Stochastic Short-term High-resolution Prediction of Solar Irradiance and Photovoltaic Power Output

Energy Technology Data Exchange (ETDEWEB)

Melin, Alexander M. [ORNL; Olama, Mohammed M. [ORNL; Dong, Jin [ORNL; Djouadi, Seddik M. [ORNL; Zhang, Yichen [University of Tennessee, Knoxville (UTK), Department of Electrical Engineering and Computer Science

2017-09-01

The increased penetration of solar photovoltaic (PV) energy sources into electric grids has increased the need for accurate modeling and prediction of solar irradiance and power production. Existing modeling and prediction techniques focus on long-term low-resolution prediction over minutes to years. This paper examines the stochastic modeling and short-term high-resolution prediction of solar irradiance and PV power output. We propose a stochastic state-space model to characterize the behaviors of solar irradiance and PV power output. This prediction model is suitable for the development of optimal power controllers for PV sources. A filter-based expectation-maximization and Kalman filtering mechanism is employed to estimate the parameters and states in the state-space model. The mechanism results in a finite dimensional filter which only uses the first and second order statistics. The structure of the scheme contributes to a direct prediction of the solar irradiance and PV power output without any linearization process or simplifying assumptions of the signal’s model. This enables the system to accurately predict small as well as large fluctuations of the solar signals. The mechanism is recursive allowing the solar irradiance and PV power to be predicted online from measurements. The mechanism is tested using solar irradiance and PV power measurement data collected locally in our lab.

Reduction of wind power induced reserve requirements by advanced shortest-term forecasts and prediction intervals

Energy Technology Data Exchange (ETDEWEB)

Dobschinski, Jan; Wessel, Arne; Lange, Bernhard; Bremen, Lueder von [Fraunhofer Institut fuer Windenergie und Energiesystemtechnik (IWES), Kassel (Germany)

2009-07-01

In electricity systems with large penetration of wind power, the limited predictability of the wind power generation leads to an increase in reserve and balancing requirements. At first the present study concentrates on the capability of dynamic day-ahead prediction intervals to reduce the wind power induced reserve and balancing requirements. Alternatively the reduction of large forecast errors of the German wind power generation by using advanced shortest-term predictions has been evaluated in a second approach. With focus on the allocation of minute reserve power the aim is to estimate the maximal remaining uncertainty after trading activities on the intraday market. Finally both approaches were used in a case study concerning the reserve requirements induced by the total German wind power expansion in 2007. (orig.)

Submaximal exercise capacity and maximal power output in polio subjects

NARCIS (Netherlands)

Nollet, F.; Beelen, A.; Sargeant, A. J.; de Visser, M.; Lankhorst, G. J.; de Jong, B. A.

2001-01-01

OBJECTIVES: To compare the submaximal exercise capacity of polio subjects with postpoliomyelitis syndrome (PPS) and without (non-PPS) with that of healthy control subjects, to investigate the relationship of this capacity with maximal short-term power and quadriceps strength, and to evaluate

Maximal network reliability for a stochastic power transmission network

International Nuclear Information System (INIS)

Lin, Yi-Kuei; Yeh, Cheng-Ta

2011-01-01

Many studies regarded a power transmission network as a binary-state network and constructed it with several arcs and vertices to evaluate network reliability. In practice, the power transmission network should be stochastic because each arc (transmission line) combined with several physical lines is multistate. Network reliability is the probability that the network can transmit d units of electric power from a power plant (source) to a high voltage substation at a specific area (sink). This study focuses on searching for the optimal transmission line assignment to the power transmission network such that network reliability is maximized. A genetic algorithm based method integrating the minimal paths and the Recursive Sum of Disjoint Products is developed to solve this assignment problem. A real power transmission network is adopted to demonstrate the computational efficiency of the proposed method while comparing with the random solution generation approach.

Laboratory- and Field-Based Assessment of Maximal Aerobic Power of Elite Stand-Up Paddle-Board Athletes.

Science.gov (United States)

Schram, Ben; Hing, Wayne; Climstein, Mike

2016-01-01

Stand-up paddle boarding (SUP) is a rapidly growing sport and recreational activity for which only anecdotal evidence exists on its proposed health, fitness, and injury-rehabilitation benefits. 10 internationally and nationally ranked elite SUP athletes. Participants were assessed for their maximal aerobic power on an ergometer in a laboratory and compared with other water-based athletes. Field-based assessments were subsequently performed using a portable gas-analysis system, and a correlation between the 2 measures was performed. Maximal aerobic power (relative) was significantly higher (P = .037) when measured in the field with a portable gas-analysis system (45.48 ± 6.96 mL · kg(-1) · min(-1)) than with laboratory-based metabolic-cart measurements (43.20 ± 6.67 mL · kg(-1) · min(-1)). There was a strong, positive correlation (r = .907) between laboratory and field maximal aerobic power results. Significantly higher (P = .000) measures of SUP paddling speed were found in the field than with the laboratory ergometer (+42.39%). There were no significant differences in maximal heart rate between the laboratory and field settings (P = .576). The results demonstrate the maximal aerobic power representative of internationally and nationally ranked SUP athletes and show that SUP athletes can be assessed for maximal aerobic power in the laboratory with high correlation to field-based measures. The field-based portable gas-analysis unit has a tendency to consistently measure higher oxygen consumption. Elite SUP athletes display aerobic power outputs similar to those of other upper-limb-dominant elite water-based athletes (surfing, dragon-boat racing, and canoeing).

Machine learning and statistical methods for the prediction of maximal oxygen uptake: recent advances

Directory of Open Access Journals (Sweden)

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

Improving the Accuracy of Predicting Maximal Oxygen Consumption (VO2pk)

Science.gov (United States)

Downs, Meghan E.; Lee, Stuart M. C.; Ploutz-Snyder, Lori; Feiveson, Alan

2016-01-01

Maximal oxygen (VO2pk) is the maximum amount of oxygen that the body can use during intense exercise and is used for benchmarking endurance exercise capacity. The most accurate method to determineVO2pk requires continuous measurements of ventilation and gas exchange during an exercise test to maximal effort, which necessitates expensive equipment, a trained staff, and time to set-up the equipment. For astronauts, accurate VO2pk measures are important to assess mission critical task performance capabilities and to prescribe exercise intensities to optimize performance. Currently, astronauts perform submaximal exercise tests during flight to predict VO2pk; however, while submaximal VO2pk prediction equations provide reliable estimates of mean VO2pk for populations, they can be unacceptably inaccurate for a given individual. The error in current predictions and logistical limitations of measuring VO2pk, particularly during spaceflight, highlights the need for improved estimation methods.

Maximal power output during incremental exercise by resistance and endurance trained athletes.

Science.gov (United States)

Sakthivelavan, D S; Sumathilatha, S

2010-01-01

This study was aimed at comparing the maximal power output by resistance trained and endurance trained athletes during incremental exercise. Thirty male athletes who received resistance training (Group I) and thirty male athletes of similar age group who received endurance training (Group II) for a period of more than 1 year were chosen for the study. Physical parameters were measured and exercise stress testing was done on a cycle ergometer with a portable gas analyzing system. The maximal progressive incremental cycle ergometer power output at peak exercise and carbon dioxide production at VO2max were measured. Highly significant (P biofeedback and perk up the athlete's performance.

Adjoint-based model predictive control of wind farms : Beyond the quasi steady-state power maximization

NARCIS (Netherlands)

Vali, M.; Petrović, Vlaho; Boersma, S.; van Wingerden, J.W.; Kuhn, Martin; Dochain, Denis; Henrion, Didier; Peaucelle, Dimitri

2017-01-01

In this paper, we extend our closed-loop optimal control framework for wind farms to minimize wake-induced power losses. We develop an adjoint-based model predictive controller which employs a medium-fidelity 2D dynamic wind farm model. The wind turbine axial induction factors are considered here

Evaluation of Maxim Module-Integrated Electronics at the DOE Regional Test Centers: Preprint

Energy Technology Data Exchange (ETDEWEB)

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.

Prediction of maximal heart rate: comparison using a novel and ...

African Journals Online (AJOL)

Prediction of maximal heart rate: comparison using a novel and conventional equation. LR Keytel, E Mukwevho, MA Will, M Lambert. Abstract. No Abstract. African Journal for Physical, Health Education, Recreation and Dance Vol. 11(3) 2005: 269-277. Full Text: EMAIL FULL TEXT EMAIL FULL TEXT · DOWNLOAD FULL ...

Maximizing Statistical Power When Verifying Probabilistic Forecasts of Hydrometeorological Events

Science.gov (United States)

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.

The Measurement of Maximal (Anaerobic Power Output on a Cycle Ergometer: A Critical Review

Directory of Open Access Journals (Sweden)

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.

Lithium-thionyl chloride battery design concepts for maximized power applications

Science.gov (United States)

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.

Prediction of maximal lactate steady state in runners with an incremental test on the field.

Science.gov (United States)

Leti, Thomas; Mendelson, Monique; Laplaud, David; Flore, Patrice

2012-01-01

During a maximal incremental ergocycle test, the power output associated with Respiratory Exchange Ratio equal to 1.00 (RER = 1.00) predicts maximal lactate steady state (MLSS). We hypothesised that these results are transferable for runners on the field. Fourteen runners performed a maximal progressive test, to assess the speed associated with RER = 1.00, and several 30 minutes constant velocity tests to determine the speed at MLSS. We observed that the speeds at RER = 1.00, at the second ventilatory threshold (VT2) and at MLSS did not differ (15.7 ± 1.1 km · h⁻¹, 16.2 ± 1.4 km · h⁻¹, 15.5 ± 1.1 km · h⁻¹ respectively). The speed associated with RER = 1.00 was better correlated with that at MLSS (r = 0.79; p = 0.0008) than that at VT2 (r = 0.73; p = 0.002). Neither the concentration of blood lactate nor the heart rate differed between the speed at RER = 1.00 and that at MLSS from the 10th and the 30th minute of the constant velocity test. Bland and Altman analysis showed a fair agreement between the speed at MLSS and that at RER (0.2 ± 1.4 km · h⁻¹). This study demonstrated that the speed associated with RER = 1.00 determined during maximal progressive track running allows a fair estimation of the speed associated with MLSS, markedly decreasing the burden of numerous invasive tests required to assess it.

Maximizing Output Power of a Solar Panel via Combination of Sun Tracking and Maximum Power Point Tracking by Fuzzy Controllers

Directory of Open Access Journals (Sweden)

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.

Energy Efficiency Maximization for WSNs with Simultaneous Wireless Information and Power Transfer.

Science.gov (United States)

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.

Energy Efficiency Maximization for WSNs with Simultaneous Wireless Information and Power Transfer

Science.gov (United States)

Yu, Hongyan; Zhang, Yongqiang; Yang, Yuanyuan; Ji, Luyue

2017-01-01

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. PMID:28820496

Size matters: Installed maximal unit size predicts market life cycles of electricity generation technologies and systems

International Nuclear Information System (INIS)

Li, N.

2008-01-01

The electricity generation technologies and systems are complex and change in very dynamic fashions, with a multitude of energy sources and prime movers. Since an important concept in generator design is the 'economies of scale', we discover that the installed maximal unit size (capacity) of the generators is a key 'envelope-pushing' characteristic with logistical behaviors. The logistical wavelet analysis of the max unit sizes for different fuels and prime movers, and the cumulative capacities, reveals universal quantitative features in the aggregate evolution of the power industry. We extract the transition times of the max sizes (spanning 10-90% of the saturation limits) for different technologies and systems, and discover that the max size saturation in the 90-99% range precedes the saturation of cumulative capacities of the corresponding systems in the US. While these universal laws are still empirical, they give us a simple yet elegant framework to examine the evolution of the power industry and markets in predictive, not just descriptive, terms. Such laws give us a quantitative tool to spot trends and predict future development, invaluable in planning and resource allocation based on intrinsic technology and system market life cycles

A study of the optimum draft of multiple resonance power buoys for maximizing electric power production

Directory of Open Access Journals (Sweden)

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.

Predicting lower body power from vertical jump prediction equations for loaded jump squats at different intensities in men and women.

Science.gov (United States)

Wright, Glenn A; Pustina, Andrew A; Mikat, Richard P; Kernozek, Thomas W

2012-03-01

The purpose of this study was to determine the efficacy of estimating peak lower body power from a maximal jump squat using 3 different vertical jump prediction equations. Sixty physically active college students (30 men, 30 women) performed jump squats with a weighted bar's applied load of 20, 40, and 60% of body mass across the shoulders. Each jump squat was simultaneously monitored using a force plate and a contact mat. Peak power (PP) was calculated using vertical ground reaction force from the force plate data. Commonly used equations requiring body mass and vertical jump height to estimate PP were applied such that the system mass (mass of body + applied load) was substituted for body mass. Jump height was determined from flight time as measured with a contact mat during a maximal jump squat. Estimations of PP (PP(est)) for each load and for each prediction equation were compared with criterion PP values from a force plate (PP(FP)). The PP(est) values had high test-retest reliability and were strongly correlated to PP(FP) in both men and women at all relative loads. However, only the Harman equation accurately predicted PP(FP) at all relative loads. It can therefore be concluded that the Harman equation may be used to estimate PP of a loaded jump squat knowing the system mass and peak jump height when more precise (and expensive) measurement equipment is unavailable. Further, high reliability and correlation with criterion values suggest that serial assessment of power production across training periods could be used for relative assessment of change by either of the prediction equations used in this study.

Subwavelength elastic joints connecting torsional waveguides to maximize the power transmission coefficient

Science.gov (United States)

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.

Coordinated Power Dispatch of a PMSG based Wind Farm for Output Power Maximizing Considering the Wake Effect and Losses

DEFF Research Database (Denmark)

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...... active power and reactive power dispatch strategy is proposed for a Permanent magnet synchronous generator (PMSG) based WF, in order to maximize the total output power by reducing the wake effect and losses inside the devices of the WF, including the copper loss and iron loss of PMSGs, losses inside...

Maximizing power output from continuous-wave single-frequency fiber amplifiers.

Science.gov (United States)

Ward, Benjamin G

2015-02-15

This Letter reports on a method of maximizing the power output from highly saturated cladding-pumped continuous-wave single-frequency fiber amplifiers simultaneously, taking into account the stimulated Brillouin scattering and transverse modal instability thresholds. This results in a design figure of merit depending on the fundamental mode overlap with the doping profile, the peak Brillouin gain coefficient, and the peak mode coupling gain coefficient. This figure of merit is then numerically analyzed for three candidate fiber designs including standard, segmented acoustically tailored, and micro-segmented acoustically tailored photonic-crystal fibers. It is found that each of the latter two fibers should enable a 50% higher output power than standard photonic crystal fiber.

Designing a solar powered Stirling heat engine based on multiple criteria: Maximized thermal efficiency and power

International Nuclear Information System (INIS)

Ahmadi, Mohammad Hossein; Sayyaadi, Hoseyn; Dehghani, Saeed; Hosseinzade, Hadi

2013-01-01

Highlights: • Thermodynamic model of a solar-dish Stirling engine was presented. • Thermal efficiency and output power of the engine were simultaneously maximized. • A final optimal solution was selected using several decision-making methods. • An optimal solution with least deviation from the ideal design was obtained. • Optimal solutions showed high sensitivity against variation of system parameters. - Abstract: A solar-powered high temperature differential Stirling engine was considered for optimization using multiple criteria. A thermal model was developed so that the output power and thermal efficiency of the solar Stirling system with finite rate of heat transfer, regenerative heat loss, conductive thermal bridging loss, finite regeneration process time and imperfect performance of the dish collector could be obtained. The output power and overall thermal efficiency were considered for simultaneous maximization. Multi-objective evolutionary algorithms (MOEAs) based on the NSGA-II algorithm were employed while the solar absorber temperature and the highest and lowest temperatures of the working fluid were considered the decision variables. The Pareto optimal frontier was obtained and a final optimal solution was also selected using various decision-making methods including the fuzzy Bellman–Zadeh, LINMAP and TOPSIS. It was found that multi-objective optimization could yield results with a relatively low deviation from the ideal solution in comparison to the conventional single objective approach. Furthermore, it was shown that, if the weight of thermal efficiency as one of the objective functions is considered to be greater than weight of the power objective, lower absorber temperature and low temperature ratio should be considered in the design of the Stirling engine

Comparison of Critical Power and W' Derived From 2 or 3 Maximal Tests.

Science.gov (United States)

Simpson, Len Parker; Kordi, Mehdi

2017-07-01

Typically, accessing the asymptote (critical power; CP) and curvature constant (W') parameters of the hyperbolic power-duration relationship requires multiple constant-power exhaustive-exercise trials spread over several visits. However, more recently single-visit protocols and personal power meters have been used. This study investigated the practicality of using a 2-trial, single-visit protocol in providing reliable CP and W' estimates. Eight trained cyclists underwent 3- and 12-min maximal-exercise trials in a single session to derive (2-trial) CP and W' estimates. On a separate occasion a 5-min trial was performed, providing a 3rd trial to calculate (3-trial) CP and W'. There were no differences in CP (283 ± 66 vs 282 ± 65 W) or W' (18.72 ± 6.21 vs 18.27 ± 6.29 kJ) obtained from either the 2-trial or 3-trial method, respectively. After 2 familiarization sessions (completing a 3- and a 12-min trial on both occasions), both CP and W' remained reliable over additional separate measurements. The current study demonstrates that after 2 familiarization sessions, reliable CP and W' parameters can be obtained from trained cyclists using only 2 maximal-exercise trials. These results offer practitioners a practical, time-efficient solution for incorporating power-duration testing into applied athlete support.

Attenuated Increase in Maximal Force of Rat Medial Gastrocnemius Muscle after Concurrent Peak Power and Endurance Training

Directory of Open Access Journals (Sweden)

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.

Test-retest reliability of maximal leg muscle power and functional performance measures in patients with severe osteoarthritis (OA)

DEFF Research Database (Denmark)

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...... and scheduled for unilateral total hip (n=9) or knee (n=11) replacement. Patients underwent a test battery on two occasions separated by approximately one week (range 7 to 11 days). Muscle power was measured using: 1. A linear encoder, unilateral lower limb isolated single-joint dynamic movement, e.g. knee...... flexion 2. A leg extension press, unilateral multi-joint knee and hip extension Functional performance was measured using: 1. 20 m walk usual pace 2. 20 m walk maximal pace 3. 5 times chair stands 4. Maximal number of knee bends/30sec Pain was measured on a VAS prior to and after conducting the entire...

Machine learning and statistical methods for the prediction of maximal oxygen uptake: recent advances.

Science.gov (United States)

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.

Maximizing and customer loyalty: Are maximizers less loyal?

Directory of Open Access Journals (Sweden)

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.

Wind power prediction models

Science.gov (United States)

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.

Maximizing gain in high-throughput screening using conformal prediction.

Science.gov (United States)

Svensson, Fredrik; Afzal, Avid M; Norinder, Ulf; Bender, Andreas

2018-02-21

Iterative screening has emerged as a promising approach to increase the efficiency of screening campaigns compared to traditional high throughput approaches. By learning from a subset of the compound library, inferences on what compounds to screen next can be made by predictive models, resulting in more efficient screening. One way to evaluate screening is to consider the cost of screening compared to the gain associated with finding an active compound. In this work, we introduce a conformal predictor coupled with a gain-cost function with the aim to maximise gain in iterative screening. Using this setup we were able to show that by evaluating the predictions on the training data, very accurate predictions on what settings will produce the highest gain on the test data can be made. We evaluate the approach on 12 bioactivity datasets from PubChem training the models using 20% of the data. Depending on the settings of the gain-cost function, the settings generating the maximum gain were accurately identified in 8-10 out of the 12 datasets. Broadly, our approach can predict what strategy generates the highest gain based on the results of the cost-gain evaluation: to screen the compounds predicted to be active, to screen all the remaining data, or not to screen any additional compounds. When the algorithm indicates that the predicted active compounds should be screened, our approach also indicates what confidence level to apply in order to maximize gain. Hence, our approach facilitates decision-making and allocation of the resources where they deliver the most value by indicating in advance the likely outcome of a screening campaign.

Optimal Operation of Network-Connected Combined Heat and Powers for Customer Profit Maximization

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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.

Maximizers versus satisficers

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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.

Optimal Battery Utilization Over Lifetime for Parallel Hybrid Electric Vehicle to Maximize Fuel Economy

Energy Technology Data Exchange (ETDEWEB)

Patil, Chinmaya; Naghshtabrizi, Payam; Verma, Rajeev; Tang, Zhijun; Smith, Kandler; Shi, Ying

2016-08-01

This paper presents a control strategy to maximize fuel economy of a parallel hybrid electric vehicle over a target life of the battery. Many approaches to maximizing fuel economy of parallel hybrid electric vehicle do not consider the effect of control strategy on the life of the battery. This leads to an oversized and underutilized battery. There is a trade-off between how aggressively to use and 'consume' the battery versus to use the engine and consume fuel. The proposed approach addresses this trade-off by exploiting the differences in the fast dynamics of vehicle power management and slow dynamics of battery aging. The control strategy is separated into two parts, (1) Predictive Battery Management (PBM), and (2) Predictive Power Management (PPM). PBM is the higher level control with slow update rate, e.g. once per month, responsible for generating optimal set points for PPM. The considered set points in this paper are the battery power limits and State Of Charge (SOC). The problem of finding the optimal set points over the target battery life that minimize engine fuel consumption is solved using dynamic programming. PPM is the lower level control with high update rate, e.g. a second, responsible for generating the optimal HEV energy management controls and is implemented using model predictive control approach. The PPM objective is to find the engine and battery power commands to achieve the best fuel economy given the battery power and SOC constraints imposed by PBM. Simulation results with a medium duty commercial hybrid electric vehicle and the proposed two-level hierarchical control strategy show that the HEV fuel economy is maximized while meeting a specified target battery life. On the other hand, the optimal unconstrained control strategy achieves marginally higher fuel economy, but fails to meet the target battery life.

Evaluation of the maximized power of a regenerative endoreversible Stirling cycle using the thermodynamic analysis

International Nuclear Information System (INIS)

Ahmadi, Mohammad H.; Mohammadi, Amir H.; Dehghani, Saeed

2013-01-01

Highlights: • The optimal power of an endoreversible Stirling cycle is investigated. • In the endoreversible cycle, external heat transfer processes are considered irreversible. • Optimal temperature of the heat source leading to a maximum power for the cycle is detained. • Effect of design parameters on the power and its corresponding thermal efficiency is studied. - Abstract: In this communication, the optimal power of an endoreversible Stirling cycle with perfect regeneration is investigated. In the endoreversible cycle, external heat transfer processes are irreversible. Optimal temperature of the heat source leading to a maximum power for the cycle is detained. Moreover, effect of design parameters of the Stirling engine on the maximized power of the engine and its corresponding thermal efficiency is studied

On maximizing profit of wind-battery supported power station based on wind power and energy price forecasting

DEFF Research Database (Denmark)

Khalid, Muhammad; Aguilera, Ricardo P.; Savkin, Andrey V.

2017-01-01

This paper proposes a framework to develop an optimal power dispatch strategy for grid-connected wind power plants containing a Battery Energy Storage System (BESS). Considering the intermittent nature of wind power and rapidly varying electricity market price, short-term forecasting...... Dynamic Programming tool which can incorporate the predictions of both wind power and market price simultaneously as inputs in a receding horizon approach. The proposed strategy is validated using real electricity market price and wind power data in different scenarios of BESS power and capacity...... of these variables is used for efficient energy management. The predicted variability trends in market price assist in earning additional income which subsequently increase the operational profit. Then on the basis of income improvement, optimal capacity of the BESS can be determined. The proposed framework utilizes...

Ingestion of High Molecular Weight Carbohydrate Enhances Subsequent Repeated Maximal Power: A Randomized Controlled Trial.

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Jonathan M Oliver

Full Text Available 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

A new approach for optimum DG placement and sizing based on voltage stability maximization and minimization of power losses

International Nuclear Information System (INIS)

Aman, M.M.; Jasmon, G.B.; Bakar, A.H.A.; Mokhlis, H.

2013-01-01

Highlights: • A new algorithm is proposed for optimum DG placement and sizing.• I 2 R losses minimization and voltage stability maximization is considered in fitness function.• Bus voltage stability and line stability is considered in voltage stability maximization.• Multi-objective PSO is used to solve the problem.• Proposed method is compared with analytical and grid search algorithm. - Abstract: Distributed Generation (DG) placement on the basis of minimization of losses and maximization of system voltage stability are two different approaches, discussed in research. In the new proposed algorithm, a multi-objective approach is used to combine the both approaches together. Minimization of power losses and maximization of voltage stability due to finding weakest voltage bus as well as due to weakest link in the system are considered in the fitness function. Particle Swarm Optimization (PSO) algorithm is used in this paper to solve the multi-objective problem. This paper will also compare the propose method with existing DG placement methods. From results, the proposed method is found more advantageous than the previous work in terms of voltage profile improvement, maximization of system loadability, reduction in power system losses and maximization of bus and line voltage stability. The results are validated on 12-bus, 30-bus, 33-bus and 69-bus radial distribution networks and also discussed in detailed

Power Maximization Control of Variable Speed Wind Generation System Using Permanent Magnet Synchronous Generator

Science.gov (United States)

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.

Optimum sample size allocation to minimize cost or maximize power for the two-sample trimmed mean test.

Science.gov (United States)

Guo, Jiin-Huarng; Luh, Wei-Ming

2009-05-01

When planning a study, sample size determination is one of the most important tasks facing the researcher. The size will depend on the purpose of the study, the cost limitations, and the nature of the data. By specifying the standard deviation ratio and/or the sample size ratio, the present study considers the problem of heterogeneous variances and non-normality for Yuen's two-group test and develops sample size formulas to minimize the total cost or maximize the power of the test. For a given power, the sample size allocation ratio can be manipulated so that the proposed formulas can minimize the total cost, the total sample size, or the sum of total sample size and total cost. On the other hand, for a given total cost, the optimum sample size allocation ratio can maximize the statistical power of the test. After the sample size is determined, the present simulation applies Yuen's test to the sample generated, and then the procedure is validated in terms of Type I errors and power. Simulation results show that the proposed formulas can control Type I errors and achieve the desired power under the various conditions specified. Finally, the implications for determining sample sizes in experimental studies and future research are discussed.

An information maximization model of eye movements

Science.gov (United States)

Renninger, Laura Walker; Coughlan, James; Verghese, Preeti; Malik, Jitendra

2005-01-01

We propose a sequential information maximization model as a general strategy for programming eye movements. The model reconstructs high-resolution visual information from a sequence of fixations, taking into account the fall-off in resolution from the fovea to the periphery. From this framework we get a simple rule for predicting fixation sequences: after each fixation, fixate next at the location that minimizes uncertainty (maximizes information) about the stimulus. By comparing our model performance to human eye movement data and to predictions from a saliency and random model, we demonstrate that our model is best at predicting fixation locations. Modeling additional biological constraints will improve the prediction of fixation sequences. Our results suggest that information maximization is a useful principle for programming eye movements.

Power-law inter-spike interval distributions infer a conditional maximization of entropy in cortical neurons.

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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.

Short-term wind power prediction

DEFF Research Database (Denmark)

Joensen, Alfred K.

2003-01-01

, 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......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...

Expected Power-Utility Maximization Under Incomplete Information and with Cox-Process Observations

International Nuclear Information System (INIS)

Fujimoto, Kazufumi; Nagai, Hideo; Runggaldier, Wolfgang J.

2013-01-01

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).

Expected Power-Utility Maximization Under Incomplete Information and with Cox-Process Observations

Energy Technology Data Exchange (ETDEWEB)

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).

Effect of accuracy of wind power prediction on power system operator

Science.gov (United States)

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.

Validation of the FAST skating protocol to predict aerobic power in ice hockey players.

Science.gov (United States)

Petrella, Nicholas J; Montelpare, William J; Nystrom, Murray; Plyley, Michael; Faught, Brent E

2007-08-01

Few studies have reported a sport-specific protocol to measure the aerobic power of ice hockey players using a predictive process. The purpose of our study was to validate an ice hockey aerobic field test on players of varying ages, abilities, and levels. The Faught Aerobic Skating Test (FAST) uses an on-ice continuous skating protocol on a course measuring 160 feet (48.8 m) using a CD to pace the skater with a beep signal to cross the starting line at each end of the course. The FAST incorporates the principle of increasing workload at measured time intervals during a continuous skating exercise. Step-wise multiple regression modelling was used to determine the estimate of aerobic power. Participants completed a maximal aerobic power test using a modified Bruce incremental treadmill protocol, as well as the on-ice FAST. Normative data were collected on 406 ice hockey players (291 males, 115 females) ranging in age from 9 to 25 y. A regression to predict maximum aerobic power was developed using body mass (kg), height (m), age (y), and maximum completed lengths of the FAST as the significant predictors of skating aerobic power (adjusted R2 = 0.387, SEE = 7.25 mL.kg-1.min-1, p < 0.0001). These results support the application of the FAST in estimating aerobic power among male and female competitive ice hockey players between the ages of 9 and 25 years.

Staying Power of Churn Prediction Models

NARCIS (Netherlands)

Risselada, Hans; Verhoef, Peter C.; Bijmolt, Tammo H. A.

In this paper, we study the staying power of various churn prediction models. Staying power is defined as the predictive performance of a model in a number of periods after the estimation period. We examine two methods, logit models and classification trees, both with and without applying a bagging

Resource allocation for maximizing prediction accuracy and genetic gain of genomic selection in plant breeding: a simulation experiment.

Science.gov (United States)

Lorenz, Aaron J

2013-03-01

Allocating resources between population size and replication affects both genetic gain through phenotypic selection and quantitative trait loci detection power and effect estimation accuracy for marker-assisted selection (MAS). It is well known that because alleles are replicated across individuals in quantitative trait loci mapping and MAS, more resources should be allocated to increasing population size compared with phenotypic selection. Genomic selection is a form of MAS using all marker information simultaneously to predict individual genetic values for complex traits and has widely been found superior to MAS. No studies have explicitly investigated how resource allocation decisions affect success of genomic selection. My objective was to study the effect of resource allocation on response to MAS and genomic selection in a single biparental population of doubled haploid lines by using computer simulation. Simulation results were compared with previously derived formulas for the calculation of prediction accuracy under different levels of heritability and population size. Response of prediction accuracy to resource allocation strategies differed between genomic selection models (ridge regression best linear unbiased prediction [RR-BLUP], BayesCπ) and multiple linear regression using ordinary least-squares estimation (OLS), leading to different optimal resource allocation choices between OLS and RR-BLUP. For OLS, it was always advantageous to maximize population size at the expense of replication, but a high degree of flexibility was observed for RR-BLUP. Prediction accuracy of doubled haploid lines included in the training set was much greater than of those excluded from the training set, so there was little benefit to phenotyping only a subset of the lines genotyped. Finally, observed prediction accuracies in the simulation compared well to calculated prediction accuracies, indicating these theoretical formulas are useful for making resource allocation

Automatic determination of pressurized water reactor core loading patterns that maximize beginning-of-cycle reactivity within power-peaking and burnup constraints

International Nuclear Information System (INIS)

Hobson, G.H.; Turinsky, P.J.

1986-01-01

Computational capability has been developed to automatically determine a good estimate of the core loading pattern, which minimizes fuel cycle costs for a pressurized water reactor (PWR). Equating fuel cycle cost minimization with core reactivity maximization, the objective is to determine the loading pattern that maximizes core reactivity while satisfying power peaking, discharge burnup, and other constraints. The method utilizes a two-dimensional, coarse-mesh, finite difference scheme to evaluate core reactivity and fluxes for an initial reference loading pattern. First-order perturbation theory is applied to determine the effects of assembly shuffling on reactivity, power distribution, end-of-cycle burnup. Monte Carlo integer programming is then used to determine a near-optimal loading pattern within a range of loading patterns near the reference pattern. The process then repeats with the new loading pattern as the reference loading pattern and terminates when no better loading pattern can be determined. The process was applied with both reactivity maximization and radial power-peaking minimization as objectives. Results on a typical large PWR indicate that the cost of obtaining an 8% improvement in radial power-peaking margin is ≅2% in fuel cycle costs, for the reload core loaded without burnable poisons that was studied

Power maximization of variable-speed variable-pitch wind turbines using passive adaptive neural fault tolerant control

Science.gov (United States)

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.

On Maximal Non-Disjoint Families of Subsets

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Yu. A. Zuev

2017-01-01

Full Text Available The paper studies maximal non-disjoint families of subsets of a finite set. Non-disjointness means that any two subsets of a family have a nonempty intersection. The maximality is expressed by the fact that adding a new subset to the family cannot increase its power without violating a non-disjointness condition. Studying the properties of such families is an important section of the extreme theory of sets. Along with purely combinatorial interest, the problems considered here play an important role in informatics, anti-noise coding, and cryptography.In 1961 this problem saw the light of day in the Erdos, Ko and Rado paper, which established a maximum power of the non-disjoint family of subsets of equal power. In 1974 the Erdos and Claytman publication estimated the number of maximal non-disjoint families of subsets without involving the equality of their power. These authors failed to establish an asymptotics of the logarithm of the number of such families when the power of a basic finite set tends to infinity. However, they suggested such an asymptotics as a hypothesis. A.D. Korshunov in two publications in 2003 and 2005 established the asymptotics for the number of non-disjoint families of the subsets of arbitrary powers without maximality condition of these families.The basis for the approach used in the paper to study the families of subsets is their description in the language of Boolean functions. A one-to-one correspondence between a family of subsets and a Boolean function is established by the fact that the characteristic vectors of subsets of a family are considered to be the unit sets of a Boolean function. The main theoretical result of the paper is that the maximal non-disjoint families are in one-to-one correspondence with the monotonic self-dual Boolean functions. When estimating the number of maximal non-disjoint families, this allowed us to use the result of A.A. Sapozhenko, who established the asymptotics of the number of the

The wind power prediction research based on mind evolutionary algorithm

Science.gov (United States)

Zhuang, Ling; Zhao, Xinjian; Ji, Tianming; Miao, Jingwen; Cui, Haina

2018-04-01

When the wind power is connected to the power grid, its characteristics of fluctuation, intermittent and randomness will affect the stability of the power system. The wind power prediction can guarantee the power quality and reduce the operating cost of power system. There were some limitations in several traditional wind power prediction methods. On the basis, the wind power prediction method based on Mind Evolutionary Algorithm (MEA) is put forward and a prediction model is provided. The experimental results demonstrate that MEA performs efficiently in term of the wind power prediction. The MEA method has broad prospect of engineering application.

Wind Power Prediction Considering Nonlinear Atmospheric Disturbances

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Yagang Zhang

2015-01-01

Full Text Available This paper considers the effect of nonlinear atmospheric disturbances on wind power prediction. A Lorenz system is introduced as an atmospheric disturbance model. Three new improved wind forecasting models combined with a Lorenz comprehensive disturbance are put forward in this study. Firstly, we define the form of the Lorenz disturbance variable and the wind speed perturbation formula. Then, different artificial neural network models are used to verify the new idea and obtain better wind speed predictions. Finally we separately use the original and improved wind speed series to predict the related wind power. This proves that the corrected wind speed provides higher precision wind power predictions. This research presents a totally new direction in the wind prediction field and has profound theoretical research value and practical guiding significance.

Potentiality Prediction of Electric Power Replacement Based on Power Market Development Strategy

Science.gov (United States)

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.

Improved techniques for predicting spacecraft power

International Nuclear Information System (INIS)

Chmielewski, A.B.

1987-01-01

Radioisotope Thermoelectric Generators (RTGs) are going to supply power for the NASA Galileo and Ulysses spacecraft now scheduled to be launched in 1989 and 1990. The duration of the Galileo mission is expected to be over 8 years. This brings the total RTG lifetime to 13 years. In 13 years, the RTG power drops more than 20 percent leaving a very small power margin over what is consumed by the spacecraft. Thus it is very important to accurately predict the RTG performance and be able to assess the magnitude of errors involved. The paper lists all the error sources involved in the RTG power predictions and describes a statistical method for calculating the tolerance

Prediction of Rowing Ergometer Performance from Functional Anaerobic Power, Strength and Anthropometric Components

Directory of Open Access Journals (Sweden)

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.

