arrival of new orders. The nondimensional coordinates dictated by the model approximately collapse data from different stocks onto a single curve. This work is important from a practical point of view, because it demonstrates the existence of simple laws relating prices to order flows and, in a broader context, suggests there are circumstances where the strategic behavior of agents may be dominated by other considerations. double auction market | market microstructure | agent-based models
D. Thirumalaikumarasamy
2017-03-01
Full Text Available Like other manufacturing techniques, plasma spraying has also a non-linear behavior because of the contribution of many coating variables. This characteristic results in finding optimal factor combination difficult. Subsequently, the issue can be solved through effective and strategic statistical procedures integrated with systematic experimental data. Plasma spray parameters such as power, stand-off distance and powder feed rate have significant influence on coating characteristics like Young's modulus. This paper presents the use of statistical techniques in specifically response surface methodology (RSM, analysis of variance, and regression analysis to develop empirical relationship to predict Young's modulus of plasma-sprayed alumina coatings. The developed empirical relationships can be effectively used to predict Young's modulus of plasma-sprayed alumina coatings at 95% confidence level. Response graphs and contour plots were constructed to identify the optimum plasma spray parameters to attain maximum Young's modulus in alumina coatings. A linear regression relationship was established between porosity and Young's modulus of the alumina coatings.
Sludge pipe flow pressure drop prediction using composite power ...
2011-09-30
Sep 30, 2011 ... pressure drop predictions in pipelines using different rheologi- cal models. This paper .... mines the curvature of the deviation from F1. The product of c and d ..... testing of a portable tube viscometer and pump rig. Proc. 18th.
Maximizing and customer loyalty: Are maximizers less loyal?
Linda Lai
2011-06-01
Full Text Available Despite their efforts to choose the best of all available solutions, maximizers seem to be more inclined than satisficers to regret their choices and to experience post-decisional dissonance. Maximizers may therefore be expected to change their decisions more frequently and hence exhibit lower customer loyalty to providers of products and services compared to satisficers. Findings from the study reported here (N = 1978 support this prediction. Maximizers reported significantly higher intentions to switch to another service provider (television provider than satisficers. Maximizers' intentions to switch appear to be intensified and mediated by higher proneness to regret, increased desire to discuss relevant choices with others, higher levels of perceived knowledge of alternatives, and higher ego involvement in the end product, compared to satisficers. Opportunities for future research are suggested.
Are maximizers really unhappy? The measurement of maximizing tendency,
Dalia L. Diab
2008-06-01
Full Text Available Recent research suggesting that people who maximize are less happy than those who satisfice has received considerable fanfare. The current study investigates whether this conclusion reflects the construct itself or rather how it is measured. We developed an alternative measure of maximizing tendency that is theory-based, has good psychometric properties, and predicts behavioral outcomes. In contrast to the existing maximization measure, our new measure did not correlate with life (dissatisfaction, nor with most maladaptive personality and decision-making traits. We conclude that the interpretation of maximizers as unhappy may be due to poor measurement of the construct. We present a more reliable and valid measure for future researchers to use.
Basic study on dynamic reactive-power control method with PV output prediction for solar inverter
Ryunosuke Miyoshi
2016-01-01
Full Text Available To effectively utilize a photovoltaic (PV system, reactive-power control methods for solar inverters have been considered. Among the various methods, the constant-voltage control outputs less reactive power compared with the other methods. We have developed a constant-voltage control to reduce the reactive-power output. However, the developed constant-voltage control still outputs unnecessary reactive power because the control parameter is constant in every waveform of the PV output. To reduce the reactive-power output, we propose a dynamic reactive-power control method with a PV output prediction. In the proposed method, the control parameter is varied according to the properties of the predicted PV waveform. In this study, we performed numerical simulations using a distribution system model, and we confirmed that the proposed method reduces the reactive-power output within the voltage constraint.
Laura Burattini
2013-01-01
Full Text Available The power of exercise-induced T-wave alternans (TWA to predict the occurrence of ventricular arrhythmias was evaluated in 67 patients with an implanted cardiac defibrillator (ICD. During the 4-year follow-up, electrocardiographic (ECG tracings were recorded in a bicycle ergometer test with increasing workload ranging from zero (NoWL to the patient's maximal capacity (MaxWL. After the follow-up, patients were classified as either ICD_Cases (n = 29, if developed ventricular tachycardia/fibrillation, or ICD_Controls (n = 38. TWA was quantified using our heart-rate adaptive match filter. Compared to NoWL, MaxWL was characterized by faster heart rates and higher TWA in both ICD_Cases (12-18 μ V vs. 20-39 μ V; P < 0.05 and ICD_Controls (9-15 μ V vs. 20-32 μ V; P < 0.05. Still, TWA was able to discriminate the two ICD groups during NoWL (sensitivity = 59-83%, specificity = 53-84% but not MaxWL (sensitivity = 55-69%, specificity = 39-74%. Thus, this retrospective observational case-control study suggests that TWA's predictive power for the occurrence of ventricular arrhythmias could increase at low heart rates.
Sullivan, C S; Casaburi, R; Storer, T W; Wasserman, K
1995-01-01
We determined the ability of gas exchange analyses during incremental exercise tests (IXT) to predict blood lactate levels associated with a range of constant power output cycle ergometer tests. Twenty-seven healthy young men performed duplicate IXT and four 15-min constant power output tests at intensities ranging from moderate to very severe, before and after a training program. End-exercise blood lactate levels were approximated from superficial venous samples obtained 60 s after each constant power output test. From IXT, the power outputs corresponding to peak oxygen uptake (Wmax) and lactic acidosis threshold (WLAT), were determined. We examined the ability of four measures of exercise intensity to predict blood lactate levels for power outputs above the LAT: (1) power output (W), (2) power difference (W-WLAT), (3) power fraction (W/Wmax) and (4) power difference to delta ratio [(W-WLAT)/(Wmax-WLAT)]. Correlation coefficients were r = 0.38, 0.69, 0.75, and 0.81, respectively. The best linear regression prediction equation was: lactate (mmol.l-1) = 12.2[(W-WLAT)/(Wmax-WLAT)] + 0.7 mmol.l-1. This relationship was not significantly affected by training, despite increased values of LAT and peak oxygen uptake. Normalizing exercise intensity to the range of power outputs between WLAT and Wmax provided an estimate of blood lactate response to constant power outputs with a standard error of the estimate of 1.66 mmol.l-1.
Dobra, R.; Pasculescu, D.; Risteiu, M.; Buica, G.; Jevremović, V.
2017-06-01
This paper describe some possibilities to minimize voltages switching-off risks from the mining power networks, in case of insulated resistance faults by using a predictive diagnose method. The cables from the neutral insulated power networks (underground mining) are designed to provide a flexible electrical connection between portable or mobile equipment and a point of supply, including main feeder cable for continuous miners, pump cable, and power supply cable. An electronic protection for insulated resistance of mining power cables can be made using this predictive strategy. The main role of electronic relays for insulation resistance degradation of the electrical power cables, from neutral insulated power networks, is to provide a permanent measurement of the insulated resistance between phases and ground, in order to switch-off voltage when the resistance value is below a standard value. The automat system of protection is able to signalize the failure and the human operator will be early informed about the switch-off power and will have time to take proper measures to fix the failure. This logic for fast and automat switch-off voltage without aprioristic announcement is suitable for the electrical installations, realizing so a protection against fires and explosion. It is presented an algorithm and an anticipative relay for insulated resistance control from three-phase low voltage installations with insulated neutral connection.
Modelling of physical properties - databases, uncertainties and predictive power
Gani, Rafiqul
Physical and thermodynamic property in the form of raw data or estimated values for pure compounds and mixtures are important pre-requisites for performing tasks such as, process design, simulation and optimization; computer aided molecular/mixture (product) design; and, product-process analysis....... While use of experimentally measured values of the needed properties is desirable in these tasks, the experimental data of the properties of interest may not be available or may not be measurable in many cases. Therefore, property models that are reliable, predictive and easy to use are necessary....... However, which models should be used to provide the reliable estimates of the required properties? And, how much measured data is necessary to regress the model parameters? How to ensure predictive capabilities in the developed models? Also, as it is necessary to know the associated uncertainties...
Profit maximization mitigates competition
Dierker, Egbert; Grodal, Birgit
1996-01-01
We consider oligopolistic markets in which the notion of shareholders' utility is well-defined and compare the Bertrand-Nash equilibria in case of utility maximization with those under the usual profit maximization hypothesis. Our main result states that profit maximization leads to less price...... competition than utility maximization. Since profit maximization tends to raise prices, it may be regarded as beneficial for the owners as a whole. Moreover, if profit maximization is a good proxy for utility maximization, then there is no need for a general equilibrium analysis that takes the distribution...... of profits among consumers fully into account and partial equilibrium analysis suffices...
Tallis, J; James, R S; Cox, V M; Duncan, M J
2017-01-01
Caffeine is a well-established performance enhancing nutritional supplement in a young healthy population, however far less is known about how its ergogenicity is affected by increasing age. A recent review has highlighted the value of studies examining the direct effect of caffeine on isolated skeletal muscle contractility, but the present work is the first to assess the direct effect of 70µM caffeine (physiological maximum) on the maximal power output of isolated mammalian muscle from an age range representing developmental to early ageing. Female CD1 mice were aged to 3, 10, 30 and 50 weeks (n = 20 in each case) and either whole EDL or a section of the diaphragm was isolated and maximal power output determined using the work loop technique. Once contractile performance was maximised, each muscle preparation was treated with 70µM caffeine and its contractile performance was measured for a further 60 minutes. In both mouse EDL and diaphragm 70µM caffeine treatment resulted in a significant increase in maximal muscle power output that was greatest at 10 or 30 weeks (up to 5% and 6% improvement respectively). This potentiation of maximal muscle power output was significantly lower at the early ageing time point, 50 weeks (up to 3% and 2% improvement respectively), and in mice in the developmental stage, at 3 weeks of age (up to 1% and 2% improvement respectively). Uniquely, the present findings indicate a reduced age specific sensitivity to the performance enhancing effect of caffeine in developmental and aged mice which is likely to be attributed to age related muscle growth and degradation, respectively. Importantly, the findings indicate that caffeine may still provide a substantial ergogenic aid in older populations which could prove important for improving functional capacity in tasks of daily living.
Kalsen, Anders; Hostrup, Morten; Backer, Vibeke
2016-01-01
L min(-1) kg(-1)) performed a 30-s cycle ergometer sprint after inhalation of either 54 µg formoterol (FOR) or placebo (PLA). Before and after the sprint, muscle biopsies were collected from vastus lateralis and maximal voluntary contraction (MVC) and contractile properties of quadriceps were measured...
Research on power grid loss prediction model based on Granger causality property of time series
Wang, J. [North China Electric Power Univ., Beijing (China); State Grid Corp., Beijing (China); Yan, W.P.; Yuan, J. [North China Electric Power Univ., Beijing (China); Xu, H.M.; Wang, X.L. [State Grid Information and Telecommunications Corp., Beijing (China)
2009-03-11
This paper described a method of predicting power transmission line losses using the Granger causality property of time series. The stable property of the time series was investigated using unit root tests. The Granger causality relationship between line losses and other variables was then determined. Granger-caused time series were then used to create the following 3 prediction models: (1) a model based on line loss binomials that used electricity sales to predict variables, (2) a model that considered both power sales and grid capacity, and (3) a model based on autoregressive distributed lag (ARDL) approaches that incorporated both power sales and the square of power sales as variables. A case study of data from China's electric power grid between 1980 and 2008 was used to evaluate model performance. Results of the study showed that the model error rates ranged between 2.7 and 3.9 percent. 6 refs., 3 tabs., 1 fig.
M. Marocolo
2007-02-01
Full Text Available Increased heart rate variability (HRV and high-frequency content of the terminal region of the ventricular activation of signal-averaged ECG (SAECG have been reported in athletes. The present study investigates HRV and SAECG parameters as predictors of maximal aerobic power (VO2max in athletes. HRV, SAECG and VO2max were determined in 18 high-performance long-distance (25 ± 6 years; 17 males runners 24 h after a training session. Clinical visits, ECG and VO2max determination were scheduled for all athletes during thew training period. A group of 18 untrained healthy volunteers matched for age, gender, and body surface area was included as controls. SAECG was acquired in the resting supine position for 15 min and processed to extract average RR interval (Mean-RR and root mean squared standard deviation (RMSSD of the difference of two consecutive normal RR intervals. SAECG variables analyzed in the vector magnitude with 40-250 Hz band-pass bi-directional filtering were: total and 40-µV terminal (LAS40 duration of ventricular activation, RMS voltage of total (RMST and of the 40-ms terminal region of ventricular activation. Linear and multivariate stepwise logistic regressions oriented by inter-group comparisons were adjusted in significant variables in order to predict VO2max, with a P < 0.05 considered to be significant. VO2max correlated significantly (P < 0.05 with RMST (r = 0.77, Mean-RR (r = 0.62, RMSSD (r = 0.47, and LAS40 (r = -0.39. RMST was the independent predictor of VO2max. In athletes, HRV and high-frequency components of the SAECG correlate with VO2max and the high-frequency content of SAECG is an independent predictor of VO2max.
Human hippocampal increases in low-frequency power during associative prediction violations.
Chen, Janice; Dastjerdi, Mohammad; Foster, Brett L; LaRocque, Karen F; Rauschecker, Andreas M; Parvizi, Josef; Wagner, Anthony D
2013-10-01
Environmental cues often trigger memories of past events (associative retrieval), and these memories are a form of prediction about imminent experience. Learning is driven by the detection of prediction violations, when the past and present diverge. Using intracranial electroencephalography (iEEG), we show that associative prediction violations elicit increased low-frequency power (in the slow-theta range) in human hippocampus, that this low-frequency power increase is modulated by whether conditions allow predictions to be generated, that the increase rapidly onsets after the moment of violation, and that changes in low-frequency power are not present in adjacent perirhinal cortex. These data suggest that associative mismatch is computed within hippocampus when cues trigger predictions that are violated by imminent experience.
Chaos in Switching Converters for Power Management Designing for Prediction and Control
Rodríguez Vilamitjana, Enric; Alarcón, Eduard
2013-01-01
This book addresses the need for models and techniques to predict stability boundaries, given trends toward miniaturization of switching power supplies in battery-operated portable devices, which lead to the exhibition of fast-scale chaotic instabilities. The authors describe a method to predict stability boundaries from a design-oriented perspective, which captures the effect of the different parameters of the system upon the particular boundary. Unlike previous methods involving complex analysis based on the discrete-time mathematical model, the method introduced here allows for prediction of the overall stability boundaries within the complete design space and is based upon a simple design-oriented index. Provides a valuable reference to the field of nonlinear dynamical behavior and bifurcation analysis and control of switch-mode power supplies. Shows limitations of existing models for predicting chaotic instabilities in switching power converters; Describes a new approach to predict instabilities fr...
THE PREDICTIVE POWER OF RELIGIOUS ORIENTATION TYPES ON AMBIVALENT SEXISM
Fatih Ozdemir
2016-07-01
Full Text Available The purpose of the present study was to predict ambivalent sexism (including hostile sexism and benevolent sexism with religious orientation types as intrinsic religiosity, extrinsic religiosity and quest religiosity. In addition, the effect of demographic variables (including age, gender, education on sexist attitudes was tested. 583 (N_female= 318; N_male= 265 university students who study in different universities of Ankara/Turkey (M_age= 22.10; SD = 2.33 completed Ambivalent Sexism Inventory, and Religious Orientation Scale. Findings indicated significant gender differences on study variables and significant associations between ambivalent sexism and religious orientation types within university students sample in Turkey.
The predictive power of Japanese candlestick charting in Chinese stock market
Chen, Shi; Bao, Si; Zhou, Yu
2016-09-01
This paper studies the predictive power of 4 popular pairs of two-day bullish and bearish Japanese candlestick patterns in Chinese stock market. Based on Morris' study, we give the quantitative details of definition of long candlestick, which is important in two-day candlestick pattern recognition but ignored by several previous researches, and we further give the quantitative definitions of these four pairs of two-day candlestick patterns. To test the predictive power of candlestick patterns on short-term price movement, we propose the definition of daily average return to alleviate the impact of correlation among stocks' overlap-time returns in statistical tests. To show the robustness of our result, two methods of trend definition are used for both the medium-market-value and large-market-value sample sets. We use Step-SPA test to correct for data snooping bias. Statistical results show that the predictive power differs from pattern to pattern, three of the eight patterns provide both short-term and relatively long-term prediction, another one pair only provide significant forecasting power within very short-term period, while the rest three patterns present contradictory results for different market value groups. For all the four pairs, the predictive power drops as predicting time increases, and forecasting power is stronger for stocks with medium market value than those with large market value.
Blickle, Gerhard; Witzki, Alexander H.; Schneider, Paula B.
2009-01-01
Career success of early employees was analyzed from a power perspective and a developmental network perspective. In a predictive field study with 112 employees mentoring support and mentors' power were assessed in the first wave, employees' networking was assessed after two years, and career success (i.e. income and hierarchical position) and…
Distributed Model Predictive Control for Active Power Control of Wind Farm
Zhao, Haoran; Wu, Qiuwei; Rasmussen, Claus Nygaard;
2014-01-01
This paper presents the active power control of a wind farm using the Distributed Model Predictive Controller (D- MPC) via dual decomposition. Different from the conventional centralized wind farm control, multiple objectives such as power reference tracking performance and wind turbine load can......-scale wind farm control....
Critical assessment of indoor noise propagation and prediction in power plants
Brittain, Frank H.
2005-09-01
Accurate prediction of indoor noise propagation in power plants is important to help estimate occupational noise exposures, and to help predict community noise radiated by plant walls-from levels predicted just inside of each wall. Unfortunately, the basic theories of room acoustics are not applicable. Most power plant rooms are both too large, and too odd shaped for basic room theory, including the Sabine and Norris-Erying theories, to be applicable. Even more important, basic room theory requires empty rooms, and power plant spaces are densely packed with equipment, piping, cable trays, etc. (called fittings). This paper reviews basic room theory, and outlines deficiencies for use in predicting noise propagation inside power plant buildings. Examples are given of walk-away measurements showing that there is no reverberant field, and that reverberation measurements do not correlate well with walk-away test data. Using measurements as an alternative to levels predicted just inside of plant walls to help predict community noise radiated by each wall are discussed. Software for predicting noise in industrial spaces is identified, and their suitability for power plants, which have unusually high fitting densities, is also discussed.
Stanton, Kasey; Rozek, David C; Stasik-O'Brien, Sara M; Ellickson-Larew, Stephanie; Watson, David
2016-10-01
Although personality and emotion regulation abilities appear to overlap considerably, few studies have adopted an integrative approach by examining personality and emotion regulation together. Therefore, it is unclear how much incremental power emotion regulation demonstrates in predicting psychopathology beyond personality traits, and vice versa. Results from a community sample characterized by high levels of psychopathology (N = 299) indicated that personality and emotion regulation represent strongly related but distinguishable constructs, with both showing incremental power beyond the other in many cases in predicting self-reported and interview-rated psychopathology. More specifically, difficulties in responding adaptively to negative emotional experiences displayed predictive power beyond neuroticism and other personality traits in predicting internalizing psychopathology and psychoticism. Conversely, neuroticism displayed substantial incremental predictive power beyond emotion regulation and other five-factor model traits, especially for anxiety and other internalizing psychopathology. Other five-factor model traits also showed incremental predictive power in specific cases (e.g., agreeableness and conscientiousness showed specificity in predicting antagonism and disinhibition, respectively). These data provide a starting point for developing a finer-grained understanding of how emotion dysregulation and personality traits are implicated in a range of psychopathology, highlighting the value of adopting an integrative approach of examining emotion regulation and personality traits concurrently. (PsycINFO Database Record (c) 2016 APA, all rights reserved).
The prediction and prevention of voltage collapse in the Finnish power system
Bastman, J.; Lakervi, E. [Tampere Univ. of Tech. (Finland); Hirvonen, R.; Kuronen, P.; Hagman, E. [IVO Group (Finland)
1994-12-31
The Finnish power system is a part of the Nordic power system (NORDEL), which includes Finland, Sweden, Norway and the eastern part of Denmark. In NORDEL the transmission distances are long, which implies that the power transmission capacities are determined by stability criteria . The methods to prevent and predict the voltage collapse during severe disturbances are studied using advances simulation program. Results are presented. (author) 10 figs., 1 tab.
Statistical Power Supply Dynamic Noise Prediction in Hierarchical Power Grid and Package Networks
Piccinini, Gianluca; Graziano, Mariagrazia
2008-01-01
One of the most crucial high performance systems-on-chip design challenge is to front their power supply noise sufferance due to high frequencies, huge number of functional blocks and technology scaling down. Marking a difference from traditional post physical-design static voltage drop analysis, /a priori dynamic voltage drop/evaluation is the focus of this work. It takes into account transient currents and on-chip and package /RLC/ parasitics while exploring the power grid design solution s...
MODEL PREDICTIVE CONTROL FOR PHOTOVOLTAIC STATION MAXIMUM POWER POINT TRACKING SYSTEM
I. Elzein
2015-01-01
Full Text Available The purpose of this paper is to present an alternative maximum power point tracking, MPPT, algorithm for a photovoltaic module, PVM, to produce the maximum power, Pmax, using the optimal duty ratio, D, for different types of converters and load matching.We present a state-based approach to the design of the maximum power point tracker for a stand-alone photovoltaic power generation system. The system under consideration consists of a solar array with nonlinear time-varying characteristics, a step-up converter with appropriate filter.The proposed algorithm has the advantages of maximizing the efficiency of the power utilization, can be integrated to other MPPT algorithms without affecting the PVM performance, is excellent for Real-Time applications and is a robust analytical method, different from the traditional MPPT algorithms which are more based on trial and error, or comparisons between present and past states. The procedure to calculate the optimal duty ratio for a buck, boost and buck-boost converters, to transfer the maximum power from a PVM to a load, is presented in the paper. Additionally, the existence and uniqueness of optimal internal impedance, to transfer the maximum power from a photovoltaic module using load matching, is proved.
Rajkumar, V. [ABB Transmission Technology Institute, Raleigh, NC (United States); Mohler, R.R. [Oregon State Univ., Corvallis, OR (United States)
1994-12-31
This paper presents a framework for the development of discrete-time, nonlinear predictive controllers using thyristor-controlled-series-capacitors and phasor measurements of bus voltage magnitude and angle, for the stabilization and rapid damping of multimachine power systems which are subjected to large disturbances. When the faults of concern are large, the nonlinear predictive controllers are used to return the power system state to a small region about the post-fault equilibrium. In this region, linear controllers provide local asymptotic stability and rapid damping. Simulation results are provided on a sample four-machine power system.
Prediction of Full-Scale Propulsion Power using Artificial Neural Networks
Pedersen, Benjamin Pjedsted; Larsen, Jan
2009-01-01
Full scale measurements of the propulsion power, ship speed, wind speed and direction, sea and air temperature from four different loading conditions, together with hind cast data of wind and sea properties; and noon report data has been used to train an Artificial Neural Network for prediction...... of propulsion power. The model was optimized using a double cross validation procedure. The network was able to predict the propulsion power with accuracy between 0.8-1.7% using onboard measurement system data and 7% from manually acquired noon reports....
Prediction of Full-Scale Propulsion Power using Artificial Neural Networks
Pedersen, Benjamin Pjedsted; Larsen, Jan
2009-01-01
Full scale measurements of the propulsion power, ship speed, wind speed and direction, sea and air temperature from four different loading conditions, together with hind cast data of wind and sea properties; and noon report data has been used to train an Artificial Neural Network for prediction...... of propulsion power. The model was optimized using a double cross validation procedure. The network was able to predict the propulsion power with accuracy between 0.8-1.7% using onboard measurement system data and 7% from manually acquired noon reports....
Synchrophasor-Assisted Prediction of Stability/Instability of a Power System
Saha Roy, Biman Kumar; Sinha, Avinash Kumar; Pradhan, Ashok Kumar
2013-05-01
This paper presents a technique for real-time prediction of stability/instability of a power system based on synchrophasor measurements obtained from phasor measurement units (PMUs) at generator buses. For stability assessment the technique makes use of system severity indices developed using bus voltage magnitude obtained from PMUs and generator electrical power. Generator power is computed using system information and PMU information like voltage and current phasors obtained from PMU. System stability/instability is predicted when the indices exceeds a threshold value. A case study is carried out on New England 10-generator, 39-bus system to validate the performance of the technique.
Najac, Julien
2014-05-01
For many applications in the energy sector, it is crucial to dispose of downscaling methods that enable to conserve space-time dependences at very fine spatial and temporal scales between variables affecting electricity production and consumption. For climate change impact studies, this is an extremely difficult task, particularly as reliable climate information is usually found at regional and monthly scales at best, although many industry oriented applications need further refined information (hydropower production model, wind energy production model, power demand model, power balance model…). Here we thus propose to investigate the question of how to predict and quantify the influence of climate change on climate-related energies and the energy demand. To do so, statistical downscaling methods originally developed for studying climate change impacts on hydrological cycles in France (and which have been used to compute hydropower production in France), have been applied for predicting wind power generation in France and an air temperature indicator commonly used for predicting power demand in France. We show that those methods provide satisfactory results over the recent past and apply this methodology to several climate model runs from the ENSEMBLES project.
Yamamoto, Shigehiro; Sumi, Kazuyoshi; Nishikawa, Eiichi; Hashimoto, Takeshi
This paper describes a novel operating method using prediction of photovoltaic (PV) power for a photovoltaic-diesel hybrid power generation system. The system is composed of a PV array, a storage battery, a bi-directional inverter and a diesel engine generator (DG). The proposed method enables the system to save fuel consumption by using PV energy effectively, reducing charge and discharge energy of the storage battery, and avoiding low-load operation of the DG. The PV power is simply predicted from a theoretical equation of solar radiation and the observed PV energy for a constant time before the prediction. The amount of fuel consumption of the proposed method is compared with that of other methods by a simulation based on measurement data of the PV power at an actual PV generation system for one year. The simulation results indicate that the amount of fuel consumption of the proposed method is smaller than that of any other methods, and is close to that of the ideal operation of the DG.
THE PREDICTIVE POWER OF RELIGIOUS ORIENTATION TYPES ON AMBIVALENT SEXISM
Gul Ulubayram
2016-07-01
Full Text Available Objective: The purpose of this study is to examine stress and stress related factors in tuberculosis patients. In addition, to determine the impact of socio-demographic variables such as age, gender and educational level over stress symptoms hereby comprises a further objective of this study. Method: The study included totally 129 tuberculosis patients and 161 non-patients (normal group participants. Tuberculosis patients registered in Ankara Tuberculosis Dispensary No.4, and Atatürk Chest Diseases and Chest Surgery Hospital. There are 75 Pulmonary Tuberculosis (AC TB and 54 Extra- Pulmonary Tuberculosis (AD TB patients. As regards data collection tools; Demographic Information Form, Brief Symptom Inventory, Stress Symptoms Scale, Stress Vulnerability Scale, and Stress Coping Scale were used. Results: Within the context of diagnosis groups; it was found that; stress symptoms of tuberculosis patients are higher than the normal group, they use their ineffective coping ways more and their life satisfactions are lower. There exists no gender and diagnosis group main effect in terms of the psychological symptoms of stress, however “gender x diagnosis group” interaction effect draws attention herein. In tuberculosis patients, ineffective coping the stress and relation pleasure variables are confronted as joint variables which are predicting both the psychological and physical health. Another point which draws attention in regression analyzes is that; “education” variable takes place among the variables which predict the psychological symptoms of stress in tuberculosis patients. Conclusion: Under the light of these findings, tuberculosis patients, during their treatment processes, may be encouraged to attend various training programs prepared for stress management and effective dealing strategies with stress. By increasing the patients’ motivation towards the treatment, these programs may provide supplementary benefits to the treatment by
Determination of Aerobic Power Through a Specific Test for Taekwondo - A Predictive Equation Model.
Rocha, Fernando P S; Louro, Hugo; Matias, Ricardo; Brito, João; Costa, Aldo M
2016-12-01
Our aim was to verify the concurrent validity of a maximal taekwondo specific test (TST) to predict VO2max through an explanatory model. Seventeen elite male taekwondo athletes (age: 17.59 ± 4.34 years; body height: 1.72 ± 6.5 m; body mass: 61.3 ± 8.7 kg) performed two graded maximal exercise tests on different days: a 20 m multistage shuttle run test (SRT) and an incremental TST. We recorded test time, VO2max, ventilation, a heart rate and time to exhaustion. Significant differences were found between observed and estimated VO2max values [F (2, 16) = 5.77, p taekwondo TST (r = 0.74, p = 0.001). Our results suggest that an incremental specific test estimates VO2max of elite taekwondo athletes with acceptable concurrent validity.