Skeletal muscle ATP turnover and muscle fiber conduction velocity are elevated at higher muscle temperatures during maximal power output development in humans.

Science.gov (United States)

Gray, Stuart R; De Vito, Giuseppe; Nimmo, Myra A; Farina, Dario; Ferguson, Richard A

2006-02-01

The effect of temperature on skeletal muscle ATP turnover and muscle fiber conduction velocity (MFCV) was studied during maximal power output development in humans. Eight male subjects performed a 6-s maximal sprint on a mechanically braked cycle ergometer under conditions of normal (N) and elevated muscle temperature (ET). Muscle temperature was passively elevated through the combination of hot water immersion and electric blankets. Anaerobic ATP turnover was calculated from analysis of muscle biopsies obtained before and immediately after exercise. MFCV was measured during exercise using surface electromyography. Preexercise muscle temperature was 34.2 degrees C (SD 0.6) in N and 37.5 degrees C (SD 0.6) in ET. During ET, the rate of ATP turnover for phosphocreatine utilization [temperature coefficient (Q10) = 3.8], glycolysis (Q10 = 1.7), and total anaerobic ATP turnover [Q10 = 2.7; 10.8 (SD 1.9) vs. 14.6 mmol x kg(-1) (dry mass) x s(-1) (SD 2.3)] were greater than during N (P < 0.05). MFCV was also greater in ET than in N [3.79 (SD 0.47) to 5.55 m/s (SD 0.72)]. Maximal power output (Q10 = 2.2) and pedal rate (Q10 = 1.6) were greater in ET compared with N (P < 0.05). The Q10 of maximal and mean power were correlated (P < 0.05; R = 0.82 and 0.85, respectively) with the percentage of myosin heavy chain type IIA. The greater power output obtained with passive heating was achieved through an elevated rate of anaerobic ATP turnover and MFCV, possibly due to a greater effect of temperature on power production of fibers, with a predominance of myosin heavy chain IIA at the contraction frequencies reached.

Calculation of the optimum fuel distribution which maximizes the power output of a reactor

International Nuclear Information System (INIS)

Santos, W.N. dos.

1979-01-01

Using optimal control techniques, the optimum fuel distribution - which maximizes the power output of a thermal reactor - is obtained. The nuclear reactor is described by a diffusion theory model with four energy groups and by assuming plane geometry. Since the analytical solution is impracticable, by using a perturbation method, a FORTRAN program was written, in order to obtain the numerical solution. Numerical results, for a thermal reactor light water moderated, non reflected, are shown. The fissile fuel material considered is Uranium-235. (Author) [pt

Isometric parameters in the monitoring of maximal strength, power, and hypertrophic resistance-training.

Science.gov (United States)

Peltonen, Heikki; Walker, Simon; Lähitie, Anuliisa; Häkkinen, Keijo; Avela, Janne

2018-02-01

This study monitored strength-training adaptations via isometric parameters throughout 2 × 10 weeks of hypertrophic (HYP I-II) or 10 weeks maximum strength (MS) followed by 10 weeks power (P) training with untrained controls. Trainees performed bilateral isometric leg press tests analyzed for peak force (maximal voluntary contraction (MVC)) and rate of force development (RFD) every 3.5 weeks. These parameters were compared with dynamic performance, voluntary and electrically induced isometric contractions, muscle activity, and cross-sectional area (CSA) in the laboratory before and after 10 and 20 weeks. RFD increased similarly during the first 7 weeks (HYP I, 44% ± 53%; MS, 48% ± 55%, P strength/power training, while MVC cannot distinguish between strength or muscle mass changes. Monitoring RFD provided important information regarding plateaus in RFD improvement, which were observed in dynamic explosive performances after HYP II compared with P.

Automatic determination of pressurized water reactor core loading patterns which maximize end-of-cycle reactivity within power peaking and burnup constraints

International Nuclear Information System (INIS)

Hobson, G.H.

1985-01-01

An automated procedure for determining the optimal core loading pattern for a pressurized water reactor which maximizes end-of-cycle k/sub eff/ while satisfying constraints on power peaking and discharge burnup has been developed. The optimization algorithm combines a two energy group, two-dimensional coarse-mesh finite difference diffusion theory neutronics model to simulate core conditions, a perturbation theory approach to determine reactivity, flux, power and burnup changes as a function of assembly shuffling, and Monte Carlo integer programming to select the optimal loading pattern solution. The core examined was a typical Cycle 2 reload with no burnable poisons. Results indicate that the core loading pattern that maximizes end-of-cycle k/sub eff/ results in a 5.4% decrease in fuel cycle costs compared with the core loading pattern that minimizes the maximum relative radial power peak

Using meteorological forecasts in on-line predictions of wind power

DEFF Research Database (Denmark)

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...

ATP and phosphocreatine utilization in single human muscle fibres during the development of maximal power output at elevated muscle temperatures.

Science.gov (United States)

Gray, Stuart R; Söderlund, Karin; Ferguson, Richard A

2008-05-01

In this study, we examined the effect of muscle temperature (Tm) on adenosine triphosphate (ATP) and phosphocreatine utilization in single muscle fibres during the development of maximal power output in humans. Six male participants performed a 6-s maximal sprint on a friction-braked cycle ergometer under both normal (Tm = 34.3 degrees C, s = 0.6) and elevated (T(m) = 37.3 degrees C, s = 0.2) muscle temperature conditions. During the elevated condition, muscle temperature of the legs was raised, passively, by hot water immersion followed by wrapping in electrically heated blankets. Muscle biopsies were taken from the vastus lateralis before and immediately after exercise. Freeze-dried single fibres were dissected, characterized according to myosin heavy chain composition, and analysed for ATP and phosphocreatine content. Single fibres were classified as: type I, IIA, IIAX25 (1 - 25% IIX isoform), IIAX50 (26 - 50% IIX), IIAX75 (51 - 75% IIX), or IIAX100 (76 - 100% IIX). Maximal power output and pedal rate were both greater (P < 0.05) during the elevated condition by 258 W (s = 110) and 22 rev . min(-1) (s = 6), respectively. In both conditions, phosphocreatine content decreased significantly in all fibre types, with a greater decrease during the elevated condition in type IIA fibres (P < 0.01). Adenosine triphosphate content was also reduced to a greater (P < 0.01) extent in type IIA fibres during the elevated condition. The results of the present study indicate that after passive elevation of muscle temperature, there was a greater decrease in ATP and phosphocreatine content in type IIA fibres than in the normal trial, which contributed to the higher maximal power output.

Power load prediction based on GM (1,1)

Science.gov (United States)

Wu, Di

2017-05-01

Currently, Chinese power load prediction is highly focused; the paper deeply studies grey prediction and applies it to Chinese electricity consumption during the recent 14 years; through after-test test, it obtains grey prediction which has good adaptability to medium and long-term power load.

Prediction of lacking control power in power plants using statistical models

DEFF Research Database (Denmark)

Odgaard, Peter Fogh; Mataji, B.; Stoustrup, Jakob

2007-01-01

Prediction of the performance of plants like power plants is of interest, since the plant operator can use these predictions to optimize the plant production. In this paper the focus is addressed on a special case where a combination of high coal moisture content and a high load limits the possible...... plant load, meaning that the requested plant load cannot be met. The available models are in this case uncertain. Instead statistical methods are used to predict upper and lower uncertainty bounds on the prediction. Two different methods are used. The first relies on statistics of recent prediction...... 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...

Model predictive control for wind power gradients

DEFF Research Database (Denmark)

Hovgaard, Tobias Gybel; Boyd, Stephen; Jørgensen, John Bagterp

2015-01-01

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...... 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...... wind data and modern wind forecasting methods. The simulation results using real wind data demonstrate the ability to reject the disturbances from fast changes in wind speed, ensuring certain power gradients, with an insignificant loss in energy production....

Conditional prediction intervals of wind power generation

DEFF Research Database (Denmark)

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...... to the case of a large number of wind farms in Europe and Australia among others is finally discussed....

Univariate Time Series Prediction of Solar Power Using a Hybrid Wavelet-ARMA-NARX Prediction Method

Energy Technology Data Exchange (ETDEWEB)

Nazaripouya, Hamidreza; Wang, Yubo; Chu, Chi-Cheng; Pota, Hemanshu; Gadh, Rajit

2016-05-02

This paper proposes a new hybrid method for super short-term solar power prediction. Solar output power usually has a complex, nonstationary, and nonlinear characteristic due to intermittent and time varying behavior of solar radiance. In addition, solar power dynamics is fast and is inertia less. An accurate super short-time prediction is required to compensate for the fluctuations and reduce the impact of solar power penetration on the power system. The objective is to predict one step-ahead solar power generation based only on historical solar power time series data. The proposed method incorporates discrete wavelet transform (DWT), Auto-Regressive Moving Average (ARMA) models, and Recurrent Neural Networks (RNN), while the RNN architecture is based on Nonlinear Auto-Regressive models with eXogenous inputs (NARX). The wavelet transform is utilized to decompose the solar power time series into a set of richer-behaved forming series for prediction. ARMA model is employed as a linear predictor while NARX is used as a nonlinear pattern recognition tool to estimate and compensate the error of wavelet-ARMA prediction. The proposed method is applied to the data captured from UCLA solar PV panels and the results are compared with some of the common and most recent solar power prediction methods. The results validate the effectiveness of the proposed approach and show a considerable improvement in the prediction precision.

Model Predictive Controller for Active Demand Side Management with PV Self-consumption in an Intelligent Building

DEFF Research Database (Denmark)

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...... settings to meet an optimization objective such as minimum cost and minimum reference temperature error. It demonstrates that this MPC strategy can realize load shifting, and maximize the PV self-consumption in the residential sector. With this demand side control study, it is expected that MPC strategy...

Optimizing Half Squat Postactivation Potential Load in Squat Jump Training for Eliciting Relative Maximal Power in Ski Jumpers.

Science.gov (United States)

Gołaś, Artur; Wilk, Michal; Stastny, Petr; Maszczyk, Adam; Pajerska, Katarzyna; Zając, Adam

2017-11-01

Gołaś, A, Wilk, M, Stastny, P, Maszczyk, A, Pajerska, K, and Zając, A. Optimizing half squat postactivation potential load in squat jump training for eliciting relative maximal power in ski jumpers. J Strength Cond Res 31(11): 3010-3017, 2017-Training load manipulation in a single workout session can increase or decrease training effectiveness in terms of athletes' strength or power gains. In ski jumping, the complex training that elicits maximal power gains may take advantage of the postactivation potentiation (PAP) mechanism. The aim of this research was to evaluate the changes in rate of force development (RFD), rate of power development (RPD), and jump height during a complex training session consisted of the barbell half squat (Sq) as a conditioning exercise with loads ranged between 60 and 100% of 1 repetition maximum (1RM), followed by a body weight squat jump (SqJ) as a performance task. The study was conducted with 16 elite athletes from the Polish National Ski Jumping Team, age 23 ± 8 years, body mass 56 ± 9 kg, and height 172 ± 12 cm. Complex training session started with the Sq at 60% of 1RM as the conditioning exercise, followed by 3 minutes of rest and the SqJ. The conditioning barbell half Sq was performed with 70, 80, 90, and 100% of 1RM with 5 minutes of rest. The differences in RFD occurred between an SqJ following the application of 80% of 1RM and all other SqJs (p = 0.01), and in RPD between SqJ without conditioning, SqJ after 60% of 1RM and 80% of 1RM (p = 0.02). On average, the most effective load in inducing PAP during ski jumpers' SqJ training is 80% of 1RM. The intensity of the conditioning exercise that elicits the greatest PAP effect should be individualized (60-100% 1RM), as it is dependent on the level of maximal strength.

Natural maximal νμ-ντ mixing

International Nuclear Information System (INIS)

Wetterich, C.

1999-01-01

The naturalness of maximal mixing between myon- and tau-neutrinos is investigated. A spontaneously broken nonabelian generation symmetry can explain a small parameter which governs the deviation from maximal mixing. In many cases all three neutrino masses are almost degenerate. Maximal ν μ -ν τ -mixing suggests that the leading contribution to the light neutrino masses arises from the expectation value of a heavy weak triplet rather than from the seesaw mechanism. In this scenario the deviation from maximal mixing is predicted to be less than about 1%. (Copyright (c) 1999 Elsevier Science B.V., Amsterdam. All rights reserved.)

Mechanisms underlying enhancements in muscle force and power output during maximal cycle ergometer exercise induced by chronic β2-adrenergic stimulation in men

DEFF Research Database (Denmark)

Hostrup, Morten; Kalsen, Anders; Onslev, Johan

2015-01-01

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...... 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...... and peak power during maximal cycling induced by chronic β2-adrenergic stimulation in humans....

Two-loop controller for maximizing performance of a grid-connected photovoltaic - fuel cell hybrid power plant

Science.gov (United States)

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.

Development and design of photovoltaic power prediction system

Science.gov (United States)

Wang, Zhijia; Zhou, Hai; Cheng, Xu

2018-02-01

In order to reduce the impact of power grid safety caused by volatility and randomness of the energy produced in photovoltaic power plants, this paper puts forward a construction scheme on photovoltaic power generation prediction system, introducing the technical requirements, system configuration and function of each module, and discussing the main technical features of the platform software development. The scheme has been applied in many PV power plants in the northwest of China. It shows that the system can produce reasonable prediction results, providing a right guidance for dispatching and efficient running for PV power plant.

Short-term wind power prediction based on LSSVM–GSA model

International Nuclear Information System (INIS)

Yuan, Xiaohui; Chen, Chen; Yuan, Yanbin; Huang, Yuehua; Tan, Qingxiong

2015-01-01

Highlights: • A hybrid model is developed for short-term wind power prediction. • The model is based on LSSVM and gravitational search algorithm. • Gravitational search algorithm is used to optimize parameters of LSSVM. • Effect of different kernel function of LSSVM on wind power prediction is discussed. • Comparative studies show that prediction accuracy of wind power is improved. - Abstract: Wind power forecasting can improve the economical and technical integration of wind energy into the existing electricity grid. Due to its intermittency and randomness, it is hard to forecast wind power accurately. For the purpose of utilizing wind power to the utmost extent, it is very important to make an accurate prediction of the output power of a wind farm under the premise of guaranteeing the security and the stability of the operation of the power system. In this paper, a hybrid model (LSSVM–GSA) based on the least squares support vector machine (LSSVM) and gravitational search algorithm (GSA) is proposed to forecast the short-term wind power. As the kernel function and the related parameters of the LSSVM have a great influence on the performance of the prediction model, the paper establishes LSSVM model based on different kernel functions for short-term wind power prediction. And then an optimal kernel function is determined and the parameters of the LSSVM model are optimized by using GSA. Compared with the Back Propagation (BP) neural network and support vector machine (SVM) model, the simulation results show that the hybrid LSSVM–GSA model based on exponential radial basis kernel function and GSA has higher accuracy for short-term wind power prediction. Therefore, the proposed LSSVM–GSA is a better model for short-term wind power prediction

Model Predictive Control of a Wave Energy Converter with Discrete Fluid Power Power Take-Off System

Directory of Open Access Journals (Sweden)

Anders Hedegaard Hansen

2018-03-01

Full Text Available Wave power extraction algorithms for wave energy converters are normally designed without taking system losses into account leading to suboptimal power extraction. In the current work, a model predictive power extraction algorithm is designed for a discretized power take of system. It is shown how the quantized nature of a discrete fluid power system may be included in a new model predictive control algorithm leading to a significant increase in the harvested power. A detailed investigation of the influence of the prediction horizon and the time step is reported. Furthermore, it is shown how the inclusion of a loss model may increase the energy output. Based on the presented results it is concluded that power extraction algorithms based on model predictive control principles are both feasible and favorable for use in a discrete fluid power power take-off system for point absorber wave energy converters.

Model Predictive Control of a Wave Energy Converter with Discrete Fluid Power Power Take-Off System

DEFF Research Database (Denmark)

Hansen, Anders Hedegaard; Asmussen, Magnus Færing; Bech, Michael Møller

2018-01-01

Wave power extraction algorithms for wave energy converters are normally designed without taking system losses into account leading to suboptimal power extraction. In the current work, a model predictive power extraction algorithm is designed for a discretized power take of system. It is shown how...... the quantized nature of a discrete fluid power system may be included in a new model predictive control algorithm leading to a significant increase in the harvested power. A detailed investigation of the influence of the prediction horizon and the time step is reported. Furthermore, it is shown how...

Maximizing the use of research reactors in training power reactor operating staff with special reference to US experience

International Nuclear Information System (INIS)

Cox, J.A.

1976-01-01

Research reactors have been used in training nuclear power plant personnel for many years. Using the experience in the United States of America a programme is proposed that will maximize the training conducted at a research reactor and lessen the time that the staff must spend training elsewhere. The programme is adaptable to future training of replacement staff and for staff retraining. (author)

Maximal heart rate in soccer players: Measured versus age-predicted

Directory of Open Access Journals (Sweden)

Pantelis T Nikolaidis

2015-02-01

Full Text Available Background: Although maximal heart rate (HR max is widely used to assess exercise intensity in sport training, and particularly in soccer, there are limited data with regards to the use of age-based prediction equations of HR max in soccer players. The aim of this study was to compare the measured-HR max with two prediction equations (Fox-HR max = 220 – age and Tanaka-HR max = 208 – 0.7 × age in soccer players. Methods: Adolescent (n = 162, 15.8 ± 1.5 years and adult players (n = 158, 23.4 ± 4.6 years, all members of competitive clubs, voluntarily performed a graded exercise field test (Conconi protocol to assess HR max . Results: The measured-HR max (197.6 ± 9.4 bpm in total, 200.2 ± 7.9 bpm in adolescent players, and 195.0 ± 10.0 bpm in adult players was explained by the formula HR max = 212.3 – 0.75 × age (r = −0.41, standard error of the estimate = 8.6. In the total sample, Fox-HR max overestimated measured-HR max [mean difference (95% confidence intervals = 2.8 bpm (1.6; 3.9], while Tanaka-HR max underestimated HR max [–3.3 bpm (–4.5; –2.2]. In adolescents, Fox-HR max overestimated measured-HR max [4.0 bpm (2.5; 5.5] and Tanaka-HR max underestimated HR max [– 3.2 bpm (–4.7; –1.8]. In adults, Tanaka-HR max underestimated HR max [–5.0 bpm (–5.3; –4.7], while there was not any difference between Fox-HR max and measured-HR max [1.6 bpm (–3.4; 0.2]. Conclusions: The results of this study failed to validate two widely used prediction equations in a large sample of soccer players, indicating the need for a sport-specific equation. On the other hand, the new equation that we presented should be investigated further by future studies before being adopted by coaches and fitness trainers.

Maximal Entanglement in High Energy Physics

Directory of Open Access Journals (Sweden)

Alba Cervera-Lierta, José I. Latorre, Juan Rojo, Luca Rottoli

2017-11-01

Full Text Available We analyze how maximal entanglement is generated at the fundamental level in QED by studying correlations between helicity states in tree-level scattering processes at high energy. We demonstrate that two mechanisms for the generation of maximal entanglement are at work: i $s$-channel processes where the virtual photon carries equal overlaps of the helicities of the final state particles, and ii the indistinguishable superposition between $t$- and $u$-channels. We then study whether requiring maximal entanglement constrains the coupling structure of QED and the weak interactions. In the case of photon-electron interactions unconstrained by gauge symmetry, we show how this requirement allows reproducing QED. For $Z$-mediated weak scattering, the maximal entanglement principle leads to non-trivial predictions for the value of the weak mixing angle $\\theta_W$. Our results are a first step towards understanding the connections between maximal entanglement and the fundamental symmetries of high-energy physics.

A phenomenological model of muscle fatigue and the power-endurance relationship.

Science.gov (United States)

James, A; Green, S

2012-11-01

The relationship between power output and the time that it can be sustained during exercise (i.e., endurance) at high intensities is curvilinear. Although fatigue is implicit in this relationship, there is little evidence pertaining to it. To address this, we developed a phenomenological model that predicts the temporal response of muscle power during submaximal and maximal exercise and which was based on the type, contractile properties (e.g., fatiguability), and recruitment of motor units (MUs) during exercise. The model was first used to predict power outputs during all-out exercise when fatigue is clearly manifest and for several distributions of MU type. The model was then used to predict times that different submaximal power outputs could be sustained for several MU distributions, from which several power-endurance curves were obtained. The model was simultaneously fitted to two sets of human data pertaining to all-out exercise (power-time profile) and submaximal exercise (power-endurance relationship), yielding a high goodness of fit (R(2) = 0.96-0.97). This suggested that this simple model provides an accurate description of human power output during submaximal and maximal exercise and that fatigue-related processes inherent in it account for the curvilinearity of the power-endurance relationship.

Social group utility maximization

CERN Document Server

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

Local Geomagnetic Indices and the Prediction of Auroral Power

Science.gov (United States)

Newell, P. T.; Gjerloev, J. W.

2014-12-01

As the number of magnetometer stations and data processing power increases, just how auroral power relates to geomagnetic observations becomes a quantitatively more tractable question. This paper compares Polar UVI auroral power observations during 1997 with a variety of geomagnetic indices. Local time (LT) versions of the SuperMAG auroral electojet (SME) are introduced and examined, along with the corresponding upper and lower envelopes (SMU and SML). Also, the East-West component, BE, is investigated. We also consider whether using any of the local indices is actually better at predicting local auroral power than a single global index. Each index is separated into 24 LT indices based on a sliding 3-h MLT window. The ability to predict - or better reconstruct - auroral power varies greatly with LT, peaking at 1900 MLT, where about 75% of the variance (r2) can be predicted at 1-min cadence. The aurora is fairly predictable from 1700 MLT - 0400 MLT, roughly the region in which substorms occur. Auroral power is poorly predicted from auroral electrojet indices from 0500 MLT - 1500 MLT, with the minima at 1000-1300 MLT. In the region of high predictability, the local variable which works best is BE, in contrast to long-standing expectations. However using global SME is better than any local variable. Auroral power is best predicted by combining global SME with a local index: BE from 1500-0200 MLT, and either SMU or SML from 0300-1400 MLT. In the region of the diffuse aurora, it is better to use a 30 min average than the cotemporaneous 1-min SME value, while from 1500-0200 MLT the cotemporaneous 1-min SME works best, suggesting a more direct physical relationship with the auroral circuit. These results suggest a significant role for discrete auroral currents closing locally with Pedersen currents.

Maximizing electrical power supply using FACTS devices

OpenAIRE

Lehmann, Karsten; Bent, Russell; Pan, Feng

2015-01-01

Modern society critically depends on the services electric power provides. Power systems rely on a network of power lines and transformers to deliver power from sources of power (generators) to the consumers (loads). However, when power lines fail (for example, through lightning or natural disasters) or when the system is heavily used, the network is often unable to fulfill all of the demand for power. While systems are vulnerable to these failures, increasingly, sophisticated control devices...

Analysis and experimental evaluation of shunt active power filter for power quality improvement based on predictive direct power control.

Science.gov (United States)

Aissa, Oualid; Moulahoum, Samir; Colak, Ilhami; Babes, Badreddine; Kabache, Nadir

2017-10-12

This paper discusses the use of the concept of classical and predictive direct power control for shunt active power filter function. These strategies are used to improve the active power filter performance by compensation of the reactive power and the elimination of the harmonic currents drawn by non-linear loads. A theoretical analysis followed by a simulation using MATLAB/Simulink software for the studied techniques has been established. Moreover, two test benches have been carried out using the dSPACE card 1104 for the classic and predictive DPC control to evaluate the studied methods in real time. Obtained results are presented and compared in this paper to confirm the superiority of the predictive technique. To overcome the pollution problems caused by the consumption of fossil fuels, renewable energies are the alternatives recommended to ensure green energy. In the same context, the tested predictive filter can easily be supplied by a renewable energy source that will give its impact to enhance the power quality.

Low levels of maximal aerobic power impair the profile of mood state in individuals with temporal lobe epilepsy

Directory of Open Access Journals (Sweden)

Rodrigo Luiz Vancini

2015-01-01

Full Text Available Objective To investigate the correlation between cardiorespiratory fitness and mood state in individuals with temporal lobe epilepsy (TLE. Method Individuals with TLE (n = 20 and healthy control subjects (C, n = 20 were evaluated. Self-rating questionnaires were used to assess mood (POMS and habitual physical activity (BAECKE. Cardiorespiratory fitness was evaluated by a maximal incremental test. Results People with TLE presented lower cardiorespiratory fitness; higher levels of mood disorders; and lower levels of vigor when compared to control health subjects. A significant negative correlation was observed between the levels of tension-anxiety and maximal aerobic power. Conclusion Low levels of cardiorespiratory fitness may modify the health status of individuals with TLE and it may be considered a risk factor for the development of mood disorders.

A Lyapunov based approach to energy maximization in renewable energy technologies

Science.gov (United States)

Iyasere, Erhun

This dissertation describes the design and implementation of Lyapunov-based control strategies for the maximization of the power captured by renewable energy harnessing technologies such as (i) a variable speed, variable pitch wind turbine, (ii) a variable speed wind turbine coupled to a doubly fed induction generator, and (iii) a solar power generating system charging a constant voltage battery. First, a torque control strategy is presented to maximize wind energy captured in variable speed, variable pitch wind turbines at low to medium wind speeds. The proposed strategy applies control torque to the wind turbine pitch and rotor subsystems to simultaneously control the blade pitch and tip speed ratio, via the rotor angular speed, to an optimum point at which the capture efficiency is maximum. The control method allows for aerodynamic rotor power maximization without exact knowledge of the wind turbine model. A series of numerical results show that the wind turbine can be controlled to achieve maximum energy capture. Next, a control strategy is proposed to maximize the wind energy captured in a variable speed wind turbine, with an internal induction generator, at low to medium wind speeds. The proposed strategy controls the tip speed ratio, via the rotor angular speed, to an optimum point at which the efficiency constant (or power coefficient) is maximal for a particular blade pitch angle and wind speed by using the generator rotor voltage as a control input. This control method allows for aerodynamic rotor power maximization without exact wind turbine model knowledge. Representative numerical results demonstrate that the wind turbine can be controlled to achieve near maximum energy capture. Finally, a power system consisting of a photovoltaic (PV) array panel, dc-to-dc switching converter, charging a battery is considered wherein the environmental conditions are time-varying. A backstepping PWM controller is developed to maximize the power of the solar generating

Skill forecasting from ensemble predictions of wind power

DEFF Research Database (Denmark)

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...... of alternative scenarios for the coming period) for a single prediction horizon or over a took-ahead period. It is shown on the test case of a Danish offshore wind farm how these prediction risk indices may be related to several levels of forecast uncertainty (and potential energy imbalances). Wind power...

Tri-maximal vs. bi-maximal neutrino mixing

International Nuclear Information System (INIS)

Scott, W.G

2000-01-01

It is argued that data from atmospheric and solar neutrino experiments point strongly to tri-maximal or bi-maximal lepton mixing. While ('optimised') bi-maximal mixing gives an excellent a posteriori fit to the data, tri-maximal mixing is an a priori hypothesis, which is not excluded, taking account of terrestrial matter effects

Prediction of future dispute concerning nuclear power generation

International Nuclear Information System (INIS)

1981-04-01

This investigation is the third research on the public acceptance of nuclear power generation by the National Congress on Social Economics. In this study, how the energy dispute including that concerning nuclear power generation will develop in 1980s and 1990s, how the form of dispute and the point of controversy will change, were predicted. Though the maintenance of the concord of groups strongly regulates the behavior of people, recently they have become to exercise individual rights frequently. The transition to the society of dispute is the natural result of the modernization of society and the increase of richness. The proper prediction of social problems and the planning and execution of proper countermeasures are very important. The background, objective, basic viewpoint, range and procedure of this investigation, the change of social dispute, the history of the dispute concerning nuclear power generation, the basic viewpoint in the prediction of the dispute concerning nuclear power generation, the social situation in 1980s, the prediction and avoidance of the dispute in view of social and energy situations, and the fundamental strategy for seeking a clue to the solution in 1980s and 1990s are described. The establishment of neutral mediation organs and the flexible technologies of nuclear reactors are necessary. (Kako, I.)

Power capability prediction for lithium-ion batteries based on multiple constraints analysis

International Nuclear Information System (INIS)

Pan, Rui; Wang, Yujie; Zhang, Xu; Yang, Duo; Chen, Zonghai

2017-01-01

Highlights: • Multiple constraints for peak power capability prediction are deeply analyzed. • Multi-limited method is proposed for the peak power capability prediction of LIBs. • The EKF is used for the model based peak power capability prediction. • The FUDS and UDDS profiles are executed to evaluate the proposed method. - Abstract: The power capability of the lithium-ion battery is a key performance indicator for electric vehicle, and it is intimately correlated with the acceleration, regenerative braking and gradient climbing power requirements. Therefore, an accurate power capability or state-of-power prediction is critical to a battery management system, which can help the battery to work in suitable area and prevent the battery from over-charging and over-discharging. However, the power capability is easily affected by dynamic load, voltage variation and temperature. In this paper, three different constraints in power capability prediction are introduced, and the advantages and disadvantages of the three methods are deeply analyzed. Furthermore, a multi-limited approach for the power capability prediction is proposed, which can overcome the drawbacks of the three methods. Subsequently, the extended Kalman filter algorithm is employed for model based state-of-power prediction. In order to verify the proposed method, diverse experiments are executed to explore the efficiency, robustness, and precision. The results indicate that the proposed method can improve the precision and robustness obviously.

Ultra-Short-Term Wind Power Prediction Using a Hybrid Model

Science.gov (United States)

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.

Atmospheric dispersion prediction and source estimation of hazardous gas using artificial neural network, particle swarm optimization and expectation maximization

Science.gov (United States)

Qiu, Sihang; Chen, Bin; Wang, Rongxiao; Zhu, Zhengqiu; Wang, Yuan; Qiu, Xiaogang

2018-04-01

Hazardous gas leak accident has posed a potential threat to human beings. Predicting atmospheric dispersion and estimating its source become increasingly important in emergency management. Current dispersion prediction and source estimation models cannot satisfy the requirement of emergency management because they are not equipped with high efficiency and accuracy at the same time. In this paper, we develop a fast and accurate dispersion prediction and source estimation method based on artificial neural network (ANN), particle swarm optimization (PSO) and expectation maximization (EM). The novel method uses a large amount of pre-determined scenarios to train the ANN for dispersion prediction, so that the ANN can predict concentration distribution accurately and efficiently. PSO and EM are applied for estimating the source parameters, which can effectively accelerate the process of convergence. The method is verified by the Indianapolis field study with a SF6 release source. The results demonstrate the effectiveness of the method.

On the way towards a generalized entropy maximization procedure

International Nuclear Information System (INIS)

Bagci, G. Baris; Tirnakli, Ugur

2009-01-01

We propose a generalized entropy maximization procedure, which takes into account the generalized averaging procedures and information gain definitions underlying the generalized entropies. This novel generalized procedure is then applied to Renyi and Tsallis entropies. The generalized entropy maximization procedure for Renyi entropies results in the exponential stationary distribution asymptotically for q element of (0,1] in contrast to the stationary distribution of the inverse power law obtained through the ordinary entropy maximization procedure. Another result of the generalized entropy maximization procedure is that one can naturally obtain all the possible stationary distributions associated with the Tsallis entropies by employing either ordinary or q-generalized Fourier transforms in the averaging procedure.

Controlled test for predictive power of Lyapunov exponents: their inability to predict epileptic seizures.

Science.gov (United States)

Lai, Ying-Cheng; Harrison, Mary Ann F; Frei, Mark G; Osorio, Ivan

2004-09-01

Lyapunov exponents are a set of fundamental dynamical invariants characterizing a system's sensitive dependence on initial conditions. For more than a decade, it has been claimed that the exponents computed from electroencephalogram (EEG) or electrocorticogram (ECoG) signals can be used for prediction of epileptic seizures minutes or even tens of minutes in advance. The purpose of this paper is to examine the predictive power of Lyapunov exponents. Three approaches are employed. (1) We present qualitative arguments suggesting that the Lyapunov exponents generally are not useful for seizure prediction. (2) We construct a two-dimensional, nonstationary chaotic map with a parameter slowly varying in a range containing a crisis, and test whether this critical event can be predicted by monitoring the evolution of finite-time Lyapunov exponents. This can thus be regarded as a "control test" for the claimed predictive power of the exponents for seizure. We find that two major obstacles arise in this application: statistical fluctuations of the Lyapunov exponents due to finite time computation and noise from the time series. We show that increasing the amount of data in a moving window will not improve the exponents' detective power for characteristic system changes, and that the presence of small noise can ruin completely the predictive power of the exponents. (3) We report negative results obtained from ECoG signals recorded from patients with epilepsy. All these indicate firmly that, the use of Lyapunov exponents for seizure prediction is practically impossible as the brain dynamical system generating the ECoG signals is more complicated than low-dimensional chaotic systems, and is noisy. Copyright 2004 American Institute of Physics

Using machine learning to predict wind turbine power output

International Nuclear Information System (INIS)

Clifton, A; Kilcher, L; Lundquist, J K; Fleming, P

2013-01-01

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. (letter)

Power Admission Control with Predictive Thermal Management in Smart Buildings

DEFF Research Database (Denmark)

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...

Design and manufacturing rules for maximizing the performance of polycrystalline piezoelectric bending actuators

International Nuclear Information System (INIS)

Jafferis, Noah T; Smith, Michael J; Wood, Robert J

2015-01-01

Increasing the energy and power density of piezoelectric actuators is very important for any weight-sensitive application, and is especially crucial for enabling autonomy in micro/milli-scale robots and devices utilizing this technology. This is achieved by maximizing the mechanical flexural strength and electrical dielectric strength through the use of laser-induced melting or polishing, insulating edge coating, and crack-arresting features, combined with features for rigid ground attachments to maximize force output. Manufacturing techniques have also been developed to enable mass customization, in which sheets of material are pre-stacked to form a laminate from which nearly arbitrary planar actuator designs can be fabricated using only laser cutting. These techniques have led to a 70% increase in energy density and an increase in mean lifetime of at least 15× compared to prior manufacturing methods. In addition, measurements have revealed a doubling of the piezoelectric coefficient when operating at the high fields necessary to achieve maximal energy densities, along with an increase in the Young’s modulus at the high compressive strains encountered—these two effects help to explain the higher performance of our actuators as compared to that predicted by linear models. (paper)

Optimization, characterization, and biological activity of polysaccharides from Berberis dasystachya Maxim.

Science.gov (United States)

Han, Lijuan; Suo, Yourui; Yang, Yongjing; Meng, Jing; Hu, Na

2016-04-01

In this study, the extraction of water-soluble polysaccharides (BDPs) from Berberis dasystachya Maxim using dynamic microwave-assisted extraction (DMAE) was discussed. A Box-Behnken design combined with response surface methodology has been employed to optimize extraction parameters of DMAE. The BDPs have been analyzed in order to identify a variety of chemical properties. Antioxidant and anti-tumor activities in vitro have been studied by DPPH, ABTS, reducing power assay, and MTT assay, respectively. The results obtained showed that the optimal extraction conditions were as follows: ratio of water to raw material (X1) 25.84 mg/L, extraction power (X2) 433.13W, extraction time (X3) 35.18 min, and the maximum yield of extraction was 6.472 ± 0.384%, which was in good agreement with the predicted value. The physicochemical tests demonstrated that the BDPs mainly consist of rhamnose, arabinose, xylose, mannose, glucose and lactose in a molar ratio of 1:17.3:1.33:7:2.33:1.78; the average molecular weight of the BDPs was estimated to be from 2.95×10(5) and 1.52×10(3)Da, respectively. Furthermore, the BDPs exhibited effective antioxidant and anti-proliferative properties in vitro. Such pharmaceutical activities could prove useful for potential future applications involving the berries of B. dasystachya Maxim. Copyright © 2015 Elsevier B.V. All rights reserved.

Adaptive maximal poisson-disk sampling on surfaces

KAUST Repository

Yan, Dongming

2012-01-01

In this paper, we study the generation of maximal Poisson-disk sets with varying radii on surfaces. Based on the concepts of power diagram and regular triangulation, we present a geometric analysis of gaps in such disk sets on surfaces, which is the key ingredient of the adaptive maximal Poisson-disk sampling framework. Moreover, we adapt the presented sampling framework for remeshing applications. Several novel and efficient operators are developed for improving the sampling/meshing quality over the state-of-theart. © 2012 ACM.

WPPT, a tool for on-line wind power prediction

Energy Technology Data Exchange (ETDEWEB)

Skov Nielsen, T. [Dept. of Mathematical Modelling (IMM-DTU), Kgs. Lyngby (Denmark); Madsen, H. [Dept. of Mathematical Modelling (IMM-DTU) Kgs. Lyngby (Denmark); Toefting, J. [Elsam, Fredericia (Denmark)

2004-07-01

This paper dsecribes VPPT (Wind Power Prediction Tool), an application for assessing the future available wind power up to 36 hours ahead in time. WPPT has been installed in the Eltra/Elsam central dispatch center since October 1997. The paper describes the prediction model used, the actual implementation of WPPT as well as the experience gained by the operators in the dispatch center (au)

On-line test of power distribution prediction system for boiling water reactors

International Nuclear Information System (INIS)

Nishizawa, Y.; Kiguchi, T.; Kobayashi, S.; Takumi, K.; Tanaka, H.; Tsutsumi, R.; Yokomi, M.

1982-01-01

A power distribution prediction system for boiling water reactors has been developed and its on-line performance test has proceeded at an operating commercial reactor. This system predicts the power distribution or thermal margin in advance of control rod operations and core flow rate change. This system consists of an on-line computer system, an operator's console with a color cathode-ray tube, and plant data input devices. The main functions of this system are present power distribution monitoring, power distribution prediction, and power-up trajectory prediction. The calculation method is based on a simplified nuclear thermal-hydraulic calculation, which is combined with a method of model identification to the actual reactor core state. It has been ascertained by the on-line test that the predicted power distribution (readings of traversing in-core probe) agrees with the measured data within 6% root-mean-square. The computing time required for one prediction calculation step is less than or equal to 1.5 min by an HIDIC-80 on-line computer

Wind power prediction based on genetic neural network

Science.gov (United States)

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.

A New Look at the Impact of Maximizing on Unhappiness: Two Competing Mediating Effects

Directory of Open Access Journals (Sweden)

Jiaxi Peng

2018-02-01

Full Text Available The current study aims to explore how the decision-making style of maximizing affects subjective well-being (SWB, which mainly focuses on the confirmation of the mediator role of regret and suppressing role of achievement motivation. A total of 402 Chinese undergraduate students participated in this study, in which they responded to the maximization, regret, and achievement motivation scales and SWB measures. Results suggested that maximizing significantly predicted SWB. Moreover, regret and achievement motivation (hope for success dimension could completely mediate and suppress this effect. That is, two competing indirect pathways exist between maximizing and SWB. One pathway is through regret. Maximizing typically leads one to regret, which could negatively predict SWB. Alternatively, maximizing could lead to high levels of hope for success, which were positively correlated with SWB. Findings offered a complex method of thinking about the relationship between maximizing and SWB.

The predictive power of Japanese candlestick charting in Chinese stock market

Science.gov (United States)

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.

No Mikheyev-Smirnov-Wolfenstein Effect in Maximal Mixing

OpenAIRE

Harrison, P. F.; Perkins, D. H.; Scott, W. G.

1996-01-01

We investigate the possible influence of the MSW effect on the expectations for the solar neutrino experiments in the maximal mixing scenario suggested by the atmospheric neutrino data. A direct numerical calculation of matter induced effects in the Sun shows that the naive vacuum predictions are left completely undisturbed in the particular case of maximal mixing, so that the MSW effect turns out to be unobservable. We give a qualitative explanation of this result.

Adaptive maximal poisson-disk sampling on surfaces

KAUST Repository

Yan, Dongming; Wonka, Peter

2012-01-01

In this paper, we study the generation of maximal Poisson-disk sets with varying radii on surfaces. Based on the concepts of power diagram and regular triangulation, we present a geometric analysis of gaps in such disk sets on surfaces, which

A THEORY OF MAXIMIZING SENSORY INFORMATION

NARCIS (Netherlands)

Hateren, J.H. van

1992-01-01

A theory is developed on the assumption that early sensory processing aims at maximizing the information rate in the channels connecting the sensory system to more central parts of the brain, where it is assumed that these channels are noisy and have a limited dynamic range. Given a stimulus power

Optimal Energy Management for a Smart Grid using Resource-Aware Utility Maximization

Science.gov (United States)

Abegaz, Brook W.; Mahajan, Satish M.; Negeri, Ebisa O.

2016-06-01

Heterogeneous energy prosumers are aggregated to form a smart grid based energy community managed by a central controller which could maximize their collective energy resource utilization. Using the central controller and distributed energy management systems, various mechanisms that harness the power profile of the energy community are developed for optimal, multi-objective energy management. The proposed mechanisms include resource-aware, multi-variable energy utility maximization objectives, namely: (1) maximizing the net green energy utilization, (2) maximizing the prosumers' level of comfortable, high quality power usage, and (3) maximizing the economic dispatch of energy storage units that minimize the net energy cost of the energy community. Moreover, an optimal energy management solution that combines the three objectives has been implemented by developing novel techniques of optimally flexible (un)certainty projection and appliance based pricing decomposition in an IBM ILOG CPLEX studio. A real-world, per-minute data from an energy community consisting of forty prosumers in Amsterdam, Netherlands is used. Results show that each of the proposed mechanisms yields significant increases in the aggregate energy resource utilization and welfare of prosumers as compared to traditional peak-power reduction methods. Furthermore, the multi-objective, resource-aware utility maximization approach leads to an optimal energy equilibrium and provides a sustainable energy management solution as verified by the Lagrangian method. The proposed resource-aware mechanisms could directly benefit emerging energy communities in the world to attain their energy resource utilization targets.

Predicting Output Power for Nearshore Wave Energy Harvesting

Directory of Open Access Journals (Sweden)

Henock Mamo Deberneh

2018-04-01

Full Text Available Energy harvested from a Wave Energy Converter (WEC varies greatly with the location of its installation. Determining an optimal location that can result in maximum output power is therefore critical. In this paper, we present a novel approach to predicting the output power of a nearshore WEC by characterizing ocean waves using floating buoys. We monitored the movement of the buoys using an Arduino-based data collection module, including a gyro-accelerometer sensor and a wireless transceiver. The collected data were utilized to train and test prediction models. The models were developed using machine learning algorithms: SVM, RF and ANN. The results of the experiments showed that measurements from the data collection module can yield a reliable predictor of output power. Furthermore, we found that the predictors work better when the regressors are combined with a classifier. The accuracy of the proposed prediction model suggests that it could be extremely useful in both locating optimal placement for wave energy harvesting plants and designing the shape of the buoys used by them.

Reserve design to maximize species persistence

Science.gov (United States)

Robert G. Haight; Laurel E. Travis

2008-01-01

We develop a reserve design strategy to maximize the probability of species persistence predicted by a stochastic, individual-based, metapopulation model. Because the population model does not fit exact optimization procedures, our strategy involves deriving promising solutions from theory, obtaining promising solutions from a simulation optimization heuristic, and...

Evaluation of peak power prediction equations in male basketball players.

Science.gov (United States)

Duncan, Michael J; Lyons, Mark; Nevill, Alan M

2008-07-01

This study compared peak power estimated using 4 commonly used regression equations with actual peak power derived from force platform data in a group of adolescent basketball players. Twenty-five elite junior male basketball players (age, 16.5 +/- 0.5 years; mass, 74.2 +/- 11.8 kg; height, 181.8 +/- 8.1 cm) volunteered to participate in the study. Actual peak power was determined using a countermovement vertical jump on a force platform. Estimated peak power was determined using countermovement jump height and body mass. All 4 prediction equations were significantly related to actual peak power (all p jump prediction equations, 12% for the Canavan and Vescovi equation, and 6% for the Sayers countermovement jump equation. In all cases peak power was underestimated.

Model output statistics applied to wind power prediction

Energy Technology Data Exchange (ETDEWEB)

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.

Prediction of Wind Energy Resources (PoWER) Users Guide

Science.gov (United States)

2016-01-01

ARL-TR-7573● JAN 2016 US Army Research Laboratory Prediction of Wind Energy Resources (PoWER) User’s Guide by David P Sauter...manufacturer’s or trade names does not constitute an official endorsement or approval of the use thereof. Destroy this report when it is no longer needed. Do...not return it to the originator. ARL-TR-7573 ● JAN 2016 US Army Research Laboratory Prediction of Wind Energy Resources (PoWER

Operational results from a physical power prediction model

Energy Technology Data Exchange (ETDEWEB)

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.

Maximal near-field radiative heat transfer between two plates

OpenAIRE

Nefzaoui, Elyes; Ezzahri, Younès; Drevillon, Jérémie; Joulain, Karl

2013-01-01

International audience; Near-field radiative transfer is a promising way to significantly and simultaneously enhance both thermo-photovoltaic (TPV) devices power densities and efficiencies. A parametric study of Drude and Lorentz models performances in maximizing near-field radiative heat transfer between two semi-infinite planes separated by nanometric distances at room temperature is presented in this paper. Optimal parameters of these models that provide optical properties maximizing the r...

Skill forecasting from different wind power ensemble prediction methods

International Nuclear Information System (INIS)

Pinson, Pierre; Nielsen, Henrik A; Madsen, Henrik; Kariniotakis, George

2007-01-01

This paper presents an investigation on alternative approaches to the providing of uncertainty estimates associated to point predictions of wind generation. Focus is given to skill forecasts in the form of prediction risk indices, aiming at giving 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 dispersion of ensemble members for a single prediction horizon, or over a set of successive look-ahead times. It is shown on the test case of a Danish offshore wind farm how prediction risk indices may be related to several levels of forecast uncertainty (and energy imbalances). Wind power ensemble predictions are derived from the transformation of ECMWF and NCEP ensembles of meteorological variables to power, as well as by a lagged average approach alternative. The ability of risk indices calculated from the various types of ensembles forecasts to resolve among situations with different levels of uncertainty is discussed

With age a lower individual breathing reserve is associated with a higher maximal heart rate.

Science.gov (United States)

Burtscher, Martin; Gatterer, Hannes; Faulhaber, Martin; Burtscher, Johannes

2018-01-01

Maximal heart rate (HRmax) is linearly declining with increasing age. Regular exercise training is supposed to partly prevent this decline, whereas sex and habitual physical activity do not. High exercise capacity is associated with a high cardiac output (HR x stroke volume) and high ventilatory requirements. Due to the close cardiorespiratory coupling, we hypothesized that the individual ventilatory response to maximal exercise might be associated with the age-related HRmax. Retrospective analyses have been conducted on the results of 129 consecutively performed routine cardiopulmonary exercise tests. The study sample comprised healthy subjects of both sexes of a broad range of age (20-86 years). Maximal values of power output, minute ventilation, oxygen uptake and heart rate were assessed by the use of incremental cycle spiroergometry. Linear multivariate regression analysis revealed that in addition to age the individual breathing reserve at maximal exercise was independently predictive for HRmax. A lower breathing reserve due to a high ventilatory demand and/or a low ventilatory capacity, which is more pronounced at a higher age, was associated with higher HRmax. Age explained the observed variance in HRmax by 72% and was improved to 83% when the variable "breathing reserve" was entered. The presented findings indicate an independent association between the breathing reserve at maximal exercise and maximal heart rate, i.e. a low individual breathing reserve is associated with a higher age-related HRmax. A deeper understanding of this association has to be investigated in a more physiological scenario. Copyright © 2017 Elsevier B.V. All rights reserved.

Phenomenology of maximal and near-maximal lepton mixing

International Nuclear Information System (INIS)

Gonzalez-Garcia, M. C.; Pena-Garay, Carlos; Nir, Yosef; Smirnov, Alexei Yu.

2001-01-01

The possible existence of maximal or near-maximal lepton mixing constitutes an intriguing challenge for fundamental theories of flavor. We study the phenomenological consequences of maximal and near-maximal mixing of the electron neutrino with other (x=tau and/or muon) neutrinos. We describe the deviations from maximal mixing in terms of a parameter ε(equivalent to)1-2sin 2 θ ex and quantify the present experimental status for |ε| e mixing comes from solar neutrino experiments. We find that the global analysis of solar neutrino data allows maximal mixing with confidence level better than 99% for 10 -8 eV 2 ∼ 2 ∼ -7 eV 2 . In the mass ranges Δm 2 ∼>1.5x10 -5 eV 2 and 4x10 -10 eV 2 ∼ 2 ∼ -7 eV 2 the full interval |ε| e mixing in atmospheric neutrinos, supernova neutrinos, and neutrinoless double beta decay

Maximal heart rate does not limit cardiovascular capacity in healthy humans

DEFF Research Database (Denmark)

Munch, G D W; Svendsen, J H; Damsgaard, R

2014-01-01

In humans, maximal aerobic power (VO2 max ) is associated with a plateau in cardiac output (Q), but the mechanisms regulating the interplay between maximal heart rate (HRmax) and stroke volume (SV) are unclear. To evaluate the effect of tachycardia and elevations in HRmax on cardiovascular function...... and capacity during maximal exercise in healthy humans, 12 young male cyclists performed incremental cycling and one-legged knee-extensor exercise (KEE) to exhaustion with and without right atrial pacing to increase HR. During control cycling, Q and leg blood flow increased up to 85% of maximal workload (WLmax...... and RAP (P healthy...

Crossfit-based high-intensity power training improves maximal aerobic fitness and body composition.

Science.gov (United States)

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.

Feature Selection and ANN Solar Power Prediction

Directory of Open Access Journals (Sweden)

Daniel O’Leary

2017-01-01

Full Text Available A novel method of solar power forecasting for individuals and small businesses is developed in this paper based on machine learning, image processing, and acoustic classification techniques. Increases in the production of solar power at the consumer level require automated forecasting systems to minimize loss, cost, and environmental impact for homes and businesses that produce and consume power (prosumers. These new participants in the energy market, prosumers, require new artificial neural network (ANN performance tuning techniques to create accurate ANN forecasts. Input masking, an ANN tuning technique developed for acoustic signal classification and image edge detection, is applied to prosumer solar data to improve prosumer forecast accuracy over traditional macrogrid ANN performance tuning techniques. ANN inputs tailor time-of-day masking based on error clustering in the time domain. Results show an improvement in prediction to target correlation, the R2 value, lowering inaccuracy of sample predictions by 14.4%, with corresponding drops in mean average error of 5.37% and root mean squared error of 6.83%.

The Comparison Study of Short-Term Prediction Methods to Enhance the Model Predictive Controller Applied to Microgrid Energy Management

Directory of Open Access Journals (Sweden)

César Hernández-Hernández

2017-06-01

Full Text Available Electricity load forecasting, optimal power system operation and energy management play key roles that can bring significant operational advantages to microgrids. This paper studies how methods based on time series and neural networks can be used to predict energy demand and production, allowing them to be combined with model predictive control. Comparisons of different prediction methods and different optimum energy distribution scenarios are provided, permitting us to determine when short-term energy prediction models should be used. The proposed prediction models in addition to the model predictive control strategy appear as a promising solution to energy management in microgrids. The controller has the task of performing the management of electricity purchase and sale to the power grid, maximizing the use of renewable energy sources and managing the use of the energy storage system. Simulations were performed with different weather conditions of solar irradiation. The obtained results are encouraging for future practical implementation.

Power Relative to Body Mass Best Predicts Change in Core Temperature During Exercise-Heat Stress.

Science.gov (United States)

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

Using data-driven approach for wind power prediction: A comparative study

International Nuclear Information System (INIS)

Taslimi Renani, Ehsan; Elias, Mohamad Fathi Mohamad; Rahim, Nasrudin Abd.

2016-01-01

Highlights: • Double exponential smoothing is the most accurate model in wind speed prediction. • A two-stage feature selection method is proposed to select most important inputs. • Direct prediction illustrates better accuracy than indirect prediction. • Adaptive neuro fuzzy inference system outperforms data mining algorithms. • Random forest performs the worst compared to other data mining algorithm. - Abstract: Although wind energy is intermittent and stochastic in nature, it is increasingly important in the power generation due to its sustainability and pollution-free. Increased utilization of wind energy sources calls for more robust and efficient prediction models to mitigate uncertainties associated with wind power. This research compares two different approaches in wind power forecasting which are indirect and direct prediction methods. In indirect method, several times series are applied to forecast the wind speed, whereas the logistic function with five parameters is then used to forecast the wind power. In this study, backtracking search algorithm with novel crossover and mutation operators is employed to find the best parameters of five-parameter logistic function. A new feature selection technique, combining the mutual information and neural network is proposed in this paper to extract the most informative features with a maximum relevancy and minimum redundancy. From the comparative study, the results demonstrate that, in the direct prediction approach where the historical weather data are used to predict the wind power generation directly, adaptive neuro fuzzy inference system outperforms five data mining algorithms namely, random forest, M5Rules, k-nearest neighbor, support vector machine and multilayer perceptron. Moreover, it is also found that the mean absolute percentage error of the direct prediction method using adaptive neuro fuzzy inference system is 1.47% which is approximately less than half of the error obtained with the

A New Optimization Approach for Maximizing the Photovoltaic Panel Power Based on Genetic Algorithm and Lagrange Multiplier Algorithm

Directory of Open Access Journals (Sweden)

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.

Testing the predictive power of nuclear mass models

International Nuclear Information System (INIS)

Mendoza-Temis, J.; Morales, I.; Barea, J.; Frank, A.; Hirsch, J.G.; Vieyra, J.C. Lopez; Van Isacker, P.; Velazquez, V.

2008-01-01

A number of tests are introduced which probe the ability of nuclear mass models to extrapolate. Three models are analyzed in detail: the liquid drop model, the liquid drop model plus empirical shell corrections and the Duflo-Zuker mass formula. If predicted nuclei are close to the fitted ones, average errors in predicted and fitted masses are similar. However, the challenge of predicting nuclear masses in a region stabilized by shell effects (e.g., the lead region) is far more difficult. The Duflo-Zuker mass formula emerges as a powerful predictive tool

Sludge pipe flow pressure drop prediction using composite power ...

African Journals Online (AJOL)

Sludge pipe flow pressure drop prediction using composite power-law friction ... Water SA. Journal Home · ABOUT THIS JOURNAL · Advanced Search · Current Issue ... When predicting pressure gradients for the flow of sludges in pipes, the ...

Significant change of predictions related to the future of nuclear power

International Nuclear Information System (INIS)

Dumitrache, Ion

2002-01-01

.6 Gwe (minimal), or 20.7 Gwe (maximal); in Taiwan, from 4.884 Gwe (1999) to 7.514 Gwe (2020, ref.); in India, from 1.897 Gwe (1999) to 7.571 Gwe (2020, ref.); in Japan, from 43.7 Gwe (1999) to 56.6 Gwe (2020, ref.); in Korea, from 13.0 Gwe (1999), to 22.1 Gwe (2020, ref.). An ambitious increase is related to the prognosis in Brazil, from 0.626 Gwe (1999) to 3.084 Gwe (2020, ref.) For the group of the all non-developed countries, other than the Eastern European ones, the predicted increase of the installed nuclear power is from 25.466 Gwe (1999) to 65.824 Gwe (2020, ref.). The decrease of the fission contribution in the European countries that are against new NPP is not very fast in the 1999-2020 period of forecast: Germany, from 21.122 Gwe to 13.134 Gwe; Sweden, from 9.432 Gwe to 6.077 Gwe; Belgium, from 5.712 Gwe to 3.966 Gwe. In Romania, a National Nuclear Plan will schedule the commissioning of the next Cernavoda NPP Units. The intention to complete the work for all the 5 Units before 2020 is clear. There are predictions that indicate 5 Units in operation at Cernavoda NPP several years earlier. A major change in the nuclear power field is related to the advanced reactors. The 'Generation III' will cover the needs for the next 10-20 years. These advanced reactors are significantly safer, cheaper, and the initial time for construction and commissioning is reduced. Most of the already available designs are based on the 'innovative concepts' and, mainly, on the 'evolutionary solutions' related to the operation of the existent NPP. The 'Generation IV' is one of the main R and D tasks of DOE, USA. Any concept and idea is accepted for development and evaluation. The needed advanced reactors are expected in the 2020-2030 period. In conclusion, the recent forecasts of the future of fission based nuclear power indicate a significant contribution to the electricity generation worldwide, at least for the first half of the century. (author)

Analysis of the maximal possible grid relief from PV-peak-power impacts by using storage systems for increased self-consumption

International Nuclear Information System (INIS)

Moshövel, Janina; Kairies, Kai-Philipp; Magnor, Dirk; Leuthold, Matthias; Bost, Mark; Gährs, Swantje; Szczechowicz, Eva; Cramer, Moritz; Sauer, Dirk Uwe

2015-01-01

Highlights: • Presentation of a MATLAB battery storage model. • Development of a controlled persistence forecast management strategy. • Perfect forecast in comparison to an easy feasible persistence forecast. • More grid relief with forecast than with strategies to maximize self-consumption. - Abstract: For future energy supply systems the effects and benefits of battery storage systems in households with photovoltaic (PV) generators and the effects on distribution and transmission grids need to be identified and analyzed. The development of grid relieving management strategies for the storage system in due consideration of self-consumption is a necessary step forward in order to analyze the potential of private home battery storage systems to reduce stress on the power supply system. A MATLAB-based model of a lithium-ion storage system has been developed. The model is applicable for a wide range of PV generator sizes, different battery storage systems and diverse management strategies. In order to identify the potential of grid relieving forecast strategies, without discharging the storage into the grid, a management strategy based on persistence forecasts of solar radiation and household load demand has been implemented and analyzed. To minimize forecast uncertainties a proportional plus integral controller has been developed. The persistence forecast management strategy is applicable in real-life PV-battery-systems and due to the simple forecast it is easy to equip existing systems with such a management system with only low effort. As a result it will be shown that a storage system management based on forecasts has a significantly higher potential to relieve the grid than a system that only maximizes self-consumption as it is usually used nowadays. Besides, such a management strategy is able to unload the grid more than a static power reduction to 70% of the nominal power rating according to the current German Renewable Energy Sources Act (EEG). At the

Maximal aerobic and anaerobic power generation in large crocodiles versus mammals: implications for dinosaur gigantothermy.

Science.gov (United States)

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.

Maximal aerobic and anaerobic power generation in large crocodiles versus mammals: implications for dinosaur gigantothermy.

Directory of Open Access Journals (Sweden)

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.

Phasic dopamine as a prediction error of intrinsic and extrinsic reinforcements driving both action acquisition and reward maximization: a simulated robotic study.

Science.gov (United States)

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. Copyright © 2013 Elsevier Ltd. All rights reserved.

Factors associated with maximal walking speed among older community-living adults

DEFF Research Database (Denmark)

Sallinen, Janne; Mänty, Minna; Leinonen, Raija

2011-01-01

explained to 38%. Further adjusting for physical activity, smoking status and use of alcohol increased the variation explained by additional 7%. A minor further increase in variability explained was gained by adding chronic diseases and depressive symptoms in the model. In the final model, the single most...... 07330512) involving 605 community-living ambulatory adults aged 75-81 years. Maximal walking speed, leg extensor power, standing balance and body mass index were measured at the research center. Physical activity, smoking, use of alcohol, chronic diseases and depressive symptoms were self-reported using...... standard questionnaires. Results: The mean maximal walking speed was 1.4 m/s (range 0.3-2.9). In linear regression analysis, age, gender and body mass index explained 11% of the variation in maximal walking speed. Adding leg extensor power and standing balance into the model increased the variation...

Maximal aerobic power in cycle ergometry in middle-aged men and women, active in sports, in relation to age and physical activity.

Science.gov (United States)

Bovens, A M; van Baak, M A; Vrencken, J G; Wijnen, J A; Saris, W H; Verstappen, F T

1993-02-01

Reliable standards of maximal power output in middle-aged and physically active men and women are desirable in sports-medical practice. For this purpose maximal cycle ergometer tests were evaluated in 2038 men and 898 women over 40 years of age (46.8 +/- 6.1 years (mean +/- SD) and 47.5 +/- 6.6 years), who volunteered in a sports-medical check-up and all of whom were active in sports for at least three months in the year preceding the screening (4.3 +/- 3.1 hours/week respectively 3.6 +/- 2.5 hours/week). The range of maximal values for power output (Wmax), heart rate (HRmax), systolic blood pressure (SBPmax) and peak plasma lactate concentrations (PPLa) during progressive cycle ergometer testing are presented for males and females who were divided into groups with a 5-years age difference. Wmax varied with sex (male = 1, female = 0), age (year) and height (cm); Wmax = 65.3 x (sex) + 2.0 x (height) -1.9 x (age) - 67.9 (See = 38.2; r = 0.76). The weighing of different factors that influence performance was also studied by multiple regression analysis to provide improved precision in standards used to interpret exercise tests. In both men and women about half of the variation of Wmax could be explained by the independent variables age, body mass, body fat, smoking habits, vital capacity, heart rate, and physical activity parameters. It is concluded that active involvement in endurance sports and/or the use of the bicycle for transport, contributed substantially to cardiovascular fitness in healthy, middle-aged men and women.

Synchrophasor-Assisted Prediction of Stability/Instability of a Power System

Science.gov (United States)

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.

Effect of formoterol, a long-acting β2-adrenergic agonist, on muscle strength and power output, metabolism and fatigue during maximal sprinting in men

DEFF Research Database (Denmark)

Kalsen, Anders; Hostrup, Morten; Backer, Vibeke

2016-01-01

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, thirteen males (VO2max: 45.0±0.2 (mean±SE) m......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...

Introducing Model Predictive Control for Improving Power Plant Portfolio Performance

DEFF Research Database (Denmark)

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...

Probabilistic Forecasts of Wind Power Generation by Stochastic Differential Equation Models

DEFF Research Database (Denmark)

Møller, Jan Kloppenborg; Zugno, Marco; Madsen, Henrik

2016-01-01

The increasing penetration of wind power has resulted in larger shares of volatile sources of supply in power systems worldwide. In order to operate such systems efficiently, methods for reliable probabilistic forecasts of future wind power production are essential. It is well known...... that the conditional density of wind power production is highly dependent on the level of predicted wind power and prediction horizon. This paper describes a new approach for wind power forecasting based on logistic-type stochastic differential equations (SDEs). The SDE formulation allows us to calculate both state......-dependent conditional uncertainties as well as correlation structures. Model estimation is performed by maximizing the likelihood of a multidimensional random vector while accounting for the correlation structure defined by the SDE formulation. We use non-parametric modelling to explore conditional correlation...

Trend analysis of the power law process using Expectation-Maximization algorithm for data censored by inspection intervals

International Nuclear Information System (INIS)

Taghipour, Sharareh; Banjevic, Dragan

2011-01-01

Trend analysis is a common statistical method used to investigate the operation and changes of a repairable system over time. This method takes historical failure data of a system or a group of similar systems and determines whether the recurrent failures exhibit an increasing or decreasing trend. Most trend analysis methods proposed in the literature assume that the failure times are known, so the failure data is statistically complete; however, in many situations, such as hidden failures, failure times are subject to censoring. In this paper we assume that the failure process of a group of similar independent repairable units follows a non-homogenous Poisson process with a power law intensity function. Moreover, the failure data are subject to left, interval and right censoring. The paper proposes using the likelihood ratio test to check for trends in the failure data. It uses the Expectation-Maximization (EM) algorithm to find the parameters, which maximize the data likelihood in the case of null and alternative hypotheses. A recursive procedure is used to solve the main technical problem of calculating the expected values in the Expectation step. The proposed method is applied to a hospital's maintenance data for trend analysis of the components of a general infusion pump.

Hybrid robust predictive optimization method of power system dispatch

Science.gov (United States)

Chandra, Ramu Sharat [Niskayuna, NY; Liu, Yan [Ballston Lake, NY; Bose, Sumit [Niskayuna, NY; de Bedout, Juan Manuel [West Glenville, NY

2011-08-02

A method of power system dispatch control solves power system dispatch problems by integrating a larger variety of generation, load and storage assets, including without limitation, combined heat and power (CHP) units, renewable generation with forecasting, controllable loads, electric, thermal and water energy storage. The method employs a predictive algorithm to dynamically schedule different assets in order to achieve global optimization and maintain the system normal operation.

Wind Power Plant Prediction by Using Neural Networks: Preprint

Energy Technology Data Exchange (ETDEWEB)

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.

Maximal Bell's inequality violation for non-maximal entanglement

International Nuclear Information System (INIS)

Kobayashi, M.; Khanna, F.; Mann, A.; Revzen, M.; Santana, A.

2004-01-01

Bell's inequality violation (BIQV) for correlations of polarization is studied for a product state of two two-mode squeezed vacuum (TMSV) states. The violation allowed is shown to attain its maximal limit for all values of the squeezing parameter, ζ. We show via an explicit example that a state whose entanglement is not maximal allow maximal BIQV. The Wigner function of the state is non-negative and the average value of either polarization is nil

Pre-stimulus thalamic theta power predicts human memory formation.

Science.gov (United States)

Sweeney-Reed, Catherine M; Zaehle, Tino; Voges, Jürgen; Schmitt, Friedhelm C; Buentjen, Lars; Kopitzki, Klaus; Richardson-Klavehn, Alan; Hinrichs, Hermann; Heinze, Hans-Jochen; Knight, Robert T; Rugg, Michael D

2016-09-01

Pre-stimulus theta (4-8Hz) power in the hippocampus and neocortex predicts whether a memory for a subsequent event will be formed. Anatomical studies reveal thalamus-hippocampal connectivity, and lesion, neuroimaging, and electrophysiological studies show that memory processing involves the dorsomedial (DMTN) and anterior thalamic nuclei (ATN). The small size and deep location of these nuclei have limited real-time study of their activity, however, and it is unknown whether pre-stimulus theta power predictive of successful memory formation is also found in these subcortical structures. We recorded human electrophysiological data from the DMTN and ATN of 7 patients receiving deep brain stimulation for refractory epilepsy. We found that greater pre-stimulus theta power in the right DMTN was associated with successful memory encoding, predicting both behavioral outcome and post-stimulus correlates of successful memory formation. In particular, significant correlations were observed between right DMTN theta power and both frontal theta and right ATN gamma (32-50Hz) phase alignment, and frontal-ATN theta-gamma cross-frequency coupling. We draw the following primary conclusions. Our results provide direct electrophysiological evidence in humans of a role for the DMTN as well as the ATN in memory formation. Furthermore, prediction of subsequent memory performance by pre-stimulus thalamic oscillations provides evidence that post-stimulus differences in thalamic activity that index successful and unsuccessful encoding reflect brain processes specifically underpinning memory formation. Finally, the findings broaden the understanding of brain states that facilitate memory encoding to include subcortical as well as cortical structures. Copyright © 2016 Elsevier Inc. All rights reserved.

Uncertainties in predicting solar panel power output

Science.gov (United States)

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.

Predictive Maintenance: One key to improved power plant availability

International Nuclear Information System (INIS)

Mobley; Allen, J.W.

1986-01-01

Recent developments in microprocessor technology has provided the ability to routinely monitor the actual mechanical condition of all rotating and reciprocating machinery and process variables (i.e. pressure, temperature, flow, etc.) of other process equipment within an operating electric power generating plant. This direct correlation between frequency domain vibration and actual mechanical condition of machinery and trending process variables of non-rotating equipment can provide the ''key'' to improving the availability and reliability, thermal efficiency and provide the baseline information necessary for developing a realistic plan for extending the useful life of power plants. The premise of utilizing microprocessor-based Predictive Maintenance to improve power plant operation has been proven by a number of utilities. This paper provides a comprehensive discussion of the TEC approach to Predictive Maintenance and examples of successful programs

Maximizing as a predictor of job satisfaction and performance: A tale of three scales

Directory of Open Access Journals (Sweden)

Nicole M. Giacopelli

2013-07-01

Full Text Available Research on individual differences in maximizing (versus satisficing has recently proliferated in the Judgment and Decision Making literature, and high scores on this construct have been linked to lower life satisfaction as well as, in some cases, to worse decision-making performance. The current study exported this construct to the organizational domain and evaluated the utility of the three most widely used measures of maximizing in predicting several criteria of interest to organizational researchers: job satisfaction, intentions to quit the organization, performance in the job role, and income. Moreover, this study used relative weight analyses to determine the relative importance of maximizing and two dispositional variables (conscientiousness and core self-evaluations that are traditionally used to predict these criteria in the organizational literature. Results indicate that relationships between maximizing and these criteria are influenced by the way in which maximizing is measured. Yet, regardless of how it is measured, maximizing is not a particularly strong predictor of these criteria compared to traditional organizational predictors. Limitations and future research directions are discussed.

Predicting Power Outages Using Multi-Model Ensemble Forecasts

Science.gov (United States)

Cerrai, D.; Anagnostou, E. N.; Yang, J.; Astitha, M.

2017-12-01

Power outages affect every year millions of people in the United States, affecting the economy and conditioning the everyday life. An Outage Prediction Model (OPM) has been developed at the University of Connecticut for helping utilities to quickly restore outages and to limit their adverse consequences on the population. The OPM, operational since 2015, combines several non-parametric machine learning (ML) models that use historical weather storm simulations and high-resolution weather forecasts, satellite remote sensing data, and infrastructure and land cover data to predict the number and spatial distribution of power outages. A new methodology, developed for improving the outage model performances by combining weather- and soil-related variables using three different weather models (WRF 3.7, WRF 3.8 and RAMS/ICLAMS), will be presented in this study. First, we will present a performance evaluation of each model variable, by comparing historical weather analyses with station data or reanalysis over the entire storm data set. Hence, each variable of the new outage model version is extracted from the best performing weather model for that variable, and sensitivity tests are performed for investigating the most efficient variable combination for outage prediction purposes. Despite that the final variables combination is extracted from different weather models, this ensemble based on multi-weather forcing and multi-statistical model power outage prediction outperforms the currently operational OPM version that is based on a single weather forcing variable (WRF 3.7), because each model component is the closest to the actual atmospheric state.

Thermal Storage Power Balancing with Model Predictive Control

DEFF Research Database (Denmark)

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...

MODEL PREDICTIVE CONTROL FOR PHOTOVOLTAIC STATION MAXIMUM POWER POINT TRACKING SYSTEM

Directory of Open Access Journals (Sweden)

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.

Gap processing for adaptive maximal poisson-disk sampling

KAUST Repository

Yan, Dongming; Wonka, Peter

2013-01-01

In this article, we study the generation of maximal Poisson-disk sets with varying radii. First, we present a geometric analysis of gaps in such disk sets. This analysis is the basis for maximal and adaptive sampling in Euclidean space and on manifolds. Second, we propose efficient algorithms and data structures to detect gaps and update gaps when disks are inserted, deleted, moved, or when their radii are changed.We build on the concepts of regular triangulations and the power diagram. Third, we show how our analysis contributes to the state-of-the-art in surface remeshing. © 2013 ACM.

Gap processing for adaptive maximal poisson-disk sampling

KAUST Repository

Yan, Dongming

2013-10-17

In this article, we study the generation of maximal Poisson-disk sets with varying radii. First, we present a geometric analysis of gaps in such disk sets. This analysis is the basis for maximal and adaptive sampling in Euclidean space and on manifolds. Second, we propose efficient algorithms and data structures to detect gaps and update gaps when disks are inserted, deleted, moved, or when their radii are changed.We build on the concepts of regular triangulations and the power diagram. Third, we show how our analysis contributes to the state-of-the-art in surface remeshing. © 2013 ACM.