ESB-Based Sensor Web Integration for the Prediction of Electric Power Supply System Vulnerability
Stoimenov, Leonid; Bogdanovic, Milos; Bogdanovic-Dinic, Sanja
2013-01-01
Electric power supply companies increasingly rely on enterprise IT systems to provide them with a comprehensive view of the state of the distribution network. Within a utility-wide network, enterprise IT systems collect data from various metering devices. Such data can be effectively used for the prediction of power supply network vulnerability. The purpose of this paper is to present the Enterprise Service Bus (ESB)-based Sensor Web integration solution that we have developed with the purpose of enabling prediction of power supply network vulnerability, in terms of a prediction of defect probability for a particular network element. We will give an example of its usage and demonstrate our vulnerability prediction model on data collected from two different power supply companies. The proposed solution is an extension of the GinisSense Sensor Web-based architecture for collecting, processing, analyzing, decision making and alerting based on the data received from heterogeneous data sources. In this case, GinisSense has been upgraded to be capable of operating in an ESB environment and combine Sensor Web and GIS technologies to enable prediction of electric power supply system vulnerability. Aside from electrical values, the proposed solution gathers ambient values from additional sensors installed in the existing power supply network infrastructure. GinisSense aggregates gathered data according to an adapted Omnibus data fusion model and applies decision-making logic on the aggregated data. Detected vulnerabilities are visualized to end-users through means of a specialized Web GIS application. PMID:23955435
Ultra-Short-Term Wind Power Prediction Using a Hybrid Model
Mohammed, E.; Wang, S.; Yu, J.
2017-05-01
This paper aims to develop and apply a hybrid model of two data analytical methods, multiple linear regressions and least square (MLR&LS), for ultra-short-term wind power prediction (WPP), for example taking, Northeast China electricity demand. The data was obtained from the historical records of wind power from an offshore region, and from a wind farm of the wind power plant in the areas. The WPP achieved in two stages: first, the ratios of wind power were forecasted using the proposed hybrid method, and then the transformation of these ratios of wind power to obtain forecasted values. The hybrid model combines the persistence methods, MLR and LS. The proposed method included two prediction types, multi-point prediction and single-point prediction. WPP is tested by applying different models such as autoregressive moving average (ARMA), autoregressive integrated moving average (ARIMA) and artificial neural network (ANN). By comparing results of the above models, the validity of the proposed hybrid model is confirmed in terms of error and correlation coefficient. Comparison of results confirmed that the proposed method works effectively. Additional, forecasting errors were also computed and compared, to improve understanding of how to depict highly variable WPP and the correlations between actual and predicted wind power.
ESB-Based Sensor Web Integration for the Prediction of Electric Power Supply System Vulnerability
Milos Bogdanovic
2013-08-01
Full Text Available Electric power supply companies increasingly rely on enterprise IT systems to provide them with a comprehensive view of the state of the distribution network. Within a utility-wide network, enterprise IT systems collect data from various metering devices. Such data can be effectively used for the prediction of power supply network vulnerability. The purpose of this paper is to present the Enterprise Service Bus (ESB-based Sensor Web integration solution that we have developed with the purpose of enabling prediction of power supply network vulnerability, in terms of a prediction of defect probability for a particular network element. We will give an example of its usage and demonstrate our vulnerability prediction model on data collected from two different power supply companies. The proposed solution is an extension of the GinisSense Sensor Web-based architecture for collecting, processing, analyzing, decision making and alerting based on the data received from heterogeneous data sources. In this case, GinisSense has been upgraded to be capable of operating in an ESB environment and combine Sensor Web and GIS technologies to enable prediction of electric power supply system vulnerability. Aside from electrical values, the proposed solution gathers ambient values from additional sensors installed in the existing power supply network infrastructure. GinisSense aggregates gathered data according to an adapted Omnibus data fusion model and applies decision-making logic on the aggregated data. Detected vulnerabilities are visualized to end-users through means of a specialized Web GIS application.
ESB-based Sensor Web integration for the prediction of electric power supply system vulnerability.
Stoimenov, Leonid; Bogdanovic, Milos; Bogdanovic-Dinic, Sanja
2013-08-15
Electric power supply companies increasingly rely on enterprise IT systems to provide them with a comprehensive view of the state of the distribution network. Within a utility-wide network, enterprise IT systems collect data from various metering devices. Such data can be effectively used for the prediction of power supply network vulnerability. The purpose of this paper is to present the Enterprise Service Bus (ESB)-based Sensor Web integration solution that we have developed with the purpose of enabling prediction of power supply network vulnerability, in terms of a prediction of defect probability for a particular network element. We will give an example of its usage and demonstrate our vulnerability prediction model on data collected from two different power supply companies. The proposed solution is an extension of the GinisSense Sensor Web-based architecture for collecting, processing, analyzing, decision making and alerting based on the data received from heterogeneous data sources. In this case, GinisSense has been upgraded to be capable of operating in an ESB environment and combine Sensor Web and GIS technologies to enable prediction of electric power supply system vulnerability. Aside from electrical values, the proposed solution gathers ambient values from additional sensors installed in the existing power supply network infrastructure. GinisSense aggregates gathered data according to an adapted Omnibus data fusion model and applies decision-making logic on the aggregated data. Detected vulnerabilities are visualized to end-users through means of a specialized Web GIS application.
Smoothing of wind farm output power using prediction based flywheel energy storage system
Islam, Farzana
Being socially beneficial, economically competitive and environment friendly, wind energy is now considered to be the world's fastest growing renewable energy source. However, the stochastic nature of wind imposes a considerable challenge in the optimal management and operation of wind power system. Wind speed prediction is critical for wind energy conversion system since it greatly influences the issues related to effective energy management, dynamic control of wind turbine, and improvement of the overall efficiency of the power generation system. This thesis focuses on integration of energy storage system with wind farm, considering wind speed prediction in the control scheme to overcome the problems associated with wind power fluctuations. In this thesis, flywheel energy storage system (FESS) with adjustable speed rotary machine has been considered for smoothing of output power in a wind farm composed of a fixed speed wind turbine generator (FSWTG). Since FESS has both active and reactive power compensation ability, it enhances the stability of the system effectively. An efficient energy management system combined with supervisory control unit (SCU) for FESS and wind speed prediction has been developed to improve the smoothing of the wind farm output effectively. Wind speed prediction model is developed by artificial neural network (ANN) which has advantages over the conventional prediction scheme including data error tolerance and ease in adaptability. The model for prediction with ANN is developed in MATLAB/Simulink and interfaced with PSCAD/EMTDC. Effectiveness of the proposed control system is illustrated using real wind speed data in various operating conditions.
Lifetime prediction of high-power press-pack IGBTs in wind power applications
Busca, Cristian
and decoupling of the generator and grid sides. Press-Pack (PP) Insulated Gate Bipolar Transistors (IGBTs) are promising semiconductor devices for the next generation large WTs due to the advantages they offer in terms of power capability, power density and thermal cycling capability. PP IGBTs require proper...... the balancing effect of the temperature dependent on-state characteristics of the Si chips. Next, the number and magnitude of the thermal cycles from the temperature curves are extracted by using the rain-flow counting algorithm. In the end, the chip-level lifetimes are calculated based on the accelerated test...
Nonlinear continuous-time generalized predictive control of solar power plant
Khoukhi Billal
2015-01-01
Full Text Available This paper presents an application of nonlinear continuous-time generalized predictive control (GPC to the distributed collector field of a solar power plant. The major characteristic of a solar power plant is that the primary energy source, solar radiation, cannot be manipulated. Solar radiation varies throughout the day, causing changes in plant dynamics and strong perturbations in the process. A brief description of the solar power plant and its simulator is given. After that, basic concepts of predictive control and continuous-time generalized predictive control are introduced. A new control strategy, named nonlinear continuous-time generalized predictive control (NCGPC, is then derived to control the process. The simulation results show that the NCGPC gives a greater flexibility to achieve performance goals and better perturbation rejection than classical control.
Qihong Chen
2014-01-01
Full Text Available This paper presents a neural network predictive control strategy to optimize power distribution for a fuel cell/ultracapacitor hybrid power system of a robot. We model the nonlinear power system by employing time variant auto-regressive moving average with exogenous (ARMAX, and using recurrent neural network to represent the complicated coefficients of the ARMAX model. Because the dynamic of the system is viewed as operating- state- dependent time varying local linear behavior in this frame, a linear constrained model predictive control algorithm is developed to optimize the power splitting between the fuel cell and ultracapacitor. The proposed algorithm significantly simplifies implementation of the controller and can handle multiple constraints, such as limiting substantial fluctuation of fuel cell current. Experiment and simulation results demonstrate that the control strategy can optimally split power between the fuel cell and ultracapacitor, limit the change rate of the fuel cell current, and so as to extend the lifetime of the fuel cell.
Chen, Qihong; Long, Rong; Quan, Shuhai; Zhang, Liyan
2014-01-01
This paper presents a neural network predictive control strategy to optimize power distribution for a fuel cell/ultracapacitor hybrid power system of a robot. We model the nonlinear power system by employing time variant auto-regressive moving average with exogenous (ARMAX), and using recurrent neural network to represent the complicated coefficients of the ARMAX model. Because the dynamic of the system is viewed as operating- state- dependent time varying local linear behavior in this frame, a linear constrained model predictive control algorithm is developed to optimize the power splitting between the fuel cell and ultracapacitor. The proposed algorithm significantly simplifies implementation of the controller and can handle multiple constraints, such as limiting substantial fluctuation of fuel cell current. Experiment and simulation results demonstrate that the control strategy can optimally split power between the fuel cell and ultracapacitor, limit the change rate of the fuel cell current, and so as to extend the lifetime of the fuel cell.
Smith, Christopher; Willits, Steven; Bull, Diana; Fontaine, Arnold
2014-01-01
This paper presents work completed by The Applied Research Laboratory at The Pennsylvania State University, in conjunction with Sandia National Labs, on the optimization of the power conversion chain (PCC) design to maximize the Average Annual Electric Power (AAEP) output of an Oscillating Water Column (OWC) device. The design consists of two independent stages. First, the design of a floating OWC, a Backward Bent Duct Buoy (BBDB), and second the design of the PCC. The pneumatic power output ...
An improved predictive deconvolution based on maximization of non-Gaussianity%一种改进的基于非高斯性最大化的预测反褶积算法
刘军; 陆文凯
2008-01-01
The predictive deconvolution algorithm (PD), which is based on second-order statistics, assumes that the primaries and the multiples are implicitly orthogonal. However,the seismic data usually do not satisfy this assumption in practice. Since the seismic data (primaries and multiples) have a non-Gaussian distribution, in this paper we present an improved predictive deconvolution algorithm (IPD) by maximizing the non-Gaussianity of the recovered primaries. Applications of the IPD method on synthetic and real seismic datasets show that the proposed method obtains promising results.
Maximally incompatible quantum observables
Heinosaari, Teiko, E-mail: teiko.heinosaari@utu.fi [Turku Centre for Quantum Physics, Department of Physics and Astronomy, University of Turku, FI-20014 Turku (Finland); Schultz, Jussi, E-mail: jussi.schultz@gmail.com [Dipartimento di Matematica, Politecnico di Milano, Piazza Leonardo da Vinci 32, I-20133 Milano (Italy); Toigo, Alessandro, E-mail: alessandro.toigo@polimi.it [Dipartimento di Matematica, Politecnico di Milano, Piazza Leonardo da Vinci 32, I-20133 Milano (Italy); Istituto Nazionale di Fisica Nucleare, Sezione di Milano, Via Celoria 16, I-20133 Milano (Italy); Ziman, Mario, E-mail: ziman@savba.sk [RCQI, Institute of Physics, Slovak Academy of Sciences, Dúbravská cesta 9, 84511 Bratislava (Slovakia); Faculty of Informatics, Masaryk University, Botanická 68a, 60200 Brno (Czech Republic)
2014-05-01
The existence of maximally incompatible quantum observables in the sense of a minimal joint measurability region is investigated. Employing the universal quantum cloning device it is argued that only infinite dimensional quantum systems can accommodate maximal incompatibility. It is then shown that two of the most common pairs of complementary observables (position and momentum; number and phase) are maximally incompatible.
Natavan M. Gadzhiyeva
2017-07-01
Full Text Available The present study investigated the effects of a salesperson's use of language power and nonverbal immediacy on the persuasiveness of the salesperson. A high level of language power and a high level of nonverbal immediacy were hypothesized to singularly and jointly increase a salesperson's level of persuasiveness. A sample of 211 undergraduate students voluntarily completed an online survey, which displayed a video clip of a sales presentation. Each participant randomly viewed one of four video clips, which differed in terms of the salesperson's levels of language power (powerful vs. powerless and nonverbal immediacy (high vs. low. A three-way ANOVA indicated that language power had a significant main effect on persuasion in the expected direction, and also revealed a significant interaction between nonverbal immediacy and participant biological sex. However, there were no main effects for nonverbal immediacy and participant biological sex, and no interaction effect was found between language power and nonverbal immediacy. Subsequent data analysis revealed that the perceived power of the speaker mediated the relationship between language power and the extent of persuasion. We conclude the article with a discussion of the implications of our findings for both researchers and practitioners.
PREDICTION OF POWER GENERATION OF SMALL SCALE VERTICAL AXIS WIND TURBINE USING FUZZY LOGIC
Altab Hossain
2009-01-01
Full Text Available Renewable energy from the wind turbine has been focused for the alternative source of power generation due to the following advances of the of the wind turbine. Firstly, the wind turbine is highly efficient and eco-friendly. Secondly, the turbine has the ability to response for the changeable power generation based on the wind velocity and structural framework. However, the competitive efficiency of the wind turbine is necessary to successfully alternate the conventional power sources. The most relevant factor which affects the overall efficiency of the wind turbine is the wind velocity and the relative turbine dimensions. Artificial intelligence systems are widely used technology that can learn from examples and are able to deal with non-linear problems. Compared with traditional approach, fuzzy logic approach is more efficient for the representation, manipulation and utilization. Therefore, the primary purpose of this work was to investigate the relationship between wind turbine power generation and wind velocity, and to illustrate how fuzzy expert system might play an important role in prediction of wind turbine power generation. The main purpose of the measurement over the small scaled prototype vertical axis wind turbine for the wind velocity is to predict the performance of full scaled H-type vertical axis wind turbine. Prediction of power generation at the different wind velocities has been tested at the Thermal Laboratory of Faculty of Engineering, Universiti Industri Selangor (UNISEL and results concerning the daily prediction have been obtained.
Thiesen, J.; Gulstad, L.; Ristic, I.; Maric, T.
2010-09-01
Summit: The wind power predictability is often a forgotten decision and planning factor for most major wind parks, both onshore and offshore. The results of the predictability are presented after having examined a number of European offshore and offshore parks power predictability by using three(3) mesoscale model IRIE_GFS and IRIE_EC and WRF. Full description: It is well known that the potential wind production is changing with latitude and complexity in terrain, but how big are the changes in the predictability and the economic impacts on a project? The concept of meteorological predictability has hitherto to some degree been neglected as a risk factor in the design, construction and operation of wind power plants. Wind power plants are generally built in places where the wind resources are high, but these are often also sites where the predictability of the wind and other weather parameters is comparatively low. This presentation addresses the question of whether higher predictability can outweigh lower average wind speeds with regard to the overall economy of a wind power project. Low predictability also tends to reduce the value of the energy produced. If it is difficult to forecast the wind on a site, it will also be difficult to predict the power production. This, in turn, leads to increased balance costs and a less reduced carbon emission from the renewable source. By investigating the output from three(3) mesoscale models IRIE and WRF, using ECMWF and GFS as boundary data over a forecasting period of 3 months for 25 offshore and onshore wind parks in Europe, the predictability are mapped. Three operational mesoscale models with two different boundary data have been chosen in order to eliminate the uncertainty with one mesoscale model. All mesoscale models are running in a 10 km horizontal resolution. The model output are converted into "day a head" wind turbine generation forecasts by using a well proven advanced physical wind power model. The power models
Outsmarting cancer: the power of hybrid genomic/proteomic biomarkers to predict drug response.
Rexer, Brent N; Arteaga, Carlos L
2014-01-01
A recent study by Niepel and colleagues describes a novel approach to predicting response to targeted anti-cancer therapies. The authors used biochemical profiling of signaling activity in basal and ligand-stimulated states for a panel of receptor and intracellular kinases to develop predictive models of drug sensitivity. In some cases, the response to ligand stimulation predicted drug response better than did target abundance or genomic alterations in the targeted pathway. Furthermore, combining biochemical profiles with genomic information was better at predicting drug response. This work suggests that incorporating biochemical signaling profiles with genomic alterations should provide powerful predictors of response to molecularly targeted therapies.
K-Line Patterns’ Predictive Power Analysis Using the Methods of Similarity Match and Clustering
Lv Tao
2017-01-01
Full Text Available Stock price prediction based on K-line patterns is the essence of candlestick technical analysis. However, there are some disputes on whether the K-line patterns have predictive power in academia. To help resolve the debate, this paper uses the data mining methods of pattern recognition, pattern clustering, and pattern knowledge mining to research the predictive power of K-line patterns. The similarity match model and nearest neighbor-clustering algorithm are proposed for solving the problem of similarity match and clustering of K-line series, respectively. The experiment includes testing the predictive power of the Three Inside Up pattern and Three Inside Down pattern with the testing dataset of the K-line series data of Shanghai 180 index component stocks over the latest 10 years. Experimental results show that (1 the predictive power of a pattern varies a great deal for different shapes and (2 each of the existing K-line patterns requires further classification based on the shape feature for improving the prediction performance.
Sergio Saponara
2016-04-01
Full Text Available This work proposes a scalable architecture of an Uninterruptible Power Supply (UPS system, with predictive diagnosis capabilities, for safety critical applications. A Failure Mode and Effect Analysis (FMEA has identified the faults occurring in the energy storage unit, based on Valve Regulated Lead-Acid batteries, and in the 3-phase high power transformers, used in switching converters and for power isolation, as the main bottlenecks for power system reliability. To address these issues, a distributed network of measuring nodes is proposed, where vibration-based mechanical stress diagnosis is implemented together with electrical (voltage, current, impedance and thermal degradation analysis. Power system degradation is tracked through multi-channel measuring nodes with integrated digital signal processing in the transformed frequency domain, from 0.1 Hz to 1 kHz. Experimental measurements on real power systems for safety-critical applications validate the diagnostic unit.
Chien, T W; Chu, H; Hsu, W C; Tseng, T K; Hsu, C H; Chen, K Y
2003-08-01
The continuous emission monitoring system (CEMS) can monitor flue gas emissions continuously and instantaneously. However, it has the disadvantages of enormous cost, easily producing errors in sampling periods of bad weather, lagging response in variable ambient environments, and missing data in daily zero and span tests and maintenance. The concept of a predictive emission monitoring system (PEMS) is to use the operating parameters of combustion equipment through thermodynamic or statistical methods to construct a mathematic model that can predict emissions by a computer program. The goal of this study is to set up a PEMS in a gas-fired combined cycle power generation unit at the Hsinta station of Taiwan Power Co. The emissions to be monitored include nitrogen oxides (NOx) and oxygen (O2) in flue gas. The major variables of the predictive model were determined based on the combustion theory. The data of these variables then were analyzed to establish a regression model. From the regression results, the influences of these variables are discussed and the predicted values are compared with the CEMS data for accuracy. In addition, according to the cost information, the capital and operation and maintenance costs for a PEMS can be much lower than those for a CEMS.
Quantifying the Effect of Lidar Turbulence Error on Wind Power Prediction
Newman, Jennifer F.; Clifton, Andrew
2016-01-01
Currently, cup anemometers on meteorological towers are used to measure wind speeds and turbulence intensity to make decisions about wind turbine class and site suitability; however, as modern turbine hub heights increase and wind energy expands to complex and remote sites, it becomes more difficult and costly to install meteorological towers at potential sites. As a result, remote-sensing devices (e.g., lidars) are now commonly used by wind farm managers and researchers to estimate the flow field at heights spanned by a turbine. Although lidars can accurately estimate mean wind speeds and wind directions, there is still a large amount of uncertainty surrounding the measurement of turbulence using these devices. Errors in lidar turbulence estimates are caused by a variety of factors, including instrument noise, volume averaging, and variance contamination, in which the magnitude of these factors is highly dependent on measurement height and atmospheric stability. As turbulence has a large impact on wind power production, errors in turbulence measurements will translate into errors in wind power prediction. The impact of using lidars rather than cup anemometers for wind power prediction must be understood if lidars are to be considered a viable alternative to cup anemometers.In this poster, the sensitivity of power prediction error to typical lidar turbulence measurement errors is assessed. Turbulence estimates from a vertically profiling WINDCUBE v2 lidar are compared to high-resolution sonic anemometer measurements at field sites in Oklahoma and Colorado to determine the degree of lidar turbulence error that can be expected under different atmospheric conditions. These errors are then incorporated into a power prediction model to estimate the sensitivity of power prediction error to turbulence measurement error. Power prediction models, including the standard binning method and a random forest method, were developed using data from the aeroelastic simulator FAST
Economically Efficient Power Storage Operation by Dealing with the Non-Normality of Power Prediction
Shiro Yano
2015-10-01
Full Text Available Various predictive models about the residential energy demand and residential renewable energy production have been proposed. Recent studies have confirmed that they are not normally distributed over time. The increase in renewable energy installation has brought the issue of energy storage charge and discharge control. Thus, storage control methods that properly address non-normality are required. In this paper, we formulated the economically optimal storage control problem using Markov decision process (MDP and the conditional value at risk (CVaR measure to deal with the non-normality of predictive distribution about the household’s net load. The CVaR measure was employed to treat with the chance constraint on the battery capacitor, in other words, overcharge risk and over-discharge risk. We conducted a simulation to compare the annual economic saving performances between two MDPs: one is the MDP with a Gaussian predictive distribution and the other is the MDP with a normalized frequency distribution (non-normal. We used the real time series of 35 residential energy consumption and PV generation data in Japan. The importance of addressing the non-normality of random variables was shown by our simulation.
Predictability of the Power Output of Three Wave Energy Technologies in the Danish North Sea
Chozas, Julia Fernandez; Jensen, N. E. Helstrup; Sørensen, H. C.
2011-01-01
The paper addresses an important challenge ahead the integration of the electricity generated by wave energy conversion technologies into the electric grid. Particularly, it looks into the role of wave energy within the day-ahead electricity market. For that the predictability of the theoretical...... of the study is to provide an indication on the accuracy of the forecast of i) wave parameters, ii) the normalised theoretical power productions from each of the selected technologies (Pelamis, Wave Dragon and Wavestar), and iii) the normalised theoretical power production of a combination of the three devices......, during a very energetic time period. Results show that for the 12 to 36 hours time horizon forecast, the accuracy in the predictions (in terms of scatter index) of the significant wave height, zero crossing period and wave power are 22%, 11% and 68%, respectively; and the accuracy in the predictions...
Varanasi, Jhansi L; Sinha, Pallavi; Das, Debabrata
2017-05-01
To selectively enrich an electrogenic mixed consortium capable of utilizing dark fermentative effluents as substrates in microbial fuel cells and to further enhance the power outputs by optimization of influential anodic operational parameters. A maximum power density of 1.4 W/m(3) was obtained by an enriched mixed electrogenic consortium in microbial fuel cells using acetate as substrate. This was further increased to 5.43 W/m(3) by optimization of influential anodic parameters. By utilizing dark fermentative effluents as substrates, the maximum power densities ranged from 5.2 to 6.2 W/m(3) with an average COD removal efficiency of 75% and a columbic efficiency of 10.6%. A simple strategy is provided for selective enrichment of electrogenic bacteria that can be used in microbial fuel cells for generating power from various dark fermentative effluents.
Modeling and Model Predictive Power and Rate Control of Wireless Communication Networks
Cunwu Han
2014-01-01
Full Text Available A novel power and rate control system model for wireless communication networks is presented, which includes uncertainties, input constraints, and time-varying delays in both state and control input. A robust delay-dependent model predictive power and rate control method is proposed, and the state feedback control law is obtained by solving an optimization problem that is derived by using linear matrix inequality (LMI techniques. Simulation results are given to illustrate the effectiveness of the proposed method.
Predictability of the Power Output of Three Wave Energy Technologies in the Danish North Sea
Chozas, Julia Fernandez; Jensen, N. E. Helstrup; Sørensen, H. C.;
2013-01-01
The paper addresses an important challenge towards the integration of the electricity generated by wave energy converters into the electric grid. Particularly, it looks into the role of wave energy within day-ahead electricity markets. For that the predictability of the theoretical power outputs ....... The best compromise between forecast accuracy and mean power production results when considering the combined production of the three converters. © 2013 Elsevier Ltd. All rights reserved....
Real-time power cycling in video on demand data centres using online Bayesian prediction
Sanz Marco, Vicent; Zheng WANG; Porter, Barry Francis
2017-01-01
Energy usage in data centres continues to be a major and growing concern as an increasing number of everyday services depend on these facilities. Research in this area has examined topics including power smoothing using batteries and deep learning to control cooling systems, in addition to optimisation techniques for the software running inside data centres. We present a novel real-time power-cycling architecture, supported by a media distribution approach and online prediction model, to auto...
Distributed Model Predictive Control of A Wind Farm for Optimal Active Power Control
Zhao, Haoran; Wu, Qiuwei; Guo, Qinglai;
2015-01-01
This paper presents a dynamic discrete-time Piece- Wise Affine (PWA) model of a wind turbine for the optimal active power control of a wind farm. The control objectives include both the power reference tracking from the system operator and the wind turbine mechanical load minimization. Instead......, which combines the clustering, linear identification and pattern recognition techniques. The developed model, consisting of 47 affine dynamics, is verified by the comparison with a widely-used nonlinear wind turbine model. It can be used as a predictive model for the Model Predictive Control (MPC......) or other advanced optimal control applications of a wind farm....
Using reference trajectories to predicted uncertain systems: exemplified on a power plant
Odgaard, Peter Fogh; Stoustrup, Jakob; Mataji, B.
2007-01-01
This paper presents a method for prediction of uncertain closed loop systems, where the uncertainties are depending on operating points. Such model uncertainties are often present when complicated non-linear systems are predicted. The method uses precomputed mean and variances of the prediction...... uncertainties. It is as well proposed to update the uncertainty prediction models on-line. The potential of the method is illustrated by an example from a coal-fired power plant. This example shows prediction of the uncertainties as a bounded region in which the given system variable can be assumed...... to be contained in. In the example these successfully bound the system variables while in comparison applying a simple prediction diverges from the system....
Nateghi, Roshanak; Guikema, Seth D; Quiring, Steven M
2011-12-01
This article compares statistical methods for modeling power outage durations during hurricanes and examines the predictive accuracy of these methods. Being able to make accurate predictions of power outage durations is valuable because the information can be used by utility companies to plan their restoration efforts more efficiently. This information can also help inform customers and public agencies of the expected outage times, enabling better collective response planning, and coordination of restoration efforts for other critical infrastructures that depend on electricity. In the long run, outage duration estimates for future storm scenarios may help utilities and public agencies better allocate risk management resources to balance the disruption from hurricanes with the cost of hardening power systems. We compare the out-of-sample predictive accuracy of five distinct statistical models for estimating power outage duration times caused by Hurricane Ivan in 2004. The methods compared include both regression models (accelerated failure time (AFT) and Cox proportional hazard models (Cox PH)) and data mining techniques (regression trees, Bayesian additive regression trees (BART), and multivariate additive regression splines). We then validate our models against two other hurricanes. Our results indicate that BART yields the best prediction accuracy and that it is possible to predict outage durations with reasonable accuracy. © 2011 Society for Risk Analysis.
Scholl, Annika; Sassenrath, Claudia; Sassenberg, Kai
2015-01-01
Depending on their motivation, individuals prefer different group contexts for social interactions. The present research sought to provide more insight into this relationship. More specifically, we tested how challenge/threat and a promotion/prevention focus predict attraction to groups with high- or low-power. As such, we examined differential outcomes of threat and prevention focus as well as challenge and promotion focus that have often been regarded as closely related. According to regulatory focus, individuals should prefer groups that they expect to "feel right" for them to join: Low-power groups should be more attractive in a prevention (than a promotion) focus, as these groups suggest security-oriented strategies, which fit a prevention focus. High-power groups should be more attractive in a promotion (rather than a prevention) focus, as these groups are associated with promotion strategies fitting a promotion focus (Sassenberg et al., 2007). In contrast, under threat (vs. challenge), groups that allow individuals to restore their (perceived) lack of control should be preferred: Low-power groups should be less attractive under threat (than challenge) because they provide low resources which threatened individuals already perceive as insufficient and high-power groups might be more attractive under threat (than under challenge), because their high resources allow individuals to restore control. Two experiments (N = 140) supported these predictions. The attractiveness of a group often depends on the motivation to engage in what fits (i.e., prefer a group that feels right in the light of one's regulatory focus). However, under threat the striving to restore control (i.e., prefer a group allowing them to change the status quo under threat vs. challenge) overrides the fit effect, which may in turn guide individuals' behavior in social interactions.
Labinov, Mark S
2014-01-01
Industrial and power systems rely on engineering predictions of the flow properties of working fluids. The paper proposes a way of the utilization of the vapor quality values along the new retrograde condensation curve in the generation of the void fraction design guidelines and reliable prediction of the saturated liquid specific volumes/densities. The new procedure eliminates the involvement of semi-empirical relationships like rectilinear diameter and other similar models.