Predicting Harmonic Distortion of Multiple Converters in a Power System

Directory of Open Access Journals (Sweden)

P. M. Ivry

2017-01-01

Full Text Available Various uncertainties arise in the operation and management of power systems containing Renewable Energy Sources (RES that affect the systems power quality. These uncertainties may arise due to system parameter changes or design parameter choice. In this work, the impact of uncertainties on the prediction of harmonics in a power system containing multiple Voltage Source Converters (VSCs is investigated. The study focuses on the prediction of harmonic distortion level in multiple VSCs when some system or design parameters are only known within certain constraints. The Univariate Dimension Reduction (UDR method was utilized in this study as an efficient predictive tool for the level of harmonic distortion of the VSCs measured at the Point of Common Coupling (PCC to the grid. Two case studies were considered and the UDR technique was also experimentally validated. The obtained results were compared with that of the Monte Carlo Simulation (MCS results.

What currency do bumble bees maximize?

Directory of Open Access Journals (Sweden)

Nicholas L Charlton

2010-08-01

Full Text Available In modelling bumble bee foraging, net rate of energetic intake has been suggested as the appropriate currency. The foraging behaviour of honey bees is better predicted by using efficiency, the ratio of energetic gain to expenditure, as the currency. We re-analyse several studies of bumble bee foraging and show that efficiency is as good a currency as net rate in terms of predicting behaviour. We suggest that future studies of the foraging of bumble bees should be designed to distinguish between net rate and efficiency maximizing behaviour in an attempt to discover which is the more appropriate currency.

Maximize the operating profit of a SWRO-PRO integrated process for optimal water production and energy recovery

KAUST Repository

Wan, Chun Feng; Chung, Neal Tai-Shung

2016-01-01

Pressure retarded osmosis (PRO) is a promising technology to reduce the specific energy consumption and the operating expenditure of a seawater reverse osmosis (SWRO) plant. In this study, a simple analytical PRO model is developed to predict the PRO performance as the dilution of draw solutions occurs. The model can predict the PRO performance with a high accuracy without carrying out complicated integrations and experiments. The operating profit of SWRO-PRO is also studied by calculating the profit generated for every m3 of seawater entering the process because maximizing the operating profit is the uttermost objective of the SWRO-PRO process. Based on the PRO analytical model, the operating profit and the dynamics of the SWRO-PRO process, a strategy has been proposed to maximize the operating profit of the SWRO-PRO process while maintaining the highest power density of the PRO membranes. This study proves that integration of SWRO with PRO can (1) push the SWRO to a higher recovery and maintain its high profitability, (2) effectively reduce the specific energy consumption of desalination by up to 35% and (3) increase the operating profit up to 100%. © 2016 Elsevier Ltd.

Maximize the operating profit of a SWRO-PRO integrated process for optimal water production and energy recovery

KAUST Repository

Wan, Chun Feng

2016-03-28

Pressure retarded osmosis (PRO) is a promising technology to reduce the specific energy consumption and the operating expenditure of a seawater reverse osmosis (SWRO) plant. In this study, a simple analytical PRO model is developed to predict the PRO performance as the dilution of draw solutions occurs. The model can predict the PRO performance with a high accuracy without carrying out complicated integrations and experiments. The operating profit of SWRO-PRO is also studied by calculating the profit generated for every m3 of seawater entering the process because maximizing the operating profit is the uttermost objective of the SWRO-PRO process. Based on the PRO analytical model, the operating profit and the dynamics of the SWRO-PRO process, a strategy has been proposed to maximize the operating profit of the SWRO-PRO process while maintaining the highest power density of the PRO membranes. This study proves that integration of SWRO with PRO can (1) push the SWRO to a higher recovery and maintain its high profitability, (2) effectively reduce the specific energy consumption of desalination by up to 35% and (3) increase the operating profit up to 100%. © 2016 Elsevier Ltd.

Is the β phase maximal?

International Nuclear Information System (INIS)

Ferrandis, Javier

2005-01-01

The current experimental determination of the absolute values of the CKM elements indicates that 2 vertical bar V ub /V cb V us vertical bar =(1-z), with z given by z=0.19+/-0.14. This fact implies that irrespective of the form of the quark Yukawa matrices, the measured value of the SM CP phase β is approximately the maximum allowed by the measured absolute values of the CKM elements. This is β=(π/6-z/3) for γ=(π/3+z/3), which implies α=π/2. Alternatively, assuming that β is exactly maximal and using the experimental measurement sin(2β)=0.726+/-0.037, the phase γ is predicted to be γ=(π/2-β)=66.3 o +/-1.7 o . The maximality of β, if confirmed by near-future experiments, may give us some clues as to the origin of CP violation

Model predictive control of a waste heat recovery system for automotive diesel engines

NARCIS (Netherlands)

Feru, E.; Willems, F.P.T.; de Jager, A.G.; Steinbuch, M.

2014-01-01

In this paper, a switching Model Predictive Control strategy is designed for an automotive Waste Heat Recovery system with two parallel evaporators. The objective is to maximize Waste Heat Recovery system output power, while satisfying safe operation under highly dynamic disturbances from the

Noncircular Chainrings Do Not Influence Maximum Cycling Power.

Science.gov (United States)

Leong, Chee-Hoi; Elmer, Steven J; Martin, James C

2017-12-01

Noncircular chainrings could increase cycling power by prolonging the powerful leg extension/flexion phases, and curtailing the low-power transition phases. We compared maximal cycling power-pedaling rate relationships, and joint-specific kinematics and powers across 3 chainring eccentricities (CON = 1.0; LOW ecc  = 1.13; HIGH ecc  = 1.24). Part I: Thirteen cyclists performed maximal inertial-load cycling under 3 chainring conditions. Maximum cycling power and optimal pedaling rate were determined. Part II: Ten cyclists performed maximal isokinetic cycling (120 rpm) under the same 3 chainring conditions. Pedal and joint-specific powers were determined using pedal forces and limb kinematics. Neither maximal cycling power nor optimal pedaling rate differed across chainring conditions (all p > .05). Peak ankle angular velocity for HIGH ecc was less than CON (p pedal system allowed cyclists to manipulate ankle angular velocity to maintain their preferred knee and hip actions, suggesting maximizing extension/flexion and minimizing transition phases may be counterproductive for maximal power.

GAPIT: genome association and prediction integrated tool.

Science.gov (United States)

Lipka, Alexander E; Tian, Feng; Wang, Qishan; Peiffer, Jason; Li, Meng; Bradbury, Peter J; Gore, Michael A; Buckler, Edward S; Zhang, Zhiwu

2012-09-15

Software programs that conduct genome-wide association studies and genomic prediction and selection need to use methodologies that maximize statistical power, provide high prediction accuracy and run in a computationally efficient manner. We developed an R package called Genome Association and Prediction Integrated Tool (GAPIT) that implements advanced statistical methods including the compressed mixed linear model (CMLM) and CMLM-based genomic prediction and selection. The GAPIT package can handle large datasets in excess of 10 000 individuals and 1 million single-nucleotide polymorphisms with minimal computational time, while providing user-friendly access and concise tables and graphs to interpret results. http://www.maizegenetics.net/GAPIT. zhiwu.zhang@cornell.edu Supplementary data are available at Bioinformatics online.

VT Predicted Mean Wind Power - 50 meter height

Data.gov (United States)

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...

Critical power prediction by CATHARE2 of the OECD/NRC BFBT benchmark

Energy Technology Data Exchange (ETDEWEB)

Lutsanych, Sergii, E-mail: s.lutsanych@ing.unipi.it [San Piero a Grado Nuclear Research Group (GRNSPG), University of Pisa, Via Livornese 1291, 56122, San Piero a Grado, Pisa (Italy); Sabotinov, Luben, E-mail: luben.sabotinov@irsn.fr [Institut for Radiological Protection and Nuclear Safety (IRSN), 31 avenue de la Division Leclerc, 92262 Fontenay-aux-Roses (France); D’Auria, Francesco, E-mail: francesco.dauria@dimnp.unipi.it [San Piero a Grado Nuclear Research Group (GRNSPG), University of Pisa, Via Livornese 1291, 56122, San Piero a Grado, Pisa (Italy)

2015-03-15

Highlights: • We used CATHARE code to calculate the critical power exercises of the OECD/NRC BFBT benchmark. • We considered both steady-state and transient critical power tests of the benchmark. • We used both the 1D and 3D features of the CATHARE code to simulate the experiments. • Acceptable prediction of the critical power and its location in the bundle is obtained using appropriate modelling. - Abstract: This paper presents an application of the French best estimate thermal-hydraulic code CATHARE 2 to calculate the critical power and departure from nucleate boiling (DNB) exercises of the International OECD/NRC BWR Fuel Bundle Test (BFBT) benchmark. The assessment activity is performed comparing the code calculation results with available in the framework of the benchmark experimental data from Japanese Nuclear Power Engineering Corporation (NUPEC). Two-phase flow calculations on prediction of the critical power have been carried out both in steady state and transient cases, using one-dimensional and three-dimensional modelling. Results of the steady-state critical power tests calculation have shown the ability of CATHARE code to predict reasonably the critical power and its location, using appropriate modelling.

Prediction of power-ramp defects in CANDU fuel

International Nuclear Information System (INIS)

Gillespie, P.; Wadsworth, S.; Daniels, T.

2010-01-01

Power ramps result in fuel pellet expansion and can lead to fuel sheath failures by fission product induced stress corrosion cracking (SCC). Historically, empirical models fit to experimental test data were used to predict the onset of power-ramp failures in CANDU fuel. In 1988, a power-ramped fuel defect event at PNGS-1 led to the refinement of these empirical models. This defect event has recently been re-analyzed and the empirical model updated. The empirical model is supported by a physically based model which can be used to extrapolate to fuel conditions (density, burnup) outside of the 1988 data set. (author)

Relations of morphological characteristics and maximal oxygen consumption of fourth grade pupils based on gender

Directory of Open Access Journals (Sweden)

Jakovljević Vladimir

2014-01-01

Full Text Available On a sample of 71 respondents, 37 boys and 34 girls, age of fourth grade elementary school, accordingly 9 years +/- 6 months, it is assessed correlation and prediction of maximal oxygen consumption based measures of morphological range. Maximum oxygen consumption was measured by indirect method, using a field test of maximal multiple load of feedback running at 20 meters. Range of morphology was analyzed based on 5 measures of longitudinal dimensionality, 4 measures of volume and body mass and 3 measures of transversal dimensionality. Results of correlation analysis showed that in both sexes there was no statistically significant correlation between results of maximal oxygen consumption and measures of longitudinal dimensionality, while regression analysis confirmed that there was no statistically significant prediction of maximum oxygen consumption based on measures of longitudinal dimensionality. While the correlation analysis deduced that part of volume measures and body mass and transversal dimensionality have statistically significant correlation only with female respondents with results of maximal oxygen consumption. Regression analysis showed statistically significant prediction of maximal oxygen consumption based on part of volume measures and body mass and transversal dimensionality. It is determined that female respondents with larger volumes of the thigh and lower leg, accordingly with smaller diameters of knee joint and ankle joint most likely will achieve better results in applied test, and therefore higher maximal oxygen consumption.

Do Maximal Roller Skiing Speed and Double Poling Performance Predict Youth Cross-Country Skiing Performance?

Directory of Open Access Journals (Sweden)

Roland Stöggl, Erich Müller, Thomas Stöggl

2017-09-01

Full Text Available The aims of the current study were to analyze whether specific roller skiing tests and cycle length are determinants of youth cross-country (XC skiing performance, and to evaluate sex specific differences by applying non-invasive diagnostics. Forty-nine young XC skiers (33 boys; 13.8 ± 0.6 yrs and 16 girls; 13.4 ± 0.9 yrs performed roller skiing tests consisting of both shorter (50 m and longer durations (575 m. Test results were correlated with on snow XC skiing performance (PXC based on 3 skating and 3 classical distance competitions (3 to 6 km. The main findings of the current study were: 1 Anthropometrics and maturity status were related to boys’, but not to girls’ PXC; 2 Significant moderate to acceptable correlations between girls’ and boys’ short duration maximal roller skiing speed (double poling, V2 skating, leg skating and PXC were found; 3 Boys’ PXC was best predicted by double poling test performance on flat and uphill, while girls’ performance was mainly predicted by uphill double poling test performance; 4 When controlling for maturity offset, boys’ PXC was still highly associated with the roller skiing tests. The use of simple non-invasive roller skiing tests for determination of PXC represents practicable support for ski clubs, schools or skiing federations in the guidance and evaluation of young talent.

Effect of active warm-up duration on morning short-term maximal ...

African Journals Online (AJOL)

Purpose: To examine the effect of active warm-up duration on short-term maximal performance assessed during Ramadan in the morning. Methods: Twelve healthy active men performed four Wingate tests for measurement of peak power and mean power before and during Ramadan at 09:00 a.m. The tests were performed ...

Modus operandi for maximizing energy efficiency and increasing permeate flux of community scale solar powered reverse osmosis systems

International Nuclear Information System (INIS)

Vyas, Harsh; Suthar, Krunal; Chauhan, Mehul; Jani, Ruchita; Bapat, Pratap; Patel, Pankaj; Markam, Bhupendra; Maiti, Subarna

2015-01-01

Highlights: • Experimental data on energy efficient photovoltaic powered reverse osmosis system. • Synergetic management of electrical, thermal and hydraulic energies. • Use of reflectors, heat exchanger and turgo turbine. - Abstract: Photovoltaic powered reverse osmosis systems can only be made cost effective if they are made highly energy efficient. In this work we describe a protocol to maximize energy efficiency and increase permeate flux in a fully integrated installation of such a system. The improved system consisted of (i) photovoltaic array fitted with suitably positioned and aligned North–South V-trough reflectors to enhance power output from the array; (ii) direct contact heat exchanger fitted on the rear of the photovoltaic modules for active cooling of the same while safeguarding the terminals from short-circuit and corrosion; (iii) use of reverse osmosis feed water as heat exchange medium while taking due care to limit the temperature rise of feed water; (iv) enhancing permeate flux through the rise in feed water temperature; (v) turgo-turbine for conversion of hydraulic energy in reverse osmosis reject water into mechanical energy to provide part of the energy to replace booster pump utilized in the reverse osmosis unit. The V-trough reflectors onto the photovoltaic modules with thermal energy recovery system brought about an increase in power output of 40% and the synergistic effect of (i)–(iv) gave rise to total permeate volume boost of 59%. Integration of (v) resulted in 56% and 26% saving of electrical power when the reverse osmosis plant was operated by battery bank and direct photovoltaic array respectively

Fuzzy-predictive direct power control implementation of a grid connected photovoltaic system, associated with an active power filter

International Nuclear Information System (INIS)

Ouchen, Sabir; Betka, Achour; Abdeddaim, Sabrina; Menadi, Abdelkrim

2016-01-01

Highlights: • An implementation on dSPACE 1104 of a double stage grid connected photovoltaic system, associated with an active power filter. • A fuzzy logic controller for maximum power point tracking of photovoltaic generator using a boost converter. • Predictive direct power control almost eliminates the effect of harmonics under a unite power factor. • The robustness of control strategies was examined in different irradiance level conditions. - Abstract: The present paper proposes a real time implementation of an optimal operation of a double stage grid connected photovoltaic system, associated with a shunt active power filter. On the photovoltaic side, a fuzzy logic based maximum power point taking control is proposed to track permanently the optimum point through an adequate tuning of a boost converter regardless the solar irradiance variations; whereas, on the grid side, a model predictive direct power control is applied, to ensure both supplying a part of the load demand with the extracted photovoltaic power, and a compensation of undesirable harmonic contents of the grid current, under a unity power factor operation. The implementation of the control strategies is conducted on a small scale photovoltaic system, controlled via a dSPACE 1104 single card. The obtained experimental results show on one hand, that the proposed Fuzzy logic based maximum power taking point technique provides fast and high performances under different irradiance levels while compared with a sliding mode control, and ensures 1.57% more in efficiency. On the other hand, the predictive power control ensures a flexible settlement of active power amounts exchanges with the grid, under a unity power functioning. Furthermore, the grid current presents a sinusoidal shape with a tolerable total harmonic distortion coefficient 4.71%.

Magnetic storm effects in electric power systems and prediction needs

Science.gov (United States)

Albertson, V. D.; Kappenman, J. G.

1979-01-01

Geomagnetic field fluctuations produce spurious currents in electric power systems. These currents enter and exit through points remote from each other. The fundamental period of these currents is on the order of several minutes which is quasi-dc compared to the normal 60 Hz or 50 Hz power system frequency. Nearly all of the power systems problems caused by the geomagnetically induced currents result from the half-cycle saturation of power transformers due to simultaneous ac and dc excitation. The effects produced in power systems are presented, current research activity is discussed, and magnetic storm prediction needs of the power industry are listed.

Principles of maximally classical and maximally realistic quantum ...

Indian Academy of Sciences (India)

Principles of maximally classical and maximally realistic quantum mechanics. S M ROY. Tata Institute of Fundamental Research, Homi Bhabha Road, Mumbai 400 005, India. Abstract. Recently Auberson, Mahoux, Roy and Singh have proved a long standing conjecture of Roy and Singh: In 2N-dimensional phase space, ...

Predictive power of the grace score in population with diabetes.

Science.gov (United States)

Baeza-Román, Anna; de Miguel-Balsa, Eva; Latour-Pérez, Jaime; Carrillo-López, Andrés

2017-12-01

Current clinical practice guidelines recommend risk stratification in patients with acute coronary syndrome (ACS) upon admission to hospital. Diabetes mellitus (DM) is widely recognized as an independent predictor of mortality in these patients, although it is not included in the GRACE risk score. The objective of this study is to validate the GRACE risk score in a contemporary population and particularly in the subgroup of patients with diabetes, and to test the effects of including the DM variable in the model. Retrospective cohort study in patients included in the ARIAM-SEMICYUC registry, with a diagnosis of ACS and with available in-hospital mortality data. We tested the predictive power of the GRACE score, calculating the area under the ROC curve. We assessed the calibration of the score and the predictive ability based on type of ACS and the presence of DM. Finally, we evaluated the effect of including the DM variable in the model by calculating the net reclassification improvement. The GRACE score shows good predictive power for hospital mortality in the study population, with a moderate degree of calibration and no significant differences based on ACS type or the presence of DM. Including DM as a variable did not add any predictive value to the GRACE model. The GRACE score has an appropriate predictive power, with good calibration and clinical applicability in the subgroup of diabetic patients. Copyright © 2017 Elsevier Ireland Ltd. All rights reserved.

Crossover and maximal fat-oxidation points in sedentary healthy subjects: methodological issues.

Science.gov (United States)

Gmada, N; Marzouki, H; Haboubi, M; Tabka, Z; Shephard, R J; Bouhlel, E

2012-02-01

Our study aimed to assess the influence of protocol on the crossover point and maximal fat-oxidation (LIPOX(max)) values in sedentary, but otherwise healthy, young men. Maximal oxygen intake was assessed in 23 subjects, using a progressive maximal cycle ergometer test. Twelve sedentary males (aged 20.5±1.0 years) whose directly measured maximal aerobic power (MAP) values were lower than their theoretical maximal values (tMAP) were selected from this group. These individuals performed, in random sequence, three submaximal graded exercise tests, separated by three-day intervals; work rates were based on the tMAP in one test and on MAP in the remaining two. The third test was used to assess the reliability of data. Heart rate, respiratory parameters, blood lactate, the crossover point and LIPOX(max) values were measured during each of these tests. The crossover point and LIPOX(max) values were significantly lower when the testing protocol was based on tMAP rather than on MAP (PtMAP at 30, 40, 50 and 60% of maximal aerobic power (PtMAP rather than MAP (P<0.001). During the first 5 min of recovery, EPOC(5 min) and blood lactate were significantly correlated (r=0.89; P<0.001). Our data show that, to assess the crossover point and LIPOX(max) values for research purposes, the protocol must be based on the measured MAP rather than on a theoretical value. Such a determination should improve individualization of training for initially sedentary subjects. Copyright © 2011 Elsevier Masson SAS. All rights reserved.

Profit maximization mitigates competition

DEFF Research Database (Denmark)

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...

Competitive power development

Energy Technology Data Exchange (ETDEWEB)

Garrity, T.F.; Stoll, H.G. [GE Power Systems Engineering, Schenectady, NY (United States)

1994-12-31

Electric power is essential to economic growth and the improvement in the standard of living in modern societies. Maximizing the overall economic efficiency of electric power production can lead to even stronger economic growth. Overall electricity efficiency can be driven by utilization of the newest and most economically efficient technologies, utilization of the most efficient financial structuring, and efficient integration of coproduction of electricity and process energy. The challenge is to drive the power generation strategy toward maximum economic efficiency while improving the overall country environment emissions. This paper reviews the key power generation technologies available today and in the near future. Of key importance is the capital cost, efficiency, environmental impacts, and reliability of each technology and how these technologies can be integrated with efficient financial structurings to maximize the country power generation economic efficiency. Examples of several countries are used to show recent successes in maximizing economic efficiency.

Communal and Agentic Interpersonal and Intergroup Motives Predict Preferences for Status Versus Power.

Science.gov (United States)

Locke, Kenneth D; Heller, Sonja

2017-01-01

Seven studies involving 1,343 participants showed how circumplex models of social motives can help explain individual differences in preferences for status (having others' admiration) versus power (controlling valuable resources). Studies 1 to 3 and 7 concerned interpersonal motives in workplace contexts, and found that stronger communal motives (to have mutual trust, support, and cooperation) predicted being more attracted to status (but not power) and achieving more workplace status, while stronger agentic motives (to be firm, decisive, and influential) predicted being more attracted to and achieving more workplace power, and experiencing a stronger connection between workplace power and job satisfaction. Studies 4 to 6 found similar effects for intergroup motives: Stronger communal motives predicted wanting one's ingroup (e.g., country) to have status-but not power-relative to other groups. Finally, most people preferred status over power, and this was especially true for women, which was partially explained by women having stronger communal motives.

Implications of maximal Jarlskog invariant and maximal CP violation

International Nuclear Information System (INIS)

Rodriguez-Jauregui, E.; Universidad Nacional Autonoma de Mexico

2001-04-01

We argue here why CP violating phase Φ in the quark mixing matrix is maximal, that is, Φ=90 . In the Standard Model CP violation is related to the Jarlskog invariant J, which can be obtained from non commuting Hermitian mass matrices. In this article we derive the conditions to have Hermitian mass matrices which give maximal Jarlskog invariant J and maximal CP violating phase Φ. We find that all squared moduli of the quark mixing elements have a singular point when the CP violation phase Φ takes the value Φ=90 . This special feature of the Jarlskog invariant J and the quark mixing matrix is a clear and precise indication that CP violating Phase Φ is maximal in order to let nature treat democratically all of the quark mixing matrix moduli. (orig.)

Model predictive control for Z-source power converter

DEFF Research Database (Denmark)

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...

When Power Shapes Interpersonal Behavior: Low Relationship Power Predicts Men’s Aggressive Responses to Low Situational Power

Science.gov (United States)

Overall, Nickola C.; Hammond, Matthew D.; McNulty, James K.; Finkel, Eli J.

2016-01-01

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 (1) only within power-relevant relationship interactions when situational power was low, and (2) 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 responses to their partner. These results demonstrate that fully understanding when and why power is associated with interpersonal behavior requires differentiating between relationship and situational power. PMID:27442766

Quantitative Prediction of Power Loss for Damaged Photovoltaic Modules Using Electroluminescence

Directory of Open Access Journals (Sweden)

Timo Kropp

2018-05-01

Full Text Available Electroluminescence (EL is a powerful tool for the qualitative mapping of the electronic properties of solar modules, where electronic and electrical defects are easily detected. However, a direct quantitative prediction of electrical module performance purely based on electroluminescence images has yet to be accomplished. Our novel approach, called “EL power prediction of modules” (ELMO as presented here, used just two electroluminescence images to predict the electrical loss of mechanically damaged modules when compared to their original (data sheet power. First, using this method, two EL images taken at different excitation currents were converted into locally resolved (relative series resistance images. From the known, total applied voltage to the module, we were then able to calculate absolute series resistance values and the real distribution of voltages and currents. Then, we reconstructed the complete current/voltage curve of the damaged module. We experimentally validated and confirmed the simulation model via the characterization of a commercially available photovoltaic module containing 60 multicrystalline silicon cells, which were mechanically damaged by hail. Deviation between the directly measured and predicted current/voltage curve was less than 4.3% at the maximum power point. For multiple modules of the same type, the level of error dropped below 1% by calibrating the simulation. We approximated the ideality factor from a module with a known current/voltage curve and then expand the application to modules of the same type. In addition to yielding series resistance mapping, our new ELMO method was also capable of yielding parallel resistance mapping. We analyzed the electrical properties of a commercially available module, containing 72 monocrystalline high-efficiency back contact solar cells, which suffered from potential induced degradation. For this module, we predicted electrical performance with an accuracy of better

On the universality of power laws for tokamak plasma predictions

Science.gov (United States)

Garcia, J.; Cambon, D.; Contributors, JET

2018-02-01

Significant deviations from well established power laws for the thermal energy confinement time, obtained from extensive databases analysis as the IPB98(y,2), have been recently reported in dedicated power scans. In order to illuminate the adequacy, validity and universality of power laws as tools for predicting plasma performance, a simplified analysis has been carried out in the framework of a minimal modeling for heat transport which is, however, able to account for the interplay between turbulence and collinear effects with the input power known to play a role in experiments with significant deviations from such power laws. Whereas at low powers, the usual scaling laws are recovered with little influence of other plasma parameters, resulting in a robust power low exponent, at high power it is shown how the exponents obtained are extremely sensitive to the heating deposition, the q-profile or even the sampling or the number of points considered due to highly non-linear behavior of the heat transport. In particular circumstances, even a minimum of the thermal energy confinement time with the input power can be obtained, which means that the approach of the energy confinement time as a power law might be intrinsically invalid. Therefore plasma predictions with a power law approximation with a constant exponent obtained from a regression of a broad range of powers and other plasma parameters which can non-linearly affect and suppress heat transport, can lead to misleading results suggesting that this approach should be taken cautiously and its results continuously compared with modeling which can properly capture the underline physics, as gyrokinetic simulations.

Empirical Information Metrics for Prediction Power and Experiment Planning

Directory of Open Access Journals (Sweden)

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.    

Maximizing hosting capacity of renewable energy sources in distribution networks: A multi-objective and scenario-based approach

International Nuclear Information System (INIS)

Rabiee, Abbas; Mohseni-Bonab, Seyed Masoud

2017-01-01

Due to the development of renewable energy sources (RESs), maximization of hosting capacity (HC) of RESs has gained significant interest in the existing and future power systems. HC maximization should be performed considering various technical constraints like power flow equations, limits on the distribution feeders' voltages and currents, as well as economic constraints such as the cost of energy procurement from the upstream network and power generation by RESs. RESs are volatile and uncertain in nature. Thus, it is necessary to handle their inherent uncertainties in the HC maximization problem. Wind power is now the fastest growing RESs around the world. Hence, in this paper a stochastic multi-objective optimization model is proposed to maximize the distribution network's HC for wind power and minimize the energy procurement costs in a wind integrated power system. The following objective functions are considered: 1) Cost of the purchased energy from upstream network (to be minimized) and 2) Operation and maintenance cost of wind farms. The proposed model is examined on a standard radial 69 bus distribution feeder and a practical 152 bus distribution system. The numerical results substantiate that the proposed model is an effective tool for distribution network operators (DNOs) to consider both technical and economic aspects of distribution network's HC for RESs. - Highlights: • Hosting capacity of wind power is improved in distribution feeders. • A stochastic multi-objective optimization model is proposed. • Wind power and load uncertainties are modeled by scenario based approach. • Purchased energy cost from upstream network and O&M cost of wind farms are used.

A New Look at the Impact of Maximizing on Unhappiness: Two Competing Mediating Effects

OpenAIRE

Peng, Jiaxi; Zhang, Jiaxi; Zhang, Yan; Gong, Pinjia; Han, Bing; Sun, Hao; Cao, Fei; Miao, Danmin

2018-01-01

The current study aims to explore how the decision-making style of maximizing affects subjective well-being (SWB), which mainly focuses on the confirmation of the mediator role of regret and suppressing role of achievement motivation. A total of 402 Chinese undergraduate students participated in this study, in which they responded to the maximization, regret, and achievement motivation scales and SWB measures. Results suggested that maximizing significantly predicted SWB. Moreover, regret and...

A variable capacitance based modeling and power capability predicting method for ultracapacitor

Science.gov (United States)

Liu, Chang; Wang, Yujie; Chen, Zonghai; Ling, Qiang

2018-01-01

Methods of accurate modeling and power capability predicting for ultracapacitors are of great significance in management and application of lithium-ion battery/ultracapacitor hybrid energy storage system. To overcome the simulation error coming from constant capacitance model, an improved ultracapacitor model based on variable capacitance is proposed, where the main capacitance varies with voltage according to a piecewise linear function. A novel state-of-charge calculation approach is developed accordingly. After that, a multi-constraint power capability prediction is developed for ultracapacitor, in which a Kalman-filter-based state observer is designed for tracking ultracapacitor's real-time behavior. Finally, experimental results verify the proposed methods. The accuracy of the proposed model is verified by terminal voltage simulating results under different temperatures, and the effectiveness of the designed observer is proved by various test conditions. Additionally, the power capability prediction results of different time scales and temperatures are compared, to study their effects on ultracapacitor's power capability.

Simulation research on multivariable fuzzy model predictive control of nuclear power plant

International Nuclear Information System (INIS)

Su Jie

2012-01-01

To improve the dynamic control capabilities of the nuclear power plant, the algorithm of the multivariable nonlinear predictive control based on the fuzzy model was applied in the main parameters control of the nuclear power plant, including control structure and the design of controller in the base of expounding the math model of the turbine and the once-through steam generator. The simulation results show that the respond of the change of the gas turbine speed and the steam pressure under the algorithm of multivariable fuzzy model predictive control is faster than that under the PID control algorithm, and the output value of the gas turbine speed and the steam pressure under the PID control algorithm is 3%-5% more than that under the algorithm of multi-variable fuzzy model predictive control. So it shows that the algorithm of multi-variable fuzzy model predictive control can control the output of the main parameters of the nuclear power plant well and get better control effect. (author)

K-Line Patterns’ Predictive Power Analysis Using the Methods of Similarity Match and Clustering

Directory of Open Access Journals (Sweden)

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.

Maximizing the spectral and energy efficiency of ARQ with a fixed outage probability

KAUST Repository

Hadjtaieb, Amir

2015-10-05

This paper studies the spectral and energy efficiency of automatic repeat request (ARQ) in Nakagami-m block-fading channels. The source encodes each packet into L similar sequences and transmits them to the destination in the L subsequent time slots. The destination combines the L sequences using maximal ratio combining and tries to decode the information. In case of decoding failure, the destination feeds back a negative acknowledgment and then the source sends the same L sequences to the destination. This process continues until successful decoding occurs at the destination with no limit on the number of retransmissions. We consider two optimization problems. In the first problem, we maximize the spectral efficiency of the system with respect to the rate for a fixed power. In the second problem, we maximize the energy efficiency with respect to the transmitted power for a fixed rate. © 2015 IEEE.

Predicting Power Output of Upper Body using the OMNI-RES Scale

Directory of Open Access Journals (Sweden)

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.

Error analysis of short term wind power prediction models

International Nuclear Information System (INIS)

De Giorgi, Maria Grazia; Ficarella, Antonio; Tarantino, Marco

2011-01-01

The integration of wind farms in power networks has become an important problem. This is because the electricity produced cannot be preserved because of the high cost of storage and electricity production must follow market demand. Short-long-range wind forecasting over different lengths/periods of time is becoming an important process for the management of wind farms. Time series modelling of wind speeds is based upon the valid assumption that all the causative factors are implicitly accounted for in the sequence of occurrence of the process itself. Hence time series modelling is equivalent to physical modelling. Auto Regressive Moving Average (ARMA) models, which perform a linear mapping between inputs and outputs, and Artificial Neural Networks (ANNs) and Adaptive Neuro-Fuzzy Inference Systems (ANFIS), which perform a non-linear mapping, provide a robust approach to wind power prediction. In this work, these models are developed in order to forecast power production of a wind farm with three wind turbines, using real load data and comparing different time prediction periods. This comparative analysis takes in the first time, various forecasting methods, time horizons and a deep performance analysis focused upon the normalised mean error and the statistical distribution hereof in order to evaluate error distribution within a narrower curve and therefore forecasting methods whereby it is more improbable to make errors in prediction. (author)

Error analysis of short term wind power prediction models

Energy Technology Data Exchange (ETDEWEB)

De Giorgi, Maria Grazia; Ficarella, Antonio; Tarantino, Marco [Dipartimento di Ingegneria dell' Innovazione, Universita del Salento, Via per Monteroni, 73100 Lecce (Italy)

2011-04-15

The integration of wind farms in power networks has become an important problem. This is because the electricity produced cannot be preserved because of the high cost of storage and electricity production must follow market demand. Short-long-range wind forecasting over different lengths/periods of time is becoming an important process for the management of wind farms. Time series modelling of wind speeds is based upon the valid assumption that all the causative factors are implicitly accounted for in the sequence of occurrence of the process itself. Hence time series modelling is equivalent to physical modelling. Auto Regressive Moving Average (ARMA) models, which perform a linear mapping between inputs and outputs, and Artificial Neural Networks (ANNs) and Adaptive Neuro-Fuzzy Inference Systems (ANFIS), which perform a non-linear mapping, provide a robust approach to wind power prediction. In this work, these models are developed in order to forecast power production of a wind farm with three wind turbines, using real load data and comparing different time prediction periods. This comparative analysis takes in the first time, various forecasting methods, time horizons and a deep performance analysis focused upon the normalised mean error and the statistical distribution hereof in order to evaluate error distribution within a narrower curve and therefore forecasting methods whereby it is more improbable to make errors in prediction. (author)

Fatigue during maximal sprint cycling: unique role of cumulative contraction cycles.

Science.gov (United States)

Tomas, Aleksandar; Ross, Emma Z; Martin, James C

2010-07-01

Maximal cycling power has been reported to decrease more rapidly when performed with increased pedaling rates. Increasing pedaling rate imposes two constraints on the neuromuscular system: 1) decreased time for muscle excitation and relaxation and 2) increased muscle shortening velocity. Using two crank lengths allows the effects of time and shortening velocity to be evaluated separately. We conducted this investigation to determine whether the time available for excitation and relaxation or the muscle shortening velocity was mainly responsible for the increased rate of fatigue previously observed with increased pedaling rates and to evaluate the influence of other possible fatiguing constraints. Seven trained cyclists performed 30-s maximal isokinetic cycling trials using two crank lengths: 120 and 220 mm. Pedaling rate was optimized for maximum power for each crank length: 135 rpm for the 120-mm cranks (1.7 m x s(-1) pedal speed) and 109 rpm for the 220-mm cranks (2.5 m x s(-1) pedal speed). Power was recorded with an SRM power meter. Crank length did not affect peak power: 999 +/- 276 W for the 120-mm crank versus 1001 +/- 289 W for the 220-mm crank. Fatigue index was greater (58.6% +/- 3.7% vs 52.4% +/- 4.8%, P < 0.01), and total work was less (20.0 +/- 1.8 vs 21.4 +/- 2.0 kJ, P < 0.01) with the higher pedaling rate-shorter crank condition. Regression analyses indicated that the power for the two conditions was most highly related to cumulative work (r2 = 0.94) and to cumulative cycles (r2 = 0.99). These results support previous findings and confirm that pedaling rate, rather than pedal speed, was the main factor influencing fatigue. Our novel result was that power decreased by a similar increment with each crank revolution for the two conditions, indicating that each maximal muscular contraction induced a similar amount of fatigue.

Model predictive control for power flows in networks with limited capacity

DEFF Research Database (Denmark)

Biegel, Benjamin; Stoustrup, Jakob; Bendtsen, Jan Dimon

2012-01-01

this problem can be formulated as an optimization problem, leading directly to the design of a model predictive controller. Using this scheme, we are able to incorporate predictions of future consumption and exploit knowledge of link limitations such that the intelligent consumers are utilized ahead of time......We consider an interconnected network of consumers powered through an electrical grid of limited capacity. A subset of the consumers are intelligent consumers and have the ability to store energy in a controllable fashion; they can be filled and emptied as desired under power and capacity...... limitations. We address the problem of maintaining power balance between production and consumption using the intelligent consumers to ensure smooth power consumption from the grid. Further, certain capacity limitations to the links interconnecting the consumers must be honored. In this paper, we show how...

Influence of the Sampling Rate and Noise Characteristics on Prediction of the Maximal Safe Laser Exposure in Human Skin Using Pulsed Photothermal Radiometry

Science.gov (United States)

Vidovič, L.; Milanič, M.; Majaron, B.

2013-09-01

Pulsed photothermal radiometry (PPTR) allows for noninvasive determination of the laser-induced temperature depth profile in strongly scattering samples, including human skin. In a recent experimental study, we have demonstrated that such information can be used to derive rather accurate predictions of the maximal safe radiant exposure on an individual patient basis. This has important implications for efficacy and safety of several laser applications in dermatology and aesthetic surgery, which are often compromised by risk of adverse side effects (e.g., scarring, and dyspigmentation) resulting from nonselective absorption of strong laser light in epidermal melanin. In this study, the differences between the individual maximal safe radiant exposure values as predicted from PPTR temperature depth profiling performed using a commercial mid-IR thermal camera (as used to acquire the original patient data) and our customized PPTR setup are analyzed. To this end, the latter has been used to acquire 17 PPTR records from three healthy volunteers, using 1 ms laser irradiation at 532 nm and a signal sampling rate of 20 000 . The laser-induced temperature profiles are reconstructed first from the intact PPTR signals, and then by binning the data to imitate the lower sampling rate of the IR camera (1000 fps). Using either the initial temperature profile in a dedicated numerical model of heat transfer or protein denaturation dynamics, the predicted levels of epidermal thermal damage and the corresponding are compared. A similar analysis is performed also with regard to the differences between noise characteristics of the two PPTR setups.

Planning Routes Across Economic Terrains: Maximizing Utility, Following Heuristics

Science.gov (United States)

Zhang, Hang; Maddula, Soumya V.; Maloney, Laurence T.

2010-01-01

We designed an economic task to investigate human planning of routes in landscapes where travel in different kinds of terrain incurs different costs. Participants moved their finger across a touch screen from a starting point to a destination. The screen was divided into distinct kinds of terrain and travel within each kind of terrain imposed a cost proportional to distance traveled. We varied costs and spatial configurations of terrains and participants received fixed bonuses minus the total cost of the routes they chose. We first compared performance to a model maximizing gain. All but one of 12 participants failed to adopt least-cost routes and their failure to do so reduced their winnings by about 30% (median value). We tested in detail whether participants’ choices of routes satisfied three necessary conditions (heuristics) for a route to maximize gain. We report failures of one heuristic for 7 out of 12 participants. Last of all, we modeled human performance with the assumption that participants assign subjective utilities to costs and maximize utility. For 7 out 12 participants, the fitted utility function was an accelerating power function of actual cost and for the remaining 5, a decelerating power function. We discuss connections between utility aggregation in route planning and decision under risk. Our task could be adapted to investigate human strategy and optimality of route planning in full-scale landscapes. PMID:21833269

PLANNING ROUTES ACROSS ECONOMIC TERRAINS: MAXIMIZING UTILITY, FOLLOWING HEURISTICS

Directory of Open Access Journals (Sweden)

Hang eZhang

2010-12-01

Full Text Available We designed an economic task to investigate human planning of routes in landscapes where travel in different kinds of terrain incurs different costs. Participants moved their finger across a touch screen from a starting point to a destination. The screen was divided into distinct kinds of terrain and travel within each kind of terrain imposed a cost proportional to distance traveled. We varied costs and spatial configurations of terrains and participants received fixed bonuses minus the total cost of the routes they chose. We first compared performance to a model maximizing gain. All but one of 12 participants failed to adopt least-cost routes and their failure to do so reduced their winnings by about 30% (median value. We tested in detail whether participants’ choices of routes satisfied three necessary conditions (heuristics for a route to maximize gain. We report failures of one heuristic for 7 out of 12 participants. Last of all, we modeled human performance with the assumption that participants assign subjective utilities to costs and maximize utility. For 7 out 12 participants, the fitted utility function was an accelerating power function of actual cost and for the remaining 5, a decelerating power function. We discuss connections between utility aggregation in route planning and decision under risk. Our task could be adapted to investigate human strategy and optimality of route planning in full-scale landscapes.

COSMIC EMULATION: FAST PREDICTIONS FOR THE GALAXY POWER SPECTRUM

Energy Technology Data Exchange (ETDEWEB)

Kwan, Juliana; Heitmann, Katrin; Habib, Salman; Frontiere, Nicholas; Pope, Adrian [High Energy Physics Division, Argonne National Laboratory, Lemont, IL 60439 (United States); Padmanabhan, Nikhil [Department of Physics, Yale University, 260 Whitney Ave., New Haven, CT 06520 (United States); Lawrence, Earl [Statistical Sciences, Los Alamos National Laboratory, Los Alamos, NM 87545 (United States); Finkel, Hal [Argonne Leadership Computing Facility, Argonne National Laboratory, Lemont, IL 60439 (United States)

2015-09-01

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–galaxy auto and galaxy–dark matter cross power spectrum and correlation function over a range of freely specifiable HOD modeling parameters. The emulator is constructed using results from 100 HOD models run on a large ΛCDM N-body simulation, with Gaussian Process interpolation applied to a PCA-based representation of the galaxy power spectrum. The total error is currently ∼1% in the auto correlations and ∼2% in the cross correlations from z = 1 to z = 0, over the considered parameter range. We use the emulator to investigate the accuracy of various analytic prescriptions for the galaxy power spectrum, parametric dependencies in the HOD model, and the behavior of galaxy bias as a function of HOD parameters. Additionally, we obtain fully nonlinear predictions for tangential shear correlations induced by galaxy–galaxy lensing from our galaxy–dark matter cross power spectrum emulator. All emulation products are publicly available at http://www.hep.anl.gov/cosmology/CosmicEmu/emu.html.

Analysis of variability and predictability challenges of wind and solar power

NARCIS (Netherlands)

Haan, de J.E.S.; Virag, A.; Kling, W.L.

2013-01-01

In power systems, reserves are essential to ensure system security, certainly when challenges of predictability (inaccurate forecast) and variability (imperfect correlation of renewable generation and system load) are causing power imbalances. Different techniques can be used to size and allocate

Does Spontaneous Favorability to Power (vs. Universalism) Values Predict Spontaneous Prejudice and Discrimination?

Science.gov (United States)

Souchon, Nicolas; Maio, Gregory R; Hanel, Paul H P; Bardin, Brigitte

2017-10-01

We conducted five studies testing whether an implicit measure of favorability toward power over universalism values predicts spontaneous prejudice and discrimination. Studies 1 (N = 192) and 2 (N = 86) examined correlations between spontaneous favorability toward power (vs. universalism) values, achievement (vs. benevolence) values, and a spontaneous measure of prejudice toward ethnic minorities. Study 3 (N = 159) tested whether conditioning participants to associate power values with positive adjectives and universalism values with negative adjectives (or inversely) affects spontaneous prejudice. Study 4 (N = 95) tested whether decision bias toward female handball players could be predicted by spontaneous attitude toward power (vs. universalism) values. Study 5 (N = 123) examined correlations between spontaneous attitude toward power (vs. universalism) values, spontaneous importance toward power (vs. universalism) values, and spontaneous prejudice toward Black African people. Spontaneous positivity toward power (vs. universalism) values was associated with spontaneous negativity toward minorities and predicted gender bias in a decision task, whereas the explicit measures did not. These results indicate that the implicit assessment of evaluative responses attached to human values helps to model value-attitude-behavior relations. © 2016 The Authors. Journal of Personality Published by Wiley Periodicals, Inc.

A new wind power prediction method based on chaotic theory and Bernstein Neural Network

International Nuclear Information System (INIS)

Wang, Cong; Zhang, Hongli; Fan, Wenhui; Fan, Xiaochao

2016-01-01

The accuracy of wind power prediction is important for assessing the security and economy of the system operation when wind power connects to the grids. However, multiple factors cause a long delay and large errors in wind power prediction. Hence, efficient wind power forecasting approaches are still required for practical applications. In this paper, a new wind power forecasting method based on Chaos Theory and Bernstein Neural Network (BNN) is proposed. Firstly, the largest Lyapunov exponent as a judgment for wind power system's chaotic behavior is made. Secondly, Phase Space Reconstruction (PSR) is used to reconstruct the wind power series' phase space. Thirdly, the prediction model is constructed using the Bernstein polynomial and neural network. Finally, the weights and thresholds of the model are optimized by Primal Dual State Transition Algorithm (PDSTA). The practical hourly data of wind power generation in Xinjiang is used to test this forecaster. The proposed forecaster is compared with several current prominent research findings. Analytical results indicate that the forecasting error of PDSTA + BNN is 3.893% for 24 look-ahead hours, and has lower errors obtained compared with the other forecast methods discussed in this paper. The results of all cases studying confirm the validity of the new forecast method. - Highlights: • Lyapunov exponent is used to verify chaotic behavior of wind power series. • Phase Space Reconstruction is used to reconstruct chaotic wind power series. • A new Bernstein Neural Network to predict wind power series is proposed. • Primal dual state transition algorithm is chosen as the training strategy of BNN.

Maximal near-field radiative heat transfer between two plates

Science.gov (United States)

Nefzaoui, Elyes; Ezzahri, Younès; Drévillon, Jérémie; Joulain, Karl

2013-09-01

Near-field radiative transfer is a promising way to significantly and simultaneously enhance both thermo-photovoltaic (TPV) devices power densities and efficiencies. A parametric study of Drude and Lorentz models performances in maximizing near-field radiative heat transfer between two semi-infinite planes separated by nanometric distances at room temperature is presented in this paper. Optimal parameters of these models that provide optical properties maximizing the radiative heat flux are reported and compared to real materials usually considered in similar studies, silicon carbide and heavily doped silicon in this case. Results are obtained by exact and approximate (in the extreme near-field regime and the electrostatic limit hypothesis) calculations. The two methods are compared in terms of accuracy and CPU resources consumption. Their differences are explained according to a mesoscopic description of nearfield radiative heat transfer. Finally, the frequently assumed hypothesis which states a maximal radiative heat transfer when the two semi-infinite planes are of identical materials is numerically confirmed. Its subsequent practical constraints are then discussed. Presented results enlighten relevant paths to follow in order to choose or design materials maximizing nano-TPV devices performances.

Predicting the emissive power of hydrocarbon pool fires

International Nuclear Information System (INIS)

Munoz, Miguel; Planas, Eulalia; Ferrero, Fabio; Casal, Joaquim

2007-01-01

The emissive power (E) of a flame depends on the size of the fire and the type of fuel. In fact, it changes significantly over the flame surface: the zones of luminous flame have high emittance, while those covered by smoke have low E values. The emissive power of each zone (that is, the luminous or clear flame and the non-luminous or smoky flame) and the portion of total flame area they occupy must be assessed when a two-zone model is used. In this study, data obtained from an experimental set-up were used to estimate the emissive power of fires and its behaviour as a function of pool size. The experiments were performed using gasoline and diesel oil as fuel. Five concentric circular pools (1.5, 3, 4, 5 and 6 m in diameter) were used. Appropriate instruments were employed to determine the main features of the fires. By superimposing IR and VHS images it was possible to accurately identify the luminous and non-luminous zones of the fire. Mathematical expressions were obtained that give a more accurate prediction of E lum , E soot and the average emissive power of a fire as a function of its luminous and smoky zones. These expressions can be used in a two-zone model to obtain a better prediction of the thermal radiation. The value of the radiative fraction was determined from the thermal flux measured with radiometers. An expression is also proposed for estimating the radiative fraction

Managing the innovation supply chain to maximize personalized medicine.

Science.gov (United States)

Waldman, S A; Terzic, A

2014-02-01

Personalized medicine epitomizes an evolving model of care tailored to the individual patient. This emerging paradigm harnesses radical technological advances to define each patient's molecular characteristics and decipher his or her unique pathophysiological processes. Translated into individualized algorithms, personalized medicine aims to predict, prevent, and cure disease without producing therapeutic adverse events. Although the transformative power of personalized medicine is generally recognized by physicians, patients, and payers, the complexity of translating discoveries into new modalities that transform health care is less appreciated. We often consider the flow of innovation and technology along a continuum of discovery, development, regulation, and application bridging the bench with the bedside. However, this process also can be viewed through a complementary prism, as a necessary supply chain of services and providers, each making essential contributions to the development of the final product to maximize value to consumers. Considering personalized medicine in this context of supply chain management highlights essential points of vulnerability and/or scalability that can ultimately constrain translation of the biological revolution or potentiate it into individualized diagnostics and therapeutics for optimized value creation and delivery.

A novel implementation of kNN classifier based on multi-tupled meteorological input data for wind power prediction

International Nuclear Information System (INIS)

Yesilbudak, Mehmet; Sagiroglu, Seref; Colak, Ilhami

2017-01-01

Highlights: • An accurate wind power prediction model is proposed for very short-term horizon. • The k-nearest neighbor classifier is implemented based on the multi-tupled inputs. • The variation of wind power prediction errors is evaluated in various aspects. • Our approach shows the superior prediction performance over the persistence method. - Abstract: With the growing share of wind power production in the electric power grids, many critical challenges to the grid operators have been emerged in terms of the power balance, power quality, voltage support, frequency stability, load scheduling, unit commitment and spinning reserve calculations. To overcome such problems, numerous studies have been conducted to predict the wind power production, but a small number of them have attempted to improve the prediction accuracy by employing the multidimensional meteorological input data. The novelties of this study lie in the proposal of an efficient and easy to implement very short-term wind power prediction model based on the k-nearest neighbor classifier (kNN), in the usage of wind speed, wind direction, barometric pressure and air temperature parameters as the multi-tupled meteorological inputs and in the comparison of wind power prediction results with respect to the persistence reference model. As a result of the achieved patterns, we characterize the variation of wind power prediction errors according to the input tuples, distance measures and neighbor numbers, and uncover the most influential and the most ineffective meteorological parameters on the optimization of wind power prediction results.

Predicting Power Output of Upper Body using the OMNI-RES Scale.

Science.gov (United States)

Bautista, Iker J; Chirosa, Ignacio J; Tamayo, Ignacio Martín; González, Andrés; Robinson, Joseph E; Chirosa, Luis J; Robertson, Robert J

2014-12-09

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.

Development of a Low Inductance Linear Alternator for Stirling Power Convertors

Science.gov (United States)

Geng, Steven M.; Schifer, Nicholas A.

2017-01-01

The free-piston Stirling power convertor is a promising technology for high efficiency heat-to-electricity power conversion in space. Stirling power convertors typically utilize linear alternators for converting mechanical motion into electricity. The linear alternator is one of the heaviest components of modern Stirling power convertors. In addition, state-of-art Stirling linear alternators usually require the use of tuning capacitors or active power factor correction controllers to maximize convertor output power. The linear alternator to be discussed in this paper, eliminates the need for tuning capacitors and delivers electrical power output in which current is inherently in phase with voltage. No power factor correction is needed. In addition, the linear alternator concept requires very little iron, so core loss has been virtually eliminated. This concept is a unique moving coil design where the magnetic flux path is defined by the magnets themselves. This paper presents computational predictions for two different low inductance alternator configurations, and compares the predictions with experimental data for one of the configurations that has been built and is currently being tested.

Development of a Low-Inductance Linear Alternator for Stirling Power Convertors

Science.gov (United States)

Geng, Steven M.; Schifer, Nicholas A.

2017-01-01

The free-piston Stirling power convertor is a promising technology for high-efficiency heat-to-electricity power conversion in space. Stirling power convertors typically utilize linear alternators for converting mechanical motion into electricity. The linear alternator is one of the heaviest components of modern Stirling power convertors. In addition, state-of-the-art Stirling linear alternators usually require the use of tuning capacitors or active power factor correction controllers to maximize convertor output power. The linear alternator to be discussed in this paper eliminates the need for tuning capacitors and delivers electrical power output in which current is inherently in phase with voltage. No power factor correction is needed. In addition, the linear alternator concept requires very little iron, so core loss has been virtually eliminated. This concept is a unique moving coil design where the magnetic flux path is defined by the magnets themselves. This paper presents computational predictions for two different low inductance alternator configurations. Additionally, one of the configurations was built and tested at GRC, and the experimental data is compared with the predictions.

A hybrid PSO-ANFIS approach for short-term wind power prediction in Portugal

International Nuclear Information System (INIS)

Pousinho, H.M.I.; Mendes, V.M.F.; Catalao, J.P.S.

2011-01-01

The increased integration of wind power into the electric grid, as nowadays occurs in Portugal, poses new challenges due to its intermittency and volatility. Wind power prediction plays a key role in tackling these challenges. The contribution of this paper is to propose a new hybrid approach, combining particle swarm optimization and adaptive-network-based fuzzy inference system, for short-term wind power prediction in Portugal. Significant improvements regarding forecasting accuracy are attainable using the proposed approach, in comparison with the results obtained with five other approaches.

A new ensemble model for short term wind power prediction

DEFF Research Database (Denmark)

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...

Hard-type nonlocality proof for two maximally entangled particles

International Nuclear Information System (INIS)

Kalamidas, D.

2005-01-01

Full text: We present, for the first time, a Hardy-type proof of nonlocality for two maximally entangled particles in a four-dimensional total Hilbert space. Furthermore, the violation of local realistic predictions occurs for 25 % of trials, exceeding the 9 % maximum obtained by Hardy for nonmaximally entangled states. (author)

Optimization of maintenance for power system equipment using a predictive health model

NARCIS (Netherlands)

Bajracharya, G.; Koltunowicz, T.; Negenborn, R.R.; Papp, Z.; Djairam, D.; Schutter, B.D. de; 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

Relationship between traditional and ballistic squat exercise with vertical jumping and maximal sprinting.

Science.gov (United States)

Requena, Bernardo; García, Inmaculada; Requena, Francisco; de Villarreal, Eduardo Sáez-Sáez; Cronin, John B

2011-08-01

The purpose of this study was to quantify the magnitude of the relationship between vertical jumping and maximal sprinting at different distances with performance in the traditional and ballistic concentric squat exercise in well-trained sprinters. Twenty-one men performed 2 types of barbell squats (ballistic and traditional) across different loads with the aim of determining the maximal peak and average power outputs and 1 repetition maximum (1RM) values. Moreover, vertical jumping (countermovement jump test [CMJ]) and maximal sprints over 10, 20, 30, 40, 60, and 80 m were also assessed. In respect to 1RM in traditional squat, (a) no significant correlation was found with CMJ performance; (b) positive strong relationships (p ballistic and traditional squat exercises (r = 0.53-0.90); (c) negative significant correlations (r = -0.49 to -0.59, p ballistic or traditional squat exercises. Sprint time at 20 m was only related to ballistic and traditional squat performance when power values were expressed in relative terms. Moderate significant correlations (r = -0.39 to -0.56, p ballistic and traditional squat exercises. Sprint times at 60 and 80 m were mainly related to ballistic squat power outputs. Although correlations can only give insights into associations and not into cause and effect, from this investigation, it can be seen that traditional squat strength has little in common with CMJ performance and that relative 1RM and power outputs for both squat exercises are statistically correlated to most sprint distances underlying the importance of strength and power to sprinting.

A novel method for predicting the power outputs of wave energy converters

Science.gov (United States)

Wang, Yingguang

2018-03-01

This paper focuses on realistically predicting the power outputs of wave energy converters operating in shallow water nonlinear waves. A heaving two-body point absorber is utilized as a specific calculation example, and the generated power of the point absorber has been predicted by using a novel method (a nonlinear simulation method) that incorporates a second order random wave model into a nonlinear dynamic filter. It is demonstrated that the second order random wave model in this article can be utilized to generate irregular waves with realistic crest-trough asymmetries, and consequently, more accurate generated power can be predicted by subsequently solving the nonlinear dynamic filter equation with the nonlinearly simulated second order waves as inputs. The research findings demonstrate that the novel nonlinear simulation method in this article can be utilized as a robust tool for ocean engineers in their design, analysis and optimization of wave energy converters.

Forced vital capacity and not central chemoreflex predicts maximal hyperoxic breath-hold duration in elite apneists.

Science.gov (United States)

Bain, Anthony R; Barak, Otto F; Hoiland, Ryan L; Drvis, Ivan; Bailey, Damian M; Dujic, Zeljko; Mijacika, Tanja; Santoro, Antoinette; DeMasi, Daniel K; MacLeod, David B; Ainslie, Philip N

2017-08-01

The determining mechanisms of a maximal hyperoxic apnea duration in elite apneists have remained unexplored. We tested the hypothesis that maximal hyperoxic apnea duration in elite apneists is related to forced vital capacity (FVC) but not the central chemoreflex (for CO 2 ). Eleven elite apneists performed a maximal dry static-apnea with prior hyperoxic (100% oxygen) pre-breathing, and a central chemoreflex test via a hyperoxic re-breathing technique (hyperoxic-hypercapnic ventilatory response: HCVR); expressed as the increase in ventilation (pneumotachometry) per increase in arterial CO 2 tension (PaCO 2 ; radial artery). FVC was assessed using standard spirometry. Maximal apnea duration ranged from 807 to 1262s (mean=1034s). Average HCVR was 2.0±1.2Lmin -1 mmHg -1 PaCO 2 . The hyperoxic apnea duration was related to the FVC (r 2 =0.45, p0.05). These findings were interpreted to suggest that during a hyperoxic apnea, a larger initial lung volume prolongs the time before reaching intolerable discomfort associated with pending lung squeeze, while CO 2 sensitivity has little impact. Copyright © 2017 Elsevier B.V. All rights reserved.

ESB-Based Sensor Web Integration for the Prediction of Electric Power Supply System Vulnerability

Directory of Open Access Journals (Sweden)

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.

Science.gov (United States)

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.

ESB-Based Sensor Web Integration for the Prediction of Electric Power Supply System Vulnerability

Science.gov (United States)

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

Predictive Smart Grid Control with Exact Aggregated Power Constraints

DEFF Research Database (Denmark)

Trangbæk, K; Petersen, Mette Højgaard; Bendtsen, Jan Dimon

2012-01-01

of autonomous consumers. The control system is tasked with balancing electric power production and consumption within the smart grid, and makes active use of the flexibility of a large number of power producing and/or power consuming units. The load variations on the grid arise on one hand from varying......This chapter deals with hierarchical model predictive control (MPC) of smart grid systems. The design consists of a high-level MPC controller, a second level of so-called aggregators,which reduces the computational and communication related load on the high-level control, and a lower level...... 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...

A hybrid PSO-ANFIS approach for short-term wind power prediction in Portugal

Energy Technology Data Exchange (ETDEWEB)

Pousinho, H.M.I. [Department of Electromechanical Engineering, University of Beira Interior, R. Fonte do Lameiro, 6201-001 Covilha (Portugal); Mendes, V.M.F. [Department of Electrical Engineering and Automation, Instituto Superior de Engenharia de Lisboa, R. Conselheiro Emidio Navarro, 1950-062 Lisbon (Portugal); Catalao, J.P.S. [Department of Electromechanical Engineering, University of Beira Interior, R. Fonte do Lameiro, 6201-001 Covilha (Portugal); Center for Innovation in Electrical and Energy Engineering, Instituto Superior Tecnico, Technical University of Lisbon, Av. Rovisco Pais, 1049-001 Lisbon (Portugal)

2011-01-15

The increased integration of wind power into the electric grid, as nowadays occurs in Portugal, poses new challenges due to its intermittency and volatility. Wind power prediction plays a key role in tackling these challenges. The contribution of this paper is to propose a new hybrid approach, combining particle swarm optimization and adaptive-network-based fuzzy inference system, for short-term wind power prediction in Portugal. Significant improvements regarding forecasting accuracy are attainable using the proposed approach, in comparison with the results obtained with five other approaches. (author)

Maximizers versus satisficers

OpenAIRE

Andrew M. Parker; 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...

Model Predictive Control of Integrated Gasification Combined Cycle Power Plants

Energy Technology Data Exchange (ETDEWEB)

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.

Wind Turbine Generator Efficiency Based on Powertrain Combination and Annual Power Generation Prediction

Directory of Open Access Journals (Sweden)

Dongmyung Kim

2018-05-01

Full Text Available Wind turbine generators are eco-friendly generators that produce electric energy using wind energy. In this study, wind turbine generator efficiency is examined using a powertrain combination and annual power generation prediction, by employing an analysis model. Performance testing was conducted in order to analyze the efficiency of a hydraulic pump and a motor, which are key components, and so as to verify the analysis model. The annual wind speed occurrence frequency for the expected installation areas was used to predict the annual power generation of the wind turbine generators. It was found that the parallel combination of the induction motors exhibited a higher efficiency when the wind speed was low and the serial combination showed higher efficiency when wind speed was high. The results of predicting the annual power generation considering the regional characteristics showed that the power generation was the highest when the hydraulic motors were designed in parallel and the induction motors were designed in series.

Blood lactate clearance after maximal exercise depends on active recovery intensity.

Science.gov (United States)

Devlin, J; Paton, B; Poole, L; Sun, W; Ferguson, C; Wilson, J; Kemi, O J

2014-06-01

High-intensity exercise is time-limited by onset of fatigue, marked by accumulation of blood lactate. This is accentuated at maximal, all-out exercise that rapidly accumulates high blood lactate. The optimal active recovery intensity for clearing lactate after such maximal, all-out exercise remains unknown. Thus, we studied the intensity-dependence of lactate clearance during active recovery after maximal exercise. We constructed a standardized maximal, all-out treadmill exercise protocol that predictably lead to voluntary exhaustion and blood lactate concentration>10 mM. Next, subjects ran series of all-out bouts that increased blood lactate concentration to 11.5±0.2 mM, followed by recovery exercises ranging 0% (passive)-100% of the lactate threshold. Repeated measurements showed faster lactate clearance during active versus passive recovery (P40%>passive recovery, Pexercise clears accumulated blood lactate faster than passive recovery in an intensity-dependent manner, with maximum clearance occurring at active recovery of 80% of lactate threshold.

Prediction on corrosion rate of pipe in nuclear power system based on optimized grey theory

International Nuclear Information System (INIS)

Chen Yonghong; Zhang Dafa; Chen Dengke; Jiang Wei

2007-01-01

For the prediction of corrosion rate of pipe in nuclear power system, the pre- diction error from the grey theory is greater, so a new method, optimized grey theory was presented in the paper. A comparison among predicted results from present and other methods was carried out, and it is seem that optimized grey theory is correct and effective for the prediction of corrosion rate of pipe in nuclear power system, and it provides a fundamental basis for the maintenance of pipe in nuclear power system. (authors)

Power system dynamic state estimation using prediction based evolutionary technique

International Nuclear Information System (INIS)

Basetti, Vedik; Chandel, Ashwani K.; Chandel, Rajeevan

2016-01-01

In this paper, a new robust LWS (least winsorized square) estimator is proposed for dynamic state estimation of a power system. One of the main advantages of this estimator is that it has an inbuilt bad data rejection property and is less sensitive to bad data measurements. In the proposed approach, Brown's double exponential smoothing technique has been utilised for its reliable performance at the prediction step. The state estimation problem is solved as an optimisation problem using a new jDE-self adaptive differential evolution with prediction based population re-initialisation technique at the filtering step. This new stochastic search technique has been embedded with different state scenarios using the predicted state. The effectiveness of the proposed LWS technique is validated under different conditions, namely normal operation, bad data, sudden load change, and loss of transmission line conditions on three different IEEE test bus systems. The performance of the proposed approach is compared with the conventional extended Kalman filter. On the basis of various performance indices, the results thus obtained show that the proposed technique increases the accuracy and robustness of power system dynamic state estimation performance. - Highlights: • To estimate the states of the power system under dynamic environment. • The performance of the EKF method is degraded during anomaly conditions. • The proposed method remains robust towards anomalies. • The proposed method provides precise state estimates even in the presence of anomalies. • The results show that prediction accuracy is enhanced by using the proposed model.

Introducing Model Predictive Control for Improving Power Plant Portfolio Performance

DEFF Research Database (Denmark)

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...

Synapse:neural network for predict power consumption: users guide

Energy Technology Data Exchange (ETDEWEB)

Muller, C; Mangeas, M; Perrot, N

1994-08-01

SYNAPSE is forecasting tool designed to predict power consumption in metropolitan France on the half hour time scale. Some characteristics distinguish this forecasting model from those which already exist. In particular, it is composed of numerous neural networks. The idea for using many neural networks arises from past tests. These tests showed us that a single neural network is not able to solve the problem correctly. From this result, we decided to perform unsupervised classification of the 24 consumption curves. From this classification, six classes appeared, linked with the weekdays: Mondays, Tuesdays, Wednesdays, Thursdays, Fridays, Saturdays, Sundays, holidays and bridge days. For each class and for each half hour, two multilayer perceptrons are built. The two of them forecast the power for one particular half hour, and for a day including one of the determined class. The input of these two network are different: the first one (short time forecasting) includes the powers for the most recent half hour and relative power of the previous day; the second (medium time forecasting) includes only the relative power of the previous day. A process connects the results of every networks and allows one to forecast more than one half-hour in advance. In this process, short time forecasting networks and medium time forecasting networks are used differently. The first kind of neural networks gives good results on the scale of one day. The second one gives good forecasts for the next predicted powers. In this note, the organization of the SYNAPSE program is detailed, and the user`s menu is described. This first version of synapse works and should allow the APC group to evaluate its utility. (authors). 6 refs., 2 appends.

Moduli dynamics as a predictive tool for thermal maximally supersymmetric Yang-Mills at large N

Energy Technology Data Exchange (ETDEWEB)

Morita, Takeshi [Department of Physics, Shizuoka University,836 Ohya, Suruga-ku, Shizuoka 422-8529 (Japan); Department of Physics and Astronomy, University of Kentucky,Lexington, KY 40506 (United States); Shiba, Shotaro [Maskawa Institute for Science and Culture, Kyoto Sangyo University,Kamigamo-Motoyama, Kita-ku, Kyoto 603-8555 (Japan); Wiseman, Toby [Theoretical Physics Group, Blackett Laboratory, Imperial College,Exhibition Road, London SW7 2AZ (United Kingdom); Withers, Benjamin [Mathematical Sciences and STAG Research Centre, University of Southampton,Highfield, Southampton SO17 1BJ (United Kingdom)

2015-07-09

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.

Moduli dynamics as a predictive tool for thermal maximally supersymmetric Yang-Mills at large N

International Nuclear Information System (INIS)

Morita, Takeshi; Shiba, Shotaro; Wiseman, Toby; Withers, Benjamin

2015-01-01

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 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.

Throughput Maximization for Cognitive Radio Networks Using Active Cooperation and Superposition Coding

KAUST Repository

Hamza, Doha R.

2015-02-13

We propose a three-message superposition coding scheme in a cognitive radio relay network exploiting active cooperation between primary and secondary users. The primary user is motivated to cooperate by substantial benefits it can reap from this access scenario. Specifically, the time resource is split into three transmission phases: The first two phases are dedicated to primary communication, while the third phase is for the secondary’s transmission. We formulate two throughput maximization problems for the secondary network subject to primary user rate constraints and per-node power constraints with respect to the time durations of primary transmission and the transmit power of the primary and the secondary users. The first throughput maximization problem assumes a partial power constraint such that the secondary power dedicated to primary cooperation, i.e. for the first two communication phases, is fixed apriori. In the second throughput maximization problem, a total power constraint is assumed over the three phases of communication. The two problems are difficult to solve analytically when the relaying channel gains are strictly greater than each other and strictly greater than the direct link channel gain. However, mathematically tractable lowerbound and upperbound solutions can be attained for the two problems. For both problems, by only using the lowerbound solution, we demonstrate significant throughput gains for both the primary and the secondary users through this active cooperation scheme. We find that most of the throughput gains come from minimizing the second phase transmission time since the secondary nodes assist the primary communication during this phase. Finally, we demonstrate the superiority of our proposed scheme compared to a number of reference schemes that include best relay selection, dual-hop routing, and an interference channel model.

Throughput Maximization for Cognitive Radio Networks Using Active Cooperation and Superposition Coding

KAUST Repository

Hamza, Doha R.; Park, Kihong; Alouini, Mohamed-Slim; Aissa, Sonia

2015-01-01

We propose a three-message superposition coding scheme in a cognitive radio relay network exploiting active cooperation between primary and secondary users. The primary user is motivated to cooperate by substantial benefits it can reap from this access scenario. Specifically, the time resource is split into three transmission phases: The first two phases are dedicated to primary communication, while the third phase is for the secondary’s transmission. We formulate two throughput maximization problems for the secondary network subject to primary user rate constraints and per-node power constraints with respect to the time durations of primary transmission and the transmit power of the primary and the secondary users. The first throughput maximization problem assumes a partial power constraint such that the secondary power dedicated to primary cooperation, i.e. for the first two communication phases, is fixed apriori. In the second throughput maximization problem, a total power constraint is assumed over the three phases of communication. The two problems are difficult to solve analytically when the relaying channel gains are strictly greater than each other and strictly greater than the direct link channel gain. However, mathematically tractable lowerbound and upperbound solutions can be attained for the two problems. For both problems, by only using the lowerbound solution, we demonstrate significant throughput gains for both the primary and the secondary users through this active cooperation scheme. We find that most of the throughput gains come from minimizing the second phase transmission time since the secondary nodes assist the primary communication during this phase. Finally, we demonstrate the superiority of our proposed scheme compared to a number of reference schemes that include best relay selection, dual-hop routing, and an interference channel model.

Design and implementation of predictive filtering system for current reference generation of active power filter

Energy Technology Data Exchange (ETDEWEB)

Kilic, Tomislav; Milun, Stanko; Petrovic, Goran [FESB University of Split, Faculty of Electrical Engineering, Machine Engineering and Naval Architecture, R. Boskovica bb, 21000, Split (Croatia)

2007-02-15

The shunt active power filters are used to attenuate the harmonic currents in power systems by injecting equal but opposite compensating currents. Successful control of the active filters requires an accurate current reference. In this paper the current reference determination based on predictive filtering structure is presented. Current reference was obtained by taking the difference of load current and its fundamental harmonic. For fundamental harmonic determination with no time delay a combination of digital predictive filter and low pass filter is used. The proposed method was implemented on a laboratory prototype of a three-phase active power filter. The algorithm for current reference determination was adapted and implemented on DSP controller. Simulation and experimental results show that the active power filter with implemented predictive filtering structure gives satisfactory performance in power system harmonic attenuation. (author)

Joint Throughput Maximization and Fair Uplink Transmission Scheduling in CDMA Systems

Directory of Open Access Journals (Sweden)

Symeon Papavassiliou

2009-01-01

Full Text Available We study the fundamental problem of optimal transmission scheduling in a code-division multiple-access wireless system in order to maximize the uplink system throughput, while satisfying the users quality-of-service (QoS requirements and maintaining fairness among them. The corresponding problem is expressed as a weighted throughput maximization problem, under certain power and QoS constraints, where the weights are the control parameters reflecting the fairness constraints. With the introduction of the power index capacity, it is shown that this optimization problem can be converted into a binary knapsack problem, where all the corresponding constraints are replaced by the power index capacities at some certain system power index. A two-step approach is followed to obtain the optimal solution. First, a simple method is proposed to find the optimal set of users to receive service for a given fixed target system load, and then the optimal solution is obtained as a global search within a certain range. Furthermore, a stochastic approximation method is presented to effectively identify the required control parameters. The performance evaluation reveals the advantages of our proposed policy over other existing ones and confirms that it achieves very high throughput while maintains fairness among the users, under different channel conditions and requirements.

Swarm Intelligence-Based Hybrid Models for Short-Term Power Load Prediction

Directory of Open Access Journals (Sweden)

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.