Zong, Yi; Kullmann, Daniel; Thavlov, Anders
2012-01-01
management. It also presents in detail how to implement a thermal model predictive controller (MPC) for the heaters' power consumption prediction in the PowerFlexHouse. It demonstrates that this MPC strategy can realize load shifting, and using good predictions in MPC-based control, a better matching...
Nonlinear Fuzzy Model Predictive Control for a PWR Nuclear Power Plant
Xiangjie Liu
2014-01-01
Full Text Available Reliable power and temperature control in pressurized water reactor (PWR nuclear power plant is necessary to guarantee high efficiency and plant safety. Since the nuclear plants are quite nonlinear, the paper presents nonlinear fuzzy model predictive control (MPC, by incorporating the realistic constraints, to realize the plant optimization. T-S fuzzy modeling on nuclear power plant is utilized to approximate the nonlinear plant, based on which the nonlinear MPC controller is devised via parallel distributed compensation (PDC scheme in order to solve the nonlinear constraint optimization problem. Improved performance compared to the traditional PID controller for a TMI-type PWR is obtained in the simulation.
Hierarchical model-based predictive control of a power plant portfolio
Edlund, Kristian; Bendtsen, Jan Dimon; Jørgensen, John Bagterp
2011-01-01
control” – becomes increasingly important as the ratio of renewable energy in a power system grows. As a consequence, tomorrow's “smart grids” require highly flexible and scalable control systems compared to conventional power systems. This paper proposes a hierarchical model-based predictive control...... design for power system portfolio control, which aims specifically at meeting these demands.The design involves a two-layer hierarchical structure with clearly defined interfaces that facilitate an object-oriented implementation approach. The same hierarchical structure is reflected in the underlying...
Performance analysis of CDMA power control system based on fuzzy prediction
杨涛; 谢剑英
2004-01-01
Power control is of paramount importance in combating the near-far problem and co-channel interference in a CDMA cellular system. Due to fast fading and ambient interference in a wireless channel, conventional fixed-step power control schemes have difficulty in compensating for the fast fading channel dynamically and in a timely manner. To acquire flexible power regulation in order to maintain required transmission capacity under the given transmission quality requirement, we propose a hybrid power control scheme which makes full use of the simple fuzzy inference rule refined by an operator in the fuzzy control and prediction property from related previous results in Generalized Prediction Control (GPC). In implementation of this strategy, we classify the fading zone into three levels according to the signal-to-noise-rate (SNR) requirement. In each level the power compensation amount varies with fading gradient and the compensation scheme varies as well. The digital results show that adoption of the fuzzy-GPC power regulation scheme has acquired a reasonable performance improvement when compared with fixed-step and fuzzy schemes. According to theoretic analysis and simulation results,we can conclude that under a variational transmission environment, a flexible power regulation scheme such as fuzzy-GPC is easy to adapt to the environment and thus overcomes the near-far effect and multi-access interference effectively.
Analytical Modeling of Wind Farms: A New Approach for Power Prediction
Amin Niayifar
2016-09-01
Full Text Available Wind farm power production is known to be strongly affected by turbine wake effects. The purpose of this study is to develop and test a new analytical model for the prediction of wind turbine wakes and the associated power losses in wind farms. The new model is an extension of the one recently proposed by Bastankhah and Porté-Agel for the wake of stand-alone wind turbines. It satisfies the conservation of mass and momentum and assumes a self-similar Gaussian shape of the velocity deficit. The local wake growth rate is estimated based on the local streamwise turbulence intensity. Superposition of velocity deficits is used to model the interaction of the multiple wakes. Furthermore, the power production from the wind turbines is calculated using the power curve. The performance of the new analytical wind farm model is validated against power measurements and large-eddy simulation (LES data from the Horns Rev wind farm for a wide range of wind directions, corresponding to a variety of full-wake and partial-wake conditions. A reasonable agreement is found between the proposed analytical model, LES data, and power measurements. Compared with a commonly used wind farm wake model, the new model shows a significant improvement in the prediction of wind farm power.
Model predictive control for power fluctuation supression in hybrid wind/PV/battery systems
You, Shi; Liu, Zongyu; Zong, Yi
2015-01-01
predictive control (MPC)-based algorithm for battery management in a hybrid wind/PV/battery system to suppress the short-term power fluctuation on the ‘minute’ scale. A case study with data collected from a practical hybrid system setup is used to demonstrate the effectiveness of the proposed algorithm......A hybrid energy system, the combination of wind turbines, PV panels and battery storage with effective control mechanism, represents a promising solution to the power fluctuation problem when integrating renewable energy resources (RES) into conventional power systems. This paper proposes a model...... together with a Monte Carlo simulation-based sensitivity analysis. In addition to illustrating the complementarity between the fluctuations of wind power and PV power, the results prove the proposed MPC algorithm is effective in fluctuation suppression but sensitive to factors such as forecast accuracy...
Parker, Andrew M.; Wandi Bruine de Bruin; Baruch Fischhoff
2007-01-01
Our previous research suggests that people reporting a stronger desire to maximize obtain worse life outcomes (Bruine de Bruin et al., 2007). Here, we examine whether this finding may be explained by the decision-making styles of self-reported maximizers. Expanding on Schwartz et al. (2002), we find that self-reported maximizers are more likely to show problematic decision-making styles, as evidenced by self-reports of less behavioral coping, greater dependence on others when making decisions...
Rehabilitation after stroke: predictive power of Barthel Index versus a cognitive and a motor index
Engberg, A; Bentzen, L; Garde, B
1995-01-01
The aim of the present study was to investigate the predictive power of ratings of Barthel Index at Day 40 post stroke, compared with and/or combined with simultaneous ratings from a mobility scale (EG motor index) and a rather simple cognitive test scale (CT50). The parameter to be individually...... predicted was the need for special living facilities and support at discharge from a rehabilitation hospital, as well as six months later; 53 stroke patients with age median 68 years were included in this prospective study. It was shown that a combination of Barthel Index and CT50 had a stronger predictive...
Unified Maximally Natural Supersymmetry
Huang, Junwu
2016-01-01
Maximally Natural Supersymmetry, an unusual weak-scale supersymmetric extension of the Standard Model based upon the inherently higher-dimensional mechanism of Scherk-Schwarz supersymmetry breaking (SSSB), possesses remarkably good fine tuning given present LHC limits. Here we construct a version with precision $SU(2)_{\\rm L} \\times U(1)_{\\rm Y} $ unification: $\\sin^2 \\theta_W(M_Z) \\simeq 0.231$ is predicted to $\\pm 2\\%$ by unifying $SU(2)_{\\rm L} \\times U(1)_{\\rm Y} $ into a 5D $SU(3)_{\\rm EW}$ theory at a Kaluza-Klein scale of $1/R_5 \\sim 4.4\\,{\\rm TeV}$, where SSSB is simultaneously realised. Full unification with $SU(3)_{\\rm C}$ is accommodated by extending the 5D theory to a $N=4$ supersymmetric $SU(6)$ gauge theory on a 6D rectangular orbifold at $1/R_6 \\sim 40 \\,{\\rm TeV}$. TeV-scale states beyond the SM include exotic charged fermions implied by $SU(3)_{\\rm EW}$ with masses lighter than $\\sim 1.2\\,{\\rm TeV}$, and squarks in the mass range $1.4\\,{\\rm TeV} - 2.3\\,{\\rm TeV}$, providing distinct signature...
Chen, Danfeng; Wang, Cong
In this paper, a bifurcation prediction approach is proposed based on dynamic recognition and further applied to predict the period-doubling bifurcation (PDB) of power systems. Firstly, modeling of the internal dynamics of nonlinear systems is obtained through deterministic learning (DL), and the modeling results are applied for constructing the dynamic training pattern database. Specifically, training patterns are chosen according to the hierarchical structured knowledge representation based on the qualitative property of dynamical systems, which is capable of arranging the dynamical models into a specific order in the pattern database. Then, a dynamic recognition-based bifurcation prediction approach is suggested. As a result, perturbations implying PDB on the testing patterns can be predicted through the minimum dynamic error between the training patterns and testing patterns by recalling the knowledge restored in the pattern database. Finally, the second-order single-machine to infinite bus power system model is introduced to check the effectiveness of this prediction approach, which implies PDB under small periodic parameter perturbations. The key point that determines the prediction effect mainly lies in two methods: (1) accurate approximation of the unknown system dynamics through DL guarantees the feasibility of the prediction process; (2) the qualitative property of PDB and the generalization ability of DL algorithm ensure the validity of the selected training patterns. Simulations are included to illustrate the effectiveness of the proposed approach.
Manoj Kumar; Anant Deshpande; Chintan Gupta; A K Biswas; A K Nath
2002-12-01
Selective multi-photon dissociation (MPD) of Freon-22 (CF2HCl) molecules has been carried out using a TEA CO2 laser at various CO2 laser lines (9(20)-9(26)) in order to maximize the yield of C-13 isotope in the product (C2F4) at an enrichment factor of 100. The effects of laser pulse tail due to the presence of N2 in the laser mixture on the enrichment factor and yield of C-13 are investigated. It is found that the addition of a small amount of N2 is possible in the laser mixture without a significant drop in the yield at desired enrichment factor. Addition of a small amount of N2 improves the laser efficiency considerably. At a given pulse energy, a slight change in the near field intensity distribution of a laser severely affects the selectivity of C-13 isotope. The computed far-field intensity distributions of the measured near-field intensities show marked spatial variation in the focal spots that leads to a drop in selectivity. For macroscopic production of C-13 isotope a simple and novel multi-pass cavity has been designed and tested to focus the energy repeatedly keeping the optimum fluence constant at each focal spot.
Research Design and the Predictive Power of Measures of Self-Efficacy
Moriarty, Beverley
2014-01-01
The purpose of this enquiry was to examine how research design impacts on the predictive power of measures of self-efficacy. Three cautions for designing research into self-efficacy drawn from the seminal work of Albert Bandura (1986) and a further caution proposed by the current author together form the analytical framework for this enquiry. For…
Maximum power point tracking for photovoltaic system using model predictive control
Ma, Chao; Li, Ning; Li, Shaoyuan [Shanghai Jiao Tong Univ., Shanghai (China). Key Lab. of System Control and Information Processing
2013-07-01
In this paper, T-G-P model is built to find maximum power point according to light intensity and temperature, making it easier and more clearly for photovoltaic system to track the MPP. A predictive controller considering constraints for safe operation is designed. The simulation results show that the system can track MPP quickly, accurately and effectively.
Research Design and the Predictive Power of Measures of Self-Efficacy
Moriarty, Beverley
2014-01-01
The purpose of this enquiry was to examine how research design impacts on the predictive power of measures of self-efficacy. Three cautions for designing research into self-efficacy drawn from the seminal work of Albert Bandura (1986) and a further caution proposed by the current author together form the analytical framework for this enquiry. For…
Aggression in Primary Schools: The Predictive Power of the School and Home Environment
Kozina, Ana
2015-01-01
In this study, we analyse the predictive power of home and school environment-related factors for determining pupils' aggression. The multiple regression analyses are performed for fourth- and eighth-grade pupils based on the Trends in Mathematics and Science Study (TIMSS) 2007 (N = 8394) and TIMSS 2011 (N = 9415) databases for Slovenia. At the…
Achievement motivation revisited : New longitudinal data to demonstrate its predictive power
Hustinx, P.W.J.; Kuyper, H.; Van der Werf, M.P.C.; Dijkstra, Pieternel
2009-01-01
During recent decades, the classical one-dimensional concept of achievement motivation has become less popular among motivation researchers. This study aims to revive the concept by demonstrating its predictive power using longitudinal data from two cohort samples, each with 20,000 Dutch secondary s
Achievement motivation revisited : New longitudinal data to demonstrate its predictive power
Hustinx, P.W.J.; Kuyper, H.; Van der Werf, M.P.C.; Dijkstra, Pieternel
2009-01-01
During recent decades, the classical one-dimensional concept of achievement motivation has become less popular among motivation researchers. This study aims to revive the concept by demonstrating its predictive power using longitudinal data from two cohort samples, each with 20,000 Dutch secondary
Relano-Iborra, Helia; May, Tobias; Zaar, Johannes
-based Envelope Power Spectrum Model (mr-sEPSM) [2], combined with the correlation back-end of the Short-Time Objective Intelligibility measure (STOI) [3]. The sEPSMcorr can accurately predict NH data for a broad range of listening conditions, e.g., additive noise, phase jitter and ideal binary mask processing....
Jiang, Hao; Lin, Jin; Song, Yonghua;
2016-01-01
Model predictive control (MPC), that can consider system constraints, is one of the most advanced control technology used nowadays. In power systems, MPC is applied in a way that an optimal control sequence is given every step by an online MPC controller. The main drawback is that the control law...
Ilhan, Tahsin
2012-01-01
This study examined the predictive power of sex roles and attachment styles on loneliness. A total of 188 undergraduate students (114 female, and 74 male) from Gazi University completed the Bem Sex Role Inventory, UCLA Loneliness Scale, and Relationship Scales Questionnaire. Hierarchic Multiple Regression analysis and t-test were used to test…
Yuksel, Ismail; Toker, Yalcin
2013-01-01
This study aims to determine language learners' autonomy, self-evaluation levels and to examine the predictive power of these two variables on language achievement. The study was designed as mixed method design and was conducted with 108 high school students. Data were collected through an autonomy scale, a self-evaluation scale, schools record on…
Predictive Power of the Success Tendency and Ego Identity Status of the University Students
Osman, Pepe
2015-01-01
The aim of this research is to assess the predictive power of the success tendency and ego identity status of the students of Physical Education and Sports Teaching Department. 581 students of Physical Education and Sports Teaching Department in Kayseri, Nigde, Burdur, Bolu and Diyarbakir participated in this research. The acquired results were…
Model Predictive Control of Offshore Power Stations With Waste Heat Recovery
Pierobon, Leonardo; Chan, Richard; Li, Xiangan;
2016-01-01
The implementation of waste heat recovery units on oil and gas offshore platforms demands advances in both design methods and control systems. Model-based control algorithms can play an important role in the operation of offshore power stations. A novel regulator based on a linear model predictive...
Güngör, Semra Kiranli
2016-01-01
The purpose of this study is to identify servant leadership and ethical leadership behaviors of administrators and the prediction power of these behaviors on teachers' job satisfaction according to the views of schoolteachers. This research, figured in accordance with the quantitative research processes. The target population of the research has…
Predictive-model-based dynamic coordination control strategy for power-split hybrid electric bus
Zeng, Xiaohua; Yang, Nannan; Wang, Junnian; Song, Dafeng; Zhang, Nong; Shang, Mingli; Liu, Jianxin
2015-08-01
Parameter-matching methods and optimal control strategies of the top-selling hybrid electric vehicle (HEV), namely, power-split HEV, are widely studied. In particular, extant research on control strategy focuses on the steady-state energy management strategy to obtain better fuel economy. However, given that multi-power sources are highly coupled in power-split HEVs and influence one another during mode shifting, conducting research on dynamic coordination control strategy (DCCS) to achieve riding comfort is also important. This paper proposes a predictive-model-based DCCS. First, the dynamic model of the objective power-split HEV is built and the mode shifting process is analyzed based on the developed model to determine the reason for the system shock generated. Engine torque estimation algorithm is then designed according to the principle of the nonlinear observer, and the prediction model of the degree of shock is established based on the theory of model predictive control. Finally, the DCCS with adaptation for a complex driving cycle is realized by combining the feedback control and the predictive model. The presented DCCS is validated on the co-simulation platform of AMESim and Simulink. Results show that the shock during mode shifting is well controlled, thereby improving riding comfort.
Very-short-term wind power prediction by a hybrid model with single- and multi-step approaches
Mohammed, E.; Wang, S.; Yu, J.
2017-05-01
Very-short-term wind power prediction (VSTWPP) has played an essential role for the operation of electric power systems. This paper aims at improving and applying a hybrid method of VSTWPP based on historical data. The hybrid method is combined by multiple linear regressions and least square (MLR&LS), which is intended for reducing prediction errors. The predicted values are obtained through two sub-processes:1) transform the time-series data of actual wind power into the power ratio, and then predict the power ratio;2) use the predicted power ratio to predict the wind power. Besides, the proposed method can include two prediction approaches: single-step prediction (SSP) and multi-step prediction (MSP). WPP is tested comparatively by auto-regressive moving average (ARMA) model from the predicted values and errors. The validity of the proposed hybrid method is confirmed in terms of error analysis by using probability density function (PDF), mean absolute percent error (MAPE) and means square error (MSE). Meanwhile, comparison of the correlation coefficients between the actual values and the predicted values for different prediction times and window has confirmed that MSP approach by using the hybrid model is the most accurate while comparing to SSP approach and ARMA. The MLR&LS is accurate and promising for solving problems in WPP.
Lenzi, Amanda; Pinson, Pierre; Clemmensen, Line Katrine Harder;
2016-01-01
Producing accurate spatial predictions for wind power generation together with a quantification of uncertainties is required to plan and design optimal networks of wind farms. Toward this aim, we propose spatial models for predicting wind power generation at two different time scales: for annual...... that our method makes it possible to obtain fast and accurate predictions from posterior marginals for wind power generation. The proposed method is applicable in scientific areas as diverse as climatology, environmental sciences, earth sciences and epidemiology....
Stassinopoulos, E. G.; Brucker, G. J.; Calvel, P.; Baiget, A.; Peyrotte, C.; Gaillard, R.
1992-01-01
The transport, energy loss, and charge production of heavy ions in the sensitive regions of IRF 150 power MOSFETs are described. The dependence and variation of transport parameters with ion type and energy relative to the requirements for single event burnout in this part type are discussed. Test data taken with this power MOSFET are used together with analyses by means of a computer code of the ion energy loss and charge production in the device to establish criteria for burnout and parameters for space predictions. These parameters are then used in an application to predict burnout rates in a geostationary orbit for power converters operating in a dynamic mode. Comparisons of rates for different geometries in simulating SEU (single event upset) sensitive volumes are presented.
Yanjun Zhang
2015-01-01
Full Text Available A new optimized extreme learning machine- (ELM- based method for power system transient stability prediction (TSP using synchrophasors is presented in this paper. First, the input features symbolizing the transient stability of power systems are extracted from synchronized measurements. Then, an ELM classifier is employed to build the TSP model. And finally, the optimal parameters of the model are optimized by using the improved particle swarm optimization (IPSO algorithm. The novelty of the proposal is in the fact that it improves the prediction performance of the ELM-based TSP model by using IPSO to optimize the parameters of the model with synchrophasors. And finally, based on the test results on both IEEE 39-bus system and a large-scale real power system, the correctness and validity of the presented approach are verified.
A Machine Learning Method for Power Prediction on the Mobile Devices.
Chen, Da-Ren; Chen, You-Shyang; Chen, Lin-Chih; Hsu, Ming-Yang; Chiang, Kai-Feng
2015-10-01
Energy profiling and estimation have been popular areas of research in multicore mobile architectures. While short sequences of system calls have been recognized by machine learning as pattern descriptions for anomalous detection, power consumption of running processes with respect to system-call patterns are not well studied. In this paper, we propose a fuzzy neural network (FNN) for training and analyzing process execution behaviour with respect to series of system calls, parameters and their power consumptions. On the basis of the patterns of a series of system calls, we develop a power estimation daemon (PED) to analyze and predict the energy consumption of the running process. In the initial stage, PED categorizes sequences of system calls as functional groups and predicts their energy consumptions by FNN. In the operational stage, PED is applied to identify the predefined sequences of system calls invoked by running processes and estimates their energy consumption.
Alves, Pedro; Liu, Shuang; Wang, Daifeng; Gerstein, Mark
2017-04-05
Machine learning is an integral part of computational biology, and has already shown its use in various applications, such as prognostic tests. In the last few years in the non-biological machine learning community, ensembling techniques have shown their power in data mining competitions such as the Netflix challenge; however, such methods have not found wide use in computational biology. In this work we endeavor to show how ensembling techniques can be applied to practical problems, including problems in the field of bioinformatics, and how they often outperform other machine learning techniques in both predictive power and robustness. Furthermore, we develop a methodology of ensembling, Multi-Swarm Ensemble (MSWE) by using multiple particle swarm optimizations and demonstrate its ability to further enhance the performance of ensembles.
Low-Complexity Seizure Prediction From iEEG/sEEG Using Spectral Power and Ratios of Spectral Power.
Zhang, Zisheng; Parhi, Keshab K
2016-06-01
Prediction of seizures is a difficult problem as the EEG patterns are not wide-sense stationary and change from seizure to seizure, electrode to electrode, and from patient to patient. This paper presents a novel patient-specific algorithm for prediction of seizures in epileptic patients from either one or two single-channel or bipolar channel intra-cranial or scalp electroencephalogram (EEG) recordings with low hardware complexity. Spectral power features are extracted and their ratios are computed. For each channel, a total of 44 features including 8 absolute spectral powers, 8 relative spectral powers and 28 spectral power ratios are extracted every two seconds using a 4-second window with a 50% overlap. These features are then ranked and selected in a patient-specific manner using a two-step feature selection. Selected features are further processed by a second-order Kalman filter and then input to a linear support vector machine (SVM) classifier. The algorithm is tested on the intra-cranial EEG (iEEG) from the Freiburg database and scalp EEG (sEEG) from the MIT Physionet database. The Freiburg database contains 80 seizures among 18 patients in 427 hours of recordings. The MIT EEG database contains 78 seizures from 17 children in 647 hours of recordings. It is shown that the proposed algorithm can achieve a sensitivity of 100% and an average false positive rate (FPR) of 0.0324 per hour for the iEEG (Freiburg) database and a sensitivity of 98.68% and an average FPR of 0.0465 per hour for the sEEG (MIT) database. These results are obtained with leave-one-out cross-validation where the seizure being tested is always left out from the training set. The proposed algorithm also has a low complexity as the spectral powers can be computed using FFT. The area and power consumption of the proposed linear SVM are 2 to 3 orders of magnitude less than a radial basis function kernel SVM (RBF-SVM) classifier. Furthermore, the total energy consumption of a system using linear
Is it really self-control? Examining the predictive power of the delay of gratification task.
Duckworth, Angela L; Tsukayama, Eli; Kirby, Teri A
2013-07-01
This investigation tests whether the predictive power of the delay of gratification task (colloquially known as the "marshmallow test") derives from its assessment of self-control or of theoretically unrelated traits. Among 56 school-age children in Study 1, delay time was associated with concurrent teacher ratings of self-control and Big Five conscientiousness-but not with other personality traits, intelligence, or reward-related impulses. Likewise, among 966 preschool children in Study 2, delay time was consistently associated with concurrent parent and caregiver ratings of self-control but not with reward-related impulses. While delay time in Study 2 was also related to concurrently measured intelligence, predictive relations with academic, health, and social outcomes in adolescence were more consistently explained by ratings of effortful control. Collectively, these findings suggest that delay task performance may be influenced by extraneous traits, but its predictive power derives primarily from its assessment of self-control.
Power and Performance Management in Nonlinear Virtualized Computing Systems via Predictive Control.
Wen, Chengjian; Mu, Yifen
2015-01-01
The problem of power and performance management captures growing research interest in both academic and industrial field. Virtulization, as an advanced technology to conserve energy, has become basic architecture for most data centers. Accordingly, more sophisticated and finer control are desired in virtualized computing systems, where multiple types of control actions exist as well as time delay effect, which make it complicated to formulate and solve the problem. Furthermore, because of improvement on chips and reduction of idle power, power consumption in modern machines shows significant nonlinearity, making linear power models(which is commonly adopted in previous work) no longer suitable. To deal with this, we build a discrete system state model, in which all control actions and time delay effect are included by state transition and performance and power can be defined on each state. Then, we design the predictive controller, via which the quadratic cost function integrating performance and power can be dynamically optimized. Experiment results show the effectiveness of the controller. By choosing a moderate weight, a good balance can be achieved between performance and power: 99.76% requirements can be dealt with and power consumption can be saved by 33% comparing to the case with open loop controller.
Power and Performance Management in Nonlinear Virtualized Computing Systems via Predictive Control.
Chengjian Wen
Full Text Available The problem of power and performance management captures growing research interest in both academic and industrial field. Virtulization, as an advanced technology to conserve energy, has become basic architecture for most data centers. Accordingly, more sophisticated and finer control are desired in virtualized computing systems, where multiple types of control actions exist as well as time delay effect, which make it complicated to formulate and solve the problem. Furthermore, because of improvement on chips and reduction of idle power, power consumption in modern machines shows significant nonlinearity, making linear power models(which is commonly adopted in previous work no longer suitable. To deal with this, we build a discrete system state model, in which all control actions and time delay effect are included by state transition and performance and power can be defined on each state. Then, we design the predictive controller, via which the quadratic cost function integrating performance and power can be dynamically optimized. Experiment results show the effectiveness of the controller. By choosing a moderate weight, a good balance can be achieved between performance and power: 99.76% requirements can be dealt with and power consumption can be saved by 33% comparing to the case with open loop controller.
Colak, R; Ozcelik, O
2004-01-01
We examined the effects of weight loss induced by diet-orlistat (DO) and diet-orlistat combined with exercise (DOE) on maximal work rate production (Wmax) capacity in obese patients. Total of 24 obese patients were involved in this study. Twelve of them were subjected to DO therapy only and the remaining 12 patients participated in a regular aerobic exercise-training program in addition to DO therapy (DOE). Each patient performed two incremental ramp exercise tests up to exhaustion using an electromagnetically-braked cycle ergometer: one at the onset and one at the end of the 4th week. DOE therapy caused a significant decrease in total body weight: 101.5+/-17.4 kg (basal) vs 96.3+/-17.3 kg (4 wk) associated with a significant decrease in body fat mass: 45.0+/-10.5 kg (basal) vs 40.9+/-9.8 kg (4 wk). DO therapy also resulted in a significant decrease of total body weight 94.9+/-14.9 kg (basal) vs 91.6+/-13.5 kg (4 wk) associated with small but significant decreases in body fat mass: 37.7+/-5.6 kg (basal) to 36.0+/-6.2 kg (4 wk). Weight reduction achieved during DO therapy was not associated with increased Wmax capacity: 106+/-32 W (basal) vs 106+/-33 W (4 wk), while DOE therapy resulted in a markedly increased Wmax capacity: 109+/-39 W (basal) vs 138+/-30 W (4 wk). DO therapy combined with aerobic exercise training resulted in a significant reduction of fat mass tissue and markedly improved the aerobic fitness and Wmax capacities of obese patients. Considering this improvement within such a short period, physicians should consider applying an aerobic exercise-training program to sedentary obese patients for improving their physical fitness and thereby reduce the negative outcomes of obesity.
Westhoff, M.; Erpicum, S.; Archambeau, P.; Pirotton, M.; Zehe, E.; Dewals, B.
2015-12-01
Power can be performed by a system driven by a potential difference. From a given potential difference, the power that can be subtracted is constraint by the Carnot limit, which follows from the first and second laws of thermodynamics. If the system is such that the flux producing power (with power being the flux times its driving potential difference) also influences the potential difference, a maximum in power can be obtained as a result of the trade-off between the flux and the potential difference. This is referred to as the maximum power principle. It has already been shown that the atmosphere operates close to this maximum power limit when it comes to heat transport from the Equator to the poles, or vertically, from the surface to the atmospheric boundary layer. To reach this state of maximum power, the effective thermal conductivity of the atmosphere is adapted by the creation of convection cells. The aim of this study is to test if the soil's effective hydraulic conductivity also adapts in such a way that it produces maximum power. However, the soil's hydraulic conductivity adapts differently; for example by the creation of preferential flow paths. Here, this process is simulated in a lab experiment, which focuses on preferential flow paths created by piping. In the lab, we created a hydrological analogue to the atmospheric model dealing with heat transport between Equator and poles, with the aim to test if the effective hydraulic conductivity of the sand bed can be predicted with the maximum power principle. The experimental setup consists of two freely draining reservoir connected with each other by a confined aquifer. By adding water to only one reservoir, a potential difference will build up until a steady state is reached. The results will indicate whether the maximum power principle does apply for groundwater flow and how it should be applied. Because of the different way of adaptation of flow conductivity, the results differ from that of the
Ming Yi WANG; Guo ZHAO
2005-01-01
A right R-module E over a ring R is said to be maximally injective in case for any maximal right ideal m of R, every R-homomorphism f : m → E can be extended to an R-homomorphism f' : R → E. In this paper, we first construct an example to show that maximal injectivity is a proper generalization of injectivity. Then we prove that any right R-module over a left perfect ring R is maximally injective if and only if it is injective. We also give a partial affirmative answer to Faith's conjecture by further investigating the property of maximally injective rings. Finally, we get an approximation to Faith's conjecture, which asserts that every injective right R-module over any left perfect right self-injective ring R is the injective hull of a projective submodule.
Brüstle, Thomas; Pérotin, Matthieu
2012-01-01
Maximal green sequences are particular sequences of quiver mutations which were introduced by Keller in the context of quantum dilogarithm identities and independently by Cecotti-Cordova-Vafa in the context of supersymmetric gauge theory. Our aim is to initiate a systematic study of these sequences from a combinatorial point of view. Interpreting maximal green sequences as paths in various natural posets arising in representation theory, we prove the finiteness of the number of maximal green sequences for cluster finite quivers, affine quivers and acyclic quivers with at most three vertices. We also give results concerning the possible numbers and lengths of these maximal green sequences. Finally we describe an algorithm for computing maximal green sequences for arbitrary valued quivers which we used to obtain numerous explicit examples that we present.
Multivariable time series prediction for the icing process on overhead power transmission line.
Li, Peng; Zhao, Na; Zhou, Donghua; Cao, Min; Li, Jingjie; Shi, Xinling
2014-01-01
The design of monitoring and predictive alarm systems is necessary for successful overhead power transmission line icing. Given the characteristics of complexity, nonlinearity, and fitfulness in the line icing process, a model based on a multivariable time series is presented here to predict the icing load of a transmission line. In this model, the time effects of micrometeorology parameters for the icing process have been analyzed. The phase-space reconstruction theory and machine learning method were then applied to establish the prediction model, which fully utilized the history of multivariable time series data in local monitoring systems to represent the mapping relationship between icing load and micrometeorology factors. Relevant to the characteristic of fitfulness in line icing, the simulations were carried out during the same icing process or different process to test the model's prediction precision and robustness. According to the simulation results for the Tao-Luo-Xiong Transmission Line, this model demonstrates a good accuracy of prediction in different process, if the prediction length is less than two hours, and would be helpful for power grid departments when deciding to take action in advance to address potential icing disasters.
McRoberts, D Brent; Quiring, Steven M; Guikema, Seth D
2016-10-25
Tropical cyclones can significantly damage the electrical power system, so an accurate spatiotemporal forecast of outages prior to landfall can help utilities to optimize the power restoration process. The purpose of this article is to enhance the predictive accuracy of the Spatially Generalized Hurricane Outage Prediction Model (SGHOPM) developed by Guikema et al. (2014). In this version of the SGHOPM, we introduce a new two-step prediction procedure and increase the number of predictor variables. The first model step predicts whether or not outages will occur in each location and the second step predicts the number of outages. The SGHOPM environmental variables of Guikema et al. (2014) were limited to the wind characteristics (speed and duration of strong winds) of the tropical cyclones. This version of the model adds elevation, land cover, soil, precipitation, and vegetation characteristics in each location. Our results demonstrate that the use of a new two-step outage prediction model and the inclusion of these additional environmental variables increase the overall accuracy of the SGHOPM by approximately 17%.
Predictive control strategy for power management in parallel hybrid-electric vehicle
Nodeh, Mohammad Taqi; Gholizade, Hossein; Hajizadeh, Amin
2016-01-01
In this paper, a hybrid model-based nonlinear optimal control method is used to compute the optimal power distribution and power management in parallel hybrid electric vehicles. In the power management strategy, for optimal power distribution between the internal combustion engine, electrical...... system and the other subsystems, nonlinear predictive control is applied. In order to achieve this goal, a hierarchical control structure is utilized. This type of control structure consists of three levels of monitoring, coordinating and local controllers. Nonlinear modeling and performance index...... in the proposed method should be formulated at the regulatory level of the controller. Discrete dynamic mode of operation (motor-generator) in hybrid electric vehicle requires to use a dual-mode switch model and to define an alternative expression of performance index for the optimal control problem...
An improved implicit multiple model predictive control used for movable nuclear power plant
Tai Yun, E-mail: nalren@stu.xjtu.edu.c [School of Energy and Power Engineering, Xi' an Jiaotong University, Xi' an Shaanxi, 710049 (China); Hou Suxia, E-mail: hsxhjj@sina.com.c [School of Energy and Power Engineering, Xi' an Jiaotong University, Xi' an Shaanxi, 710049 (China); Li Chong, E-mail: abcdirxj@stu.xjtu.edu.c [School of Energy and Power Engineering, Xi' an Jiaotong University, Xi' an Shaanxi, 710049 (China); Zhao Fuyu, E-mail: fyzhao@mail.xjtu.edu.c [School of Energy and Power Engineering, Xi' an Jiaotong University, Xi' an Shaanxi, 710049 (China)
2010-10-15
Compared with the nuclear power station, the movable nuclear plant has the special requirement of the load following ability and is more difficult to control. In this work, a MMPC (multiple model predictive control) method is applied to the power system of the movable nuclear plant. The linear models used to describe the power changing process, according to which the local controllers are designed, still suffer rough switching. In this paper, work has been done on the improvement of MMPC to make it better in application to the power system of the movable nuclear plant. The simulation results show that these modifications are available to improve the system's dynamic characters, and the multiple strategy is efficacious to solve the control problem of the parameter time-variable nonlinear system.
Predictability of the Power Output of Three Wave Energy Technologies in the Danish North Sea
Chozas, Julia Fernandez; Jensen, N. E. Helstrup; Sørensen, H. C.;
2011-01-01
of the study is to provide an indication on the accuracy of the forecast of i) wave parameters, ii) the normalised theoretical power productions from each of the selected technologies (Pelamis, Wave Dragon and Wavestar), and iii) the normalised theoretical power production of a combination of the three devices...... of the normalised theoretical power outputs of Pelamis, Wave Dragon and Wavestar are 44%, 52% and 62%, respectively. The best compromise between forecast accuracy and mean power production results when considering the combined production of the three devices.......The paper addresses an important challenge ahead the integration of the electricity generated by wave energy conversion technologies into the electric grid. Particularly, it looks into the role of wave energy within the day-ahead electricity market. For that the predictability of the theoretical...
Wiegman, H.L.N. [General Electric Corporate Research and Development, Schenectady, NY (United States)
2000-07-01
Some recent advances in battery modeling were discussed with reference to on-line impedance estimates and power performance predictions for aqueous solution, porous electrode cell structures. The objective was to determine which methods accurately estimate a battery's internal state and power capability while operating a charge and sustaining a hybrid electric vehicle (HEV) over a wide range of driving conditions. The enhancements to the Randles-Ershler equivalent electrical model of common cells with lead-acid, nickel-cadmium and nickel-metal hydride chemistries were described. This study also investigated which impedances are sensitive to boundary layer charge concentrations and mass transport limitations. Non-linear impedances were shown to significantly affect the battery's ability to process power. The main advantage of on-line estimating a battery's impedance state and power capability is that the battery can be optimally sized for any application. refs., tabs., figs., append.
Hanon, Christine; Dorel, Sylvain; Delfour-Peyrethon, Rémi; Leprêtre, Pierre-Marie; Bishop, David J; Perrey, Stéphane; Thomas, Claire
2013-01-01
To investigate the physiological mechanisms that explain the end-exercise decrease in oxygen uptake [Formula: see text] during strenuous constant-power exercise, we recruited eleven trained, track cyclists. On two separated days they performed 1) resting spirometric measures, followed by an incremental test on a cycle ergometer to determine the power output at [Formula: see text] and 2) an exhaustive isokinetic supramaximal cycling exercise (Tlimsupra) at 185 ± 24% of [Formula: see text] (i.e., 640.5 ± 50.8 W). During cycling exercise tests, [Formula: see text], ventilation parameters, stroke volume (SV) and heart rate were continuously recorded. Furthermore, arterialised capillary blood samples were collected to measure blood pH, arterial oxygen saturation, lactate and bicarbonate concentration before and 5 min after Tlimsupra. A > 5% decrease in [Formula: see text] and/or SV was observed in 6 subjects, with 5 out of 6 subjects presenting both phenomena. The magnitude of the [Formula: see text] decrease was correlated with the magnitude of the SV decrease (R = 0.75, P decrease in forced vital capacity and forced inspiratory volume corroborate with a possible respiratory muscle fatigue. Based on these findings, we demonstrate that the occurrence of [Formula: see text] decrease in more than half of our subjects, during a strenuous constant-power exercise leading to a mild-acidosis (pH = 7.21 ± 0.04), results mainly from cardio-respiratory factors and not from blood metabolic responses.
A Bayesian Prediction Framework of Weather Based Power Line Damages in the Northeast
frediani, M.; Anagnostou, E. N.; Wanik, D.; Scerbo, D.
2012-12-01
This study aims to evaluate the predictability of damages to overhead power distribution lines from severe weather events in the New England area. During storms, trees and branches can come down and interact with power lines that results in significant interruptions to electricity distribution, causing major interruptions to residents and monetary losses to the utility company. In Connecticut, a densely forested state, severe winds and precipitation (in the form of rain and snow) from storms are key weather factors that challenge the power grid infrastructure vulnerability. Evaluating the local predictability of these impacts may aid local power utilities with crew allocation and preparedness during an event. A probabilistic approach to damage prediction caused by trees subjected to severe weather is being investigated in the region. This study specifically, explores the feasibility of applying Bayesian inversion technique to weather parameters by developing a damage decision tree composed of various meteorological and static parameters, like wind gust, precipitation (rain and snow accumulation and rates), high canopy forest density and tree trimming history for the power distribution lines. The resulting decision tree can be used as a Bayesian inversion database to predict the probability distribution of damages given a storm forecast. The Bayesian database is based on a historical data source provided by The Connecticut Light & Power Company (Connecticut's primary power utility) containing geographical information of trouble spots caused by thunderstorm and winter/snow-storm events; power line specifications and trimming history; and high-resolution model analysis of those storms. The analysis is based on a 2-sqkm model grid cropped over the state of Connecticut comprising a database of 3,307 pixels per storm. Each storm pixel is flagged to contain power line damages or no-damages. A total of 50 storm simulations is used to build the database. Pairs of
Predicted power in ultra high energy cosmic rays from active galaxies
Caramete, Laurentiu I; Biermann, Peter L; Stanev, Todor
2011-01-01
Context: As more and more data are collected by cosmic ray experiments such as the Pierre Auger Observatory and Telescope Array (TA), the search for the sources of the Ultra High Energy Cosmic Rays (UHECR) continues. Already we have some hints but no certain source or type of source is confirmed yet. Aims: We intend to predict the UHECR fluxes and the maximal energies of particles from two complete samples of nearby active galaxies, selected at radio and far-infrared frequencies. Also, we investigate the magnetic scattering of the UHECR path in the intervening cosmic space. Methods. We propose here a new method of searching for the sources of the UHECR in three steps, first we model the activity of the type of sources and get the flux of UHECR and a maximal energy for particle acceleration, then we model the interaction and angle deflection in the inter-galactic space and finally we get the distribution of the cosmic rays events that can be statistically compared with future data of the cosmic rays observator...
Wanink, JH; Zwarts, L
2001-01-01
1. The timing of prey exploitation by oystercatcher Haematopus ostralegus L, was predicted from detailed knowledge of the characteristics of its prey, the clam Scrobicularia plana da Costa. 2, Growth, mortality and depth distribution of a single cohort of Scrobicularia were monitored on a tidal flat
Wanink, JH; Zwarts, L
1. The timing of prey exploitation by oystercatcher Haematopus ostralegus L, was predicted from detailed knowledge of the characteristics of its prey, the clam Scrobicularia plana da Costa. 2, Growth, mortality and depth distribution of a single cohort of Scrobicularia were monitored on a tidal flat
Using Reanalysis Data for the Prediction of Seasonal Wind Turbine Power Losses Due to Icing
Burtch, D.; Mullendore, G. L.; Delene, D. J.; Storm, B.
2013-12-01
The Northern Plains region of the United States is home to a significant amount of potential wind energy. However, in winter months capturing this potential power is severely impacted by the meteorological conditions, in the form of icing. Predicting the expected loss in power production due to icing is a valuable parameter that can be used in wind turbine operations, determination of wind turbine site locations and long-term energy estimates which are used for financing purposes. Currently, losses due to icing must be estimated when developing predictions for turbine feasibility and financing studies, while icing maps, a tool commonly used in Europe, are lacking in the United States. This study uses the Modern-Era Retrospective Analysis for Research and Applications (MERRA) dataset in conjunction with turbine production data to investigate various methods of predicting seasonal losses (October-March) due to icing at two wind turbine sites located 121 km apart in North Dakota. The prediction of icing losses is based on temperature and relative humidity thresholds and is accomplished using three methods. For each of the three methods, the required atmospheric variables are determined in one of two ways: using industry-specific software to correlate anemometer data in conjunction with the MERRA dataset and using only the MERRA dataset for all variables. For each season, a percentage of the total expected generated power lost due to icing is determined and compared to observed losses from the production data. An optimization is performed in order to determine the relative humidity threshold that minimizes the difference between the predicted and observed values. Eight seasons of data are used to determine an optimal relative humidity threshold, and a further three seasons of data are used to test this threshold. Preliminary results have shown that the optimized relative humidity threshold for the northern turbine is higher than the southern turbine for all methods
Predicting Power Output of Upper Body using the OMNI-RES Scale
Bautista, Iker J.; Chirosa, Ignacio J.; Tamayo, Ignacio Martín; González, Andrés; Robinson, Joseph E.; Chirosa, Luis J.; Robertson, Robert J.
2014-01-01
The main aim of this study was to determine the optimal training zone for maximum power output. This was to be achieved through estimating mean bar velocity of the concentric phase of a bench press using a prediction equation. The values for the prediction equation would be obtained using OMNI–RES scale values of different loads of the bench press exercise. Sixty males (age 23.61 2.81 year; body height 176.29 6.73 cm; body mass 73.28 4.75 kg) voluntarily participated in the study and were tested using an incremental protocol on a Smith machine to determine one repetition maximum (1RM) in the bench press exercise. A linear regression analysis produced a strong correlation (r = −0.94) between rating of perceived exertion (RPE) and mean bar velocity (Velmean). The Pearson correlation analysis between real power output (PotReal) and estimated power (PotEst) showed a strong correlation coefficient of r = 0.77, significant at a level of p = 0.01. Therefore, the OMNI–RES scale can be used to predict Velmean in the bench press exercise to control the intensity of the exercise. The positive relationship between PotReal and PotEst allowed for the identification of a maximum power-training zone. PMID:25713677
Predicting Power Output of Upper Body using the OMNI-RES Scale
Bautista Iker J.
2014-12-01
Full Text Available The main aim of this study was to determine the optimal training zone for maximum power output. This was to be achieved through estimating mean bar velocity of the concentric phase of a bench press using a prediction equation. The values for the prediction equation would be obtained using OMNI-RES scale values of different loads of the bench press exercise. Sixty males ( voluntarily participated in the study and were tested using an incremental protocol on a Smith machine to determine one repetition maximum (1RM in the bench press exercise. A linear regression analysis produced a strong correlation (r = -0.94 between rating of perceived exertion (RPE and mean bar velocity (Velmean. The Pearson correlation analysis between real power output (PotReal and estimated power (PotEst showed a strong correlation coefficient of r = 0.77, significant at a level of p = 0.01. Therefore, the OMNI-RES scale can be used to predict Velmean in the bench press exercise to control the intensity of the exercise. The positive relationship between PotReal and PotEst allowed for the identification of a maximum power-training zone.
Odgaard, Peter Fogh; Stoustrup, Jakob; Mataji, B.
2007-01-01
Predicting the performance of large scale plants can be difficult due to model uncertainties etc, meaning that one can be almost certain that the prediction will diverge from the plant performance with time. In this paper output multiplicative uncertainty models are used as dynamical models of th...... models, is applied to two different sets of measured plant data. The computed uncertainty bounds cover the measured plant output, while the nominal prediction is outside these uncertainty bounds for some samples in these examples. ......Predicting the performance of large scale plants can be difficult due to model uncertainties etc, meaning that one can be almost certain that the prediction will diverge from the plant performance with time. In this paper output multiplicative uncertainty models are used as dynamical models...... of the prediction error. These proposed dynamical uncertainty models result in an upper and lower bound on the predicted performance of the plant. The dynamical uncertainty models are used to estimate the uncertainty of the predicted performance of a coal-fired power plant. The proposed scheme, which uses dynamical...
风电功率预测研究%Study on Prediction of Wind Power
张晓焱
2015-01-01
The output power of wind power generation has the characteristics of volatility and unpredictability,which wil increase the difficulty of regional power planning and bring huge chal enges to the safety, economic operation of electric power system. Therefore, high accuracy prediction of wind power can ease a series of problems caused by large scale wind power integration in a certain extent. This paper analyzes how to quantitatively describe the volatility of wind power.%风力发电输出功率具有波动性、不可准确预测的特点，当风电大规模接入后，将提升该区域发电计划难度，给电力系统的安全、经济运行带来巨大的挑战。所以，对风电功率进行高精度预测可以在一定程度上缓解风电大规模并网造成的一系列问题。本文就如何定量地描述风电功率的波动性，即风电功率预测展开分析。
Quan, Hao; Srinivasan, Dipti; Khosravi, Abbas
2015-09-01
Penetration of renewable energy resources, such as wind and solar power, into power systems significantly increases the uncertainties on system operation, stability, and reliability in smart grids. In this paper, the nonparametric neural network-based prediction intervals (PIs) are implemented for forecast uncertainty quantification. Instead of a single level PI, wind power forecast uncertainties are represented in a list of PIs. These PIs are then decomposed into quantiles of wind power. A new scenario generation method is proposed to handle wind power forecast uncertainties. For each hour, an empirical cumulative distribution function (ECDF) is fitted to these quantile points. The Monte Carlo simulation method is used to generate scenarios from the ECDF. Then the wind power scenarios are incorporated into a stochastic security-constrained unit commitment (SCUC) model. The heuristic genetic algorithm is utilized to solve the stochastic SCUC problem. Five deterministic and four stochastic case studies incorporated with interval forecasts of wind power are implemented. The results of these cases are presented and discussed together. Generation costs, and the scheduled and real-time economic dispatch reserves of different unit commitment strategies are compared. The experimental results show that the stochastic model is more robust than deterministic ones and, thus, decreases the risk in system operations of smart grids.
Air quality measurements versus model predictions: a case study for the Sugozu power plant
A. Korur; C. Derinoz; C. Yurteri [ENVY Energy and Environmental Investments Inc., Ankara (Turkey)
2003-07-01
Air quality modeling is one of the tools used in Environmental Impact Assessment (EIA) studies in order to predict the potential impacts of atmospheric emissions. The main advantage of air quality modeling is the simulation of the ground-level concentrations under different conditions (i.e., meteorological variations and other pollutant sources in the vicinity). The accuracy of model predictions, on the other hand, depends mainly on the quality of the input data reflecting meteorological and topographical conditions as well as emission sources. In this regard, the model predictions should be supported with monitoring data. In the paper, the predictions of Gaussian air dispersion model (Industrial Source Complex - ISC) for SO{sub 2} and NO{sub 2} carried out in the vicinity of the Sugozu Power Plant on the coast of Turkey are compared with the air quality monitoring results of the same region. 2 refs., 3 figs., 2 tabs.
Multivariate power-law models for streamflow prediction in the Mekong Basin
Guillaume Lacombe
2014-11-01
New hydrological insights for the region: A combination of 3–6 explanatory variables – chosen among annual rainfall, drainage area, perimeter, elevation, slope, drainage density and latitude – is sufficient to predict a range of flow metrics with a prediction R-squared ranging from 84 to 95%. The inclusion of forest or paddy percentage coverage as an additional explanatory variable led to slight improvements in the predictive power of some of the low-flow models (lowest prediction R-squared = 89%. A physical interpretation of the model structure was possible for most of the resulting relationships. Compared to regional regression models developed in other parts of the world, this new set of equations performs reasonably well.
Predictions for the 21cm-galaxy cross-power spectrum observable with LOFAR and Subaru
Vrbanec, Dijana; Jelić, Vibor; Jensen, Hannes; Zaroubi, Saleem; Fernandez, Elizabeth R; Ghosh, Abhik; Iliev, Ilian T; Kakiichi, Koki; Koopmans, Léon V E; Mellema, Garrelt
2016-01-01
The 21cm-galaxy cross-power spectrum is expected to be one of the promising probes of the Epoch of Reionization (EoR), as it could offer information about the progress of reionization and the typical scale of ionized regions at different redshifts. With upcoming observations of 21cm emission from the EoR with the Low Frequency Array (LOFAR), and of high redshift Lyalpha emitters (LAEs) with Subaru's Hyper Suprime Cam (HSC), we investigate the observability of such cross-power spectrum with these two instruments, which are both planning to observe the ELAIS-N1 field at z=6.6. In this paper we use N-body + radiative transfer (both for continuum and Lyalpha photons) simulations at redshift 6.68, 7.06 and 7.3 to compute the 3D theoretical 21cm-galaxy cross-power spectrum, as well as to predict the 2D 21cm-galaxy cross-power spectrum expected to be observed by LOFAR and HSC. Once noise and projection effects are accounted for, our predictions of the 21cm-galaxy cross-power spectrum show clear anti-correlation on s...
Gritti, Fabrice; Gilar, Martin; Jarrell, Joseph A
2016-04-29
A cylindrical vacuum chamber (inner diameter 5 cm) housing a narrow-bore 2.1 mm×100 mm column packed with 1.8 μm HSS-T3 fully porous particles was built in order to isolate thermally the chromatographic column from the external air environment. Consistent with statistical physics and the mean free path of air molecules, the experimental results show that natural air convection and conduction are fully eliminated for housing air pressures smaller than 10(-4) Torr. Heat radiation is minimized by wrapping up the column with low-emissivity aluminum-tape (emissivity coefficient ϵ=0.03 vs. 0.28 for polished stainless steel 316). Overall, the heat flux at the column wall is reduced by 96% with respect to standard still-air ovens. From a practical viewpoint, the efficiency of the column run at a flow rate of 0.6 mL/min at a constant 13,000 psi pressure drop (the viscous heat power is around 9 W/m) is improved by up to 35% irrespective of the analyte retention. Models of heat and mass transfer reveal that (1) the amplitude of the radial temperature gradient is significantly reduced from 0.30 to 0.01 K and (2) the observed improvement in resolution power stems from a more uniform distribution of the flow velocity across the column diameter. The eddy dispersion term in the van Deemter equation is reduced by 0.8±0.1 reduced plate height unit, a significant gain in column performance. Copyright © 2016 Elsevier B.V. All rights reserved.
Adaptive ultra-short-term wind power prediction based on risk assessment
Xue, Yusheng; Yu, Chen; Li, Kang;
2016-01-01
A risk assessment based adaptive ultra-short-term wind power prediction (USTWPP) method is proposed in this paper. The method first extracts features from the historical data, and split every wind power time series (WPTS) into several subsets defined by their stationary patterns. A WPTS that does...... not match with any of the stationary patterns is then included into a subset of non-stationary patterns. Every WPTS subset is then related to a USTWPP model which is specially selected and optimized offline based on the proposed risk assessment index. For on-line applications, the pattern of the last short...
Detailed analysis of the predictions of loop quantum cosmology for the primordial power spectra
Agullo, Ivan
2015-01-01
We provide an exhaustive numerical exploration of the predictions of loop quantum cosmology (LQC) with a post-bounce phase of inflation for the primordial power spectrum of scalar and tensor perturbations. We extend previous analysis by characterizing the phenomenologically relevant parameter space and by constraining it using observations. Furthermore, we characterize the shape of LQC-corrections to observable quantities across this parameter space. Our analysis provides a framework to contrast more accurately the theory with forthcoming polarization data, and it also paves the road for the computation of other observables beyond the power spectra, such as non-Gaussianity.
Model Predictive Current Control for High-Power Grid-Connected Converters with Output LCL Filter
Delpino, Hernan Anres Miranda; Teodorescu, Remus; Rodriguez, Pedro
2009-01-01
A model predictive control strategy for a highpower, grid connected 3-level neutral clamped point converter is presented. Power losses constraints set a limit on commutation losses so reduced switching frequency is required, thus producing low frequency current harmonics. To reduce these harmonics...... an LCL filter is used. The proposed control strategy allows control of the active and reactive power fed into the grid, reduce the switching frequency within acceptable operational margins and keep balance of the DC-link capacitor voltages while avoiding excitation of the filter resonance frequencies....
Determination of Aerobic Power Through a Specific Test for Taekwondo - A Predictive Equation Model
Rocha Fernando P.S.
2016-12-01
Full Text Available Our aim was to verify the concurrent validity of a maximal taekwondo specific test (TST to predict VO2max through an explanatory model. Seventeen elite male taekwondo athletes (age: 17.59 ± 4.34 years; body height: 1.72 ± 6.5 m; body mass: 61.3 ± 8.7 kg performed two graded maximal exercise tests on different days: a 20 m multistage shuttle run test (SRT and an incremental TST. We recorded test time, VO2max, ventilation, a heart rate and time to exhaustion. Significant differences were found between observed and estimated VO2max values [F (2, 16 = 5.77, p < 0.01]; post-hoc subgroup analysis revealed the existence of significant differences (p = 0.04 between the estimated VO2max value in the SRT and the observed value recorded in the TST (58.4 ± 6.4 ml/kg/min and 52.6 ± 5.2 ml/kg/min, respectively. Our analysis also revealed a moderate correlation between both testing protocols regarding VO2max (r = 0.70; p = 0.005, test time (r = 0.77; p = 0.02 and ventilation (r = 0.69; p = 0.03. There was no proportional bias in the mean difference (t = -1.04; p = 0.313, and there was a level of agreement between both tests. An equation/model was used to estimate VO2max during the TST based on the mean heart rate, test time, body height and mass, which explained 74.3% of the observed VO2max variability. A moderate correlation was found between the observed and predicted VO2max values in the taekwondo TST (r = 0.74, p = 0.001. Our results suggest that an incremental specific test estimates VO2max of elite taekwondo athletes with acceptable concurrent validity.
Swarm Intelligence-Based Hybrid Models for Short-Term Power Load Prediction
Jianzhou Wang
2014-01-01
Full Text Available Swarm intelligence (SI is widely and successfully applied in the engineering field to solve practical optimization problems because various hybrid models, which are based on the SI algorithm and statistical models, are developed to further improve the predictive abilities. In this paper, hybrid intelligent forecasting models based on the cuckoo search (CS as well as the singular spectrum analysis (SSA, time series, and machine learning methods are proposed to conduct short-term power load prediction. The forecasting performance of the proposed models is augmented by a rolling multistep strategy over the prediction horizon. The test results are representative of the out-performance of the SSA and CS in tuning the seasonal autoregressive integrated moving average (SARIMA and support vector regression (SVR in improving load forecasting, which indicates that both the SSA-based data denoising and SI-based intelligent optimization strategy can effectively improve the model’s predictive performance. Additionally, the proposed CS-SSA-SARIMA and CS-SSA-SVR models provide very impressive forecasting results, demonstrating their strong robustness and universal forecasting capacities in terms of short-term power load prediction 24 hours in advance.
PID and predictive control of electrical drives and power converters using MATLAB/Simulink
Wang, Liuping; Yoo, Dae; Gan, Lu; Ng, Ki
2015-01-01
A timely introduction to current research on PID and predictive control by one of the leading authors on the subject PID and Predictive Control of Electric Drives and Power Supplies using MATLAB/Simulink examines the classical control system strategies, such as PID control, feed-forward control and cascade control, which are widely used in current practice. The authors share their experiences in actual design and implementation of the control systems on laboratory test-beds, taking the reader from the fundamentals through to more sophisticated design and analysis. The book contains secti
Capacity Maximizing Constellations
Barsoum, Maged; Jones, Christopher
2010-01-01
Some non-traditional signal constellations have been proposed for transmission of data over the Additive White Gaussian Noise (AWGN) channel using such channel-capacity-approaching codes as low-density parity-check (LDPC) or turbo codes. Computational simulations have shown performance gains of more than 1 dB over traditional constellations. These gains could be translated to bandwidth- efficient communications, variously, over longer distances, using less power, or using smaller antennas. The proposed constellations have been used in a bit-interleaved coded modulation system employing state-ofthe-art LDPC codes. In computational simulations, these constellations were shown to afford performance gains over traditional constellations as predicted by the gap between the parallel decoding capacity of the constellations and the Gaussian capacity
Rudiger Bubner
1998-12-01
Full Text Available Even though the maxims' theory is not at thecenter of Kant's ethics, it is the unavoidable basis of the categoric imperative's formulation. Kant leanson the transmitted representations of modem moral theory. During the last decades, the notion of maxims has deserved more attention, due to the philosophy of language's debates on rules, and due to action theory's interest in this notion. I here by brietly expound my views in these discussions.
Line Brotnow
Full Text Available Mothers' stress in pregnancy is considered an environmental risk factor in child development. Multiple stressors may combine to increase risk, and maternal personal characteristics may offset the effects of stress. This study aimed to test the effect of 1 multifactorial prenatal stress, integrating objective "stressors" and subjective "distress" and 2 the moderating effects of maternal characteristics (perceived social support, self-esteem and specific personality traits on infant birthweight.Hierarchical regression modeling was used to examine cross-sectional data on 403 birth mothers and their newborns from an adoption study.Distress during pregnancy showed a statistically significant association with birthweight (R2 = 0.032, F(2, 398 = 6.782, p = .001. The hierarchical regression model revealed an almost two-fold increase in variance of birthweight predicted by stressors as compared with distress measures (R2Δ = 0.049, F(4, 394 = 5.339, p < .001. Further, maternal characteristics moderated this association (R2Δ = 0.031, F(4, 389 = 3.413, p = .009. Specifically, the expected benefit to birthweight as a function of higher SES was observed only for mothers with lower levels of harm-avoidance and higher levels of perceived social support. Importantly, the results were not better explained by prematurity, pregnancy complications, exposure to drugs, alcohol or environmental toxins.The findings support multidimensional theoretical models of prenatal stress. Although both objective stressors and subjectively measured distress predict birthweight, they should be considered distinct and cumulative components of stress. This study further highlights that jointly considering risk factors and protective factors in pregnancy improves the ability to predict birthweight.