Automatic Power Control for Daily Load-following Operation using Model Predictive Control Method

Energy Technology Data Exchange (ETDEWEB)

Yu, Keuk Jong; Kim, Han Gon [KH, Daejeon (Korea, Republic of)

2009-10-15

Under the circumstances that nuclear power occupies more than 50%, nuclear power plants are required to be operated on load-following operation in order to make the effective management of electric grid system and enhanced responsiveness to rapid changes in power demand. Conventional reactors such as the OPR1000 and APR1400 have a regulating system that controls the average temperature of the reactor core relation to the reference temperature. This conventional method has the advantages of proven technology and ease of implementation. However, this method is unsuitable for controlling the axial power shape, particularly the load following operation. Accordingly, this paper reports on the development of a model predictive control method which is able to control the reactor power and the axial shape index. The purpose of this study is to analyze the behavior of nuclear reactor power and the axial power shape by using a model predictive control method when the power is increased and decreased for a daily load following operation. The study confirms that deviations in the axial shape index (ASI) are within the operating limit.

Maximizing carbon storage in the Appalachians: A method for considering the risk of disturbance events

Science.gov (United States)

Michael R. Vanderberg; Kevin Boston; John. Bailey

2011-01-01

Accounting for the probability of loss due to disturbance events can influence the prediction of carbon flux over a planning horizon, and can affect the determination of optimal silvicultural regimes to maximize terrestrial carbon storage. A preliminary model that includes forest disturbance-related carbon loss was developed to maximize expected values of carbon stocks...

Optimizing operation costs of the heating system of a household using model predictive control considering a local PV installation

DEFF Research Database (Denmark)

Koch-Ciobotaru, Cosmin; Isleifsson, Fridrik Rafn; Gehrke, Oliver

2012-01-01

This paper presents a model predictive controller developed in order to minimize the cost of grid energy consumption and maximize the amount of energy consumed from a local photovoltaic (PV) installation. The usage of as much locally produced renewable energy sources (RES) as possible, diminishes...... the effects of their large penetration in the distribution grid and reduces overloading the grid capacity, which is an increasing problem for the power system. The controller uses 24 hour prediction data for the ambient temperature, the solar irradiance, and for the PV output power. Simulation results...

Optimized Power Dispatch in Wind Farms for Power Maximizing Considering Fatigue Loads

DEFF Research Database (Denmark)

Zhang, Baohua; N. Soltani, Mohsen; Hu, Weihao

2018-01-01

Wake effects in a wind farm (WF) include the wind velocity deficit and added turbulence. The wind velocity deficit may bring significant loss of the wind power and the added turbulence may cause extra fatigue load on the wind turbines (WTs). Inclusion of the wake effects in the wind farm control...... at a series of turbulence intensity, mean wind speed and active power reference to form a lookup table, which is used for the WF control. The proposed strategy is compared with WT MPPT control strategy and WF MPPT control strategy. The simulation results show the effectiveness of the proposed strategy....

A Fuzzy-Logic Power Management Strategy Based on Markov Random Prediction for Hybrid Energy Storage Systems

Directory of Open Access Journals (Sweden)

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.

Forecasting Electricity Spot Prices Accounting for Wind Power Predictions

DEFF Research Database (Denmark)

Jónsson, Tryggvi; Pinson, Pierre; Nielsen, Henrik Aalborg

2013-01-01

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...

Wind Power Ramp Events Prediction with Hybrid Machine Learning Regression Techniques and Reanalysis Data

Directory of Open Access Journals (Sweden)

Laura Cornejo-Bueno

2017-11-01

Full Text Available Wind Power Ramp Events (WPREs are large fluctuations of wind power in a short time interval, which lead to strong, undesirable variations in the electric power produced by a wind farm. Its accurate prediction is important in the effort of efficiently integrating wind energy in the electric system, without affecting considerably its stability, robustness and resilience. In this paper, we tackle the problem of predicting WPREs by applying Machine Learning (ML regression techniques. Our approach consists of using variables from atmospheric reanalysis data as predictive inputs for the learning machine, which opens the possibility of hybridizing numerical-physical weather models with ML techniques for WPREs prediction in real systems. Specifically, we have explored the feasibility of a number of state-of-the-art ML regression techniques, such as support vector regression, artificial neural networks (multi-layer perceptrons and extreme learning machines and Gaussian processes to solve the problem. Furthermore, the ERA-Interim reanalysis from the European Center for Medium-Range Weather Forecasts is the one used in this paper because of its accuracy and high resolution (in both spatial and temporal domains. Aiming at validating the feasibility of our predicting approach, we have carried out an extensive experimental work using real data from three wind farms in Spain, discussing the performance of the different ML regression tested in this wind power ramp event prediction problem.

Maximal planar networks with large clustering coefficient and power-law degree distribution

International Nuclear Information System (INIS)

Zhou Tao; Yan Gang; Wang Binghong

2005-01-01

In this article, we propose a simple rule that generates scale-free networks with very large clustering coefficient and very small average distance. These networks are called random Apollonian networks (RANs) as they can be considered as a variation of Apollonian networks. We obtain the analytic results of power-law exponent γ=3 and clustering coefficient C=(46/3)-36 ln (3/2)≅0.74, which agree with the simulation results very well. We prove that the increasing tendency of average distance of RANs is a little slower than the logarithm of the number of nodes in RANs. Since most real-life networks are both scale-free and small-world networks, RANs may perform well in mimicking the reality. The RANs possess hierarchical structure as C(k)∼k -1 that are in accord with the observations of many real-life networks. In addition, we prove that RANs are maximal planar networks, which are of particular practicability for layout of printed circuits and so on. The percolation and epidemic spreading process are also studied and the comparisons between RANs and Barabasi-Albert (BA) as well as Newman-Watts (NW) networks are shown. We find that, when the network order N (the total number of nodes) is relatively small (as N∼10 4 ), the performance of RANs under intentional attack is not sensitive to N, while that of BA networks is much affected by N. And the diseases spread slower in RANs than BA networks in the early stage of the suseptible-infected process, indicating that the large clustering coefficient may slow the spreading velocity, especially in the outbreaks

Electrical predictive maintenance at Trillo I Nuclear Power Plant

International Nuclear Information System (INIS)

Vicente, L. R.; Fernandez de la Mata, R.; Cano Gonzalez, J. C.

1998-01-01

An electrical predictive maintenance plan is currently being put into effect at Trillo I Nuclear Power Plant which is initially being applied to three types of equipment: motors, transformers and motor-driven valves. This paper describes the different phases considered in the implementation of the Predictive Maintenance Plan: study of existing techniques for such equipment (tangoδ, spectral analysis of stator current, chromatographic analysis of gases, spectral analysis of the axial stray magnetic flux, etc), study of the special characteristics of the electrical equipment at Trillo NPP, analysis of applicable techniques (characteristic parameters, alert-alarm values, experience with such techniques, etc), analysis of machine history records, study of the optimum preventive-predictive case, study of applicable frequencies and definition of the computerised predictive maintenance management tool. With the exception of the computerised predictive maintenance management applications which are presently being implemented, all the activities described above have been carried out on the three types of equipment mentioned. (Author)

Integrated Solid Oxide Fuel Cell Power System Characteristics Prediction

Directory of Open Access Journals (Sweden)

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.

Entropy maximization

Indian Academy of Sciences (India)

Abstract. 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 f that satisfy. ∫ fhi dμ = λi for i = 1, 2,...,...k the maximizer of entropy is an f0 that is pro- portional to exp(. ∑ ci hi ) for some choice of ci . An extension of this to a continuum of.

Evaluation of a Trapezoidal Predictive Controller for a Four-Wire Active Power Filter for Utility Equipment of Metro Railway, Power-Land Substations

Directory of Open Access Journals (Sweden)

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.

Transmit coil design for Wireless Power Transfer for medical implants.

Science.gov (United States)

Lemdiasov, Rosti; Venkatasubramanian, Arun

2017-07-01

A new design approach for the design of transmit coils for Wireless Power Transfer (WPT) is presented. The theoretical formulation involves a figure of merit that has to be maximized to solve for the surface current. Numerical predictions and comparisons with practical measurements for the coil parameters (inductance. resistance) underscore the success of this approach in terms of achieving strong coupling with a receive coil while maintaining low resistance.

Method for Prediction of the Power Output from Photovoltaic Power Plant under Actual Operating Conditions

Science.gov (United States)

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.

Dynamic Modeling and Very Short-term Prediction of Wind Power Output Using Box-Cox Transformation

Science.gov (United States)

Urata, Kengo; Inoue, Masaki; Murayama, Dai; Adachi, Shuichi

2016-09-01

We propose a statistical modeling method of wind power output for very short-term prediction. The modeling method with a nonlinear model has cascade structure composed of two parts. One is a linear dynamic part that is driven by a Gaussian white noise and described by an autoregressive model. The other is a nonlinear static part that is driven by the output of the linear part. This nonlinear part is designed for output distribution matching: we shape the distribution of the model output to match with that of the wind power output. The constructed model is utilized for one-step ahead prediction of the wind power output. Furthermore, we study the relation between the prediction accuracy and the prediction horizon.

A model to predict the power output from wind farms

Energy Technology Data Exchange (ETDEWEB)

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.

Automatic optimization of core loading patterns to maximize cycle energy production within operational constraints

International Nuclear Information System (INIS)

Hobson, G.H.; Turinsky, P.J.

1986-01-01

Computational capability has been developed to automatically determine the core loading pattern which minimizes fuel cycle costs for a pressurized water reactor. Equating fuel cycle cost minimization with core reactivity maximization, the objective is to determine the loading pattern which maximizes core reactivity at end-of-cycle while satisfying the power peaking constraint throughout the cycle and region average discharge burnup limit. The method utilizes a two-dimensional, coarse mesh, finite difference scheme to evaluate core reactivity and fluxes for an initial reference loading pattern as a function of cycle burnup. First order perturbation theory is applied to determine the effects of assembly shuffling on reactivity, power distribution, and end-of-cycle burnup

Prediction of reflood behavior for tests with differing axial power shapes using WCOBRA/TRAC

International Nuclear Information System (INIS)

Bajorek, S.M.; Hochreiter, L.E.

1991-01-01

The rector core power shape can vary over the fuel cycle due to load follow, control rod movement, burnup effects and Xenon transients. a best estimate thermal-hydraulic code must be able to accurately predict the reflooding behavior for different axial power shapes in order to find the power shapes effects on the loss-of-coolant peak cladding temperature. Several different reflood heat transfer experiments have been performed at the same or similar PWR reflood conditions with different axial power shapes. These experiments have different rod diameters, were full length, 3.65 m (12 feet) in height, and had simple egg crate grids. The WCOBRA/TRAC code has been used to model several different tests from these three experiments to examine the code's capability to predict the reflood transient for different power shapes, with a consistent model and noding scheme. This paper describes these different experiments, their power shapes, and the test conditions. The WCOBRA/TRAC code is described as well as the noding scheme, and the calculated results will be compared in detail with the test data rod temperatures. An overall assessment of the code's predictions of these experiments is presented

Entropy Maximization

Indian Academy of Sciences (India)

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 ∫ f h i d = i for i = 1 , 2 , … , … k the maximizer of entropy is an f 0 that is proportional to exp ⁡ ( ∑ c i h i ) for some choice of c i . An extension of this to a continuum of ...

Survival associated pathway identification with group Lp penalized global AUC maximization

Directory of Open Access Journals (Sweden)

Liu Zhenqiu

2010-08-01

Full Text Available Abstract It has been demonstrated that genes in a cell do not act independently. They interact with one another to complete certain biological processes or to implement certain molecular functions. How to incorporate biological pathways or functional groups into the model and identify survival associated gene pathways is still a challenging problem. In this paper, we propose a novel iterative gradient based method for survival analysis with group Lp penalized global AUC summary maximization. Unlike LASSO, Lp (p 1. We first extend Lp for individual gene identification to group Lp penalty for pathway selection, and then develop a novel iterative gradient algorithm for penalized global AUC summary maximization (IGGAUCS. This method incorporates the genetic pathways into global AUC summary maximization and identifies survival associated pathways instead of individual genes. The tuning parameters are determined using 10-fold cross validation with training data only. The prediction performance is evaluated using test data. We apply the proposed method to survival outcome analysis with gene expression profile and identify multiple pathways simultaneously. Experimental results with simulation and gene expression data demonstrate that the proposed procedures can be used for identifying important biological pathways that are related to survival phenotype and for building a parsimonious model for predicting the survival times.

Robust Distributed Model Predictive Load Frequency Control of Interconnected Power System

Directory of Open Access Journals (Sweden)

Xiangjie Liu

2013-01-01

Full Text Available Considering the load frequency control (LFC of large-scale power system, a robust distributed model predictive control (RDMPC is presented. The system uncertainty according to power system parameter variation alone with the generation rate constraints (GRC is included in the synthesis procedure. The entire power system is composed of several control areas, and the problem is formulated as convex optimization problem with linear matrix inequalities (LMI that can be solved efficiently. It minimizes an upper bound on a robust performance objective for each subsystem. Simulation results show good dynamic response and robustness in the presence of power system dynamic uncertainties.

Evidence for maximal acceleration and singularity resolution in covariant loop quantum gravity.

Science.gov (United States)

Rovelli, Carlo; Vidotto, Francesca

2013-08-30

A simple argument indicates that covariant loop gravity (spin foam theory) predicts a maximal acceleration and hence forbids the development of curvature singularities. This supports the results obtained for cosmology and black holes using canonical methods.

Adaptive on-line prediction of the available power of lithium-ion batteries

Science.gov (United States)

Waag, Wladislaw; Fleischer, Christian; Sauer, Dirk Uwe

2013-11-01

In this paper a new approach for prediction of the available power of a lithium-ion battery pack is presented. It is based on a nonlinear battery model that includes current dependency of the battery resistance. It results in an accurate power prediction not only at room temperature, but also at lower temperatures at which the current dependency is substantial. The used model parameters are fully adaptable on-line to the given state of the battery (state of charge, state of health, temperature). This on-line adaption in combination with an explicit consideration of differences between characteristics of individual cells in a battery pack ensures an accurate power prediction under all possible conditions. The proposed trade-off between the number of used cell parameters and the total accuracy as well as the optimized algorithm results in a real-time capability of the method, which is demonstrated on a low-cost 16 bit microcontroller. The verification tests performed on a software-in-the-loop test bench system with four 40 Ah lithium-ion cells show promising results.

PREDICTION OF POWER GENERATION OF SMALL SCALE VERTICAL AXIS WIND TURBINE USING FUZZY LOGIC

Directory of Open Access Journals (Sweden)

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.

PREDICTION OF POWER GENERATION OF SMALL SCALE VERTICAL AXIS WIND TURBINE USING FUZZY LOGIC

Directory of Open Access Journals (Sweden)

Altab Md. Hossain

2009-12-01

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.

Power-Controlled MAC Protocols with Dynamic Neighbor Prediction for Ad hoc Networks

Institute of Scientific and Technical Information of China (English)

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.

Maximally incompatible quantum observables

Energy Technology Data Exchange (ETDEWEB)

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.

Maximally incompatible quantum observables

International Nuclear Information System (INIS)

Heinosaari, Teiko; Schultz, Jussi; Toigo, Alessandro; Ziman, Mario

2014-01-01

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.

Power Management Strategy by Enhancing the Mission Profile Configuration of Solar-Powered Aircraft

Directory of Open Access Journals (Sweden)

Parvathy Rajendran

2016-01-01

Full Text Available Solar energy offers solar-powered unmanned aerial vehicle (UAV the possibility of unlimited endurance. Some researchers have developed techniques to achieve perpetual flight by maximizing the power from the sun and by flying in accordance with its azimuth angles. However, flying in a path that follows the sun consumes more energy to sustain level flight. This study optimizes the overall power ratio by adopting the mission profile configuration of optimal solar energy exploitation. Extensive simulation is conducted to optimize and restructure the mission profile phases of UAV and to determine the optimal phase definition of the start, ascent, and descent periods, thereby maximizing the energy from the sun. In addition, a vertical cylindrical flight trajectory instead of maximizing the solar inclination angle has been adopted. This approach improves the net power ratio by 30.84% compared with other techniques. As a result, the battery weight may be massively reduced by 75.23%. In conclusion, the proposed mission profile configuration with the optimal power ratio of the trajectory of the path planning effectively prolongs UAV operation.

Optimized Extreme Learning Machine for Power System Transient Stability Prediction Using Synchrophasors

Directory of Open Access Journals (Sweden)

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.

Application of clustering analysis in the prediction of photovoltaic power generation based on neural network

Science.gov (United States)

Cheng, K.; Guo, L. M.; Wang, Y. K.; Zafar, M. T.

2017-11-01

In order to select effective samples in the large number of data of PV power generation years and improve the accuracy of PV power generation forecasting model, this paper studies the application of clustering analysis in this field and establishes forecasting model based on neural network. Based on three different types of weather on sunny, cloudy and rainy days, this research screens samples of historical data by the clustering analysis method. After screening, it establishes BP neural network prediction models using screened data as training data. Then, compare the six types of photovoltaic power generation prediction models before and after the data screening. Results show that the prediction model combining with clustering analysis and BP neural networks is an effective method to improve the precision of photovoltaic power generation.

Maximal Repetitions in Written Texts: Finite Energy Hypothesis vs. Strong Hilberg Conjecture

Directory of Open Access Journals (Sweden)

Łukasz Dębowski

2015-08-01

Full Text Available The article discusses two mutually-incompatible hypotheses about the stochastic mechanism of the generation of texts in natural language, which could be related to entropy. The first hypothesis, the finite energy hypothesis, assumes that texts are generated by a process with exponentially-decaying probabilities. This hypothesis implies a logarithmic upper bound for maximal repetition, as a function of the text length. The second hypothesis, the strong Hilberg conjecture, assumes that the topological entropy grows as a power law. This hypothesis leads to a hyperlogarithmic lower bound for maximal repetition. By a study of 35 written texts in German, English and French, it is found that the hyperlogarithmic growth of maximal repetition holds for natural language. In this way, the finite energy hypothesis is rejected, and the strong Hilberg conjecture is partly corroborated.

On the impact of NWP model resolution and power source disaggregation on photovoltaic power prediction

Czech Academy of Sciences Publication Activity Database

Eben, Kryštof; Juruš, Pavel; Resler, Jaroslav; Pelikán, Emil; Krč, Pavel

2011-01-01

Roč. 8, - (2011), EMS2011-667-4 [EMS Annual Meeting /11./ and European Conference on Applications of Meteorology /10./. 12.09.2011-16.09.2011, Berlin] Institutional research plan: CEZ:AV0Z10300504 Keywords : photovoltaic power prediction * NWP * numerical model parameterization Subject RIV: DG - Athmosphere Sciences, Meteorology

The prediction and prevention of voltage collapse in the Finnish power system

Energy Technology Data Exchange (ETDEWEB)

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.

Prediction of Chiller Power Consumption: An Entropy Generation Approach

KAUST Repository

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.

The maximization of the efficiency in the energy conversion in isolated photovoltaic systems; Tecnicas de maxima transferencia de potencia em sistemas fotovoltaicos isolados

Energy Technology Data Exchange (ETDEWEB)

Machado-Neto, L. V. B.; Cabral, C. V. T.; Diniz, A. S. A. C.; Cortizo, P. C.; Oliveira-Filho, D.

2004-07-01

The maximization of the efficiency in the energy conversion is essential into the developing of technical and economic sustainability of photovoltaic solar energy systems. In this paper is realized the study of a power maximization technique for photovoltaic generators. The power maximization technique explored in this paper is the Maximum Power Point Tracking (MPPT). There are different strategies being studied currently; this work consists of the development of an electronic converter prototype for MPPT, including the developing of the tracking algorithm implemented in a microcontroller. It is also realized a simulation of the system and a prototype was assembled and the first results are presented here. (Author)

Considering linear generator copper losses on model predictive control for a point absorber wave energy converter

International Nuclear Information System (INIS)

Montoya Andrade, Dan-El; Villa Jaén, Antonio de la; García Santana, Agustín

2014-01-01

Highlights: • We considered the linear generator copper losses in the proposed MPC strategy. • We maximized the power transferred to the generator side power converter. • The proposed MPC increases the useful average power injected into the grid. • The stress level of the PTO system can be reduced by the proposed MPC. - Abstract: The amount of energy that a wave energy converter can extract depends strongly on the control strategy applied to the power take-off system. It is well known that, ideally, the reactive control allows for maximum energy extraction from waves. However, the reactive control is intrinsically noncausal in practice and requires some kind of causal approach to be applied. Moreover, this strategy does not consider physical constraints and this could be a problem because the system could achieve unacceptable dynamic values. These, and other control techniques have focused on the wave energy extraction problem in order to maximize the energy absorbed by the power take-off device without considering the possible losses in intermediate devices. In this sense, a reactive control that considers the linear generator copper losses has been recently proposed to increase the useful power injected into the grid. Among the control techniques that have emerged recently, the model predictive control represents a promising strategy. This approach performs an optimization process on a time prediction horizon incorporating dynamic constraints associated with the physical features of the power take-off system. This paper proposes a model predictive control technique that considers the copper losses in the control optimization process of point absorbers with direct drive linear generators. This proposal makes the most of reactive control as it considers the copper losses, and it makes the most of the model predictive control, as it considers the system constraints. This means that the useful power transferred from the linear generator to the power

Power Prediction and Technoeconomic Analysis of a Solar PV Power Plant by MLP-ABC and COMFAR III, considering Cloudy Weather Conditions

Directory of Open Access Journals (Sweden)

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.

Maximal combustion temperature estimation

International Nuclear Information System (INIS)

Golodova, E; Shchepakina, E

2006-01-01

This work is concerned with the phenomenon of delayed loss of stability and the estimation of the maximal temperature of safe combustion. Using the qualitative theory of singular perturbations and canard techniques we determine the maximal temperature on the trajectories located in the transition region between the slow combustion regime and the explosive one. This approach is used to estimate the maximal temperature of safe combustion in multi-phase combustion models

Offset-Free Direct Power Control of DFIG Under Continuous-Time Model Predictive Control

DEFF Research Database (Denmark)

Errouissi, Rachid; Al-Durra, Ahmed; Muyeen, S.M.

2017-01-01

This paper presents a robust continuous-time model predictive direct power control for doubly fed induction generator (DFIG). The proposed approach uses Taylor series expansion to predict the stator current in the synchronous reference frame over a finite time horizon. The predicted stator current...... is directly used to compute the required rotor voltage in order to minimize the difference between the actual stator currents and their references over the predictive time. However, as the proposed strategy is sensitive to parameter variations and external disturbances, a disturbance observer is embedded...... into the control loop to remove the steady-state error of the stator current. It turns out that the steady-state and the transient performances can be identified by simple design parameters. In this paper, the reference of the stator current is directly calculated from the desired stator active and reactive powers...

Steady-State Plant Model to Predict Hydroden Levels in Power Plant Components

Energy Technology Data Exchange (ETDEWEB)

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.

A new scheme for maximizing the lifetime of heterogeneous wireless sensor networks

OpenAIRE

Aldaihani, Reem; AboElFotoh, Hosam

2016-01-01

Heterogeneous wireless sensor network consists of wireless sensor nodes with different abilities, such as different computing power and different initial energy. We present in this paper a new scheme for maximizing heterogeneous WSN lifetime. The proposed scheme employs two types of sensor nodes that are named (consistent with IEEE 802.15.4 standard) Full Function Device (FFD) and Reduced Function Device (RFD). The FFDs are the expensive sensor nodes with high power and computational capabili...

Recent advances in prediction of emission of hazardous air pollutants from coal-fired power plants

International Nuclear Information System (INIS)

Senior, C.L.; Helble, J.J.; Sarofim, A.F.

2000-01-01

Coal-fired power plants are a primary source of mercury discharge into the atmosphere along with fine particulates containing arsenic, selenium, cadmium, and other hazardous air pollutants. Information regarding the speciation of these toxic metals is necessary to accurately predict their atmospheric transport and fate in the environment. New predictive tools have been developed to allow utilities to better estimate the emissions of toxic metals from coal-fired power plants. These prediction equations are based on fundamental physics and chemistry and can be applied to a wide variety of fuel types and combustion conditions. The models have significantly improved the ability to predict the emissions of air toxic metals in fine particulate and gas-phase mercury. In this study, the models were successfully tested using measured mercury speciation and mass balance information collected from coal-fired power plants

Research on prediction of agricultural machinery total power based on grey model optimized by genetic algorithm

Science.gov (United States)

Xie, Yan; Li, Mu; Zhou, Jin; Zheng, Chang-zheng

2009-07-01

Agricultural machinery total power is an important index to reflex and evaluate the level of agricultural mechanization. It is the power source of agricultural production, and is the main factors to enhance the comprehensive agricultural production capacity expand production scale and increase the income of the farmers. Its demand is affected by natural, economic, technological and social and other "grey" factors. Therefore, grey system theory can be used to analyze the development of agricultural machinery total power. A method based on genetic algorithm optimizing grey modeling process is introduced in this paper. This method makes full use of the advantages of the grey prediction model and characteristics of genetic algorithm to find global optimization. So the prediction model is more accurate. According to data from a province, the GM (1, 1) model for predicting agricultural machinery total power was given based on the grey system theories and genetic algorithm. The result indicates that the model can be used as agricultural machinery total power an effective tool for prediction.

Speeding Up Maximal Causality Reduction with Static Dependency Analysis

OpenAIRE

Huang, Shiyou; Huang, Jeff

2017-01-01

Stateless Model Checking (SMC) offers a powerful approach to verifying multithreaded programs but suffers from the state-space explosion problem caused by the huge thread interleaving space. The pioneering reduction technique Partial Order Reduction (POR) mitigates this problem by pruning equivalent interleavings from the state space. However, limited by the happens-before relation, POR still explores redundant executions. The recent advance, Maximal Causality Reduction (MCR), shows a promisi...

Basic study on dynamic reactive-power control method with PV output prediction for solar inverter

Directory of Open Access Journals (Sweden)

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.

Linear maps preserving maximal deviation and the Jordan structure of quantum systems

International Nuclear Information System (INIS)

Hamhalter, Jan

2012-01-01

In the algebraic approach to quantum theory, a quantum observable is given by an element of a Jordan algebra and a state of the system is modelled by a normalized positive functional on the underlying algebra. Maximal deviation of a quantum observable is the largest statistical deviation one can obtain in a particular state of the system. The main result of the paper shows that each linear bijective transformation between JBW algebras preserving maximal deviations is formed by a Jordan isomorphism or a minus Jordan isomorphism perturbed by a linear functional multiple of an identity. It shows that only one numerical statistical characteristic has the power to determine the Jordan algebraic structure completely. As a consequence, we obtain that only very special maps can preserve the diameter of the spectra of elements. Nonlinear maps preserving the pseudometric given by maximal deviation are also described. The results generalize hitherto known theorems on preservers of maximal deviation in the case of self-adjoint parts of von Neumann algebras proved by Molnár.

Energy-Efficient Power Allocation for MIMO-SVD Systems

KAUST Repository

Sboui, Lokman; Rezki, Zouheir; Alouini, Mohamed-Slim

2017-01-01

In this paper, we address the problem of energyefficient power allocation in MIMO systems. In fact, the widely adopted water-filling power allocation does not ensure the maximization of the energy efficiency (EE). Since the EE maximization is a non

Prediction of Full-Scale Propulsion Power using Artificial Neural Networks

DEFF Research Database (Denmark)

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...

Multivariate power-law models for streamflow prediction in the Mekong Basin

Directory of Open Access Journals (Sweden)

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.

AUC-Maximizing Ensembles through Metalearning.

Science.gov (United States)

LeDell, Erin; van der Laan, Mark J; Petersen, Maya

2016-05-01

Area Under the ROC Curve (AUC) is often used to measure the performance of an estimator in binary classification problems. An AUC-maximizing classifier can have significant advantages in cases where ranking correctness is valued or if the outcome is rare. In a Super Learner ensemble, maximization of the AUC can be achieved by the use of an AUC-maximining metalearning algorithm. We discuss an implementation of an AUC-maximization technique that is formulated as a nonlinear optimization problem. We also evaluate the effectiveness of a large number of different nonlinear optimization algorithms to maximize the cross-validated AUC of the ensemble fit. The results provide evidence that AUC-maximizing metalearners can, and often do, out-perform non-AUC-maximizing metalearning methods, with respect to ensemble AUC. The results also demonstrate that as the level of imbalance in the training data increases, the Super Learner ensemble outperforms the top base algorithm by a larger degree.

Numerical Calculation of Overhead Power Lines Dynamics

Directory of Open Access Journals (Sweden)

Gogola Roman

2016-11-01

Full Text Available This paper contains results of transient analysis of airflow around the ACSR power line cross-section in unsymmetric multi-span. The forces applied to the power line are obtained from CFD simulations, where the wind induced vibration is studied. Effect of these forces to the maximal displacement of the power line and the maximal mechanical forces in the points of attachment are studied and evaluated.

Applications of expectation maximization algorithm for coherent optical communication

DEFF Research Database (Denmark)

Carvalho, L.; Oliveira, J.; Zibar, Darko

2014-01-01

In this invited paper, we present powerful statistical signal processing methods, used by machine learning community, and link them to current problems in optical communication. In particular, we will look into iterative maximum likelihood parameter estimation based on expectation maximization...... algorithm and its application in coherent optical communication systems for linear and nonlinear impairment mitigation. Furthermore, the estimated parameters are used to build the probabilistic model of the system for the synthetic impairment generation....

Effect of active warm-up duration on morning short-term maximal performance during Ramadan.

Science.gov (United States)

Baklouti, Hana; Chtourou, Hamdi; Aloui, Asma; Chaouachi, Anis; Souissi, Nizar

2015-01-01

To examine the effect of active warm-up duration on short-term maximal performance assessed during Ramadan in the morning. Twelve healthy active men performed four Wingate tests for measurement of peak power and mean power before and during Ramadan at 09:00 a.m. The tests were performed on separate days, after either a 5-min or a 15-min warm-up. The warm-up consisted in pedaling at 50% of the power output obtained at the last stage of a submaximal multistage cycling test. Oral temperature was measured at rest and after warming-up. Furthermore, ratings of perceived exertion were obtained immediately after the Wingate test. Oral temperature was higher after the 15-min warm-up than the 5-min warm-up throughout the study. Moreover, peak power and mean power were higher after the 15-min warm-up than the 5-min warm-up before Ramadan. However, during Ramadan, there was no significant difference between the two warm-up durations. In addition, ratings of perceived exertion were higher after the 15-min warm-up than the 5-min warm-up only during Ramadan. There is no need to prolong the warm-up period before short-term maximal exercise performed during Ramadan in the morning.

Application of Model Predictive Control for Active Load Management in a Distributed Power System with High Wind Penetration

DEFF Research Database (Denmark)

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...

Wind Power Grid Connected Capacity Prediction Using LSSVM Optimized by the Bat Algorithm

Directory of Open Access Journals (Sweden)

Qunli Wu

2015-12-01

Full Text Available Given the stochastic nature of wind, wind power grid-connected capacity prediction plays an essential role in coping with the challenge of balancing supply and demand. Accurate forecasting methods make enormous contribution to mapping wind power strategy, power dispatching and sustainable development of wind power industry. This study proposes a bat algorithm (BA–least squares support vector machine (LSSVM hybrid model to improve prediction performance. In order to select input of LSSVM effectively, Stationarity, Cointegration and Granger causality tests are conducted to examine the influence of installed capacity with different lags, and partial autocorrelation analysis is employed to investigate the inner relationship of grid-connected capacity. The parameters in LSSVM are optimized by BA to validate the learning ability and generalization of LSSVM. Multiple model sufficiency evaluation methods are utilized. The research results reveal that the accuracy improvement of the present approach can reach about 20% compared to other single or hybrid models.

Joint analysis of psychiatric disorders increases accuracy of risk prediction for schizophrenia, bipolar disorder, and major depressive disorder

DEFF Research Database (Denmark)

Maier, Robert; Moser, Gerhard; Chen, Guo-Bo

2015-01-01

Genetic risk prediction has several potential applications in medical research and clinical practice and could be used, for example, to stratify a heterogeneous population of patients by their predicted genetic risk. However, for polygenic traits, such as psychiatric disorders, the accuracy of risk...... number of GWAS datasets of correlated traits, it is a flexible and powerful tool to maximize prediction accuracy. With current sample size, risk predictors are not useful in a clinical setting but already are a valuable research tool, for example in experimental designs comparing cases with high and low...

Model Predictive Voltage Control of Wind Power Plants

DEFF Research Database (Denmark)

Zhao, Haoran; Wu, Qiuwei

2018-01-01

the efficacy of the proposed WFVC, two case scenarios were designed: the wind farm is under normal operating conditions and the internal wind power fluctuation is considered; and besides internal power fluctuation, the impact of the external grid on the wind farm is considered.......This chapter proposes an autonomous wind farm voltage controller (WFVC) based on model predictive control (MPC). It also introduces the analytical expressions for the voltage sensitivity to tap positions of a transformer. The chapter then describes the discrete models for the wind turbine...... generators (WTGs) and static var compensators (SVCs)/static var generators (SVGs). Next, it describes the implementation of the on‐load tap changing (OLTC) in the MPC. Furthermore, the chapter examines the cost function as well as the constraints of the MPC‐based WFVC for both control modes. In order to test...

Maximal loads acting on legs of powered roof support unit in longwalls with bumping hazards

Institute of Scientific and Technical Information of China (English)

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

Is CP violation maximal

International Nuclear Information System (INIS)

Gronau, M.

1984-01-01

Two ambiguities are noted in the definition of the concept of maximal CP violation. The phase convention ambiguity is overcome by introducing a CP violating phase in the quark mixing matrix U which is invariant under rephasing transformations. The second ambiguity, related to the parametrization of U, is resolved by finding a single empirically viable definition of maximal CP violation when assuming that U does not single out one generation. Considerable improvement in the calculation of nonleptonic weak amplitudes is required to test the conjecture of maximal CP violation. 21 references

Shareholder, stakeholder-owner or broad stakeholder maximization

OpenAIRE

Mygind, Niels

2004-01-01

With reference to the discussion about shareholder versus stakeholder maximization it is argued that the normal type of maximization is in fact stakeholder-owner maxi-mization. This means maximization of the sum of the value of the shares and stake-holder benefits belonging to the dominating stakeholder-owner. Maximization of shareholder value is a special case of owner-maximization, and only under quite re-strictive assumptions shareholder maximization is larger or equal to stakeholder-owner...

Maximizing the Social Welfare of Virtual Power Players Operation in Case of Excessive Wind Power

DEFF Research Database (Denmark)

Faria, Pedro; Vale, Zita; Morais, Hugo

2013-01-01

based generation (including wind power) has caused several changes in the operation and planning of power systems and of electricity markets. Sometimes the available non-dispatchable generation is higher than the demand. This generation must be used; otherwise it is wasted if not stored or used...... 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...... in this paper using a real 937-bus distribution network with 20.310 consumers and 548 distributed generators, some of them non-dispatchable and with must take contracts. The implemented scenario corresponds to a real day in Portuguese power system....

Maximum Power from a Solar Panel

Directory of Open Access Journals (Sweden)

Michael Miller

2010-01-01

Full Text Available Solar energy has become a promising alternative to conventional fossil fuel sources. Solar panels are used to collect solar radiation and convert it into electricity. One of the techniques used to maximize the effectiveness of this energy alternative is to maximize the power output of the solar collector. In this project the maximum power is calculated by determining the voltage and the current of maximum power. These quantities are determined by finding the maximum value for the equation for power using differentiation. After the maximum values are found for each time of day, each individual quantity, voltage of maximum power, current of maximum power, and maximum power is plotted as a function of the time of day.