Han, Seung-Ryong; Guikema, Seth D; Quiring, Steven M
2009-10-01
Electric power is a critical infrastructure service after hurricanes, and rapid restoration of electric power is important in order to minimize losses in the impacted areas. However, rapid restoration of electric power after a hurricane depends on obtaining the necessary resources, primarily repair crews and materials, before the hurricane makes landfall and then appropriately deploying these resources as soon as possible after the hurricane. This, in turn, depends on having sound estimates of both the overall severity of the storm and the relative risk of power outages in different areas. Past studies have developed statistical, regression-based approaches for estimating the number of power outages in advance of an approaching hurricane. However, these approaches have either not been applicable for future events or have had lower predictive accuracy than desired. This article shows that a different type of regression model, a generalized additive model (GAM), can outperform the types of models used previously. This is done by developing and validating a GAM based on power outage data during past hurricanes in the Gulf Coast region and comparing the results from this model to the previously used generalized linear models.
Short-term load and wind power forecasting using neural network-based prediction intervals.
Quan, Hao; Srinivasan, Dipti; Khosravi, Abbas
2014-02-01
Electrical power systems are evolving from today's centralized bulk systems to more decentralized systems. Penetrations of renewable energies, such as wind and solar power, significantly increase the level of uncertainty in power systems. Accurate load forecasting becomes more complex, yet more important for management of power systems. Traditional methods for generating point forecasts of load demands cannot properly handle uncertainties in system operations. To quantify potential uncertainties associated with forecasts, this paper implements a neural network (NN)-based method for the construction of prediction intervals (PIs). A newly introduced method, called lower upper bound estimation (LUBE), is applied and extended to develop PIs using NN models. A new problem formulation is proposed, which translates the primary multiobjective problem into a constrained single-objective problem. Compared with the cost function, this new formulation is closer to the primary problem and has fewer parameters. Particle swarm optimization (PSO) integrated with the mutation operator is used to solve the problem. Electrical demands from Singapore and New South Wales (Australia), as well as wind power generation from Capital Wind Farm, are used to validate the PSO-based LUBE method. Comparative results show that the proposed method can construct higher quality PIs for load and wind power generation forecasts in a short time.
Artificial Neural Networks to Predict the Power Output of a PV Panel
Valerio Lo Brano
2014-01-01
Full Text Available The paper illustrates an adaptive approach based on different topologies of artificial neural networks (ANNs for the power energy output forecasting of photovoltaic (PV modules. The analysis of the PV module’s power output needed detailed local climate data, which was collected by a dedicated weather monitoring system. The Department of Energy, Information Engineering, and Mathematical Models of the University of Palermo (Italy has built up a weather monitoring system that worked together with a data acquisition system. The power output forecast is obtained using three different types of ANNs: a one hidden layer Multilayer perceptron (MLP, a recursive neural network (RNN, and a gamma memory (GM trained with the back propagation. In order to investigate the influence of climate variability on the electricity production, the ANNs were trained using weather data (air temperature, solar irradiance, and wind speed along with historical power output data available for the two test modules. The model validation was performed by comparing model predictions with power output data that were not used for the network's training. The results obtained bear out the suitability of the adopted methodology for the short-term power output forecasting problem and identified the best topology.
Prediction and attendance of Angra 2 nuclear power plant cycle extension
Dias, Amory [ELETROBRAS Termonuclear S.A. - ELETRONUCLEAR, Rio de Janeiro, RJ (Brazil)]. E-mail: adias@eletronuclear.gov.br; Ferreira Junior, Decio Brandes M.; Morgado, Mario Monteiro; Santos, Barbara Oliveira dos; Oliveira, Monica Georgia Nunes [ELETROBRAS Termonuclear S.A. - ELETRONUCLEAR, Angra dos Reis, RJ (Brazil)]. E-mails: deciobr@eletronuclear.gov.br; mariomm@eletronuclear.gov.br; oliveira@eletronuclear.gov.br; mongeor@eletronuclear.gov.br
2007-07-01
The Report Project Nuclear and Thermohydraulic (RPNT) of the Nuclear Power Plant Angra 2 previews extension of the cycle, using a feedback of core reactor reactivity, through the reduction of the moderator average temperature and power. In this phase, the reactor power remains almost invariable. Furthermore, the extension of cycle can be stretch after the limit of the temperature reduction has been reached, through of reactor power fall until the determined date for the end cycle and the start outage for the next cycle. The proposal of this work is to show the Power Plant results during the phase of moderator temperature reduction and to compare with the predict values obtained from reactivity balance calculation methodology used for the Reactor Physics. In general, the results of this work can collaborate for the extension behavior evaluation of the cycles of the Nuclear Power Plant 2, being used the procedure of cooling reduction average temperature, as well as, it will also collaborate for methodology qualification applied for the Reactor Physics during the reactivity balance calculation. (author)
RAPID program to predict radial power and burnup distribution of UO{sub 2} fuel
Lee, Chan Bock; Song, Jae Sung; Bang, Je Gun; Kim, Dae Ho [Korea Atomic Energy Research Institute, Taejon (Korea)
1999-02-01
Due to the radial variation of the neutron flux and its energy spectrum inside UO{sub 2} fuel, the fission density and fissile isotope production rates are varied radially in the pellet, and it becomes necessary to know the accurate radial power and burnup variation to predict the high burnup fuel behavior such as rim effects. Therefore, to predict the radial distribution of power, burnup and fissionable nuclide densities in the pellet with the burnup and U-235 enrichment, RAPID(RAdial power and burnup Prediction by following fissile Isotope Distribution in the pellet) program was developed. It considers the specific radial variation of the neutron reaction of the nuclides while the constant radial variation of neutron reaction except neutron absorption of U-238 regardless of the nuclides, the burnup and U-235 enrichment is assumed in TUBRNP model which is recognized as the one of the most reliable models. Therefore, it is expected that RAPID may be more accurate than TUBRNP, specially at high burnup region. RAPID is based upon and validated by the detailed reactor physics code, HELIOS which is one of few codes that can calculates the radial variations of the nuclides inside the pellet. Comparison of RAPID prediction with the measured data of the irradiated fuels showed very good agreement. RAPID can be used to calculate the local variations of the fissionable nuclide concentrations as well as the local power and burnup inside that pellet as a function of the burnup up to 10 w/o U-235 enrichment and 150 MWD/kgU burnup under the LWR environment. (author). 8 refs., 50 figs., 1 tab.
C. Muniraj; Chandrasekar, S
2011-01-01
This paper presents the prediction of pollution severity of the polymeric insulators used in power transmission lines using adaptive neurofuzzy inference system (ANFIS) model. In this work, laboratory-based pollution performance tests were carried out on 11 kV silicone rubber polymeric insulator under AC voltage at different pollution levels with sodium chloride as a contaminant. Leakage current was measured during the laboratory tests. Time domain and frequency domain characteristics of leak...
Steady-state plant model to predict hydrogen levels in power plant components
Glatzmaier, Greg C.; Cable, Robert; Newmarker, Marc
2017-06-01
The National Renewable Energy Laboratory (NREL) and Acciona Energy North America developed a full-plant steady-state computational model that estimates levels of hydrogen in parabolic trough power plant components. The model estimated dissolved hydrogen concentrations in the circulating heat transfer fluid (HTF), and corresponding partial pressures within each component. Additionally for collector field receivers, the model estimated hydrogen pressure in the receiver annuli. The model was developed to estimate long-term equilibrium hydrogen levels in power plant components, and to predict the benefit of hydrogen mitigation strategies for commercial power plants. Specifically, the model predicted reductions in hydrogen levels within the circulating HTF that result from purging hydrogen from the power plant expansion tanks at a specified target rate. Our model predicted hydrogen partial pressures from 8.3 mbar to 9.6 mbar in the power plant components when no mitigation treatment was employed at the expansion tanks. Hydrogen pressures in the receiver annuli were 8.3 to 8.4 mbar. When hydrogen partial pressure was reduced to 0.001 mbar in the expansion tanks, hydrogen pressures in the receiver annuli fell to a range of 0.001 mbar to 0.02 mbar. When hydrogen partial pressure was reduced to 0.3 mbar in the expansion tanks, hydrogen pressures in the receiver annuli fell to a range of 0.25 mbar to 0.28 mbar. Our results show that controlling hydrogen partial pressure in the expansion tanks allows us to reduce and maintain hydrogen pressures in the receiver annuli to any practical level.
Steady-State Plant Model to Predict Hydroden Levels in Power Plant Components
Glatzmaier, Greg C.; Cable, Robert; Newmarker, Marc
2017-06-27
The National Renewable Energy Laboratory (NREL) and Acciona Energy North America developed a full-plant steady-state computational model that estimates levels of hydrogen in parabolic trough power plant components. The model estimated dissolved hydrogen concentrations in the circulating heat transfer fluid (HTF), and corresponding partial pressures within each component. Additionally for collector field receivers, the model estimated hydrogen pressure in the receiver annuli. The model was developed to estimate long-term equilibrium hydrogen levels in power plant components, and to predict the benefit of hydrogen mitigation strategies for commercial power plants. Specifically, the model predicted reductions in hydrogen levels within the circulating HTF that result from purging hydrogen from the power plant expansion tanks at a specified target rate. Our model predicted hydrogen partial pressures from 8.3 mbar to 9.6 mbar in the power plant components when no mitigation treatment was employed at the expansion tanks. Hydrogen pressures in the receiver annuli were 8.3 to 8.4 mbar. When hydrogen partial pressure was reduced to 0.001 mbar in the expansion tanks, hydrogen pressures in the receiver annuli fell to a range of 0.001 mbar to 0.02 mbar. When hydrogen partial pressure was reduced to 0.3 mbar in the expansion tanks, hydrogen pressures in the receiver annuli fell to a range of 0.25 mbar to 0.28 mbar. Our results show that controlling hydrogen partial pressure in the expansion tanks allows us to reduce and maintain hydrogen pressures in the receiver annuli to any practical level.
Rufibach, Kaspar; Burger, Hans Ulrich; Abt, Markus
2016-09-01
Bayesian predictive power, the expectation of the power function with respect to a prior distribution for the true underlying effect size, is routinely used in drug development to quantify the probability of success of a clinical trial. Choosing the prior is crucial for the properties and interpretability of Bayesian predictive power. We review recommendations on the choice of prior for Bayesian predictive power and explore its features as a function of the prior. The density of power values induced by a given prior is derived analytically and its shape characterized. We find that for a typical clinical trial scenario, this density has a u-shape very similar, but not equal, to a β-distribution. Alternative priors are discussed, and practical recommendations to assess the sensitivity of Bayesian predictive power to its input parameters are provided. Copyright © 2016 John Wiley & Sons, Ltd.
Neural Network Ensemble Based Approach for 2D-Interval Prediction of Solar Photovoltaic Power
Mashud Rana
2016-10-01
Full Text Available Solar energy generated from PhotoVoltaic (PV systems is one of the most promising types of renewable energy. However, it is highly variable as it depends on the solar irradiance and other meteorological factors. This variability creates difficulties for the large-scale integration of PV power in the electricity grid and requires accurate forecasting of the electricity generated by PV systems. In this paper we consider 2D-interval forecasts, where the goal is to predict summary statistics for the distribution of the PV power values in a future time interval. 2D-interval forecasts have been recently introduced, and they are more suitable than point forecasts for applications where the predicted variable has a high variability. We propose a method called NNE2D that combines variable selection based on mutual information and an ensemble of neural networks, to compute 2D-interval forecasts, where the two interval boundaries are expressed in terms of percentiles. NNE2D was evaluated for univariate prediction of Australian solar PV power data for two years. The results show that it is a promising method, outperforming persistence baselines and other methods used for comparison in terms of accuracy and coverage probability.
Power prediction in mobile communication systems using an optimal neural-network structure.
Gao, X M; Gao, X Z; Tanskanen, J A; Ovaska, S J
1997-01-01
Presents a novel neural-network-based predictor for received power level prediction in direct sequence code division multiple access (DS/CDMA) systems. The predictor consists of an adaptive linear element (Adaline) followed by a multilayer perceptron (MLP). An important but difficult problem in designing such a cascade predictor is to determine the complexity of the networks. We solve this problem by using the predictive minimum description length (PMDL) principle to select the optimal numbers of input and hidden nodes. This approach results in a predictor with both good noise attenuation and excellent generalization capability. The optimized neural networks are used for predictive filtering of very noisy Rayleigh fading signals with 1.8 GHz carrier frequency. Our results show that the optimal neural predictor can provide smoothed in-phase and quadrature signals with signal-to-noise ratio (SNR) gains of about 12 and 7 dB at the urban mobile speeds of 5 and 50 km/h, respectively. The corresponding power signal SNR gains are about 11 and 5 dB. Therefore, the neural predictor is well suitable for power control applications where ldquodelaylessrdquo noise attenuation and efficient reduction of fast fading are required.
Measuring the benefits of climate forecasts in predicting PV power production
De Felice, Matteo; Alessandri, Andrea; Pollino, Maurizio
2016-04-01
Surface solar radiation is an important variable to model and predict solar power output. Having accurate forecast may be of potential use for planning and operational tasks, both at short- and long-time scales. This study examines the predictability of seasonal surface solar radiation comparing ECMWF System4 Seasonal operational forecasts the SARAH Satellite Dataset on the period 1984-2007. This work tries to answer the following question: how useful are climate forecasts in predicting seasonal PV production? The "information layer" provided by climate information is overlapped with 1) the information about the land cover (CLC2006) to consider the potential amount of land available for PV panels and 2) the information about the solar power installed capacity for European region in order to define the areas where an improved forecast could have a bigger impact. All the information layers are summarised by using a simple scalar index (Index of Opportunity) computed for all the European regions for the four seasons. The results are very interesting, in fact the potential benefits of climate forecasts are not (only) related to their statistical skills (e.g. probabilistic scores) but also to the actual and potential installed capacity of solar power. Here, we show that to assess the usefulness of climate forecasts in the energy sector we should use all the relevant information layers, combining them according to the "needs" of the potential users.
Predicted and verified evolution of power-law exponent in product market
Hisano, Ryohei; Mizuno, Takayuki
2011-01-01
Power-law distributions constitute a generic empirical statistical regularity found in many complex systems. A recently developed theory finds that the interplay between one of the most universal ingredient, i.e., stochastic proportional growth, and stochastic birth and death processes, leads to generic power law distributions together with a non-universal exponent which depends explicitly on the characteristics of growth, birth and death. In particular, the theory rationalizes Zipf's law and explains deviations from it, for instance for the distribution of firm and of city sizes. Here, we report the first complete test of the theory, based on the empirical analysis from a real world complex phenomenon, namely the dynamics of market shares in the consumer electronics market. We estimate directly from the data the average growth rate of market shares, their standard deviation, the birth rates as well as the "death" hazard rate of products. When plugged in the theory, this predicts the power law exponent of the...
Combined Active and Reactive Power Control of Wind Farms based on Model Predictive Control
Zhao, Haoran; Wu, Qiuwei; Wang, Jianhui;
2017-01-01
This paper proposes a combined wind farm controller based on Model Predictive Control (MPC). Compared with the conventional decoupled active and reactive power control, the proposed control scheme considers the significant impact of active power on voltage variations due to the low X=R ratio...... of wind farm collector systems. The voltage control is improved. Besides, by coordination of active and reactive power, the Var capacity is optimized to prevent potential failures due to Var shortage, especially when the wind farm operates close to its full load. An analytical method is used to calculate...... the sensitivity coefficients to improve the computation efficiency and overcome the convergence problem. Two control modes are designed for both normal and emergency conditions. A wind farm with 20 wind turbines was used to verify the proposed combined control scheme....
Research on Short-Term Wind Power Prediction Based on Combined Forecasting Models
Zhang Chi
2016-01-01
Full Text Available Short-Term wind power forecasting is crucial for power grid since the generated energy of wind farm fluctuates frequently. In this paper, a physical forecasting model based on NWP and a statistical forecasting model with optimized initial value in the method of BP neural network are presented. In order to make full use of the advantages of the models presented and overcome the limitation of the disadvantage, the equal weight model and the minimum variance model are established for wind power prediction. Simulation results show that the combination forecasting model is more precise than single forecasting model and the minimum variance combination model can dynamically adjust weight of each single method, restraining the forecasting error further.
Power Prediction Model for Turning EN-31 Steel Using Response Surface Methodology
M. Hameedullah
2010-01-01
Full Text Available Power consumption in turning EN-31 steel (a material that is most extensively used in automotive industry with tungstencarbide tool under different cutting conditions was experimentally investigated. The experimental runs were planned accordingto 24+8 added centre point factorial design of experiments, replicated thrice. The data collected was statisticallyanalyzed using Analysis of Variance technique and first order and second order power consumption prediction models weredeveloped by using response surface methodology (RSM. It is concluded that second-order model is more accurate than thefirst-order model and fit well with the experimental data. The model can be used in the automotive industries for decidingthe cutting parameters for minimum power consumption and hence maximum productivity
Linear Predictive Detection for Power Line Communications Impaired by Colored Noise
Pighi Riccardo
2007-01-01
Full Text Available Robust detection algorithms capable of mitigating the effects of colored noise are of primary interest in communication systems operating on power line channels. In this paper, we present a sequence detection scheme based on linear prediction to be applied in single-carrier power line communications impaired by colored noise. The presence of colored noise and the need for statistical sufficiency requires the design of an optimal front-end stage, whereas the need for a low-complexity solution suggests a more practical suboptimal front-end. The performance of receivers employing both optimal and suboptimal front-ends has been assessed by means of minimum mean square prediction error (MMSPE analysis and bit-error rate (BER simulations. We show that the proposed optimal solution improves the BER performance with respect to conventional systems and makes the receiver more robust against colored noise. As case studies, we investigate the performance of the proposed receivers in a low-voltage (LV power line channel limited by colored background noise and in a high-voltage (HV power line channel limited by corona noise.
Razi M.
2017-01-01
Full Text Available Tremendous studied had been conducted on small hydropower system based on run-of-river schemes as an alternative renewable energy. Small hydropower system can be classified based on electricity generated between 1MW to 10MW. This system is normally being applied in rural area for providing the consumer electricity demand. Basically the researches to date are more focusing on the large scale of hydropower rather than the small scale hydropower technology. Therefore, this study is aimed to focus on predicting the available power generated by the small hydropower system specifically for the river stream in peninsular Malaysia. The water flow rate is measured by using ultrasonic level sensor located at the intake of the small hydropower system. The water flow rate is important data to be used in predicting the power output of the power house. The result shows that, the power outputs are depending on the fluctuation of water flow rate and the electricity being generated is more than 1MW. This finding can be used as the benchmark for daily and monthly monitoring process of the system efficiency or target output.
Power-Controlled MAC Protocols with Dynamic Neighbor Prediction for Ad hoc Networks
LI Meng; ZHANG Lin; XIAO Yong-kang; SHAN Xiu-ming
2004-01-01
Energy and bandwidth are the scarce resources in ad hoc networks because most of the mobile nodes are battery-supplied and share the exclusive wireless medium. Integrating the power control into MAC protocol is a promising technique to fully exploit these precious resources of ad hoc wireless networks. In this paper, a new intelligent power-controlled Medium Access Control (MAC) (iMAC) protocol with dynamic neighbor prediction is proposed. Through the elaborate design of the distributed transmit-receive strategy of mobile nodes, iMAC greatly outperforms the prevailing IEEE 802.11 MAC protocols in not only energy conservation but also network throughput. Using the Dynamic Neighbor Prediction (DNP), iMAC performs well in mobile scenes. To the best of our knowledge, iMAC is the first protocol that considers the performance deterioration of power-controlled MAC protocols in mobile scenes and then proposes a solution. Simulation results indicate that DNP is important and necessary for power-controlled MAC protocols in mobile ad hoc networks.
Performance Prediction of Active Piezo Fiber Rackets in Terms of Tennis Power
Kawazoe, Yoshihiko; Takeda, Yukihiro; Nakagawa, Masamichi
Several former top players sent a letter to the International Tennis Federation (ITF) encouraging the governing body to revisit the question of rackets. In the letter, the players wrote that racket technology has led to major changes in how the game is played at the top level. This paper investigated the physical properties of a new type of racket with active piezoelectric fibers appeared recently in the market, and predicted the various factors associated with the frontal impact, such as impact force, contact time, deformation of ball and strings, and also estimated the racket performance such as the coefficient of restitution, the rebound power coefficient, the post-impact ball velocity and the sweet areas relevant to the power in tennis. It is based on the experimental identification of the dynamics of the ball-racket-arm system and the approximate nonlinear impact analysis with a simple swing model. The predicted results with forehand stroke model can explain the difference in mechanism of performance between the new type racket with active piezoelectric fibers and the conventional passive representative rackets. It showed that this new type racket provides higher coefficient of restitution on the whole area of string face and also gives larger rebound power coefficients particularly at the topside and bigger powers on the whole area of string face but the difference was not so large. It seems that the racket-related improvements in play are relatively small and the players themselves continue to improve, accordingly there is a gap between a perception and reality.
Drag prediction method of powered-on civil aircraft based on thrust drag bookkeeping
Zhang Yufei
2015-08-01
Full Text Available A drag prediction method based on thrust drag bookkeeping (TDB is introduced for civil jet propulsion/airframe integration performance analysis. The method is derived from the control volume theory of a powered-on nacelle. Key problem of the TDB is identified to be accurate prediction of velocity coefficient of the powered-on nacelle. Accuracy of CFD solver is validated by test cases of the first AIAA Propulsion Aerodynamics Workshop. Then the TDB method is applied to thrust and drag decomposing of a realistic aircraft. A linear relation between the computations assumed free stream Mach number and the velocity coefficient result is revealed. The thrust losses caused by nozzle internal drag and pylon scrubbing are obtained by the isolated nacelle and mapped on to the in-flight whole configuration analysis. Effects of the powered-on condition are investigated by comparing through-flow configuration with powered-on configuration. The variance on aerodynamic coefficients and pressure distribution is numerically studied.
Linear Predictive Detection for Power Line Communications Impaired by Colored Noise
Riccardo Raheli
2007-01-01
Full Text Available Robust detection algorithms capable of mitigating the effects of colored noise are of primary interest in communication systems operating on power line channels. In this paper, we present a sequence detection scheme based on linear prediction to be applied in single-carrier power line communications impaired by colored noise. The presence of colored noise and the need for statistical sufficiency requires the design of an optimal front-end stage, whereas the need for a low-complexity solution suggests a more practical suboptimal front-end. The performance of receivers employing both optimal and suboptimal front-ends has been assessed by means of minimum mean square prediction error (MMSPE analysis and bit-error rate (BER simulations. We show that the proposed optimal solution improves the BER performance with respect to conventional systems and makes the receiver more robust against colored noise. As case studies, we investigate the performance of the proposed receivers in a low-voltage (LV power line channel limited by colored background noise and in a high-voltage (HV power line channel limited by corona noise.
Qureshi, Abid; Tandon, Himani; Kumar, Manoj
2015-11-01
Peptide-based antiviral therapeutics has gradually paved their way into mainstream drug discovery research. Experimental determination of peptides' antiviral activity as expressed by their IC50 values involves a lot of effort. Therefore, we have developed "AVP-IC50 Pred," a regression-based algorithm to predict the antiviral activity in terms of IC50 values (μM). A total of 759 non-redundant peptides from AVPdb and HIPdb were divided into a training/test set having 683 peptides (T(683)) and a validation set with 76 independent peptides (V(76)) for evaluation. We utilized important peptide sequence features like amino-acid compositions, binary profile of N8-C8 residues, physicochemical properties and their hybrids. Four different machine learning techniques (MLTs) namely Support vector machine, Random Forest, Instance-based classifier, and K-Star were employed. During 10-fold cross validation, we achieved maximum Pearson correlation coefficients (PCCs) of 0.66, 0.64, 0.56, 0.55, respectively, for the above MLTs using the best combination of feature sets. All the predictive models also performed well on the independent validation dataset and achieved maximum PCCs of 0.74, 0.68, 0.59, 0.57, respectively, on the best combination of feature sets. The AVP-IC50 Pred web server is anticipated to assist the researchers working on antiviral therapeutics by enabling them to computationally screen many compounds and focus experimental validation on the most promising set of peptides, thus reducing cost and time efforts. The server is available at http://crdd.osdd.net/servers/ic50avp.
Asymptotics of robust utility maximization
Knispel, Thomas
2012-01-01
For a stochastic factor model we maximize the long-term growth rate of robust expected power utility with parameter $\\lambda\\in(0,1)$. Using duality methods the problem is reformulated as an infinite time horizon, risk-sensitive control problem. Our results characterize the optimal growth rate, an optimal long-term trading strategy and an asymptotic worst-case model in terms of an ergodic Bellman equation. With these results we propose a duality approach to a "robust large deviations" criterion for optimal long-term investment.
Data Analytics Based Dual-Optimized Adaptive Model Predictive Control for the Power Plant Boiler
Zhenhao Tang
2017-01-01
Full Text Available To control the furnace temperature of a power plant boiler precisely, a dual-optimized adaptive model predictive control (DoAMPC method is designed based on the data analytics. In the proposed DoAMPC, an accurate predictive model is constructed adaptively by the hybrid algorithm of the least squares support vector machine and differential evolution method. Then, an optimization problem is constructed based on the predictive model and many constraint conditions. To control the boiler furnace temperature, the differential evolution method is utilized to decide the control variables by solving the optimization problem. The proposed method can adapt to the time-varying situation by updating the sample data. The experimental results based on practical data illustrate that the DoAMPC can control the boiler furnace temperature with errors of less than 1.5% which can meet the requirements of the real production process.
Prediction of Critical Power and W′ in Hypoxia: Application to Work-Balance Modelling
Townsend, Nathan E.; Nichols, David S.; Skiba, Philip F.; Racinais, Sebastien; Périard, Julien D.
2017-01-01
Purpose: Develop a prediction equation for critical power (CP) and work above CP (W′) in hypoxia for use in the work-balance (WBAL′) model. Methods: Nine trained male cyclists completed cycling time trials (TT; 12, 7, and 3 min) to determine CP and W′ at five altitudes (250, 1,250, 2,250, 3,250, and 4,250 m). Least squares regression was used to predict CP and W′ at altitude. A high-intensity intermittent test (HIIT) was performed at 250 and 2,250 m. Actual and predicted CP and W′ were used to compute W′ during HIIT using differential (WBALdiff′) and integral (WBALint′) forms of the WBAL′ model. Results: CP decreased at altitude (P hypoxia. This enables the application of WBAL′ modelling to training prescription and competition analysis at altitude. PMID:28386237
A Mechanistic Approach for the Prediction of Critical Power in BWR Fuel Bundles
Chandraker, Dinesh Kumar; Vijayan, Pallipattu Krishnan; Sinha, Ratan Kumar; Aritomi, Masanori
The critical power corresponding to the Critical Heat Flux (CHF) or dryout condition is an important design parameter for the evaluation of safety margins in a nuclear fuel bundle. The empirical approaches for the prediction of CHF in a rod bundle are highly geometric specific and proprietary in nature. The critical power experiments are very expensive and technically challenging owing to the stringent simulation requirements for the rod bundle tests involving radial and axial power profiles. In view of this, the mechanistic approach has gained momentum in the thermal hydraulic community. The Liquid Film Dryout (LFD) in an annular flow is the mechanism of CHF under BWR conditions and the dryout modeling has been found to predict the CHF quite accurately for a tubular geometry. The successful extension of the mechanistic model of dryout to the rod bundle application is vital for the evaluation of critical power in the rod bundle. The present work proposes the uniform film flow approach around the rod by analyzing individual film of the subchannel bounded by rods with different heat fluxes resulting in different film flow rates around a rod and subsequently distributing the varying film flow rates of a rod to arrive at the uniform film flow rate as it has been found that the liquid film has a strong tendency to be uniform around the rod. The FIDOM-Rod code developed for the dryout prediction in BWR assemblies provides detailed solution of the multiple liquid films in a subchannel. The approach of uniform film flow rate around the rod simplifies the liquid film cross flow modeling and was found to provide dryout prediction with a good accuracy when compared with the experimental data of 16, 19 and 37 rod bundles under BWR conditions. The critical power has been predicted for a newly designed 54 rod bundle of the Advanced Heavy Water Reactor (AHWR). The selected constitutive models for the droplet entrainment and deposition rates validated for the dryout in tube were
Predicting the long tail of book sales: Unearthing the power-law exponent
Fenner, Trevor; Levene, Mark; Loizou, George
2010-06-01
The concept of the long tail has recently been used to explain the phenomenon in e-commerce where the total volume of sales of the items in the tail is comparable to that of the most popular items. In the case of online book sales, the proportion of tail sales has been estimated using regression techniques on the assumption that the data obeys a power-law distribution. Here we propose a different technique for estimation based on a generative model of book sales that results in an asymptotic power-law distribution of sales, but which does not suffer from the problems related to power-law regression techniques. We show that the proportion of tail sales predicted is very sensitive to the estimated power-law exponent. In particular, if we assume that the power-law exponent of the cumulative distribution is closer to 1.1 rather than to 1.2 (estimates published in 2003, calculated using regression by two groups of researchers), then our computations suggest that the tail sales of Amazon.com, rather than being 40% as estimated by Brynjolfsson, Hu and Smith in 2003, are actually closer to 20%, the proportion estimated by its CEO.
Recovery and prediction of postoperative muscle power - is it still a problem?
Zoremba, Martin; Kornmann, Dennis; Vojnar, Benjamin; Burchard, Rene; Wiesmann, Thomas; Wulf, Hinnerk; Kratz, Thomas
2017-08-22
In the postoperative period, immediate recovery of muscular power is essential for patient safety, but this can be affected by anaesthetic drugs, opioids and neuromuscular blocking agents (NMBA). In this cohort study, we evaluated anaesthetic and patient-related factors contributing to reduced postoperative muscle power and pulse oximetric saturation. We prospectively observed 615 patients scheduled for minor surgery. Premedication, general anaesthesia and respiratory settings were standardized according to standard operating procedures (SOP). If NMBAs were administered, neuromuscular monitoring was applied to establish a Train of four (TOF)-Ratio of >0.9 before extubation. After achieving a modified fast track score > 10 at 4 time points up to 2 h postoperatively, we measured pulse oximetric saturation and also static and dynamic muscle power, using a high precision digital force gauge. Loss of muscle power in relation to the individual preoperative baseline value was analysed in relation to patient and anaesthesia-related factors using the T-test, simple and multiple stepwise regression analysis. Despite having achieved a TOF ratio of >0.9 a decrease in postoperative muscle power was detectable in most patients and correlated with reduced postoperative pulse oximetric saturation. Independent contributing factors were use of neuromuscular blocking agents (p 120 min (p = 0.019). Significant loss of muscle power and reduced pulse oximetric saturation are often present despite a TOF-Ratio > 0.9. Gender differences are also significant. A modified fast track score > 10 failed to predict recovery of muscle power in most patients. German Clinical Trial Register DRKS-ID DRKS00006032 ; Registered: 2014/04/03.
Maximization, learning, and economic behavior.
Erev, Ido; Roth, Alvin E
2014-07-22
The rationality assumption that underlies mainstream economic theory has proved to be a useful approximation, despite the fact that systematic violations to its predictions can be found. That is, the assumption of rational behavior is useful in understanding the ways in which many successful economic institutions function, although it is also true that actual human behavior falls systematically short of perfect rationality. We consider a possible explanation of this apparent inconsistency, suggesting that mechanisms that rest on the rationality assumption are likely to be successful when they create an environment in which the behavior they try to facilitate leads to the best payoff for all agents on average, and most of the time. Review of basic learning research suggests that, under these conditions, people quickly learn to maximize expected return. This review also shows that there are many situations in which experience does not increase maximization. In many cases, experience leads people to underweight rare events. In addition, the current paper suggests that it is convenient to distinguish between two behavioral approaches to improve economic analyses. The first, and more conventional approach among behavioral economists and psychologists interested in judgment and decision making, highlights violations of the rational model and proposes descriptive models that capture these violations. The second approach studies human learning to clarify the conditions under which people quickly learn to maximize expected return. The current review highlights one set of conditions of this type and shows how the understanding of these conditions can facilitate market design.
Predictions for the 21 cm-galaxy cross-power spectrum observable with LOFAR and Subaru
Vrbanec, Dijana; Ciardi, Benedetta; Jelić, Vibor; Jensen, Hannes; Zaroubi, Saleem; Fernandez, Elizabeth R.; Ghosh, Abhik; Iliev, Ilian T.; Kakiichi, Koki; Koopmans, Léon V. E.; Mellema, Garrelt
2016-03-01
The 21 cm-galaxy cross-power spectrum is expected to be one of the promising probes of the Epoch of Reionization (EoR), as it could offer information about the progress of reionization and the typical scale of ionized regions at different redshifts. With upcoming observations of 21 cm emission from the EoR with the Low Frequency Array (LOFAR), and of high-redshift Ly α emitters with Subaru's Hyper Suprime-Cam (HSC), we investigate the observability of such cross-power spectrum with these two instruments, which are both planning to observe the ELAIS-N1 field at z = 6.6. In this paper, we use N-body + radiative transfer (both for continuum and Ly α photons) simulations at redshift 6.68, 7.06 and 7.3 to compute the 3D theoretical 21 cm-galaxy cross-power spectrum and cross-correlation function, as well as to predict the 2D 21 cm-galaxy cross-power spectrum and cross-correlation function expected to be observed by LOFAR and HSC. Once noise and projection effects are accounted for, our predictions of the 21 cm-galaxy cross-power spectrum show clear anti-correlation on scales larger than ˜60 h-1 Mpc (corresponding to k ˜ 0.1 h Mpc-1), with levels of significance p = 0.003 at z = 6.6 and p = 0.08 at z = 7.3. On smaller scales, instead, the signal is completely contaminated. On the other hand, our 21 cm-galaxy cross-correlation function is strongly contaminated by noise on all scales, since the noise is no longer being separated by its k modes.
Maternal cortisol slope at 6 months predicts infant cortisol slope and EEG power at 12 months.
St John, Ashley M; Kao, Katie; Liederman, Jacqueline; Grieve, Philip G; Tarullo, Amanda R
2017-09-01
Physiological stress systems and the brain rapidly develop through infancy. While the roles of caregiving and environmental factors have been studied, implications of maternal physiological stress are unclear. We assessed maternal and infant diurnal cortisol when infants were 6 and 12 months. We measured 12-month infant electroencephalography (EEG) 6-9 Hz power during a social interaction. Steeper 6-month maternal slope predicted steeper 12-month infant slope controlling for 6-month infant slope and breastfeeding. Steeper 6-month maternal slope predicted lower 6-9 Hz power. Six-month maternal area under the cuve (AUCg) was unrelated to 12-month infant AUCg and 6-9 Hz power. Psychosocial, caregiving, and breastfeeding variables did not explain results. At 6 months, maternal and infant slopes correlated, as did maternal and infant AUCg. Twelve-month maternal and infant cortisol were unrelated. Results indicate maternal slope is an informative predictor of infant physiology and suggest the importance of maternal physiological stress in this developmental period. © 2017 Wiley Periodicals, Inc.
An Observer-Based Finite Control Set Model Predictive Control for Three-Phase Power Converters
Tao Liu
2014-01-01
Full Text Available Finite control set model predictive control (FCS-MPC for three-phase power converters uses a discrete mathematical model of the power converter to predict the future current value for all possible switching states. The circuit parameters and measured input currents are necessary components. For this reason, parameter error and time delay of current signals may degrade the performance of the control system. In the previous studies of the FCS-MPC, few articles study these aspects in detail and almost no method is proposed to avoid these negative influences. This paper, first, investigates the negative impacts of inductance inaccuracy and AC-side current distortion due to the time delay caused by filter on FCS-MPC system. Then, it proposes an observer-based FCS-MPC approach with which the inductance error can be corrected, the current signal’s time delay caused by filter can be compensated, and therefore the performance of FCS-MPC will be improved. At last, as an example, it illustrates the effectiveness of the proposed approach with experimental testing results for a power converter.
NIU Junchuan; GE Peiqi; HOU Cuirong; LIM C W; SONG Kongjie
2009-01-01
For estimating the vibration transmission accurately and performing vibration control efficiently in isolation systems, a novel general model is presented to predict the power flow transmitted into the complicate flexible bases of laminated beams. In the model, the laminated beam bases are simulated by the first-order shear deformation laminated plate theory, which is relatively simple and economic but accurate in predicting the vibration solutions of flexible isolation systems with laminated beam bases in comparison with classical laminated beam theories and higher order theories. On the basis of the presented model, substructure technique and variational principle are employed to obtain the governing equation of the isolation system and the power flow solution. Then, the vibration characteristics of the flexible isolation systems with laminated bases are investigated. Several numerical examples are given to show the validity and efficiency of the presented model. It is concluded that the presented model is the extension of the classical one and it can obtain more accurate power flow solutions.
Saad, Ahmed S.; Hamdy, Abdallah M.; Salama, Fathy M.; Abdelkawy, Mohamed
2016-10-01
Effect of data manipulation in preprocessing step proceeding construction of chemometric models was assessed. The same set of UV spectral data was used for construction of PLS and PCR models directly and after mathematically manipulation as per well known first and second derivatives of the absorption spectra, ratio spectra and first and second derivatives of the ratio spectra spectrophotometric methods, meanwhile the optimal working wavelength ranges were carefully selected for each model and the models were constructed. Unexpectedly, number of latent variables used for models' construction varied among the different methods. The prediction power of the different models was compared using a validation set of 8 mixtures prepared as per the multilevel multifactor design and results were statistically compared using two-way ANOVA test. Root mean squares error of prediction (RMSEP) was used for further comparison of the predictability among different constructed models. Although no significant difference was found between results obtained using Partial Least Squares (PLS) and Principal Component Regression (PCR) models, however, discrepancies among results was found to be attributed to the variation in the discrimination power of adopted spectrophotometric methods on spectral data.
ANN-based wavelet analysis for predicting electrical signal from photovoltaic power supply system
Mellit, A. [Medea Univ., Medea (Algeria). Inst. of Science Engineering, Dept. of Electronics
2007-07-01
This study was conducted to predict different electrical signals from a photovoltaic power supply system (PVPS) using an artificial neural networks (ANN) with wavelet analysis. It involved the creation of a database of electrical signals (PV-generator current, voltage, battery current voltage, regulator current and voltage) obtained from an experimental PVPS system installed in the south of Algeria. The potential applications were for sizing and analyzing the performance of PVPS systems; control of maximum power point tracker (MPPT) in order to deliver the maximum energy from the PV-array; prediction of the optimal configuration (PV-array and battery sizing) of PVPS systems; expert configuration of PV-systems; faults diagnosis; supervision; and, control and monitoring. First, based on the wavelet analysis each electrical signal was mapped in several time frequency domains. The PV-system was then divided into 3-subsystems corresponding to ANN-PV generator model, ANN-battery model, and ANN-regulator model. An example of day-by-day prediction for each electrical signal was presented. The results of the proposed approach were in good agreement with experimental results. In addition, the accuracy of the proposed approach was more satisfactory when only ANN was used. It was concluded that this methodology offers the possibility of developing a new expert configuration of PVPS by implementing the soft computing ANN-wavelet program with a digital signal processing (DSP) circuit. 26 refs., 1 tab., 5 figs.
Parvez Akter, Md.; Dah-Chuan Lu, Dylan
2017-07-01
This paper presents a model predictive controlled three-level three-phase active neutral-point-clamped (ANPC) inverter for distributing the voltage stress among the semiconductor power switches as well as balancing the neutral-point voltage. The model predictive control (MPC) concept uses the discrete variables and effectively operates the ANPC inverter by avoiding any linear controller or modulation techniques. A 4.0 kW three-level three-phase ANPC inverter is developed in the MATLAB/Simulink environment to verify the effectiveness of the proposed MPC scheme. The results confirm that the proposed model predictive controlled ANPC inverter equally distributes the voltage across all the semiconductor power switches and provides lowest THD (0.99%) compared with the traditional NPC inverter. Moreover, the neutral-point voltage balancing is accurately maintained by the proposed MPC algorithm. Furthermore, this MPC concept shows the robustness capability against the parameter uncertainties of the system which is also analyzed by MATLAB/Simulink.
基于统计聚类分析的短期风电功率预测%Short-term wind power prediction based on statistical clustering analysis
方江晓; 周晖; 黄梅; T.S.Sidhu
2011-01-01
Considering that in the process of establishing short-term wind power prediction model, the sample selection would affect the predication accuracy of wind power model, it is necessary to process the history wind speed data prior to modeling.Data classification is automatically accomplished through the statistical clustering approach.With the criterion of maximal similarity, we select a group of data as our trained samples according to the average and maximum wind speed of prediction day.Then we establish the prediction model of wind speed based on ARIMA process.Compared with the conventional ARIMA process, the prediction accuracy using statistic clustering approach we proposed is improved.An example is used to verify the correctness of our assumption.Finally, with power curve of a wind turbine, anticipated wind power is easily gotten, which offers valuable reference for drawing out operation schedule of power system integrated with wind power.%考虑到短期风电功率预测模型建立时,样本的选取对预测模型的精度有较大影响,提出了运用聚类方法对历史风速数据进行处理,实现了历史数据的自动分类.根据预测日的平均风速和最大风速等特征参数,按照相似度最大的原则,选择合适的类别作为预测建模用的训练样本.运用时间序列方法,建立风速预测模型,与不经过预处理的相比,所建立预测精度得到了提高,验证了运用聚类进行数据预处理的正确性.运用风力发电机的出力曲线,得到了未来日的风电功率的预测值,为含风电系统的电力系统运行计划的制定,提供了基础数据支持.
Hongzheng Fang
2013-01-01
Full Text Available Solar arrays are the main source of energy to the on-orbit satellite, whose output power largely determines the life cycle of on-orbit satellites. Monitoring and further forecasting the output power of solar arrays by using the real-time observational data are very important for the study of satellite design and on-orbit satellite control. In this paper, we firstly describe the dynamical model of output power with summarizing the influencing factors of attenuation for solar arrays and elaborating the evolution trend of influencing factors which change with time. Based on the empirical model, a particle filtering algorithm is formulated to predict the output power of solar arrays and update the model parameters, simultaneously. Finally, using eight-year observational data of voltage and current from a synchronous on-orbit satellite, an experiment is carried out to illustrate the reliability and accuracy of the particle filtering method. Comparative results with classical curve fitting also are presented with statistical root mean square error and mean relative error analysis.
Sliding Mode Predictive Control of Main Steam Pressure in Coal-fired Power Plant Boiler
史元浩; 王景成; 章云锋
2012-01-01
Since the combustion system of coal-fired boiler in thermal power plant is characterized as time varying, strongly coupled, and nonlinear, it is hard to achieve a satisfactory performance by the conventional proportional integral derivative (PID) control scheme. For the characteristics of the main steam pressure in coal-fired power plant boiler, the sliding mode control system with Smith predictive structure is proposed to look for performance and robustness improvement. First, internal model control (IMC) and Smith predictor (SP) is used to deal with the time delay, and sliding mode controller (SMCr) is designed to overcome the model mismatch. Simulation results show the effectiveness of the proposed controller compared with conventional ones.
Power-law decay exponents: A dynamical criterion for predicting thermalization
Távora, Marco; Torres-Herrera, E. J.; Santos, Lea F.
2017-01-01
From the analysis of the relaxation process of isolated lattice many-body quantum systems quenched far from equilibrium, we deduce a criterion for predicting when they are certain to thermalize. It is based on the algebraic behavior ∝t-γ of the survival probability at long times. We show that the value of the power-law exponent γ depends on the shape and filling of the weighted energy distribution of the initial state. Two scenarios are explored in detail: γ ≥2 and γ energy distribution of the initial state is ergodically filled and the eigenstates are uncorrelated, so thermalization is guaranteed to happen. In this case, the power-law behavior is caused by bounds in the energy spectrum. Decays with γ energy eigenstates are correlated and signal lack of ergodicity. They are typical of systems undergoing localization due to strong onsite disorder and are found also in clean integrable systems.
Unity power factor converter based on a fuzzy controller and predictive input current.
Bouafassa, Amar; Rahmani, Lazhar; Kessal, Abdelhalim; Babes, Badreddine
2014-11-01
This paper proposes analysis and control of a single-phase power factor corrector (PFC). The proposed control is capable of achieving a unity power factor for each DC link voltage or load fluctuation. The method under study is composed of two intelligent approaches, a fuzzy logic controller to ensure an output voltage at a suitable value and predictive current control. The fuzzy controller is used with minimum rules to attain a low cost. The method is verified and discussed through simulation on the MATLAB/Simulink platform. It presents high dynamic performance under various parameter changes. Moreover, in order to examine and evaluate the method in real-time, a test bench is built using dSPACE 1104. The implantation of the proposed method is very easy and flexible and allows for operation under parameter variations. Additionally, the obtained results are very significant.
Tobias Heppelmann
2017-06-01
Full Text Available For a secure integration of weather dependent renewable energies in Germany's mixed power supply, precise forecasts of expected wind power are indispensable. These in turn are heavily dependent on numerical weather prediction (NWP. With this relevant area of application, NWP models need to be evaluated concerning new variables such as wind speed at hub heights of wind power plants. This article presents verification results of the deterministic NWP forecasts of the global ICON model, its ICON-EU nest, the COSMO-EU, and the COSMO-DE as well as of the ensemble prediction system COSMO-DE-EPS of the German National Weather Service (DWD, against wind mast observations. The focus is on the diurnal cycle in the Planetary Boundary Layer as wind power forecasts for Germany exhibit pronounced systematic amplitude and phase errors in the morning and evening hours. NWP forecasts with lead times up to 48 hours are examined. All considered NWP models reveal shortcomings concerning the representation of the diurnal cycle. Especially in summertime at onshore locations, when Low-Level Jets form, nocturnal wind speeds at hub height are underestimated. In the COSMO model, stable conditions are not sufficiently reflected in the first part of the night and the vertical mixing after sunrise establishes too late. The verification results of the COSMO-DE-EPS confirm the deficiencies of the deterministic forecasts. The deficiencies are present in all ensemble members and thus indicate potential for improvement not only in the model physics parameterization but also concerning the physical ensemble perturbations.
Active power filter for medium voltage networks with predictive current control
Verne, Santiago A.; Valla, Maria I. [Laboratorio de Electronica Industrial, Control e Instrumentacion (LEICI), Facultad de Ingenieria, Universidad Nacional de La Plata and CONICET, La Plata (Argentina)
2010-12-15
A transformer less Shunt Active Power Filter (SAPF) for medium voltage distribution networks based on Multilevel Diode Clamped Inverter is presented in this paper. Converter current control is based on a Model Predictive strategy, which gives very fast current response. Also, the algorithm includes voltage balancing capability which is essential for proper converter operation. The presented current control algorithm is naturally applicable to converters with an arbitrary number of levels with reduced computational effort by virtue of the incorporation of switching restrictions which are necessary for reliable converter operation. The performance of the proposed algorithm is evaluated by means of computer simulations. (author)
2011-01-01
The speech-based envelope power spectrum model (sEPSM) [Jørgensen and Dau (2011). J. Acoust. Soc. Am., 130 (3), 1475–1487] estimates the envelope signal-to-noise ratio (SNRenv) of distorted speech and accurately describes the speech recognition thresholds (SRT) for normal-hearing listeners...... conditions by comparing predictions to measured data from [Kjems et al. (2009). J. Acoust. Soc. Am. 126 (3), 1415-1426] where speech is mixed with four different interferers, including speech-shaped noise, bottle noise, car noise, and cafe noise. The model accounts well for the differences in intelligibility...
Knowledge discovery by accuracy maximization.
Cacciatore, Stefano; Luchinat, Claudio; Tenori, Leonardo
2014-04-01
Here we describe KODAMA (knowledge discovery by accuracy maximization), an unsupervised and semisupervised learning algorithm that performs feature extraction from noisy and high-dimensional data. Unlike other data mining methods, the peculiarity of KODAMA is that it is driven by an integrated procedure of cross-validation of the results. The discovery of a local manifold's topology is led by a classifier through a Monte Carlo procedure of maximization of cross-validated predictive accuracy. Briefly, our approach differs from previous methods in that it has an integrated procedure of validation of the results. In this way, the method ensures the highest robustness of the obtained solution. This robustness is demonstrated on experimental datasets of gene expression and metabolomics, where KODAMA compares favorably with other existing feature extraction methods. KODAMA is then applied to an astronomical dataset, revealing unexpected features. Interesting and not easily predictable features are also found in the analysis of the State of the Union speeches by American presidents: KODAMA reveals an abrupt linguistic transition sharply separating all post-Reagan from all pre-Reagan speeches. The transition occurs during Reagan's presidency and not from its beginning.
Multi-model Predictive Control of Ultra-supercritical Coal-fired Power Unit
Guoliang Wang; Weiwu Yan; Shihe Chen; Xi Zhang; Huihe Shao
2014-01-01
The control of ultra-supercritical (USC) power unit is a difficult issue for its characteristic of the nonlinearity, large dead time and coupling of the unit. In this paper, model predictive control (MPC) based on multi-model and double layered optimization is introduced for coordinated control of USC unit. The linear programming (LP) com-bined with quadratic programming (QP) is used in steady optimization for computation of the ideal value of dynamic optimization. Three inputs (i.e. valve opening, coal flow and feedwater flow) are employed to control three outputs (i.e. load, main steam temperature and main steam pressure). The step response models for the dynamic matrix control (DMC) are constructed using the three inputs and the three outputs. Piecewise models are built at selected operation points. Double-layered multi-model predictive controller is implemented in sim-ulation with satisfactory performance.
Xu, Cheng-Jian; van der Schaaf, Arjen; Schilstra, Cornelis; Langendijk, Johannes A; van't Veld, Aart A
2012-03-15
To study the impact of different statistical learning methods on the prediction performance of multivariate normal tissue complication probability (NTCP) models. In this study, three learning methods, stepwise selection, least absolute shrinkage and selection operator (LASSO), and Bayesian model averaging (BMA), were used to build NTCP models of xerostomia following radiotherapy treatment for head and neck cancer. Performance of each learning method was evaluated by a repeated cross-validation scheme in order to obtain a fair comparison among methods. It was found that the LASSO and BMA methods produced models with significantly better predictive power than that of the stepwise selection method. Furthermore, the LASSO method yields an easily interpretable model as the stepwise method does, in contrast to the less intuitive BMA method. The commonly used stepwise selection method, which is simple to execute, may be insufficient for NTCP modeling. The LASSO method is recommended. Copyright Â© 2012 Elsevier Inc. All rights reserved.
Hovgaard, Tobias Gybel; Larsen, Lars F. S.; Edlund, Kristian;
2012-01-01
. In this paper we describe a novel economic-optimizing Model Predictive Control (MPC) scheme that reduces operating costs by utilizing the thermal storage capabilities. A nonlinear optimization tool to handle a non-convex cost function is utilized for simulations with validated scenarios. In this way we...... for the system itself, while crucial services can be delivered to a future flexible and intelligent power grid (Smart Grid). Furthermore, we discuss a novel incorporation of probabilistic constraints and Second Order Cone Programming (SOCP) with economic MPC. A Finite Impulse Response (FIR) formulation...... of the system models allows us to describe and handle model as well as prediction uncertainties in this framework. This means we can demonstrate means for robustifying the performance of the controller....
Farmer, Samuel; Silver-Thorn, Barbara; Voglewede, Philip; Beardsley, Scott A.
2014-10-01
Objective. Powered robotic prostheses create a need for natural-feeling user interfaces and robust control schemes. Here, we examined the ability of a nonlinear autoregressive model to continuously map the kinematics of a transtibial prosthesis and electromyographic (EMG) activity recorded within socket to the future estimates of the prosthetic ankle angle in three transtibial amputees. Approach. Model performance was examined across subjects during level treadmill ambulation as a function of the size of the EMG sampling window and the temporal ‘prediction’ interval between the EMG/kinematic input and the model’s estimate of future ankle angle to characterize the trade-off between model error, sampling window and prediction interval. Main results. Across subjects, deviations in the estimated ankle angle from the actual movement were robust to variations in the EMG sampling window and increased systematically with prediction interval. For prediction intervals up to 150 ms, the average error in the model estimate of ankle angle across the gait cycle was less than 6°. EMG contributions to the model prediction varied across subjects but were consistently localized to the transitions to/from single to double limb support and captured variations from the typical ankle kinematics during level walking. Significance. The use of an autoregressive modeling approach to continuously predict joint kinematics using natural residual muscle activity provides opportunities for direct (transparent) control of a prosthetic joint by the user. The model’s predictive capability could prove particularly useful for overcoming delays in signal processing and actuation of the prosthesis, providing a more biomimetic ankle response.
Bum Ju Lee
Full Text Available BACKGROUND AND AIMS: It is commonly accepted that body fat distribution is associated with hypertension, but the strongest anthropometric indicator of the risk of hypertension is still controversial. Furthermore, no studies on the association of hypotension with anthropometric indices have been reported. The objectives of the present study were to determine the best predictors of hypertension and hypotension among various anthropometric indices and to assess the use of combined indices as a method of improving the predictive power in adult Korean women and men. METHODS: For 12789 subjects 21-85 years of age, we assessed 41 anthropometric indices using statistical analyses and data mining techniques to determine their ability to discriminate between hypertension and normotension as well as between hypotension and normotension. We evaluated the predictive power of combined indices using two machine learning algorithms and two variable subset selection techniques. RESULTS: The best indicator for predicting hypertension was rib circumference in both women (p = <0.0001; OR = 1.813; AUC = 0.669 and men (p = <0.0001; OR = 1.601; AUC = 0.627; for hypotension, the strongest predictor was chest circumference in women (p = <0.0001; OR = 0.541; AUC = 0.657 and neck circumference in men (p = <0.0001; OR = 0.522; AUC = 0.672. In experiments using combined indices, the areas under the receiver operating characteristic curves (AUC for the prediction of hypertension risk in women and men were 0.721 and 0.652, respectively, according to the logistic regression with wrapper-based variable selection; for hypotension, the corresponding values were 0.675 in women and 0.737 in men, according to the naïve Bayes with wrapper-based variable selection. CONCLUSIONS: The best indicators of the risk of hypertension and the risk of hypotension may differ. The use of combined indices seems to slightly improve the predictive
Fernando dos Santos Nogueira
2006-08-01
Full Text Available OBJETIVO: Este estudo buscou derivar equações generalizadas para predição da carga máxima para homens e mulheres jovens. MÉTODOS: O método da ergoespirometria direta (Aerosport® TEEM 100, Estados Unidos da América do Norte foi empregado para determinar o VO2máx e a carga máxima (Wmáx, no cicloergômetro (Monark®, Brasil, de 30 homens (25 ± 5 anos, 75,0 ± 10,7 kg; 48,4 ± 8,8 mL . kg -1 . min -1 e 243 ± 51 Watts e 30 mulheres (26 ± 5 anos, 56,7 ± 5,9 kg, 39,8 ± 7,6 mL . kg -1 . min -1 e 172 ± 37 Watts. A idade e a massa corporal foram empregadas como variáveis independentes. Para todos os testes estatísticos aceitou-se o nível de significância de p OBJECTIVE: This study sought to derive generalized equations for predicting maximal workload for young men and women. METHODS: Direct ergospirometry (Aerosport® TEEM 100, USA was used to determine VO2máx and the maximal work load (Wmax on the cycle ergometer test (Monark®, Brazil of thirty men (25 ± 5 years, 75.0 ± 10.7 kg; 48.4 ± 8.8 mL . kg -1 . min -1 and 243 ± 51 Watts and thirty women (26 ± 5 years, 56.7 ± 5.9 kg, 39.8 ± 7.6 mL . kg -1 . min -1 and 172 ± 37 Watts. Age and body mass were used as independent variables. For all statistic tests, a p < 0.05 significance level was adopted. RESULTS: In the multiple linear adjustment, the maximal workload was explained by age and body mass as 54% (r = 0.73 for men, and as 76% (r = 0.87 for women, with standard errors of 0.66 W . kg -1 and 25 Watts. The proposed equations were cross-validated using another sample with similar age and VO2máx characteristics comprised of fifteen men and fifteen women. The intraclass correlation between the predicted Wmax values and those measures by ergospirometry were 0.70 and 0.69, with standard errors of 28.4 and 15.8 Watts, respectively, for men and women. CONCLUSIONS: This study exhibits valid generalized equations for determining the maximal cycle ergonometer workload for men and
Janusz Brzozowski
2014-05-01
Full Text Available The atoms of a regular language are non-empty intersections of complemented and uncomplemented quotients of the language. Tight upper bounds on the number of atoms of a language and on the quotient complexities of atoms are known. We introduce a new class of regular languages, called the maximally atomic languages, consisting of all languages meeting these bounds. We prove the following result: If L is a regular language of quotient complexity n and G is the subgroup of permutations in the transition semigroup T of the minimal DFA of L, then L is maximally atomic if and only if G is transitive on k-subsets of 1,...,n for 0 <= k <= n and T contains a transformation of rank n-1.
Andersen, Klaus Ejner
1985-01-01
Guinea pig maximization tests (GPMT) with chlorocresol were performed to ascertain whether the sensitization rate was affected by minor changes in the Freund's complete adjuvant (FCA) emulsion used. Three types of emulsion were evaluated: the oil phase was mixed with propylene glycol, saline with...... to the saline/oil emulsion. Placing of the challenge patches affected the response, as simultaneous chlorocresol challenge on the flank located 2 cm closer to the abdomen than the usual challenge site gave decreased reactions....