Attracted to power: challenge/threat and promotion/prevention focus differentially predict the attractiveness of group power

Science.gov (United States)

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. PMID:25904887

Profit maximization with customer satisfaction control for electric vehicle charging in smart grids

Directory of Open Access Journals (Sweden)

Edwin Collado

2017-05-01

Full Text Available As the market of electric vehicles is gaining popularity, large-scale commercialized or privately-operated charging stations are expected to play a key role as a technology enabler. In this paper, we study the problem of charging electric vehicles at stations with limited charging machines and power resources. The purpose of this study is to develop a novel profit maximization framework for station operation in both offline and online charging scenarios, under certain customer satisfaction constraints. The main goal is to maximize the profit obtained by the station owner and provide a satisfactory charging service to the customers. The framework includes not only the vehicle scheduling and charging power control, but also the managing of user satisfaction factors, which are defined as the percentages of finished charging targets. The profit maximization problem is proved to be NPcomplete in both scenarios (NP refers to “nondeterministic polynomial time”, for which two-stage charging strategies are proposed to obtain efficient suboptimal solutions. Competitive analysis is also provided to analyze the performance of the proposed online two-stage charging algorithm against the offline counterpart under non-congested and congested charging scenarios. Finally, the simulation results show that the proposed two-stage charging strategies achieve performance close to that with exhaustive search. Also, the proposed algorithms provide remarkable performance gains compared to the other conventional charging strategies with respect to not only the unified profit, but also other practical interests, such as the computational time, the user satisfaction factor, the power consumption, and the competitive ratio.

Nonlinear Fuzzy Model Predictive Control for a PWR Nuclear Power Plant

Directory of Open Access Journals (Sweden)

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.

Task-oriented maximally entangled states

International Nuclear Information System (INIS)

Agrawal, Pankaj; Pradhan, B

2010-01-01

We introduce the notion of a task-oriented maximally entangled state (TMES). This notion depends on the task for which a quantum state is used as the resource. TMESs are the states that can be used to carry out the task maximally. This concept may be more useful than that of a general maximally entangled state in the case of a multipartite system. We illustrate this idea by giving an operational definition of maximally entangled states on the basis of communication tasks of teleportation and superdense coding. We also give examples and a procedure to obtain such TMESs for n-qubit systems.

Solar photovoltaic system design optimization by shading analysis to maximize energy generation from limited urban area

International Nuclear Information System (INIS)

Rachchh, Ravi; Kumar, Manoj; Tripathi, Brijesh

2016-01-01

Highlights: • Scheme to maximize total number of solar panels in a given area. • Enhanced energy output from a fixed area without compromising the efficiency. • Capacity and generated energy are enhanced by more than 25%. - Abstract: In the urban areas the demand of solar power is increasing due to better awareness about the emission of green house gases from conventional thermal power plants and significant decrease in the installation cost of residential solar power plants. But the land cost and the under utilization of available space is hindering its further growth. Under these circumstances, solar photovoltaic system installation needs to accommodate the maximum number of solar panels in either roof-top or land-mounted category. In this article a new approach is suggested to maximize the total number of solar panels in a given area with enhanced energy output without compromising the overall efficiency of the system. The number of solar panels can be maximized in a solar photovoltaic energy generation system by optimizing installation parameters such as tilt angle, pitch, gain factor, altitude angle and shading to improve the energy yield. In this paper mathematical analysis is done to show that the capacity and generated energy can be enhanced by more than 25% for a given land area by optimization various parameters.

Hierarchical model-based predictive control of a power plant portfolio

DEFF Research Database (Denmark)

Edlund, Kristian; Bendtsen, Jan Dimon; Jørgensen, John Bagterp

2011-01-01

One of the main difficulties in large-scale implementation of renewable energy in existing power systems is that the production from renewable sources is difficult to predict and control. For this reason, fast and efficient control of controllable power producing units – so-called “portfolio...... 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...... optimisation problem, which is solved using Dantzig–Wolfe decomposition. This decomposition yields improved computational efficiency and better scalability compared to centralised methods.The proposed control scheme is compared to an existing, state-of-the-art portfolio control system (operated by DONG Energy...

Deconstructing the power resistance relationship for squats: A joint-level analysis.

Science.gov (United States)

Farris, D J; Lichtwark, G A; Brown, N A T; Cresswell, A G

2016-07-01

Generating high leg power outputs is important for executing rapid movements. Squats are commonly used to increase leg strength and power. Therefore, it is useful to understand factors affecting power output in squatting. We aimed to deconstruct the mechanisms behind why power is maximized at certain resistances in squatting. Ten male rowers (age = 20 ± 2.2 years; height = 1.82 ± 0.03 m; mass = 86 ± 11 kg) performed maximal power squats with resistances ranging from body weight to 80% of their one repetition maximum (1RM). Three-dimensional kinematics was combined with ground reaction force (GRF) data in an inverse dynamics analysis to calculate leg joint moments and powers. System center of mass (COM) velocity and power were computed from GRF data. COM power was maximized across a range of resistances from 40% to 60% 1RM. This range was identified because a trade-off in hip and knee joint powers existed across this range, with maximal knee joint power occurring at 40% 1RM and maximal hip joint power at 60% 1RM. A non-linear system force-velocity relationship was observed that dictated large reductions in COM power below 20% 1RM and above 60% 1RM. These reductions were due to constraints on the control of the movement. © 2015 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

Power flow prediction in vibrating systems via model reduction

Science.gov (United States)

Li, Xianhui

This dissertation focuses on power flow prediction in vibrating systems. Reduced order models (ROMs) are built based on rational Krylov model reduction which preserve power flow information in the original systems over a specified frequency band. Stiffness and mass matrices of the ROMs are obtained by projecting the original system matrices onto the subspaces spanned by forced responses. A matrix-free algorithm is designed to construct ROMs directly from the power quantities at selected interpolation frequencies. Strategies for parallel implementation of the algorithm via message passing interface are proposed. The quality of ROMs is iteratively refined according to the error estimate based on residual norms. Band capacity is proposed to provide a priori estimate of the sizes of good quality ROMs. Frequency averaging is recast as ensemble averaging and Cauchy distribution is used to simplify the computation. Besides model reduction for deterministic systems, details of constructing ROMs for parametric and nonparametric random systems are also presented. Case studies have been conducted on testbeds from Harwell-Boeing collections. Input and coupling power flow are computed for the original systems and the ROMs. Good agreement is observed in all cases.

Comparison and validation of statistical methods for predicting power outage durations in the event of hurricanes.

Science.gov (United States)

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.

FLOUTING MAXIMS IN INDONESIA LAWAK KLUB CONVERSATION

Directory of Open Access Journals (Sweden)

Rahmawati Sukmaningrum

2017-04-01

Full Text Available This study aims to identify the types of maxims flouted in the conversation in famous comedy show, Indonesia Lawak Club. Likewise, it also tries to reveal the speakers‘ intention of flouting the maxim in the conversation during the show. The writers use descriptive qualitative method in conducting this research. The data is taken from the dialogue of Indonesia Lawak club and then analyzed based on Grice‘s cooperative principles. The researchers read the dialogue‘s transcripts, identify the maxims, and interpret the data to find the speakers‘ intention for flouting the maxims in the communication. The results show that there are four types of maxims flouted in the dialogue. Those are maxim of quality (23%, maxim of quantity (11%, maxim of manner (31%, and maxim of relevance (35. Flouting the maxims in the conversations is intended to make the speakers feel uncomfortable with the conversation, show arrogances, show disagreement or agreement, and ridicule other speakers.

Power output and efficiency of a thermoelectric generator under temperature control

International Nuclear Information System (INIS)

Chen, Wei-Hsin; Wu, Po-Hua; Wang, Xiao-Dong; Lin, Yu-Li

2016-01-01

Highlights: • Power output and efficiency of a thermoelectric generator (TEG) is studied. • Temperatures at the module’s surfaces are approximated by sinusoidal functions. • Mean output power and efficiency are enhanced by the temperature oscillation. • The maximum mean efficiency of the TEG in this study is 8.45%. • The phase angle of 180° is a feasible operation for maximizing the performance. - Abstract: Operation control is an effective way to improve the output power of thermoelectric generators (TEGs). The present study is intended to numerically investigate the power output and efficiency of a TEG and find the operating conditions for maximizing its performance. The temperature distributions at the hot side and cold side surfaces of the TEG are approximated by sinusoidal functions. The influences of the temperature amplitudes at the hot side surface and the cold side surface, the phase angle, and the figure-of-merit (ZT) on the performance of the TEG are analyzed. The predictions indicate that the mean output power and efficiency of the TEG are significantly enhanced by the temperature oscillation, whereas the mean absorbed heat by the TEG is slightly influenced. An increase in the temperature amplitude of the hot side surface and the phase angle can effectively improve the performance. For the phase angle of 0°, a smaller temperature amplitude at the cold side surface renders the better performance compared to that with a larger amplitude. When the ZT value increases from 0.736 to 1.8, the mean efficiency at the phase angle of 180° is amplified by a factor of 1.72, and the maximum mean efficiency is 8.45%. In summary, a larger temperature amplitude at the hot side surface with the phase angle of 180° is a feasible operation for maximizing the performance.

State-space model predictive control method for core power control in pressurized water reactor nuclear power stations

Energy Technology Data Exchange (ETDEWEB)

Wang, Guo Xu; Wu, Jie; Zeng, Bifan; Wu, Wangqiang; Ma, Xiao Qian [School of Electric Power, South China University of Technology, Guangzhou (China); Xu, Zhibin [Electric Power Research Institute of Guangdong Power Grid Corporation, Guangzhou (China)

2017-02-15

A well-performed core power control to track load changes is crucial in pressurized water reactor (PWR) nuclear power stations. It is challenging to keep the core power stable at the desired value within acceptable error bands for the safety demands of the PWR due to the sensitivity of nuclear reactors. In this paper, a state-space model predictive control (MPC) method was applied to the control of the core power. The model for core power control was based on mathematical models of the reactor core, the MPC model, and quadratic programming (QP). The mathematical models of the reactor core were based on neutron dynamic models, thermal hydraulic models, and reactivity models. The MPC model was presented in state-space model form, and QP was introduced for optimization solution under system constraints. Simulations of the proposed state-space MPC control system in PWR were designed for control performance analysis, and the simulation results manifest the effectiveness and the good performance of the proposed control method for core power control.

Lifetime Maximizing Adaptive Power Control in Wireless Sensor Networks

National Research Council Canada - National Science Library

Sun, Fangting; Shayman, Mark

2006-01-01

...: adaptive power control. They focus on the sensor networks that consist of a sink and a set of homogeneous wireless sensor nodes, which are randomly deployed according to a uniform distribution...

Achievement motivation revisited : New longitudinal data to demonstrate its predictive power

NARCIS (Netherlands)

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

VIOLATION OF CONVERSATION MAXIM ON TV ADVERTISEMENTS

Directory of Open Access Journals (Sweden)

Desak Putu Eka Pratiwi

2015-07-01

Full Text Available Maxim is a principle that must be obeyed by all participants textually and interpersonally in order to have a smooth communication process. Conversation maxim is divided into four namely maxim of quality, maxim of quantity, maxim of relevance, and maxim of manner of speaking. Violation of the maxim may occur in a conversation in which the information the speaker has is not delivered well to his speaking partner. Violation of the maxim in a conversation will result in an awkward impression. The example of violation is the given information that is redundant, untrue, irrelevant, or convoluted. Advertisers often deliberately violate the maxim to create unique and controversial advertisements. This study aims to examine the violation of maxims in conversations of TV ads. The source of data in this research is food advertisements aired on TV media. Documentation and observation methods are applied to obtain qualitative data. The theory used in this study is a maxim theory proposed by Grice (1975. The results of the data analysis are presented with informal method. The results of this study show an interesting fact that the violation of maxim in a conversation found in the advertisement exactly makes the advertisements very attractive and have a high value.

Finding Maximal Quasiperiodicities in Strings

DEFF Research Database (Denmark)

Brodal, Gerth Stølting; Pedersen, Christian N. S.

2000-01-01

of length n in time O(n log n) and space O(n). Our algorithm uses the suffix tree as the fundamental data structure combined with efficient methods for merging and performing multiple searches in search trees. Besides finding all maximal quasiperiodic substrings, our algorithm also marks the nodes......Apostolico and Ehrenfeucht defined the notion of a maximal quasiperiodic substring and gave an algorithm that finds all maximal quasiperiodic substrings in a string of length n in time O(n log2 n). In this paper we give an algorithm that finds all maximal quasiperiodic substrings in a string...... in the suffix tree that have a superprimitive path-label....

Age-Predicted Maximal Heart Rate in Recreational Marathon Runners: A Cross-Sectional Study on Fox's and Tanaka's Equations

Science.gov (United States)

Nikolaidis, Pantelis T.; Rosemann, Thomas; Knechtle, Beat

2018-01-01

Age-based prediction equations of maximal heart rate (HRmax), such as the popular formulas Fox's 220-age, or Tanaka's 208-0.7 × age, have been widely used in various populations. Surprisingly, so far these equations have not been validated in marathon runners, despite the importance of the role of HRmax for training purposes in endurance running. The aim of the present study was to examine the validity of Fox and Tanaka equations in a large sample of women and men recreational marathon runners. Participants (n = 180, age 43.2 ± 8.5 years, VO2max 46.8 mL/min/kg, finishers in at least one marathon during the last year) performed a graded exercise test on a treadmill, where HRmax was measured. Measured HRmax correlated largely with age in the total sample (r = −0.50, p marathon runners. In addition, exercise physiologists and sport scientists should consider the observed differences among various assessment methods when performing exercise testing or prescribing training program relying on HR. PMID:29599724

Age-Predicted Maximal Heart Rate in Recreational Marathon Runners: A Cross-Sectional Study on Fox's and Tanaka's Equations.

Science.gov (United States)

Nikolaidis, Pantelis T; Rosemann, Thomas; Knechtle, Beat

2018-01-01

Age-based prediction equations of maximal heart rate (HR max ), such as the popular formulas Fox's 220-age, or Tanaka's 208-0.7 × age, have been widely used in various populations. Surprisingly, so far these equations have not been validated in marathon runners, despite the importance of the role of HR max for training purposes in endurance running. The aim of the present study was to examine the validity of Fox and Tanaka equations in a large sample of women and men recreational marathon runners. Participants ( n = 180, age 43.2 ± 8.5 years, VO 2max 46.8 mL/min/kg, finishers in at least one marathon during the last year) performed a graded exercise test on a treadmill, where HR max was measured. Measured HR max correlated largely with age in the total sample ( r = -0.50, p marathon runners. In addition, exercise physiologists and sport scientists should consider the observed differences among various assessment methods when performing exercise testing or prescribing training program relying on HR.

Lactate Parameters Predict Clinical Outcomes in Patients with Nonvariceal Upper Gastrointestinal Bleeding.

Science.gov (United States)

Lee, Seung Hoon; Min, Yang Won; Bae, Joohwan; Lee, Hyuk; Min, Byung Hoon; Lee, Jun Haeng; Rhee, Poong Lyul; Kim, Jae J

2017-11-01

The predictive role of lactate in patients with nonvariceal upper gastrointestinal bleeding (NVUGIB) has been suggested. This study evaluated several lactate parameters in terms of predicting outcomes of bleeding patients and sought to establish a new scoring model by combining lactate parameters and the AIMS65 score. A total of 114 patients with NVUGIB who underwent serum lactate level testing at least twice and endoscopic hemostasis within 24 hours after admission were retrospectively analyzed. The associations between five lactate parameters and clinical outcomes were evaluated and the predictive power of lactate parameter combined AIMS65s (L-AIMS65s) and AIMS56 scoring was compared. The most common cause of bleeding was gastric ulcer (48.2%). Lactate clearance rate (LCR) was associated with 30-day rebleeding (odds ratio [OR], 0.931; 95% confidence interval [CI], 0.872-0.994; P = 0.033). Initial lactate (OR, 1.313; 95% CI, 1.050-1.643; P = 0.017), maximal lactate (OR, 1.277; 95% CI, 1.037-1.573; P = 0.021), and average lactate (OR, 1.535; 95% CI, 1.137-2.072; P = 0.005) levels were associated with 30-day mortality. Initial lactate (OR, 1.213; 95% CI, 1.027-1.432; P = 0.023), maximal lactate (OR, 1.271; 95% CI, 1.074-1.504; P = 0.005), and average lactate (OR, 1.501; 95% CI, 1.150-1.959; P = 0.003) levels were associated with admission over 7 days. Although L-AIMS65s showed the highest area under the curve for prediction of each outcome, differences between L-AIMS65s and AIMS65 did not reach statistical significance. In conclusion, lactate parameters have a prognostic role in patients with NVUGIB. However, they do not increase the predictive power of AIMS65 when combined. © 2017 The Korean Academy of Medical Sciences.

Laboratory and Field-Based Evaluation of Short-Term Effort with Maximal Intensity in Individuals with Intellectual Disabilities

Directory of Open Access Journals (Sweden)

Lencse-Mucha Judit

2015-12-01

Full Text Available Results of previous studies have not indicated clearly which tests should be used to assess short-term efforts of people with intellectual disabilities. Thus, the aim of the present study was to evaluate laboratory and field-based tests of short-term effort with maximal intensity of subjects with intellectual disabilities. Twenty four people with intellectual disability, who trained soccer, participated in this study. The 30 s Wingate test and additionally an 8 s test with maximum intensity were performed on a bicycle ergometer. The fatigue index, maximal and mean power, relative maximal and relative mean power were measured. Overall, nine field-based tests were conducted: 5, 10 and 20 m sprints, a 20 m shuttle run, a seated medicine ball throw, a bent arm hang test, a standing broad jump, sit-ups and a hand grip test. The reliability of the 30 s and 8 s Wingate tests for subjects with intellectual disability was confirmed. Significant correlation was observed for mean power between the 30 s and 8 s tests on the bicycle ergometer at a moderate level (r >0.4. Moreover, significant correlations were indicated between the results of laboratory tests and field tests, such as the 20 m sprint, the 20 m shuttle run, the standing long jump and the medicine ball throw. The strongest correlation was in the medicine ball throw. The 30 s Wingate test is a reliable test assessing maximal effort in subjects with intellectual disability. The results of this research confirmed that the 8 s test on a bicycle ergometer had a moderate correlation with the 30 s Wingate test in this population, thus, this comparison needs further investigation to examine alternativeness of the 8 s to 30 s Wingate tests. The non-laboratory tests could be used to indirectly assess performance in short-term efforts with maximal intensity.

Laboratory and Field-Based Evaluation of Short-Term Effort with Maximal Intensity in Individuals with Intellectual Disabilities

Science.gov (United States)

Lencse-Mucha, Judit; Molik, Bartosz; Marszałek, Jolanta; Kaźmierska-Kowalewska, Kalina; Ogonowska-Słodownik, Anna

2015-01-01

Results of previous studies have not indicated clearly which tests should be used to assess short-term efforts of people with intellectual disabilities. Thus, the aim of the present study was to evaluate laboratory and field-based tests of short-term effort with maximal intensity of subjects with intellectual disabilities. Twenty four people with intellectual disability, who trained soccer, participated in this study. The 30 s Wingate test and additionally an 8 s test with maximum intensity were performed on a bicycle ergometer. The fatigue index, maximal and mean power, relative maximal and relative mean power were measured. Overall, nine field-based tests were conducted: 5, 10 and 20 m sprints, a 20 m shuttle run, a seated medicine ball throw, a bent arm hang test, a standing broad jump, sit-ups and a hand grip test. The reliability of the 30 s and 8 s Wingate tests for subjects with intellectual disability was confirmed. Significant correlation was observed for mean power between the 30 s and 8 s tests on the bicycle ergometer at a moderate level (r >0.4). Moreover, significant correlations were indicated between the results of laboratory tests and field tests, such as the 20 m sprint, the 20 m shuttle run, the standing long jump and the medicine ball throw. The strongest correlation was in the medicine ball throw. The 30 s Wingate test is a reliable test assessing maximal effort in subjects with intellectual disability. The results of this research confirmed that the 8 s test on a bicycle ergometer had a moderate correlation with the 30 s Wingate test in this population, thus, this comparison needs further investigation to examine alternativeness of the 8 s to 30 s Wingate tests. The non-laboratory tests could be used to indirectly assess performance in short-term efforts with maximal intensity. PMID:26834874

LONG-LASTING SUPERNORMAL CONDUCTION-VELOCITY AFTER SUSTAINED MAXIMAL ISOMETRIC CONTRACTION IN HUMAN MUSCLE

NARCIS (Netherlands)

VANDERHOEVEN, JH; VANWEERDEN, TW; ZWARTS, MJ

Local muscle fatigue (1 min maximal voluntary contraction) and recovery were studied by means of surface and invasive EMG on elbow flexors to record the changes in muscle fiber conduction velocity (MFCV), median power frequency (MPF), integrated EMG (IEMG), and force. The main finding was a

Electrodynamic Wireless Power Transmission to Rotating Magnet Receivers

International Nuclear Information System (INIS)

Garraud, A; Jimenez, J D; Garraud, N; Arnold, D P

2014-01-01

This paper presents an approach for electrodynamic wireless power transmission (EWPT) using a synchronously rotating magnet located in a 3.2 cm 3 receiver. We demonstrate wireless power transmission up to 99 mW (power density equal to 31 mW/cm 3 ) over a 5-cm distance and 5 mW over a 20-cm distance. The maximum operational frequency, and hence maximal output power, is constrained by the magnetic field amplitude. A quadratic relationship is found between the maximal output power and the magnetic field. We also demonstrate simultaneous, power transmission to multiple receivers positioned at different locations

Agreement of Power Measures between Garmin Vector and SRM Cycle Power Meters

Science.gov (United States)

Novak, Andrew R.; Dascombe, Benjamin J.

2016-01-01

This study aimed to determine if the Garmin Vector (Schaffhausen, Switzerland) power meter produced acceptable measures when compared with the Schoberer Rad Messetechnik (SRM; Julich, Germany) power meter across a range of high-intensity efforts. Twenty-one well-trained cyclists completed power profiles (seven maximal mean efforts between 5 and…

Application of neural networks to signal prediction in nuclear power plant

International Nuclear Information System (INIS)

Wan Joo Kim; Soon Heung Chang; Byung Ho Lee

1993-01-01

This paper describes the feasibility study of an artificial neural network for signal prediction. The purpose of signal prediction is to estimate the value of undetected next time step signal. As the prediction method, based on the idea of auto regression, a few previous signals are inputs to the artificial neural network and the signal value of next time step is estimated with the outputs of the network. The artificial neural network can be applied to the nonlinear system and answers in short time. The training algorithm is a modified backpropagation model, which can effectively reduce the training time. The target signal of the simulation is the steam generator water level, which is one of the important parameters in nuclear power plants. The simulation result shows that the predicted value follows the real trend well

Power quality control of an autonomous wind-diesel power system based on hybrid intelligent controller.

Science.gov (United States)

Ko, Hee-Sang; Lee, Kwang Y; Kang, Min-Jae; Kim, Ho-Chan

2008-12-01

Wind power generation is gaining popularity as the power industry in the world is moving toward more liberalized trade of energy along with public concerns of more environmentally friendly mode of electricity generation. The weakness of wind power generation is its dependence on nature-the power output varies in quite a wide range due to the change of wind speed, which is difficult to model and predict. The excess fluctuation of power output and voltages can influence negatively the quality of electricity in the distribution system connected to the wind power generation plant. In this paper, the authors propose an intelligent adaptive system to control the output of a wind power generation plant to maintain the quality of electricity in the distribution system. The target wind generator is a cost-effective induction generator, while the plant is equipped with a small capacity energy storage based on conventional batteries, heater load for co-generation and braking, and a voltage smoothing device such as a static Var compensator (SVC). Fuzzy logic controller provides a flexible controller covering a wide range of energy/voltage compensation. A neural network inverse model is designed to provide compensating control amount for a system. The system can be optimized to cope with the fluctuating market-based electricity price conditions to lower the cost of electricity consumption or to maximize the power sales opportunities from the wind generation plant.

Effect of Ramadan observance on maximal muscular performance of trained men.

Science.gov (United States)

Bouhlel, Hatem; Shephard, Roy J; Gmada, Nebil; Aouichaoui, Chirine; Peres, Gilbert; Tabka, Zouhair; Bouhlel, Ezdine

2013-05-01

To assess the influence of Ramadan fasting on maximal performance of moderately trained young men using various tests of muscle performance. Comparison of Ramadan fasting (n = 10) versus control group (n = 10) over 3 test sessions, before Ramadan (B), at the end of the first week of Ramadan (R-1), and during the fourth week of Ramadan (R-4). At each 2-day test session, 4 tests were performed in the same order: measurement of vertical jump height (VJH) and a force-velocity test using the arms on day 1, and measurement of handgrip force (HGF), and a force-velocity test using the legs on day 2. Twenty trained men. Maximal power of the arms and of the legs (force-velocity testing), vertical jump performance, HGF, anthropometric data, dietary intake, hemoglobin, and hematocrit. Two-way analyses of variance (group × time) showed Ramadan fasters with decreased maximal anaerobic power of the arms (Wmax-A) and legs (Wmax-L) at R-1, with a partial return of arm data to initial values at R-4. Vertical jump height and HGF remained unchanged throughout. Other changes in Ramadan observers were a decreased energy intake and a decrease of plasma volume at R-1. These results suggest that Ramadan observance initially had detrimental effects on Wmax-A, and Wmax-L, with a tendency to recovery by week 4 of Ramadan. Reductions of total energy intake and intramuscular glycogen may contribute to the reduced Wmax-A and Wmax-L during Ramadan fasting.

Real-time prediction models for output power and efficiency of grid-connected solar photovoltaic systems

International Nuclear Information System (INIS)

Su, Yan; Chan, Lai-Cheong; Shu, Lianjie; Tsui, Kwok-Leung

2012-01-01

Highlights: ► We develop online prediction models for solar photovoltaic system performance. ► The proposed prediction models are simple but with reasonable accuracy. ► The maximum monthly average minutely efficiency varies 10.81–12.63%. ► The average efficiency tends to be slightly higher in winter months. - Abstract: This paper develops new real time prediction models for output power and energy efficiency of solar photovoltaic (PV) systems. These models were validated using measured data of a grid-connected solar PV system in Macau. Both time frames based on yearly average and monthly average are considered. It is shown that the prediction model for the yearly/monthly average of the minutely output power fits the measured data very well with high value of R 2 . The online prediction model for system efficiency is based on the ratio of the predicted output power to the predicted solar irradiance. This ratio model is shown to be able to fit the intermediate phase (9 am to 4 pm) very well but not accurate for the growth and decay phases where the system efficiency is near zero. However, it can still serve as a useful purpose for practitioners as most PV systems work in the most efficient manner over this period. It is shown that the maximum monthly average minutely efficiency varies over a small range of 10.81% to 12.63% in different months with slightly higher efficiency in winter months.

MAXIMIZING HYDROPOWER PRODUCTION FROM RESERVOIRS:THE CASE STUDY OF MARKABA

International Nuclear Information System (INIS)

Jaafar, H.

2014-01-01

Hydropower is a form of renewable energy that is clean and cheap. Under uncertain climatic conditions, maximization of hydropower production becomes a challenging task.Stochastic Dynamic programming (SDP) is a promising optimization algorithm that is usedfor complex non-linear reservoir operational policies and strategies.In this research, a combined simulation-SDPoptimization model isdeveloped andverified for maximizing large-scale hydropower production in a monthly time step. The model isdeveloped to generate optimal operational policies for the Qarawn reservoir in Lebanon and test these policies in real time conditions. The model isused to derive operational regimes for the Qarawn reservoirunder varying flows using transitional probability matrices. Simulating the derived rules and the generated operational policies proved effective in maximizingthe hydropower production from the Markaba power plant. The model could be successfully applied to other hydropower dams in the region. (author)

CFTR Genotype and Maximal Exercise Capacity in Cystic Fibrosis: A Cross-sectional Study.

Science.gov (United States)

Radtke, Thomas; Hebestreit, Helge; Gallati, Sabina; Schneiderman, Jane E; Braun, Julia; Stevens, Daniel; Hulzebos, Erik Hj; Takken, Tim; Boas, Steven R; Urquhart, Don S; Lands, Larry C; Tejero, Sergio; Sovtic, Aleksandar; Dwyer, Tiffany; Petrovic, Milos; Harris, Ryan A; Karila, Chantal; Savi, Daniela; Usemann, Jakob; Mei-Zahav, Meir; Hatziagorou, Elpis; Ratjen, Felix; Kriemler, Susi

2018-02-01

Cystic fibrosis transmembrane conductance regulator (CFTR) is expressed in human skeletal muscle cells. Variations of CFTR dysfunction among patients with cystic fibrosis may be an important determinant of maximal exercise capacity in cystic fibrosis. Previous studies on the relationship between CFTR genotype and maximal exercise capacity are scarce and contradictory. This study was designed to explore factors influencing maximal exercise capacity, expressed as peak oxygen uptake (V.O2peak), with a specific focus on CFTR genotype in children and adults with cystic fibrosis. In an international, multicenter, cross-sectional study, we collected data on CFTR genotype and cardiopulmonary exercise tests in patients with cystic fibrosis who were ages 8 years and older. CFTR mutations were classified into functional classes I–V. The final analysis included 726 patients (45% females; age range, 8–61 yr; forced expiratory volume in 1 s, 16 to 123% predicted) from 17 cystic fibrosis centers in North America, Europe, Australia, and Asia, all of whom had both valid maximal cardiopulmonary exercise tests and complete CFTR genotype data. Overall, patients exhibited exercise intolerance (V.O2peak, 77.3 ± 19.1% predicted), but values were comparable among different CFTR classes. We did not detect an association between CFTR genotype functional classes I–III and either V.O2peak (percent predicted) (adjusted β = −0.95; 95% CI, −4.18 to 2.29; P = 0.57) or maximum work rate (Wattmax) (adjusted β = −1.38; 95% CI, −5.04 to 2.27; P = 0.46) compared with classes IV–V. Those with at least one copy of a F508del-CFTR mutation and one copy of a class V mutation had a significantly lower V.O2peak (β = −8.24%; 95% CI, −14.53 to −2.99; P = 0.003) and lower Wattmax (adjusted β = −7.59%; 95% CI, −14.21 to −0.95; P = 0.025) than those with two copies of a class II mutation. On the basis of linear regression analysis adjusted for

Hierarchical Model Predictive Control for Plug-and-Play Resource Distribution

DEFF Research Database (Denmark)

Bendtsen, Jan Dimon; Trangbæk, K; Stoustrup, Jakob

2012-01-01

of autonomous units. The approach is inspired by smart-grid electric power production and consumption systems, where the flexibility of a large number of power producing and/or power consuming units can be exploited in a smart-grid solution. The objective is to accommodate the load variation on the grid......This chapter deals with hierarchical model predictive control (MPC) of distributed systems. A three level hierarchical approach is proposed, consisting of a high level MPC controller, a second level of so-called aggregators, controlled by an online MPC-like algorithm, and a lower level......, arising on one hand from varying consumption, on the other hand by natural variations in power production e.g. from wind turbines. The proposed method can also be applied to supply chain management systems, where the challenge is to balance demand and supply, using a number of storages each with a maximal...

Optimal Design of Wireless Power Transmission Links for Millimeter-Sized Biomedical Implants.

Science.gov (United States)

Ahn, Dukju; Ghovanloo, Maysam

2016-02-01

This paper presents a design methodology for RF power transmission to millimeter-sized implantable biomedical devices. The optimal operating frequency and coil geometries are found such that power transfer efficiency (PTE) and tissue-loss-constrained allowed power are maximized. We define receiver power reception susceptibility (Rx-PRS) and transmitter figure of merit (Tx-FoM) such that their multiplication yields the PTE. Rx-PRS and Tx-FoM define the roles of the Rx and Tx in the PTE, respectively. First, the optimal Rx coil geometry and operating frequency range are identified such that the Rx-PRS is maximized for given implant constraints. Since the Rx is very small and has lesser design freedom than the Tx, the overall operating frequency is restricted mainly by the Rx. Rx-PRS identifies such operating frequency constraint imposed by the Rx. Secondly, the Tx coil geometry is selected such that the Tx-FoM is maximized under the frequency constraint at which the Rx-PRS was saturated. This aligns the target frequency range of Tx optimization with the frequency range at which Rx performance is high, resulting in the maximum PTE. Finally, we have found that even in the frequency range at which the PTE is relatively flat, the tissue loss per unit delivered power can be significantly different for each frequency. The Rx-PRS can predict the frequency range at which the tissue loss per unit delivered power is minimized while PTE is maintained high. In this way, frequency adjustment for the PTE and tissue-loss-constrained allowed power is realized by characterizing the Rx-PRS. The design procedure was verified through full-wave electromagnetic field simulations and measurements using de-embedding method. A prototype implant, 1 mm in diameter, achieved PTE of 0.56% ( -22.5 dB) and power delivered to load (PDL) was 224 μW at 200 MHz with 12 mm Tx-to-Rx separation in the tissue environment.

Method of critical power prediction based on film flow model coupled with subchannel analysis

International Nuclear Information System (INIS)

Tomiyama, Akio; Yokomizo, Osamu; Yoshimoto, Yuichiro; Sugawara, Satoshi.

1988-01-01

A new method was developed to predict critical powers for a wide variety of BWR fuel bundle designs. This method couples subchannel analysis with a liquid film flow model, instead of taking the conventional way which couples subchannel analysis with critical heat flux correlations. Flow and quality distributions in a bundle are estimated by the subchannel analysis. Using these distributions, film flow rates along fuel rods are then calculated with the film flow model. Dryout is assumed to occur where one of the film flows disappears. This method is expected to give much better adaptability to variations in geometry, heat flux, flow rate and quality distributions than the conventional methods. In order to verify the method, critical power data under BWR conditions were analyzed. Measured and calculated critical powers agreed to within ±7%. Furthermore critical power data for a tight-latticed bundle obtained by LeTourneau et al. were compared with critical powers calculated by the present method and two conventional methods, CISE correlation and subchannel analysis coupled with the CISE correlation. It was confirmed that the present method can predict critical powers more accurately than the conventional methods. (author)

A study on the characteristics, predictions and policies of China’s eight main power grids

International Nuclear Information System (INIS)

Wang, Jianzhou; Dong, Yao; Jiang, He

2014-01-01

Highlights: • Indian blackout is analyzed as a warning for China’s power system. • Issues and recommendations of China’s eight power grids are presented. • Five models are employed for scenario analysis on power generation and consumption. • The optimized combined model outperforms other models. • Methods towards balancing power generation and environmental impacts are proposed. - Abstract: Electricity is an indispensable energy source for modern social and economic development. However, large-scale blackouts can cause incalculable loss to society. In 2012, three major Indian power grids collapsed, resulting in the interruption of the electricity supply to over 600 million people. To avoid an event like that, China needs to forecast the power generation and consumption of eight power grids effectively. This paper first analyzes the characteristics of eight power grids and then proposes a combined model based on three improved grey models optimized by a differential evolution algorithm to predict electricity production and consumption of each power grid. The optimized combined forecasting model provides a better prediction than other models, and it is also the most workable and satisfactory model. Experiment results show electricity production and consumption would increase. In consideration of the real situation and existing problems, some suggestions are proposed. The government could decrease thermal power and exploit renewable energy power, like hydroelectric power, wind power and solar power, to ensure the safe and reliable operation of China’s major power grids and protect environment

Shareholder, stakeholder-owner or broad stakeholder maximization

DEFF Research Database (Denmark)

Mygind, Niels

2004-01-01

With reference to the discussion about shareholder versus stakeholder maximization it is argued that the normal type of maximization is in fact stakeholder-owner maxi-mization. This means maximization of the sum of the value of the shares and stake-holder benefits belonging to the dominating...... including the shareholders of a company. Although it may be the ultimate goal for Corporate Social Responsibility to achieve this kind of maximization, broad stakeholder maximization is quite difficult to give a precise definition. There is no one-dimensional measure to add different stakeholder benefits...... not traded on the mar-ket, and therefore there is no possibility for practical application. Broad stakeholder maximization instead in practical applications becomes satisfying certain stakeholder demands, so that the practical application will be stakeholder-owner maximization un-der constraints defined...

Predictive Power Estimation Algorithm (PPEA--a new algorithm to reduce overfitting for genomic biomarker discovery.