Zak, Michail
2008-01-01
A report discusses an algorithm for a new kind of dynamics based on a quantum- classical hybrid-quantum-inspired maximizer. The model is represented by a modified Madelung equation in which the quantum potential is replaced by different, specially chosen 'computational' potential. As a result, the dynamics attains both quantum and classical properties: it preserves superposition and entanglement of random solutions, while allowing one to measure its state variables, using classical methods. Such optimal combination of characteristics is a perfect match for quantum-inspired computing. As an application, an algorithm for global maximum of an arbitrary integrable function is proposed. The idea of the proposed algorithm is very simple: based upon the Quantum-inspired Maximizer (QIM), introduce a positive function to be maximized as the probability density to which the solution is attracted. Then the larger value of this function will have the higher probability to appear. Special attention is paid to simulation of integer programming and NP-complete problems. It is demonstrated that the problem of global maximum of an integrable function can be found in polynomial time by using the proposed quantum- classical hybrid. The result is extended to a constrained maximum with applications to integer programming and TSP (Traveling Salesman Problem).
A physical approach of the short-term wind power prediction based on CFD pre-calculated flow fields
LI Li; LIU Yong-qian; YANG Yong-ping; HAN Shuang; WANG Yi-mei
2013-01-01
A physical approach of the wind power prediction based on the CFD pre-calculated flow fields is proposed in this paper.The flow fields are obtained based on a steady CFD model with the discrete inflow wind conditions as the boundary conditions,and a database is established containing the important parameters including the inflow wind conditions,the flow fields and the corresponding wind power for each wind turbine.The power is predicted via the database by taking the Numerical Weather Prediction (NWP)wind as the input data.In order to evaluate the approach,the short-term wind power prediction for an actual wind farm is conducted as an example during the period of the year 2010.Compared with the measured power,the predicted results enjoy a high accuracy with the annual Root Mean Square Error (RMSE) of 15.2％ and the annual MAE of 10.80％.A good performance is shown in predicting the wind power's changing trend.This approach is independent of the historical data and can be widely used for all kinds of wind farms including the newly-built wind farms.At the same time,it does not take much computation time while it captures the local air flows more precisely by the CFD model.So it is especially practical for engineering projects.
Bogner, Konrad; Monhart, Samuel; Liniger, Mark; Spririg, Christoph; Jordan, Fred; Zappa, Massimiliano
2015-04-01
In recent years large progresses have been achieved in the operational prediction of floods and hydrological drought with up to ten days lead time. Both the public and the private sectors are currently using probabilistic runoff forecast in order to monitoring water resources and take actions when critical conditions are to be expected. The use of extended-range predictions with lead times exceeding 10 days is not yet established. The hydropower sector in particular might have large benefits from using hydro meteorological forecasts for the next 15 to 60 days in order to optimize the operations and the revenues from their watersheds, dams, captions, turbines and pumps. The new Swiss Competence Centers in Energy Research (SCCER) targets at boosting research related to energy issues in Switzerland. The objective of HEPS4POWER is to demonstrate that operational extended-range hydro meteorological forecasts have the potential to become very valuable tools for fine tuning the production of energy from hydropower systems. The project team covers a specific system-oriented value chain starting from the collection and forecast of meteorological data (MeteoSwiss), leading to the operational application of state-of-the-art hydrological models (WSL) and terminating with the experience in data presentation and power production forecasts for end-users (e-dric.ch). The first task of the HEPS4POWER will be the downscaling and post-processing of ensemble extended-range meteorological forecasts (EPS). The goal is to provide well-tailored forecasts of probabilistic nature that should be reliable in statistical and localized at catchment or even station level. The hydrology related task will consist in feeding the post-processed meteorological forecasts into a HEPS using a multi-model approach by implementing models with different complexity. Also in the case of the hydrological ensemble predictions, post-processing techniques need to be tested in order to improve the quality of the
Evaluation of Maxim Module-Integrated Electronics at the DOE Regional Test Centers (Presentation)
Deline, C.; Sekulic, B.; Barkaszi, S.; Yang, J.; Kahn, S.
2014-06-01
Module-embedded power electronics developed by Maxim Integrated are under evaluation through a partnership with the Department of Energy's Regional Test Center (RTC) program. Field deployments of both conventional modules and electronics-enhanced modules are designed to quantify the performance advantage of Maxim's products under different amounts of interrow shading, and their ability to be deployed at a greater ground-coverage ratio than conventional modules. Simulations in PVSYST have quantified the predicted performance difference between conventional modules and Maxim's modules from interrow shading. Initial performance results have identified diffuse irradiance losses at tighter row spacing for both the Maxim and conventional modules. Comparisons with published models show good agreement with models predicting the greatest diffuse irradiance losses. At tighter row spacing, all of the strings equipped with embedded power electronics outperformed their conventional peers. An even greater performance advantage is predicted to occur in the winter months when the amount of interrow shading mismatch is at a maximum.
Evaluation of Maxim Module-Integrated Electronics at the DOE Regional Test Centers: Preprint
Deline, C.; Sekulic, B.; Stein, J.; Barkaszi, S.; Yang, J.; Kahn, S.
2014-07-01
Module-embedded power electronics developed by Maxim Integrated are under evaluation through a partnership with the Department of Energy's Regional Test Center (RTC) program. Field deployments of both conventional modules and electronics-enhanced modules are designed to quantify the performance advantage of Maxim's products under different amounts of inter-row shading, and their ability to be deployed at a greater ground-coverage-ratio than conventional modules. Simulations in PVSYST have quantified the predicted performance difference between conventional modules and Maxim's modules from inter-row shading. Initial performance results have identified diffuse irradiance losses at tighter row spacing for both the Maxim and conventional modules. Comparisons with published models show good agreement with models predicting the greatest diffuse irradiance losses. At tighter row spacing, all of the strings equipped with embedded power electronics outperformed their conventional peers. An even greater performance advantage is predicted to occur in the winter months when the amount of inter-row shading mismatch is at a maximum.
Imaging descriptors improve the predictive power of survival models for glioblastoma patients.
Mazurowski, Maciej Andrzej; Desjardins, Annick; Malof, Jordan Milton
2013-10-01
Because effective prediction of survival time can be highly beneficial for the treatment of glioblastoma patients, the relationship between survival time and multiple patient characteristics has been investigated. In this paper, we investigate whether the predictive power of a survival model based on clinical patient features improves when MRI features are also included in the model. The subjects in this study were 82 glioblastoma patients for whom clinical features as well as MR imaging exams were made available by The Cancer Genome Atlas (TCGA) and The Cancer Imaging Archive (TCIA). Twenty-six imaging features in the available MR scans were assessed by radiologists from the TCGA Glioma Phenotype Research Group. We used multivariate Cox proportional hazards regression to construct 2 survival models: one that used 3 clinical features (age, gender, and KPS) as the covariates and 1 that used both the imaging features and the clinical features as the covariates. Then, we used 2 measures to compare the predictive performance of these 2 models: area under the receiver operating characteristic curve for the 1-year survival threshold and overall concordance index. To eliminate any positive performance estimation bias, we used leave-one-out cross-validation. The performance of the model based on both clinical and imaging features was higher than the performance of the model based on only the clinical features, in terms of both area under the receiver operating characteristic curve (P < .01) and the overall concordance index (P < .01). Imaging features assessed using a controlled lexicon have additional predictive value compared with clinical features when predicting survival time in glioblastoma patients.
Witheephanich, K.; Escaño, J. M.; Hayes, M. J.
2011-08-01
This work considers the problem of controlling transmit power within a wireless sensor network (WSN), where the practical constraints typically posed by an ambulatory healthcare setting are explicitly taken into account, as a constrained received signal strength indicator (RSSI) tracking control problem. The problem is formulated using an explicit generalised predictive control (GPC) strategy for dynamic transmission power control that ensures a balance between energy consumption and quality of service (QoS) through the creation of a stable floor on information throughput. Optimal power assignment is achieved by an explicit solution of the constrained GPC problem that is computed off-line using a multi-parametric quadratic program (mpQP). The solution is shown to be a piecewise-affine function. The new design is demonstrated to be practically feasible via a resource-constrained, fully IEEE 802.15.4 compliant, Moteiv's Tmote Sky sensor node platform. Design utility is benchmarked experimentally using a representative selection of scaled ambulatory scenarios.
Decentralized model predictive based load frequency control in an interconnected power system
Mohamed, T.H., E-mail: tarekhie@yahoo.co [High Institute of Energy, South Valley University (Egypt); Bevrani, H., E-mail: bevrani@ieee.or [Dept. of Electrical Engineering and Computer Science, University of Kurdistan (Iran, Islamic Republic of); Hassan, A.A., E-mail: aahsn@yahoo.co [Faculty of Engineering, Dept. of Electrical Engineering, Minia University, Minia (Egypt); Hiyama, T., E-mail: hiyama@cs.kumamoto-u.ac.j [Dept. of Electrical Engineering and Computer Science, Kumamoto University, Kumamoto (Japan)
2011-02-15
This paper presents a new load frequency control (LFC) design using the model predictive control (MPC) technique in a multi-area power system. The MPC technique has been designed such that the effect of the uncertainty due to governor and turbine parameters variation and load disturbance is reduced. Each local area controller is designed independently such that stability of the overall closed-loop system is guaranteed. A frequency response model of multi-area power system is introduced, and physical constraints of the governors and turbines are considered. The model was employed in the MPC structures. Digital simulations for both two and three-area power systems are provided to validate the effectiveness of the proposed scheme. The results show that, with the proposed MPC technique, the overall closed-loop system performance demonstrated robustness in the face of uncertainties due to governors and turbines parameters variation and loads disturbances. A performance comparison between the proposed controller and a classical integral control scheme is carried out confirming the superiority of the proposed MPC technique.
Gore, K.L.; Thomas, J.M.; Kannberg, L.D.; Mahaffey, J.A.; Waton, D.G.
1976-12-01
A study was undertaken by the U.S. Nuclear Regulatory Commission (NRC) to evaluate the nonradiological environmental data obtained from three nuclear power plants operating for a period of one year or longer. The document presented reports the second of three nuclear power plants to be evaluated in detail by Battelle, Pacific Northwest Laboratories. Haddam Neck (Connecticut Yankee) Nuclear Power Plant nonradiological monitoring data were assessed to determine their effectiveness in the measurement of environmental impacts. Efforts were made to determine if: (1) monitoring programs, as designed, can detect environmental impacts, (2) appropriate statistical analyses were performed and if they were sensitive enough to detect impacts, (3) predicted impacts could be verified by monitoring programs, and (4) monitoring programs satisfied the requirements of the Environmental Technical Specifications. Both preoperational and operational monitoring data were examined to test the usefulness of baseline information in evaluating impacts. This included an examination of the methods used to measure ecological, chemical, and physical parameters, and an assessment of sampling periodicity and sensitivity where appropriate data sets were available. From this type of analysis, deficiencies in both preoperational and operational monitoring programs may be identified and provide a basis for suggested improvement.
Fluctuations of prestimulus oscillatory power predict subjective perception of tactile simultaneity.
Lange, Joachim; Halacz, Johanna; van Dijk, Hanneke; Kahlbrock, Nina; Schnitzler, Alfons
2012-11-01
Oscillatory activity is modulated by sensory stimulation but can also fluctuate in the absence of sensory input. Recent studies have demonstrated that such fluctuations of oscillatory activity can have substantial influence on the perception of subsequent stimuli. In the present study, we employed a simultaneity task in the somatosensory domain to study the role of prestimulus oscillatory activity on the temporal perception of 2 events. Subjects received electrical stimulations of the left and right index finger with varying stimulus onset asynchronies (SOAs) and reported their subjective perception of simultaneity, while brain activity was recorded with magnetoencephalography. With intermediate SOAs (30 and 45 ms), subjects frequently misperceived the stimulation as simultaneously. We compared neuronal oscillatory power in these conditions and found that power in the high beta band (∼20 to 40 Hz) in primary and secondary somatosensory cortex prior to the electrical stimulation predicted subjects' reports of simultaneity. Additionally, prestimulus alpha-band power influenced perception in the condition SOA 45 ms. Our results indicate that fluctuations of ongoing oscillatory activity in the beta and alpha bands shape subjective perception of physically identical stimulation.
A predictive controller based on transient simulations for controlling a power plant
Svingen, B.
2016-11-01
A predictive governor based on an embedded, online transient simulation was commissioned at Tonstad power plant in Norway in December 2014. This governor controls each individual turbine governor by feeding them modified setpoints. Tonstad power plant consists of 4 × 160 MW + 1 × 320 MW high head Francis turbines. With a yearly production of 3888 GWh, it is the largest in Norway. The plant is a typical high head Norwegian plant with very long tunnels and correspondingly active dynamic behaviour. This new governor system continuously simulates the entire plant, and appropriate actions are taken automatically by special algorithms. The simulations are based on the method of characteristics (MOC). The governing system has been in full operational mode since December 19 2014. The testing period also included special acceptance tests to be able to deliver FRR, both on the Nordic grid and on DC cable to Denmark. Although in full operational mode, this system is still a prototype under constant development. It shows a new way of using transient analysis that may become increasingly important in the future with added power from un-regulated sources such as wind, solar and bio.
Kwon, Seung Hee; Jang, Kyung Pil [Department of Civil and Environmental Engineering, Myongji University, Yongin (Korea, Republic of); Bang, Jin-Wook [Department of Civil Engineering, Chungnam National University, Daejeon (Korea, Republic of); Lee, Jang Hwa [Structural Engineering Research Division, Korea Institute of Construction Technology (Korea, Republic of); Kim, Yun Yong, E-mail: yunkim@cnu.ac.kr [Structural Engineering Research Division, Korea Institute of Construction Technology (Korea, Republic of)
2014-08-15
Highlights: • Compressive strength tests for three concrete mixes were performed. • The parameters of the humidity-adjusted maturity function were determined. • Strength can be predicted considering temperature and relative humidity. - Abstract: This study proposes a method for predicting compressive strength developments in the early ages of concretes used in the construction of nuclear power plants. Three representative mixes with strengths of 6000 psi (41.4 MPa), 4500 psi (31.0 MPa), and 4000 psi (27.6 MPa) were selected and tested under various curing conditions; the temperature ranged from 10 to 40 °C, and the relative humidity from 40 to 100%. In order to consider not only the effect of the temperature but also that of humidity, an existing model, i.e. the humidity-adjusted maturity function, was adopted and the parameters used in the function were determined from the test results. A series of tests were also performed in the curing condition of a variable temperature and constant humidity, and a comparison between the measured and predicted strengths were made for the verification.
Prediction of Critical Power and W' in Hypoxia: Application to Work-Balance Modelling.
Townsend, Nathan E; Nichols, David S; Skiba, Philip F; Racinais, Sebastien; Périard, Julien D
2017-01-01
Purpose: Develop a prediction equation for critical power (CP) and work above CP (W') in hypoxia for use in the work-balance ([Formula: see text]) model. Methods: Nine trained male cyclists completed cycling time trials (TT; 12, 7, and 3 min) to determine CP and W' at five altitudes (250, 1,250, 2,250, 3,250, and 4,250 m). Least squares regression was used to predict CP and W' at altitude. A high-intensity intermittent test (HIIT) was performed at 250 and 2,250 m. Actual and predicted CP and W' were used to compute W' during HIIT using differential ([Formula: see text]) and integral ([Formula: see text]) forms of the [Formula: see text] model. Results: CP decreased at altitude (P CP and W') on modelled [Formula: see text] at 2,250 m (P = 0.24). [Formula: see text] returned higher values than [Formula: see text] throughout HIIT (P CP and W' developed in this study are suitable for use with the [Formula: see text] model in acute hypoxia. This enables the application of [Formula: see text] modelling to training prescription and competition analysis at altitude.
Yanzi Wang
2016-01-01
Full Text Available Over the last few years; issues regarding the use of hybrid energy storage systems (HESSs in hybrid electric vehicles have been highlighted by the industry and in academic fields. This paper proposes a fuzzy-logic power management strategy based on Markov random prediction for an active parallel battery-UC HESS. The proposed power management strategy; the inputs for which are the vehicle speed; the current electric power demand and the predicted electric power demand; is used to distribute the electrical power between the battery bank and the UC bank. In this way; the battery bank power is limited to a certain range; and the peak and average charge/discharge power of the battery bank and overall loss incurred by the whole HESS are also reduced. Simulations and scaled-down experimental platforms are constructed to verify the proposed power management strategy. The simulations and experimental results demonstrate the advantages; feasibility and effectiveness of the fuzzy-logic power management strategy based on Markov random prediction.
Andersen, Michael Andreas E.
1997-01-01
Two new and simple methods to make predictions of the differential mode (DM) input filter requirements are presented, one for flyback and one for boost unity power factor converters. They have been verified by measurements. They give the designer the ability to predict the DM input noise filter...
M. Khademi
2016-01-01
Full Text Available The prediction of power generated by photovoltaic (PV panels in different climates is of great importance. The aim of this paper is to predict the output power of a 3.2 kW PV power plant using the MLP-ABC (multilayer perceptron-artificial bee colony algorithm. Experimental data (ambient temperature, solar radiation, and relative humidity was gathered at five-minute intervals from Tehran University’s PV Power Plant from September 22nd, 2012, to January 14th, 2013. Following data validation, 10665 data sets, equivalent to 35 days, were used in the analysis. The output power was predicted using the MLP-ABC algorithm with the mean absolute percentage error (MAPE, the mean bias error (MBE, and correlation coefficient (R2, of 3.7, 3.1, and 94.7%, respectively. The optimized configuration of the network consisted of two hidden layers. The first layer had four neurons and the second had two neurons. A detailed economic analysis is also presented for sunny and cloudy weather conditions using COMFAR III software. A detailed cost analysis indicated that the total investment’s payback period would be 3.83 years in sunny periods and 4.08 years in cloudy periods. The results showed that the solar PV power plant is feasible from an economic point of view in both cloudy and sunny weather conditions.
Gu, Rongbao; Xiong, Wei; Li, Xinjie
2015-12-01
This paper analyzes the predictive ability of the singular value decomposition entropy for the Shenzhen Component Index based on different scales. It is found that, the predictive ability of the entropy for the index is affected by the width of moving time windows and the structural break in stock market. By moving time windows with one year, the predictive power of singular value decomposition entropy of Shenzhen stock market for its component index is found after the reform of non-tradable shares.
Brandes, U; Gaertler, M; Goerke, R; Hoefer, M; Nikoloski, Z; Wagner, D
2006-01-01
Several algorithms have been proposed to compute partitions of networks into communities that score high on a graph clustering index called modularity. While publications on these algorithms typically contain experimental evaluations to emphasize the plausibility of results, none of these algorithms has been shown to actually compute optimal partitions. We here settle the unknown complexity status of modularity maximization by showing that the corresponding decision version is NP-complete in the strong sense. As a consequence, any efficient, i.e. polynomial-time, algorithm is only heuristic and yields suboptimal partitions on many instances.
C. Muniraj
2011-01-01
Full Text Available This paper presents the prediction of pollution severity of the polymeric insulators used in power transmission lines using adaptive neurofuzzy inference system (ANFIS model. In this work, laboratory-based pollution performance tests were carried out on 11 kV silicone rubber polymeric insulator under AC voltage at different pollution levels with sodium chloride as a contaminant. Leakage current was measured during the laboratory tests. Time domain and frequency domain characteristics of leakage current, such as mean value, maximum value, standard deviation, and total harmonics distortion (THD, have been extracted, which jointly describe the pollution severity of the polymeric insulator surface. Leakage current characteristics are used as the inputs of ANFIS model. The pollution severity index “equivalent salt deposit density” (ESDD is used as the output of the proposed model. Results of the research can give sufficient prewarning time before pollution flashover and help in the condition based maintenance (CBM chart preparation.
A review on the young history of the wind power short-term prediction
Costa, A.; Crespo, A.; Navarro, J.
2008-01-01
This paper makes a brief review on 30 years of history of the wind power short-term prediction, since the first ideas and sketches on the theme to the actual state of the art oil models and tools, giving emphasis to the most significant proposals and developments. The two principal lines of thought...... the same in order to compare two models (this fact makes it almost impossible to carry out a quantitative comparison between a huge number of models and methods). In place of a quantitative description, a qualitative approach is preferred for this review, remarking the contribution (and innovative aspect......) of each model. On the basis of the review, some topics for future research are pointed out....
Ruiz-Arias, Jose A; Gueymard, Christian A; Santos-Alamillos, Francisco J; Pozo-Vázquez, David
2016-08-10
Concentrating solar technologies, which are fuelled by the direct normal component of solar irradiance (DNI), are among the most promising solar technologies. Currently, the state-of the-art methods for DNI evaluation use datasets of aerosol optical depth (AOD) with only coarse (typically monthly) temporal resolution. Using daily AOD data from both site-specific observations at ground stations as well as gridded model estimates, a methodology is developed to evaluate how the calculated long-term DNI resource is affected by using AOD data averaged over periods from 1 to 30 days. It is demonstrated here that the use of monthly representations of AOD leads to systematic underestimations of the predicted long-term DNI up to 10% in some areas with high solar resource, which may result in detrimental consequences for the bankability of concentrating solar power projects. Recommendations for the use of either daily or monthly AOD data are provided on a geographical basis.
Maximizing without difficulty: A modified maximizing scale and its correlates
Linda Lai
2010-01-01
This article presents several studies that replicate and extend previous research on maximizing. A modified scale for measuring individual maximizing tendency is introduced. The scale has adequate psychometric properties and reflects maximizers' aspirations for high standards and their preference for extensive alternative search, but not the decision difficulty aspect included in several previous studies. Based on this scale, maximizing is positively correlated with optimism, need for cogniti...
Zong, Yi; Bindner, Henrik W.; Gehrke, Oliver
2013-01-01
is built around a small power grid with renewable power generations (two wind turbines and solar panels), a vanadium battery for storage, EV-charging infrastructure for EVs, and an intelligent office building. The simulation and field tests demonstrated that GA-based and MPC-based predictive control......In order to achieve a Danish energy supply based on 100% renewable energy from combinations of wind, biomass, wave and solar power in 2050 and to cover 50% of the Danish electricity consumption by wind power in 2020, it requires more renewable energy in buildings and industries (e.g. cold stores...
Lívia Pinheiro Carvalho
Full Text Available Impaired cardiorespiratory fitness (CRF is a hallmark characteristic in obese and lean sedentary young women. Peak oxygen consumption (VO2peak prediction from the six-minute step test (6MST has not been established for sedentary females. It is recognized that lower-limb muscle strength and power play a key role during functional activities. The aim of this study was to investigate cardiorespiratory responses during the 6MST and CPX and to develop a predictive equation to estimate VO2peak in both lean and obese subjects. Additionally we aim to investigate how muscle function impacts functional performance. Lean (LN = 13 and obese (OB = 18 women, aged 20-45, underwent a CPX, two 6MSTs, and isokinetic and isometric knee extensor strength and power evaluations. Regression analysis assessed the ability to predict VO2peak from the 6MST, age and body mass index (BMI. CPX and 6MST main outcomes were compared between LN and OB and correlated with strength and power variables. CRF, functional capacity, and muscle strength and power were lower in the OB compared to LN (<0.05. During the 6MST, LN and OB reached ~90% of predicted maximal heart rate and ~80% of the VO2peak obtained during CPX. BMI, age and number of step cycles (NSC explained 83% of the total variance in VO2peak. Moderate to strong correlations between VO2peak at CPX and VO2peak at 6MST (r = 0.86, VO2peak at CPX and NSC (r = 0.80, as well as between VO2peak, NSC and muscle strength and power variables were found (p<0.05. These findings indicate the 6MST, BMI and age accurately predict VO2peak in both lean and obese young sedentary women. Muscle strength and power were related to measures of aerobic and functional performance.
Sergio Salas-Duarte
2016-01-01
Full Text Available The realization of an improved predictive current controller based on a trapezoidal model is described, and the impact of this technique is assessed on the performance of a 2 kW, 21.6 kHz, four-wire, Active Power Filter for utility equipment of Metro Railway, Power-Land Substations. The operation of the trapezoidal predictive current controller is contrasted with that of a typical predictive control technique, based on a single Euler approximation, which has demonstrated generation of high-quality line currents, each using a 400 V DC link to improve the power quality of an unbalanced nonlinear load of Metro Railway. The results show that the supply current waveforms become virtually sinusoidal waves, reducing the current ripple by 50% and improving its power factor from 0.8 to 0.989 when the active filter is operated with a 1.6 kW load. The principle of operation of the trapezoidal predictive controller is analysed together with a description of its practical development, showing experimental results obtained with a 2 kW prototype.
Jassmann, U.; Dickler, S.; Zierath, J.; Hakenberg, M.; Abel, D.
2016-09-01
This contribution presents a Model Predictive Controller (MPC) with moveblocking strategy for combined power leveling and load alleviation in wind turbine operation with a focus on extreme loads. The controller is designed for a 3 MW wind turbine developed by W2E Wind to Energy GmbH and compared to a baseline controller, using a classic control scheme, which currently operates the wind turbine. All simulations are carried out with a detailed multibody simulation turbine model implemented in alaska/Wind. The performance of the two different controllers is compared using a 50-year Extreme Operation Gust event, since it is one of the main design drivers for the wind turbine considered in this work. The implemented MPC is able to level electrical output power and reduce mechanical loads at the same time. Without de-rating the achieved control results, a move-blocking strategy is utilized and allowed to reduce the computational burden of the MPC by more than 50% compared to a baseline MPC implementation. This even allows to run the MPC on a state of the art Programmable Logic Controller.
Luna, Julio; Jemei, Samir; Yousfi-Steiner, Nadia; Husar, Attila; Serra, Maria; Hissel, Daniel
2016-10-01
In this work, a nonlinear model predictive control (NMPC) strategy is proposed to improve the efficiency and enhance the durability of a proton exchange membrane fuel cell (PEMFC) power system. The PEMFC controller is based on a distributed parameters model that describes the nonlinear dynamics of the system, considering spatial variations along the gas channels. Parasitic power from different system auxiliaries is considered, including the main parasitic losses which are those of the compressor. A nonlinear observer is implemented, based on the discretised model of the PEMFC, to estimate the internal states. This information is included in the cost function of the controller to enhance the durability of the system by means of avoiding local starvation and inappropriate water vapour concentrations. Simulation results are presented to show the performance of the proposed controller over a given case study in an automotive application (New European Driving Cycle). With the aim of representing the most relevant phenomena that affects the PEMFC voltage, the simulation model includes a two-phase water model and the effects of liquid water on the catalyst active area. The control model is a simplified version that does not consider two-phase water dynamics.
Predictable and powerful unconfined turbidity currents examined by a custom cabled platform
Scherwath, M.; Lintern, D. G.
2016-12-01
This poster presents direct and high bandwidth observation of turbidity current using a cabled sea floor observatory. Lines of evidence indicate that the flows are in the form of a bed hugging wedge, and built up to between 1 m and 4 m in height as the head passed through. Comparison with laboratory data suggest that the flow was initially supercritical. The remarkable aspects of this research follow. The flows are powerful enough to carry a 1 tonne platform and sever a heavily armoured cable. The current occurred on the unchannelized open slope. This powerful event failed to cause discernible seabed elevation change. The flow was triggered by tidal conditions. The event was detected by a purpose-designed cabled observatory, thus providing high bandwidth data and also alerting researchers in real time to mount follow-on investigations. This poster illustrated morphological and hydrological characteristics of the flows. We present a theory on how the flows are tidally drive, and thus how they are predictable.
Pre-stimulus beta and gamma oscillatory power predicts perceived audiovisual simultaneity.
Yuan, Xiangyong; Li, Haijiang; Liu, Peiduo; Yuan, Hong; Huang, Xiting
2016-09-01
Pre-stimulus oscillation activity in the brain continuously fluctuates, but it is correlated with subsequent behavioral and perceptual performance. Here, using fast Fourier transformation of pre-stimulus electroencephalograms, we explored how oscillatory power modulates the subsequent discrimination of perceived simultaneity from non-simultaneity in the audiovisual domain. We found that the over-scalp high beta (20-28Hz), parieto-occipital low beta (14-20Hz), and high gamma oscillations (55-80Hz) were significantly stronger before audition-then-vision sequence when they were judged as simultaneous rather than non-simultaneous. In contrast, a broad range of oscillations, mainly the beta and gamma bands over a great part of the scalp were significantly weaker before vision-then-audition sequences when they were judged as simultaneous versus non-simultaneous. Moreover, for auditory-leading sequence, pre-stimulus beta and gamma oscillatory power successfully predicted subjects' reports of simultaneity on a trial-by-trial basis, with stronger activity resulting in more simultaneous judgments. These results indicate that ongoing fluctuations of beta and gamma oscillations can modulate subsequent perceived audiovisual simultaneity, but with an opposing pattern for auditory- and visual-leading sequences.
Colin, Samuel
2015-01-01
The de Broglie-Bohm pilot-wave formulation of quantum theory allows the existence of physical states that violate the Born probability rule. Recent work has shown that in pilot-wave field theory on expanding space relaxation to the Born rule is suppressed for long-wavelength field modes, resulting in a large-scale power deficit {\\xi}(k) which for a radiation-dominated expansion is found to have a characteristic (approximate) inverse-tangent dependence on k. In this paper we show that the functional form of {\\xi}(k) is robust under changes in the initial nonequilibrium distribution as well as under the addition of an inflationary era at the end of the radiation-dominated phase. In both cases the predicted deficit {\\xi}(k) remains an inverse-tangent function of k. Furthermore, with the inflationary phase the dependence of the fitting parameters on the number of superposed pre-inflationary energy states is comparable to that found previously. Our results indicate that an inverse-tangent power deficit is likely t...
Char characterization and DTF assays as tools to predict burnout of coal blends in power plants
C. Ulloa; A.G. Borrego; S. Helle; A.L. Gordon; X. Garcia [Universidad de Concepcion, Concepcion (Chile). Departamento de Ingenieria Quimica
2005-02-01
The aim of this study is to predict efficiency deviations in the combustion of coal blends in power plants. Combustion of blends, as compared to its single coals, shows that for some blends the behavior is non-additive in nature. Samples of coal feed and fly ashes from combustion of blends at two power plants, plus chars of the parent coals generated in a drop-tube furnace (DTF) at temperatures and heating rates similar to those found in the industrial boilers were used. Intrinsic kinetic parameters, burning profiles and petrographic characteristics of these chars correlated well with the burnout in power plants and DTF experiments. The blend combustion in a DTF reproduces both positive and negative burnout deviations from the expected weighted average. These burnout deviations have been previously attributed to parallel or parallel-series pathways of competition for oxygen. No deviations were found for blends of low rank coals of similar characteristics yielding chars close in morphology, optical texture and reactivity. Negative deviations were found for blends of coals differing moderately in rank and were interpreted as associated with long periods of competition. In this case, fly-ashes were enriched in material derived from the least reactive char, but also unburnt material attributed to the most reactive char was identified. Improved burnout compared to the weighted average was observed for blends of coals very different in rank, and interpreted as the result of a short interaction period, followed by a period where the less reactive char burns under conditions that are more favorable to its combustion. In this case, only unburned material from the least reactive char was identified in the fly-ashes. 20 refs., 9 figs., 5 tabs.
Keil, Petr; Herben, Tomás; Rosindell, James; Storch, David
2010-07-07
There has recently been increasing interest in neutral models of biodiversity and their ability to reproduce the patterns observed in nature, such as species abundance distributions. Here we investigate the ability of a neutral model to predict phenomena observed in single-population time series, a study complementary to most existing work that concentrates on snapshots in time of the whole community. We consider tests for density dependence, the dominant frequencies of population fluctuation (spectral density) and a relationship between the mean and variance of a fluctuating population (Taylor's power law). We simulated an archipelago model of a set of interconnected local communities with variable mortality rate, migration rate, speciation rate, size of local community and number of local communities. Our spectral analysis showed 'pink noise': a departure from a standard random walk dynamics in favor of the higher frequency fluctuations which is partly consistent with empirical data. We detected density dependence in local community time series but not in metacommunity time series. The slope of the Taylor's power law in the model was similar to the slopes observed in natural populations, but the fit to the power law was worse. Our observations of pink noise and density dependence can be attributed to the presence of an upper limit to community sizes and to the effect of migration which distorts temporal autocorrelation in local time series. We conclude that some of the phenomena observed in natural time series can emerge from neutral processes, as a result of random zero-sum birth, death and migration. This suggests the neutral model would be a parsimonious null model for future studies of time series data.
Heat Transfer Measurements and Predictions on a Power Generation Gas Turbine Blade
Giel, Paul W.; Bunker, Ronald S.; VanFossen, G. James; Boyle, Robert J.
2000-01-01
Detailed heat transfer measurements and predictions are given for a power generation turbine rotor with 129 deg of nominal turning and an axial chord of 137 mm. Data were obtained for a set of four exit Reynolds numbers comprised of the design point of 628,000, -20%, +20%, and +40%. Three ideal exit pressure ratios were examined including the design point of 1.378, -10%, and +10%. Inlet incidence angles of 0 deg and +/-2 deg were also examined. Measurements were made in a linear cascade with highly three-dimensional blade passage flows that resulted from the high flow turning and thick inlet boundary layers. Inlet turbulence was generated with a blown square bar grid. The purpose of the work is the extension of three-dimensional predictive modeling capability for airfoil external heat transfer to engine specific conditions including blade shape, Reynolds numbers, and Mach numbers. Data were obtained by a steady-state technique using a thin-foil heater wrapped around a low thermal conductivity blade. Surface temperatures were measured using calibrated liquid crystals. The results show the effects of strong secondary vortical flows, laminar-to-turbulent transition, and also show good detail in the stagnation region.
A review on the young history of the wind power short-term prediction
Costa, Alexandre; Navarro, Jorge [Wind Energy, Division of Renewable Energies, Department of Energy, CIEMAT, Av. Complutense, 22, Ed. 42, 28044 Madrid (Spain); Crespo, Antonio [Laboratorio de Mecanica de Fluidos, Departmento de Ingenieria Energetica y Fluidomecanica, ETSII, Universidad Politecnica de Madrid, C/Jose Gutierrez Abascal, 2-28006 Madrid (Spain); Lizcano, Gil [Oxford University Centre for the Environment, University of Oxford, South Parks Road, Oxford OX1 3QY (United Kingdom); Madsen, Henrik [Informatics and Mathematical Modelling - IMM, Technical University of Denmark, Richard Petersens Plads, Building 321, Office 019, 2800 Kgs. Lyngby (Denmark); Feitosa, Everaldo [Brazilian Wind Energy Centre - CBEE, Centro de Tecnologia e Geociencias, UFPE-50.740-530 Recife, PE (Brazil)
2008-08-15
This paper makes a brief review on 30 years of history of the wind power short-term prediction, since the first ideas and sketches on the theme to the actual state of the art on models and tools, giving emphasis to the most significant proposals and developments. The two principal lines of thought on short-term prediction (mathematical and physical) are indistinctly treated here and comparisons between models and tools are avoided, mainly because, on the one hand, a standard for a measure of performance is still not adopted and, on the other hand, it is very important that the data are exactly the same in order to compare two models (this fact makes it almost impossible to carry out a quantitative comparison between a huge number of models and methods). In place of a quantitative description, a qualitative approach is preferred for this review, remarking the contribution (and innovative aspect) of each model. On the basis of the review, some topics for future research are pointed out. (author)
LVP modeling and dynamic characteristics prediction of a hydraulic power unit in deep-sea
Cao, Xue-peng; Ye, Min; Deng, Bin; Zhang, Cui-hong; Yu, Zu-ying
2013-03-01
A hydraulic power unit (HPU) is the driving "heart" of deep-sea working equipment. It is critical to predict its dynamic performances in deep-water before being immerged in the seawater, while the experimental tests by simulating deep-sea environment have many disadvantages, such as expensive cost, long test cycles, and difficult to achieve low-temperature simulation, which is only used as a supplementary means for confirmatory experiment. This paper proposes a novel theoretical approach based on the linear varying parameters (LVP) modeling to foresee the dynamic performances of the driving unit. Firstly, based on the varying environment features, dynamic expressions of the compressibility and viscosity of hydraulic oil are derived to reveal the fluid performances changing. Secondly, models of hydraulic system and electrical system are accomplished respectively through studying the control process and energy transfer, and then LVP models of the pressure and flow rate control is obtained through the electro-hydraulic models integration. Thirdly, dynamic characteristics of HPU are obtained by the model simulating within bounded closed sets of varying parameters. Finally, the developed HPU is tested in a deep-sea imitating hull, and the experimental results are well consistent with the theoretical analysis outcomes, which clearly declare that the LVP modeling is a rational way to foresee dynamic performances of HPU. The research approach and model analysis results can be applied to the predictions of working properties and product designs for other deep-sea hydraulic pump.
A Predictive Power Control Strategy for DFIGs Based on a Wind Energy Converter System
Xiaoliang Yang
2017-07-01
Full Text Available A feasible control strategy is proposed to control a doubly fed induction generator based on the wind energy converter system (DFIG-WECS. The main aim is to enhance the steady state and dynamic performance under the condition of the parameter perturbations and external disturbances and to satisfy the stator power response of the system. Within the proposed control method, the control scheme for the rotor side converter (RSC is developed on the model predictive control. Firstly, the self-adaptive reference trajectory is established from the deduced discrete state-space equation of the generator. Then, the rotor voltage is calculated by minimizing the global performance index under the current prediction steps at the sampling instant. Through the control scheme for the grid side converter (GSC and wind turbine, we have re-applied the conventional control. The effectiveness of the proposed control strategy is verified via time domain simulation of a 150 kW-575 V DFIG-WECS using Matlab/Simulink. The simulation result shows that the control of the DFIG with the proposed control method can enhance the steady and dynamic response capability better than the conventional ones when the system faces errors due to the parameter perturbations, external disturbances and the rotor speed.
Hurricane destructive power predictions based on historical storm and sea surface temperature data.
Bogen, Kenneth T; Jones, Edwin D; Fischer, Larry E
2007-12-01
Forecasting destructive hurricane potential is complicated by substantial, unexplained intraannual variation in storm-specific power dissipation index (PDI, or integrated third power of wind speed), and interannual variation in annual accumulated PDI (APDI). A growing controversy concerns the recent hypothesis that the clearly positive trend in North Atlantic Ocean (NAO) sea surface temperature (SST) since 1970 explains increased hurricane intensities over this period, and so implies ominous PDI and APDI growth as global warming continues. To test this "SST hypothesis" and examine its quantitative implications, a combination of statistical and probabilistic methods were applied to National Hurricane Center HURDAT best-track data on NAO hurricanes during 1880-2002, and corresponding National Oceanographic and Atmospheric Administration Extended Reconstruction SST estimates. Notably, hurricane behavior was compared to corresponding hurricane-specific (i.e., spatiotemporally linked) SST; previous similar comparisons considered only SST averaged over large NAO regions. Contrary to the SST hypothesis, SST was found to vary in a monthly pattern inconsistent with that of corresponding PDI, and to be at best weakly associated with PDI or APDI despite strong correlation with corresponding mean latitude (R(2)= 0.55) or with combined mean location and a approximately 90-year periodic trend (R(2)= 0.70). Over the last century, the lower 75% of APDIs appear randomly sampled from a nearly uniform distribution, and the upper 25% of APDIs from a nearly lognormal distribution. From the latter distribution, a baseline (SST-independent) stochastic model was derived predicting that over the next half century, APDI will not likely exceed its maximum value over the last half century by more than a factor of 1.5. This factor increased to 2 using a baseline model modified to assume SST-dependence conditioned on an upper bound of the increasing NAO SST trend observed since 1970. An
Kunstman, Jonathan W; Clerkin, Elise M; Palmer, Kateyln; Peters, M Taylar; Dodd, Dorian R; Smith, April R
2016-03-01
This study tested whether relatively low levels of interoceptive accuracy (IAcc) are associated with body dysmorphic disorder (BDD) symptoms. Additionally, given research indicating that power attunes individuals to their internal states, we sought to determine if state interoceptive accuracy could be improved through an experimental manipulation of power.. Undergraduate women (N = 101) completed a baseline measure of interoceptive accuracy and then were randomized to a power or control condition. Participants were primed with power or a neutral control topic and then completed a post-manipulation measure of state IAcc. Trait BDD symptoms were assessed with a self-report measure. Controlling for baseline IAcc, within the control condition, there was a significant inverse relationship between trait BDD symptoms and interoceptive accuracy. Continuing to control for baseline IAcc, within the power condition, there was not a significant relationship between trait BDD symptoms and IAcc, suggesting that power may have attenuated this relationship. At high levels of BDD symptomology, there was also a significant simple effect of experimental condition, such that participants in the power (vs. control) condition had better interoceptive accuracy. These results provide initial evidence that power may positively impact interoceptive accuracy among those with high levels of BDD symptoms.. This cross-sectional study utilized a demographically homogenous sample of women that reflected a broad range of symptoms; thus, although there were a number of participants reporting elevated BDD symptoms, these findings might not generalize to other populations or clinical samples. This study provides the first direct test of the relationship between trait BDD symptoms and IAcc, and provides preliminary evidence that among those with severe BDD symptoms, power may help connect individuals with their internal states. Future research testing the mechanisms linking BDD symptoms with IAcc, as
Atilla ÖZDEMİR
2016-12-01
Full Text Available It is seen that education has a significant effect that changes an individual’s life in our country in which education is a way of moving up the social ladder. In order to continue to a higher education program after graduating from high school, students have to succeed in transition to higher education examination. Thus, the entrance exam is an important factor to determine the future of the students. In our country, middle school grades and high school grade point average that is added to university placement score are also determinants. When spiral structure of our curriculum is considered, it is expected that related courses’ grades at middle school will predict the scores obtained from the first stage of transition to higher education exam (YGS. Since high school grade point average forms university placement score, being aware of how related courses’ achievement scores at secondary school predict raw scores of YGS subtests is significant in terms of our education system’s feedback and integrity. As a result, observing students’ achievement scores in related courses during their middle and high school education longitudinally and predicting raw scores on the subtests of the first stage of university entrance exam, YGS, from middle school and high scool achievement scores are substantial with regards to provide feedback to our education system. Because of those reasons, the predictive power of 7th - 12th grade year-end grade point averages ofstudents who took YGS in 2013 on their 2013 YGS subtests’ raw scvores is examined. Students who took YGS exam in Ankara province at 2012-2013 school year formed the aimed population of this study and 533 students who took YGS exam in 2013 in Altındağ district of Ankara formed target population of the study. Data was obtained from 533 students at three different schools in Altındağ district of Ankara province. Stepwise multiple regression analysis was used to answer research questions
Duque, Earl P. N.; Johnson, Wayne; vanDam, C. P.; Chao, David D.; Cortes, Regina; Yee, Karen
1999-01-01
Accurate, reliable and robust numerical predictions of wind turbine rotor power remain a challenge to the wind energy industry. The literature reports various methods that compare predictions to experiments. The methods vary from Blade Element Momentum Theory (BEM), Vortex Lattice (VL), to variants of Reynolds-averaged Navier-Stokes (RaNS). The BEM and VL methods consistently show discrepancies in predicting rotor power at higher wind speeds mainly due to inadequacies with inboard stall and stall delay models. The RaNS methodologies show promise in predicting blade stall. However, inaccurate rotor vortex wake convection, boundary layer turbulence modeling and grid resolution has limited their accuracy. In addition, the inherently unsteady stalled flow conditions become computationally expensive for even the best endowed research labs. Although numerical power predictions have been compared to experiment. The availability of good wind turbine data sufficient for code validation experimental data that has been extracted from the IEA Annex XIV download site for the NREL Combined Experiment phase II and phase IV rotor. In addition, the comparisons will show data that has been further reduced into steady wind and zero yaw conditions suitable for comparisons to "steady wind" rotor power predictions. In summary, the paper will present and discuss the capabilities and limitations of the three numerical methods and make available a database of experimental data suitable to help other numerical methods practitioners validate their own work.
HEMI: Hyperedge Majority Influence Maximization
Gangal, Varun; Narayanam, Ramasuri
2016-01-01
In this work, we consider the problem of influence maximization on a hypergraph. We first extend the Independent Cascade (IC) model to hypergraphs, and prove that the traditional influence maximization problem remains submodular. We then present a variant of the influence maximization problem (HEMI) where one seeks to maximize the number of hyperedges, a majority of whose nodes are influenced. We prove that HEMI is non-submodular under the diffusion model proposed.
Andersen, Klaus Ejner
1985-01-01
Guinea pig maximization tests (GPMT) with chlorocresol were performed to ascertain whether the sensitization rate was affected by minor changes in the Freund's complete adjuvant (FCA) emulsion used. Three types of emulsion were evaluated: the oil phase was mixed with propylene glycol, saline...... with 30% (v/v) ethanol or saline, respectively. Relative viscosity was used as one measure of physical properties of the emulsion. Higher degrees of sensitization (but not rates) were obtained at the 48 h challenge reading with the oil/propylene glycol and oil/saline + ethanol emulsions compared...... to the saline/oil emulsion. Placing of the challenge patches affected the response, as simultaneous chlorocresol challenge on the flank located 2 cm closer to the abdomen than the usual challenge site gave decreased reactions....
Zong, Yi; Mihet-Popa, Lucian; Kullmann, Daniel
2012-01-01
This paper presents a Model Predictive Controller (MPC) for electrical heaters’ predictive power consumption including maximizing the use of local generation (e.g. solar power) in an intelligent building. The MPC is based on dynamic power price and weather forecast, considering users’ comfort...
Smith, Christopher S. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Bull, Diana L [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Willits, Steven M. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States); Fontaine, Arnold A. [Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)
2014-08-01
This Technical Report presents work completed by The Applied Research Laboratory at The Pennsylvania State University, in conjunction with Sandia National Labs, on the optimization of the power conversion chain (PCC) design to maximize the Average Annual Electric Power (AAEP) output of an Oscillating Water Column (OWC) device. The design consists of two independent stages. First, the design of a floating OWC, a Backward Bent Duct Buoy (BBDB), and second the design of the PCC. The pneumatic power output of the BBDB in random waves is optimized through the use of a hydrodynamically coupled, linear, frequency-domain, performance model that links the oscillating structure to internal air-pressure fluctuations. The PCC optimization is centered on the selection and sizing of a Wells Turbine and electric power generation equipment. The optimization of the PCC involves the following variables: the type of Wells Turbine (fixed or variable pitched, with and without guide vanes), the radius of the turbine, the optimal vent pressure, the sizing of the power electronics, and number of turbines. Also included in this Technical Report are further details on how rotor thrust and torque are estimated, along with further details on the type of variable frequency drive selected.
MAXIMS VIOLATIONS IN LITERARY WORK
Widya Hanum Sari Pertiwi
2015-12-01
Full Text Available This study was qualitative research action that focuses to find out the flouting of Gricean maxims and the functions of the flouting in the tales which are included in collection of children literature entitled My Giant Treasury of Stories and Rhymes. The objective of the study is generally to identify the violation of maxims of quantity, quality, relevance, and manner in the data sources and also to analyze the use of the flouting in the tales which are included in the book. Qualitative design using categorizing strategies, specifically coding strategy, was applied. Thus, the researcher as the instrument in this investigation was selecting the tales, reading them, and gathering every item which reflects the violation of Gricean maxims based on some conditions of flouting maxims. On the basis of the data analysis, it was found that the some utterances in the tales, both narration and conversation, flouting the four maxims of conversation, namely maxim of quality, maxim of quantity, maxim of relevance, and maxim of manner. The researcher has also found that the flouting of maxims has one basic function that is to encourage the readers’ imagination toward the tales. This one basic function is developed by six others functions: (1 generating specific situation, (2 developing the plot, (3 enlivening the characters’ utterance, (4 implicating message, (5 indirectly characterizing characters, and (6 creating ambiguous setting. Keywords: children literature, tales, flouting maxims
Hydren, Jay R; Borges, Alexander S; Sharp, Marilyn A
2017-04-01
Hydren, JR, Borges, AS, and Sharp, MA. Systematic review and meta-analysis of predictors of military task performance: maximal lift capacity. J Strength Cond Res 31(4): 1142-1164, 2017-Physical performance tests (e.g., physical employment tests, return-to-duty tests) are commonly used to predict occupational task performance to assess the ability of individuals to do a job. The purpose of this systematic review was to identify predictive tests that correlate well with maximal lifting capacity in military personnel. Three databases were searched and experts in the field were contacted, resulting in the identification of 9 reports confined to military personnel that presented correlations between predictor tests and job tasks that measured maximal lift capacity. These 9 studies used 9 variations of a maximal lift capacity test, which were pooled to evaluate comparisons. The predictive tests were categorized into 10 fitness domains, which in ranked order were as follows: body mass and composition, absolute aerobic capacity, dynamic strength, power, isometric strength, strength-endurance, speed, isokinetic strength, flexibility, and age. Limitations of these data include a restricted age range (95% confidence interval [95% CI], 20-35; no correlations to maximal lift capacity) and the limited number of comparisons available within the cited studies. Weighted mean correlations ((Equation is included in full-text article.)) and 95% CI were calculated for each test. Lean body mass (kg) was the strongest overall predictor ((Equation is included in full-text article.); 95% CI, 0.697-0.966). Tests of dynamic strength had stronger correlations than strength endurance ((Equation is included in full-text article.), 95% CI, 0.69-0.89 vs. (Equation is included in full-text article.), 95% CI, 0.21-0.61). The following 6 domains of physical performance predictive tests had pooled correlations of 0.40 or greater for combined-sex samples: dynamic strength, power, isometric strength
The role of predictive on-line monitoring systems in the power generation industry
Gittings, S.D.; Baldwin, J. [AEA Technology Energy plc (United Kingdom)
1998-12-31
It has been apparent in the power generation sector for some time that utilities are moving away from large scale, labour intensive, inspection and overhaul programmes. These are being replaced by targeted inspection and replacement programmes supported by engineering assessment. Such engineering assessments address the predominant long-term damage mechanisms and are aimed at predicting failure timescales based upon historic operating data. From these predictions extended inspection intervals can be justified and replacement schedules planned in advance, ensuring maximum plant availability and deferred capital expenditure. However, as these assessments are based upon an examination of past operating history they must be periodically re-visited and up-dated. The cost of such reassessments is usually close to that performed initially, although cost savings can arise from reductions in work-scope which have been previously justified. As computers have become more advanced (and significantly cheaper) some of the expertise used in these assessments has been transferred into software based products. However, these products are generally aimed at replacing specific parts of the desk-based analysis, necessitating a suite of products to be used in order to address all of the components and damage mechanisms, which must be assessed. As these products require specialized knowledge to be used effectively they are often employed by consultants and rarely by plant operators, except in the largest of organisations which can support an in-house team of `experts`. This has in essence led to an increase in the number of companies capable of offering assessment services, but has maintained, in the majority of cases, the plant operators reliance upon external consultants. These software based assessment methods rely upon historic operating data (in the same manner as their desk- based counterparts) and hence also need to be periodically up-dated. However, as previous assessments can
Lack of predictive power of trait fear and anxiety for conditioned pain modulation (CPM).
Horn-Hofmann, Claudia; Priebe, Janosch A; Schaller, Jörg; Görlitz, Rüdiger; Lautenbacher, Stefan
2016-12-01
In recent years the association of conditioned pain modulation (CPM) with trait fear and anxiety has become a hot topic in pain research due to the assumption that such variables may explain the low CPM efficiency in some individuals. However, empirical evidence concerning this association is still equivocal. Our study is the first to investigate the predictive power of fear and anxiety for CPM by using a well-established psycho-physiological measure of trait fear, i.e. startle potentiation, in addition to two self-report measures of pain-related trait anxiety. Forty healthy, pain-free participants (female: N = 20; age: M = 23.62 years) underwent two experimental blocks in counter-balanced order: (1) a startle paradigm with affective picture presentation and (2) a CPM procedure with hot water as conditioning stimulus (CS) and contact heat as test stimulus (TS). At the end of the experimental session, pain catastrophizing (PCS) and pain anxiety (PASS) were assessed. PCS score, PASS score and startle potentiation to threatening pictures were entered as predictors in a linear regression model with CPM magnitude as criterion. We were able to show an inhibitory CPM effect in our sample: pain ratings of the heat stimuli were significantly reduced during hot water immersion. However, CPM was neither predicted by self-report of pain-related anxiety nor by startle potentiation as psycho-physiological measure of trait fear. These results corroborate previous negative findings concerning the association between trait fear/anxiety and CPM efficiency and suggest that shifting the focus from trait to state measures might be promising.
LVP Modeling and Dynamic Characteristics Prediction of A Hydraulic Power Unit in Deep-Sea
CAO Xue-peng; YE Min; DENG Bin; ZHANG Cui-hong; YU Zu-ying
2013-01-01
A hydraulic power unit (HPU) is the driving "heart" of deep-sea working equipment.It is critical to predict its dynamic performances in deep-water before being immerged in the seawater,while the experimental tests by simulating deep-sea environment have many disadvantages,such as expensive cost,long test cycles,and difficult to achieve low-temperature simulation,which is only used as a supplementary means for confirmatory experiment.This paper proposes a novel theoretical approach based on the linear varying parameters (LVP) modeling to foresee the dynamic performances of the driving unit.Firstly,based on the varying environment features,dynamic expressions of the compressibility and viscosity of hydraulic oil are derived to reveal the fluid performances changing.Secondly,models of hydraulic system and electrical system are accomplished respectively through studying the control process and energy transfer,and then LVP models of the pressure and flow rate control is obtained through the electro-hydraulic models integration.Thirdly,dynamic characteristics of HPU are obtained by the model simulating within bounded closed sets of varying parameters.Finally,the developed HPU is tested in a deep-sea imitating hull,and the experimental results are well consistent with the theoretical analysis outcomes,which clearly declare that the LVP modeling is a rational way to foresee dynamic performances of HPU.The research approach and model analysis results can be applied to the predictions of working properties and product designs for other deep-sea hydraulic pump.
Choi, Geon Pil; Kim, Dong Yeong; Yoo, Kwae Hwan; Na, Man Gyun, E-mail: magyna@chosun.ac.kr
2016-04-15
Highlights: • We present a hydrogen-concentration prediction method in an NPP containment. • The cascaded fuzzy neural network (CFNN) is used in this prediction model. • The CFNN model is much better than the existing FNN model. • This prediction can help prevent severe accidents in NPP due to hydrogen explosion. - Abstract: Recently, severe accidents in nuclear power plants (NPPs) have attracted worldwide interest since the Fukushima accident. If the hydrogen concentration in an NPP containment is increased above 4% in atmospheric pressure, hydrogen combustion will likely occur. Therefore, the hydrogen concentration must be kept below 4%. This study presents the prediction of hydrogen concentration using cascaded fuzzy neural network (CFNN). The CFNN model repeatedly applies FNN modules that are serially connected. The CFNN model was developed using data on severe accidents in NPPs. The data were obtained by numerically simulating the accident scenarios using the MAAP4 code for optimized power reactor 1000 (OPR1000) because real severe accident data cannot be obtained from actual NPP accidents. The root-mean-square error level predicted by the CFNN model is below approximately 5%. It was confirmed that the CFNN model could accurately predict the hydrogen concentration in the containment. If NPP operators can predict the hydrogen concentration in the containment using the CFNN model, this prediction can assist them in preventing a hydrogen explosion.
Swanepoel, Konrad J
2011-01-01
A subset of a normed space X is called equilateral if the distance between any two points is the same. Let m(X) be the smallest possible size of an equilateral subset of X maximal with respect to inclusion. We first observe that Petty's construction of a d-dimensional X of any finite dimension d >= 4 with m(X)=4 can be generalised to show that m(X\\oplus_1\\R)=4 for any X of dimension at least 2 which has a smooth point on its unit sphere. By a construction involving Hadamard matrices we then show that both m(\\ell_p) and m(\\ell_p^d) are finite and bounded above by a function of p, for all 1 1 such that m(X) <= d+1 for all d-dimensional X with Banach-Mazur distance less than c from \\ell_p^d. Using Brouwer's fixed-point theorem we show that m(X) <= d+1 for all d-\\dimensional X with Banach-Mazur distance less than 3/2 from \\ell_\\infty^d. A graph-theoretical argument furthermore shows that m(\\ell_\\infty^d)=d+1. The above results lead us to conjecture that m(X) <= 1+\\dim X.
Towards more accurate wind and solar power prediction by improving NWP model physics
Steiner, Andrea; Köhler, Carmen; von Schumann, Jonas; Ritter, Bodo
2014-05-01
The growing importance and successive expansion of renewable energies raise new challenges for decision makers, economists, transmission system operators, scientists and many more. In this interdisciplinary field, the role of Numerical Weather Prediction (NWP) is to reduce the errors and provide an a priori estimate of remaining uncertainties associated with the large share of weather-dependent power sources. For this purpose it is essential to optimize NWP model forecasts with respect to those prognostic variables which are relevant for wind and solar power plants. An improved weather forecast serves as the basis for a sophisticated power forecasts. Consequently, a well-timed energy trading on the stock market, and electrical grid stability can be maintained. The German Weather Service (DWD) currently is involved with two projects concerning research in the field of renewable energy, namely ORKA*) and EWeLiNE**). Whereas the latter is in collaboration with the Fraunhofer Institute (IWES), the project ORKA is led by energy & meteo systems (emsys). Both cooperate with German transmission system operators. The goal of the projects is to improve wind and photovoltaic (PV) power forecasts by combining optimized NWP and enhanced power forecast models. In this context, the German Weather Service aims to improve its model system, including the ensemble forecasting system, by working on data assimilation, model physics and statistical post processing. This presentation is focused on the identification of critical weather situations and the associated errors in the German regional NWP model COSMO-DE. First steps leading to improved physical parameterization schemes within the NWP-model are presented. Wind mast measurements reaching up to 200 m height above ground are used for the estimation of the (NWP) wind forecast error at heights relevant for wind energy plants. One particular problem is the daily cycle in wind speed. The transition from stable stratification during