Directory of Open Access Journals (Sweden)

Jiangang Liu

Full Text Available Toxicogenomics promises to aid in predicting adverse effects, understanding the mechanisms of drug action or toxicity, and uncovering unexpected or secondary pharmacology. However, modeling adverse effects using high dimensional and high noise genomic data is prone to over-fitting. Models constructed from such data sets often consist of a large number of genes with no obvious functional relevance to the biological effect the model intends to predict that can make it challenging to interpret the modeling results. To address these issues, we developed a novel algorithm, Predictive Power Estimation Algorithm (PPEA, which estimates the predictive power of each individual transcript through an iterative two-way bootstrapping procedure. By repeatedly enforcing that the sample number is larger than the transcript number, in each iteration of modeling and testing, PPEA reduces the potential risk of overfitting. We show with three different cases studies that: (1 PPEA can quickly derive a reliable rank order of predictive power of individual transcripts in a relatively small number of iterations, (2 the top ranked transcripts tend to be functionally related to the phenotype they are intended to predict, (3 using only the most predictive top ranked transcripts greatly facilitates development of multiplex assay such as qRT-PCR as a biomarker, and (4 more importantly, we were able to demonstrate that a small number of genes identified from the top-ranked transcripts are highly predictive of phenotype as their expression changes distinguished adverse from nonadverse effects of compounds in completely independent tests. Thus, we believe that the PPEA model effectively addresses the over-fitting problem and can be used to facilitate genomic biomarker discovery for predictive toxicology and drug responses.

On the maximal superalgebras of supersymmetric backgrounds

International Nuclear Information System (INIS)

Figueroa-O'Farrill, Jose; Hackett-Jones, Emily; Moutsopoulos, George; Simon, Joan

2009-01-01

In this paper we give a precise definition of the notion of a maximal superalgebra of certain types of supersymmetric supergravity backgrounds, including the Freund-Rubin backgrounds, and propose a geometric construction extending the well-known construction of its Killing superalgebra. We determine the structure of maximal Lie superalgebras and show that there is a finite number of isomorphism classes, all related via contractions from an orthosymplectic Lie superalgebra. We use the structure theory to show that maximally supersymmetric waves do not possess such a maximal superalgebra, but that the maximally supersymmetric Freund-Rubin backgrounds do. We perform the explicit geometric construction of the maximal superalgebra of AdS 4 X S 7 and find that it is isomorphic to osp(1|32). We propose an algebraic construction of the maximal superalgebra of any background asymptotic to AdS 4 X S 7 and we test this proposal by computing the maximal superalgebra of the M2-brane in its two maximally supersymmetric limits, finding agreement.

Maximizing the science return of interplanetary missions using nuclear electric power

International Nuclear Information System (INIS)

Zubrin, R.M.

1995-01-01

The multi-kilowatt power sources on the spaecraft also enables active sensing, including radar, which could be used to do topographic and subsurface studies of clouded bodies such as Titan, ground pentrating sounding of Pluto, the major planet's moons, and planetoids, and topside sounding of the electrically conductive atmospheres of Jupiter, Saturn, Uranus and Neptune to produce profiles of fluid density, conductivity, and horizontal and vertical velocity as a function of depth and global location. Radio science investigations of planetary atmospheres and ring systems would be greatly enhanced by increased transmitter power. The scientific benefits of utilizing such techniques are discussed, and a comparison is made with the quantity and quality of science that a low-powered spacecraft employing RTGs could return. It is concluded that the non-propulsive benefits of nuclear power for spacecraft exploring the outer solar system are enormous, and taken together with the well documented mission enhancements enabled by electric propulsion fully justify the expanditures needed to bring a space qualified nuclear electric power source into being. copyright 1995 American Institute of Physics

Prediction and attendance of Angra 2 nuclear power plant cycle extension

International Nuclear Information System (INIS)

Dias, Amory; Ferreira Junior, Decio Brandes M.; Morgado, Mario Monteiro; Santos, Barbara Oliveira dos; Oliveira, Monica Georgia Nunes

2007-01-01

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)

Validation of Lifetime Prediction of IGBT Modules Based on Linear Damage Accumulation by Means of Superimposed Power Cycling Tests

DEFF Research Database (Denmark)

Choi, Ui-Min; Ma, Ke; Blaabjerg, Frede

2018-01-01

In this paper, the lifetime prediction of power device modules based on the linear damage accumulation is studied in conjunction with simple mission profiles of converters. Superimposed power cycling conditions, which are called simple mission profiles in this paper, are made based on a lifetime ...... prediction of IGBT modules under power converter applications.......In this paper, the lifetime prediction of power device modules based on the linear damage accumulation is studied in conjunction with simple mission profiles of converters. Superimposed power cycling conditions, which are called simple mission profiles in this paper, are made based on a lifetime...... model in respect to junction temperature swing duration. This model has been built based on 39 power cycling test results of 600-V 30-A three-phase-molded IGBT modules. Six tests are performed under three superimposed power cycling conditions using an advanced power cycling test setup. The experimental...

Optimization of E-DCH channel power ratios to maximize link level efficiency

DEFF Research Database (Denmark)

Zarco, Carlos Ruben Delgado; Malone, Jaime Tito; Wigard, Jeroen

2006-01-01

For the WCDMA/HSUPA concept, a key to ensuring high spectral efficiency is to correctly adjust the transmission power ratios among the data and control channels. This paper provides optimal values for the power ratio between the Enhanced-Dedicated Physical Data Channel (E-DPDCH) and the Dedicated...... rate (typical values ranging from 8.1 to 9.9 dB) and the RSN target (maintaining or decreasing their value as the target increases). These results show that it is more link efficient to increase the DPCCH transmission power with the bit rate (and the E-DPDCH's by applying the power ratio) than...... to maintain a constant DPCCH transmission power and just increase the EDPDCH to DPCCH power ratio....

Getting data for prediction of electricity generation from photovoltaic power plants

International Nuclear Information System (INIS)

Majer, V.; Hejtmankova, P.

2012-01-01

This paper deals with the short term prediction of generated electricity from photovoltaic power plants. This way of electricity generation is strongly dependent on the actual weather, mainly solar radiation and temperature. In this paper the simple method for getting solar radiation data is presented. (Authors)

Prediction of small hydropower plant power production in Himreen Lake dam (HLD using artificial neural network

Directory of Open Access Journals (Sweden)

Ali Thaeer Hammid

2018-03-01

Full Text Available In developing countries, the power production is properly less than the request of power or load, and sustaining a system stability of power production is a trouble quietly. Sometimes, there is a necessary development to the correct quantity of load demand to retain a system of power production steadily. Thus, Small Hydropower Plant (SHP includes a Kaplan turbine was verified to explore its applicability. This paper concentrates on applying on Artificial Neural Networks (ANNs by approaching of Feed-Forward, Back-Propagation to make performance predictions of the hydropower plant at the Himreen lake dam-Diyala in terms of net turbine head, flow rate of water and power production that data gathered during a research over a 10 year period. The model studies the uncertainties of inputs and output operation and there's a designing to network structure and then trained by means of the entire of 3570 experimental and observed data. Furthermore, ANN offers an analyzing and diagnosing instrument effectively to model performance of the nonlinear plant. The study suggests that the ANN may predict the performance of the plant with a correlation coefficient (R between the variables of predicted and observed output that would be higher than 0.96. Keywords: Himreen Lake Dam, Small Hydropower plants, Artificial Neural Networks, Feed forward-back propagation model, Generation system's prediction

Distributed Model Predictive Control for Active Power Control of Wind Farm

DEFF Research Database (Denmark)

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...... be considered to achieve a trade-off between them. Additionally, D- MPC is based on communication among the subsystems. Through the interaction among the neighboring subsystems, the global optimization could be achieved, which significantly reduces the computation burden. It is suitable for the modern large......-scale wind farm control....

Maximally multipartite entangled states

Science.gov (United States)

Facchi, Paolo; Florio, Giuseppe; Parisi, Giorgio; Pascazio, Saverio

2008-06-01

We introduce the notion of maximally multipartite entangled states of n qubits as a generalization of the bipartite case. These pure states have a bipartite entanglement that does not depend on the bipartition and is maximal for all possible bipartitions. They are solutions of a minimization problem. Examples for small n are investigated, both analytically and numerically.

Maximally Symmetric Composite Higgs Models.

Science.gov (United States)

Csáki, Csaba; Ma, Teng; Shu, Jing

2017-09-29

Maximal symmetry is a novel tool for composite pseudo Goldstone boson Higgs models: it is a remnant of an enhanced global symmetry of the composite fermion sector involving a twisting with the Higgs field. Maximal symmetry has far-reaching consequences: it ensures that the Higgs potential is finite and fully calculable, and also minimizes the tuning. We present a detailed analysis of the maximally symmetric SO(5)/SO(4) model and comment on its observational consequences.

Achievement Motivation Revisited: New Longitudinal Data to Demonstrate Its Predictive Power

Science.gov (United States)

Hustinx, Paul W. J.; Kuyper, Hans; van der Werf, Margaretha 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 school students. Two measures of achievement…

Maximal respiratory pressures and pulmonary function in male runners.

OpenAIRE

Cordain, L; Glisan, B J; Latin, R W; Tucker, A; Stager, J M

1987-01-01

To determine the effects of long term exercise on respiratory muscle strength, maximal inspiratory (Pl max) and expiratory (PE max) pressures, pulmonary volumes and capacities and anthropometric parameters were measured in a group of 101 male runners aged 16 to 58 years. The runners exhibited significantly (p less than 0.05) lower PE max (202 +/- 41 cm H2O and significantly greater residual lung volumes (RV) (2.08 +/- 0.49 L) than predicted values for normal subjects of similar height and age...

Applying model predictive control to power system frequency control

OpenAIRE

Ersdal, AM; Imsland, L; Cecilio, IM; Fabozzi, D; Thornhill, NF

2013-01-01

16.07.14 KB Ok to add accepted version to Spiral Model predictive control (MPC) is investigated as a control method which may offer advantages in frequency control of power systems than the control methods applied today, especially in presence of increased renewable energy penetration. The MPC includes constraints on both generation amount and generation rate of change, and it is tested on a one-area system. The proposed MPC is tested against a conventional proportional-integral (PI) cont...

Comparison of Comet Enflow and VA One Acoustic-to-Structure Power Flow Predictions

Science.gov (United States)

Grosveld, Ferdinand W.; Schiller, Noah H.; Cabell, Randolph H.

2010-01-01

Comet Enflow is a commercially available, high frequency vibroacoustic analysis software based on the Energy Finite Element Analysis (EFEA). In this method the same finite element mesh used for structural and acoustic analysis can be employed for the high frequency solutions. Comet Enflow is being validated for a floor-equipped composite cylinder by comparing the EFEA vibroacoustic response predictions with Statistical Energy Analysis (SEA) results from the commercial software program VA One from ESI Group. Early in this program a number of discrepancies became apparent in the Enflow predicted response for the power flow from an acoustic space to a structural subsystem. The power flow anomalies were studied for a simple cubic, a rectangular and a cylindrical structural model connected to an acoustic cavity. The current investigation focuses on three specific discrepancies between the Comet Enflow and the VA One predictions: the Enflow power transmission coefficient relative to the VA One coupling loss factor; the importance of the accuracy of the acoustic modal density formulation used within Enflow; and the recommended use of fast solvers in Comet Enflow. The frequency region of interest for this study covers the one-third octave bands with center frequencies from 16 Hz to 4000 Hz.

An Optimized Prediction Intervals Approach for Short Term PV Power Forecasting

Directory of Open Access Journals (Sweden)

Qiang Ni

2017-10-01

Full Text Available High quality photovoltaic (PV power prediction intervals (PIs are essential to power system operation and planning. To improve the reliability and sharpness of PIs, in this paper, a new method is proposed, which involves the model uncertainties and noise uncertainties, and PIs are constructed with a two-step formulation. In the first step, the variance of model uncertainties is obtained by using extreme learning machine to make deterministic forecasts of PV power. In the second stage, innovative PI-based cost function is developed to optimize the parameters of ELM and noise uncertainties are quantization in terms of variance. The performance of the proposed approach is examined by using the PV power and meteorological data measured from 1kW rooftop DC micro-grid system. The validity of the proposed method is verified by comparing the experimental analysis with other benchmarking methods, and the results exhibit a superior performance.

Effect of traditional resistance and power training using rated perceived exertion for enhancement of muscle strength, power, and functional performance.

Science.gov (United States)

Tiggemann, Carlos Leandro; Dias, Caroline Pieta; Radaelli, Regis; Massa, Jéssica Cassales; Bortoluzzi, Rafael; Schoenell, Maira Cristina Wolf; Noll, Matias; Alberton, Cristine Lima; Kruel, Luiz Fernando Martins

2016-04-01

The present study compared the effects of 12 weeks of traditional resistance training and power training using rated perceived exertion (RPE) to determine training intensity on improvements in strength, muscle power, and ability to perform functional task in older women. Thirty healthy elderly women (60-75 years) were randomly assigned to traditional resistance training group (TRT; n = 15) or power training group (PT; n = 15). Participants trained twice a week for 12 weeks using six exercises. The training protocol was designed to ascertain that participants exercised at an RPE of 13-18 (on a 6-20 scale). Maximal dynamic strength, muscle power, and functional performance of lower limb muscles were assessed. Maximal dynamic strength muscle strength leg press (≈58 %) and knee extension (≈20 %) increased significantly (p training. Muscle power also increased with training (≈27 %; p functional performance after training period (≈13 %; p effective in improving maximal strength, muscle power, and functional performance of lower limbs in elderly women.

Maximal quantum Fisher information matrix

International Nuclear Information System (INIS)

Chen, Yu; Yuan, Haidong

2017-01-01

We study the existence of the maximal quantum Fisher information matrix in the multi-parameter quantum estimation, which bounds the ultimate precision limit. We show that when the maximal quantum Fisher information matrix exists, it can be directly obtained from the underlying dynamics. Examples are then provided to demonstrate the usefulness of the maximal quantum Fisher information matrix by deriving various trade-off relations in multi-parameter quantum estimation and obtaining the bounds for the scalings of the precision limit. (paper)

Understanding Violations of Gricean Maxims in Preschoolers and Adults

Directory of Open Access Journals (Sweden)

Mako eOkanda

2015-07-01

Full Text Available This study used a revised Conversational Violations Test to examine Gricean maxim violations in 4- to 6-year-old Japanese children and adults. Participants’ understanding of the following maxims was assessed: be informative (first maxim of quantity, avoid redundancy (second maxim of quantity, be truthful (maxim of quality, be relevant (maxim of relation, avoid ambiguity (second maxim of manner, and be polite (maxim of politeness. Sensitivity to violations of Gricean maxims increased with age: 4-year-olds’ understanding of maxims was near chance, 5-year-olds understood some maxims (first maxim of quantity and maxims of quality, relation, and manner, and 6-year-olds and adults understood all maxims. Preschoolers acquired the maxim of relation first and had the greatest difficulty understanding the second maxim of quantity. Children and adults differed in their comprehension of the maxim of politeness. The development of the pragmatic understanding of Gricean maxims and implications for the construction of developmental tasks from early childhood to adulthood are discussed.

The future of distributed power in Alberta

International Nuclear Information System (INIS)

Bobenic, J.

2002-01-01

Maxim Power Corporation is a provider of distributed energy and environmental solutions with a total of 55 MW of installed generating capacity in Canada, Europe and Asia, with 35 MW in Alberta. The 8 MW Taber facility in southern Alberta was described. Maxim operates 25 other small scale power generation stations (1 MW units) across 4 sites in southern Alberta. All the sites are interconnected at 25 kV and are eligible for distribution credits. The 3 MW EVI facility which utilizes solution gas was also described in the PowerPoint presentation. Maxim operates an additional 3 projects totaling 10 MW. The paper made reference to issues regarding market attributes for distributed power, policy framework and the transition to a competitive power market in Alberta. The chronology of events in Alberta's power market from August 2000 to June 2001 was outlined. The impacts of deregulation on distributed power include: (1) artificially low price environment from market intervention, (2) high efficiency cogeneration opportunities have been eliminated, (3) business failures and reduced investment, and (4) private investment not afforded the same alternative cost recovery mechanisms as the Alberta balancing pool. The presentation concluded with a report card for Alberta's deregulation, giving a grade F for both present and future opportunities for distributed power in Alberta. 2 figs

Determinants of time trial performance and maximal incremental exercise in highly trained endurance athletes

DEFF Research Database (Denmark)

Jacobs, Robert Acton; Rasmussen, Peter; Siebenmann, Christoph

2011-01-01

Human endurance performance can be predicted from maximal oxygen consumption (VO(2max)), lactate threshold, and exercise efficiency. These physiologic parameters, however, are not wholly exclusive from one another and their interplay is complex. Accordingly, we sought to identify more specific me...

Data Assimilation in Air Contaminant Dispersion Using a Particle Filter and Expectation-Maximization Algorithm

Directory of Open Access Journals (Sweden)

Rongxiao Wang

2017-09-01

Full Text Available The accurate prediction of air contaminant dispersion is essential to air quality monitoring and the emergency management of contaminant gas leakage incidents in chemical industry parks. Conventional atmospheric dispersion models can seldom give accurate predictions due to inaccurate input parameters. In order to improve the prediction accuracy of dispersion models, two data assimilation methods (i.e., the typical particle filter & the combination of a particle filter and expectation-maximization algorithm are proposed to assimilate the virtual Unmanned Aerial Vehicle (UAV observations with measurement error into the atmospheric dispersion model. Two emission cases with different dimensions of state parameters are considered. To test the performances of the proposed methods, two numerical experiments corresponding to the two emission cases are designed and implemented. The results show that the particle filter can effectively estimate the model parameters and improve the accuracy of model predictions when the dimension of state parameters is relatively low. In contrast, when the dimension of state parameters becomes higher, the method of particle filter combining the expectation-maximization algorithm performs better in terms of the parameter estimation accuracy. Therefore, the proposed data assimilation methods are able to effectively support air quality monitoring and emergency management in chemical industry parks.

Evaluating Upper-Body Strength and Power From a Single Test: The Ballistic Push-up.

Science.gov (United States)

Wang, Ran; Hoffman, Jay R; Sadres, Eliahu; Bartolomei, Sandro; Muddle, Tyler W D; Fukuda, David H; Stout, Jeffrey R

2017-05-01

Wang, R, Hoffman, JR, Sadres, E, Bartolomei, S, Muddle, TWD, Fukuda, DH, and Stout, JR. Evaluating upper-body strength and power from a single test: the ballistic push-up. J Strength Cond Res 31(5): 1338-1345, 2017-The purpose of this study was to examine the reliability of the ballistic push-up (BPU) exercise and to develop a prediction model for both maximal strength (1 repetition maximum [1RM]) in the bench press exercise and upper-body power. Sixty recreationally active men completed a 1RM bench press and 2 BPU assessments in 3 separate testing sessions. Peak and mean force, peak and mean rate of force development, net impulse, peak velocity, flight time, and peak and mean power were determined. Intraclass correlation coefficients were used to examine the reliability of the BPU. Stepwise linear regression was used to develop 1RM bench press and power prediction equations. Intraclass correlation coefficient's ranged from 0.849 to 0.971 for the BPU measurements. Multiple regression analysis provided the following 1RM bench press prediction equation: 1RM = 0.31 × Mean Force - 1.64 × Body Mass + 0.70 (R = 0.837, standard error of the estimate [SEE] = 11 kg); time-based power prediction equation: Peak Power = 11.0 × Body Mass + 2012.3 × Flight Time - 338.0 (R = 0.658, SEE = 150 W), Mean Power = 6.7 × Body Mass + 1004.4 × Flight Time - 224.6 (R = 0.664, SEE = 82 W); and velocity-based power prediction equation: Peak Power = 8.1 × Body Mass + 818.6 × Peak Velocity - 762.0 (R = 0.797, SEE = 115 W); Mean Power = 5.2 × Body Mass + 435.9 × Peak Velocity - 467.7 (R = 0.838, SEE = 57 W). The BPU is a reliable test for both upper-body strength and power. Results indicate that the mean force generated from the BPU can be used to predict 1RM bench press, whereas peak velocity and flight time measured during the BPU can be used to predict upper-body power. These findings support the potential use of the BPU as a valid method to evaluate upper-body strength and power.

Isometric strength, sprint power, and aerobic power in individuals with a spinal cord injury

NARCIS (Netherlands)

Janssen, T W; van Oers, C A; Hollander, A P; Veeger, DirkJan (H. E. J.); van der Woude, L H

This study investigated in rather specific wheelchair tests the relationships among estimates of isometric upper-body strength (Fiso), sprint power (P30), aerobic power (VO2peak), and maximal power output (POaer) in a group of 44 men (age 34 +/- 12 yr) with longstanding spinal cord injuries ranging

Self-Powered Wireless Sensor Network for Automated Corrosion Prediction of Steel Reinforcement

Directory of Open Access Journals (Sweden)

Dan Su

2018-01-01

Full Text Available Corrosion is one of the key issues that affect the service life and hinders wide application of steel reinforcement. Moreover, corrosion is a long-term process and not visible for embedded reinforcement. Thus, this research aims at developing a self-powered smart sensor system with integrated innovative prediction module for forecasting corrosion process of embedded steel reinforcement. Vibration-based energy harvester is used to harvest energy for continuous corrosion data collection. Spatial interpolation module was developed to interpolate corrosion data at unmonitored locations. Dynamic prediction module is used to predict the long-term corrosion based on collected data. Utilizing this new sensor network, the corrosion process can be automated predicted and appropriate mitigation actions will be recommended accordingly.

Maximal power training induced different improvement in throwing velocity and muscle strength according to playing positions in elite male handball players.

Science.gov (United States)

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.

Maximal Predictability Approach for Identifying the Right Descriptors for Electrocatalytic Reactions.

Science.gov (United States)

Krishnamurthy, Dilip; Sumaria, Vaidish; Viswanathan, Venkatasubramanian

2018-02-01

Density functional theory (DFT) calculations are being routinely used to identify new material candidates that approach activity near fundamental limits imposed by thermodynamics or scaling relations. DFT calculations are associated with inherent uncertainty, which limits the ability to delineate materials (distinguishability) that possess high activity. Development of error-estimation capabilities in DFT has enabled uncertainty propagation through activity-prediction models. In this work, we demonstrate an approach to propagating uncertainty through thermodynamic activity models leading to a probability distribution of the computed activity and thereby its expectation value. A new metric, prediction efficiency, is defined, which provides a quantitative measure of the ability to distinguish activity of materials and can be used to identify the optimal descriptor(s) ΔG opt . We demonstrate the framework for four important electrochemical reactions: hydrogen evolution, chlorine evolution, oxygen reduction and oxygen evolution. Future studies could utilize expected activity and prediction efficiency to significantly improve the prediction accuracy of highly active material candidates.

Prediction of requirements on labor force in the fuel and power generation sector

International Nuclear Information System (INIS)

Kaveckova, R.

1990-01-01

One of the aspects of socio-economic assessment of development is quantification of the expected requirements on the number of personnel. Predictions are discussed for the period before the year 2005 for solid fuel mining and treatment, gas production and bitumen mining, power and heat generation and also for the production of electricity and heat by nuclear power plants. They are based on an analysis of past development and the present state, on presumed implementation of various concept variants, on the type structure of nuclear power plants, on the rules of the electric power supply system, and also on foreign materials. It is expected that in 2005, nuclear power will employ 15,654 personnel. (M.D.). 4 tabs., 16 refs

Modeling and Model Predictive Power and Rate Control of Wireless Communication Networks

Directory of Open Access Journals (Sweden)

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.

Prediction of speech intelligibility based on a correlation metric in the envelope power spectrum domain

DEFF Research Database (Denmark)

Relano-Iborra, Helia; May, Tobias; Zaar, Johannes

A powerful tool to investigate speech perception is the use of speech intelligibility prediction models. Recently, a model was presented, termed correlation-based speechbased envelope power spectrum model (sEPSMcorr) [1], based on the auditory processing of the multi-resolution speech-based Envel...

Maximization of revenues for power sales from a solid waste resources recovery facility

Energy Technology Data Exchange (ETDEWEB)

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.

Severity scoring in the critically ill: part 2: maximizing value from outcome prediction scoring systems.

Science.gov (United States)

Breslow, Michael J; Badawi, Omar

2012-02-01

Part 2 of this review of ICU scoring systems examines how scoring system data should be used to assess ICU performance. There often are two different consumers of these data: lCU clinicians and quality leaders who seek to identify opportunities to improve quality of care and operational efficiency, and regulators, payors, and consumers who want to compare performance across facilities. The former need to know how to garner maximal insight into their care practices; this includes understanding how length of stay (LOS) relates to quality, analyzing the behavior of different subpopulations, and following trends over time. Segregating patients into low-, medium-, and high-risk populations is especially helpful, because care issues and outcomes may differ across this severity continuum. Also, LOS behaves paradoxically in high-risk patients (survivors often have longer LOS than nonsurvivors); failure to examine this subgroup separately can penalize ICUs with superior outcomes. Consumers of benchmarking data often focus on a single score, the standardized mortality ratio (SMR). However, simple SMRs are disproportionately affected by outcomes in high-risk patients, and differences in population composition, even when performance is otherwise identical, can result in different SMRs. Future benchmarking must incorporate strategies to adjust for differences in population composition and report performance separately for low-, medium- and high-acuity patients. Moreover, because many ICUs lack the resources to care for high-acuity patients (predicted mortality >50%), decisions about where patients should receive care must consider both ICU performance scores and their capacity to care for different types of patients.

Nonlinear impairment compensation using expectation maximization for dispersion managed and unmanaged PDM 16-QAM transmission

DEFF Research Database (Denmark)

Zibar, Darko; Winther, Ole; Franceschi, Niccolo

2012-01-01

In this paper, we show numerically and experimentally that expectation maximization (EM) algorithm is a powerful tool in combating system impairments such as fibre nonlinearities, inphase and quadrature (I/Q) modulator imperfections and laser linewidth. The EM algorithm is an iterative algorithm ...

Model Predictive Control for Flexible Power Consumption of Large-Scale Refrigeration Systems

DEFF Research Database (Denmark)

Shafiei, Seyed Ehsan; Stoustrup, Jakob; Rasmussen, Henrik

2014-01-01

A model predictive control (MPC) scheme is introduced to directly control the electrical power consumption of large-scale refrigeration systems. Deviation from the baseline of the consumption is corresponded to the storing and delivering of thermal energy. By virtue of such correspondence...

Computational models for residual creep life prediction of power plant components

International Nuclear Information System (INIS)

Grewal, G.S.; Singh, A.K.; Ramamoortry, M.

2006-01-01

All high temperature - high pressure power plant components are prone to irreversible visco-plastic deformation by the phenomenon of creep. The steady state creep response as well as the total creep life of a material is related to the operational component temperature through, respectively, the exponential and inverse exponential relationships. Minor increases in the component temperature can thus have serious consequences as far as the creep life and dimensional stability of a plant component are concerned. In high temperature steam tubing in power plants, one mechanism by which a significant temperature rise can occur is by the growth of a thermally insulating oxide film on its steam side surface. In the present paper, an elegantly simple and computationally efficient technique is presented for predicting the residual creep life of steel components subjected to continual steam side oxide film growth. Similarly, fabrication of high temperature power plant components involves extensive use of welding as the fabrication process of choice. Naturally, issues related to the creep life of weldments have to be seriously addressed for safe and continual operation of the welded plant component. Unfortunately, a typical weldment in an engineering structure is a zone of complex microstructural gradation comprising of a number of distinct sub-zones with distinct meso-scale and micro-scale morphology of the phases and (even) chemistry and its creep life prediction presents considerable challenges. The present paper presents a stochastic algorithm, which can be' used for developing experimental creep-cavitation intensity versus residual life correlations for welded structures. Apart from estimates of the residual life in a mean field sense, the model can be used for predicting the reliability of the plant component in a rigorous probabilistic setting. (author)

Optimal Parameter Selection for Support Vector Machine Based on Artificial Bee Colony Algorithm: A Case Study of Grid-Connected PV System Power Prediction.

Science.gov (United States)

Gao, Xiang-Ming; Yang, Shi-Feng; Pan, San-Bo

2017-01-01

Predicting the output power of photovoltaic system with nonstationarity and randomness, an output power prediction model for grid-connected PV systems is proposed based on empirical mode decomposition (EMD) and support vector machine (SVM) optimized with an artificial bee colony (ABC) algorithm. First, according to the weather forecast data sets on the prediction date, the time series data of output power on a similar day with 15-minute intervals are built. Second, the time series data of the output power are decomposed into a series of components, including some intrinsic mode components IMFn and a trend component Res, at different scales using EMD. The corresponding SVM prediction model is established for each IMF component and trend component, and the SVM model parameters are optimized with the artificial bee colony algorithm. Finally, the prediction results of each model are reconstructed, and the predicted values of the output power of the grid-connected PV system can be obtained. The prediction model is tested with actual data, and the results show that the power prediction model based on the EMD and ABC-SVM has a faster calculation speed and higher prediction accuracy than do the single SVM prediction model and the EMD-SVM prediction model without optimization.

Optimal Parameter Selection for Support Vector Machine Based on Artificial Bee Colony Algorithm: A Case Study of Grid-Connected PV System Power Prediction

Directory of Open Access Journals (Sweden)

Xiang-ming Gao

2017-01-01

Full Text Available Predicting the output power of photovoltaic system with nonstationarity and randomness, an output power prediction model for grid-connected PV systems is proposed based on empirical mode decomposition (EMD and support vector machine (SVM optimized with an artificial bee colony (ABC algorithm. First, according to the weather forecast data sets on the prediction date, the time series data of output power on a similar day with 15-minute intervals are built. Second, the time series data of the output power are decomposed into a series of components, including some intrinsic mode components IMFn and a trend component Res, at different scales using EMD. The corresponding SVM prediction model is established for each IMF component and trend component, and the SVM model parameters are optimized with the artificial bee colony algorithm. Finally, the prediction results of each model are reconstructed, and the predicted values of the output power of the grid-connected PV system can be obtained. The prediction model is tested with actual data, and the results show that the power prediction model based on the EMD and ABC-SVM has a faster calculation speed and higher prediction accuracy than do the single SVM prediction model and the EMD-SVM prediction model without optimization.

Some Comparisons of Measured and Predicted Primary Radiation Levels in the Aagesta Power Plant

Energy Technology Data Exchange (ETDEWEB)

Aalto, E; Sandlin, R; Krell, Aa

1968-05-15

Neutron fluxes and gamma exposure rates in the primary shields of the Aagesta nuclear plant have been measured and the results compared with values predicted during shield design, and with values obtained later by the NRN bulk shielding code. The input data for the problems are given. The radial predictions are conservative by a factor of not more than 2 close to the reactor and by an unknown, higher factor further out. The conservatism is explainable by the differences between the true local conditions and core power distributions and those assumed in the predictions. The axial flux levels based on streaming calculations are found to agree quite well with the estimated values. The conservatism here is not so large and it seems to be necessary to be very careful when handling streaming problems. The experience gained shows that a power plant is less suitable for studying the accuracy of the shield design codes as such, but the practical results from the combined application of massive shield codes and void streaming predictions to complicated problems give information about the true degree of conservatism present.

Method for assessing wind power integration in a hydro based power system

International Nuclear Information System (INIS)

Norheim, I.; Palsson, M.; Tande, J.O.G.; Uhlen, K.

2006-01-01

The present paper demonstrates a method for assessment of how much wind power that can be integrated in a system with limited transmission capacity. Based on hydro inflow data and wind measurements (for different locations of planned wind farms in an area) it is possible to assess how much wind power that can be fed into a certain point in the transmission network without violating the transmission capacity limits. The proposed method combines the use of market modelling and detailed network analysis in order to assess the probability of network congestions rather than focusing on extreme cases. By computing the probability distribution of power flow on critical corridors in the grid it is possible to assess the likelihood of network congestions and the amount of energy that must be curtailed to fulfil power system security requirements (n-1). This way the assessment is not only made of worst case scenarios, assuming maximal flow from hydro plants and maximal wind power production. As extreme case scenarios are short term and may be solved by market mechanisms or automatic system protection schemes (disconnection of wind power or hydro power), the proposed method may reveal that it would be economic to install more wind power than if only based on analysis of worst case scenarios. (orig.)

On maximal massive 3D supergravity

OpenAIRE

Bergshoeff , Eric A; Hohm , Olaf; Rosseel , Jan; Townsend , Paul K

2010-01-01

ABSTRACT We construct, at the linearized level, the three-dimensional (3D) N = 4 supersymmetric " general massive supergravity " and the maximally supersymmetric N = 8 " new massive supergravity ". We also construct the maximally supersymmetric linearized N = 7 topologically massive supergravity, although we expect N = 6 to be maximal at the non-linear level. (Bergshoeff, Eric A) (Hohm, Olaf) (Rosseel, Jan) P.K.Townsend@da...

On the configuration of supercapacitors for maximizing electrochemical performance.

Science.gov (United States)

Zhang, Jintao; Zhao, X S

2012-05-01

Supercapacitors, which are attracting rapidly growing interest from both academia and industry, are important energy-storage devices for acquiring sustainable energy. Recent years have seen a number of significant breakthroughs in the research and development of supercapacitors. The emergence of innovative electrode materials (e.g., graphene) has clearly provided great opportunities for advancing the science in the field of electrochemical energy storage. Conversely, smart configurations of electrode materials and new designs of supercapacitor devices have, in many cases, boosted the electrochemical performance of the materials. We attempt to summarize recent research progress towards the design and configuration of electrode materials to maximize supercapacitor performance in terms of energy density, power density, and cycle stability. With a brief description of the structure, energy-storage mechanism, and electrode configuration of supercapacitor devices, the design and configuration of symmetric supercapacitors are discussed, followed by that of asymmetric and hybrid supercapacitors. Emphasis is placed on the rational design and configuration of supercapacitor electrodes to maximize the electrochemical performance of the device. Copyright © 2012 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Gamma loop contributing to maximal voluntary contractions in man.

Science.gov (United States)

Hagbarth, K E; Kunesch, E J; Nordin, M; Schmidt, R; Wallin, E U

1986-01-01

A local anaesthetic drug was injected around the peroneal nerve in healthy subjects in order to investigate whether the resulting loss in foot dorsiflexion power in part depended on a gamma-fibre block preventing 'internal' activation of spindle end-organs and thereby depriving the alpha-motoneurones of an excitatory spindle inflow during contraction. The motor outcome of maximal dorsiflexion efforts was assessed by measuring firing rates of individual motor units in the anterior tibial (t.a.) muscle, mean voltage e.m.g. from the pretibial muscles, dorsiflexion force and range of voluntary foot dorsiflexion movements. The tests were performed with and without peripheral conditioning stimuli, such as agonist or antagonist muscle vibration or imposed stretch of the contracting muscles. As compared to control values of t.a. motor unit firing rates in maximal isometric voluntary contractions, the firing rates were lower and more irregular during maximal dorsiflexion efforts performed during subtotal peroneal nerve blocks. During the development of paresis a gradual reduction of motor unit firing rates was observed before the units ceased responding to the voluntary commands. This change in motor unit behaviour was accompanied by a reduction of the mean voltage e.m.g. activity in the pretibial muscles. At a given stage of anaesthesia the e.m.g. responses to maximal voluntary efforts were more affected than the responses evoked by electric nerve stimuli delivered proximal to the block, indicating that impaired impulse transmission in alpha motor fibres was not the sole cause of the paresis. The inability to generate high and regular motor unit firing rates during peroneal nerve blocks was accentuated by vibration applied over the antagonistic calf muscles. By contrast, in eight out of ten experiments agonist stretch or vibration caused an enhancement of motor unit firing during the maximal force tasks. The reverse effects of agonist and antagonist vibration on the

Power Prediction Model for Turning EN-31 Steel Using Response Surface Methodology

Directory of Open Access Journals (Sweden)

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

Balancing Power Absorption and Structural Loading for a Novel Fixed-Bottom Wave Energy Converter with Nonideal Power Take-Off in Regular Waves: Preprint

Energy Technology Data Exchange (ETDEWEB)

Tom, Nathan M [National Renewable Energy Laboratory (NREL), Golden, CO (United States); Yu, Yi-Hsiang [National Renewable Energy Laboratory (NREL), Golden, CO (United States); Wright, Alan D [National Renewable Energy Laboratory (NREL), Golden, CO (United States)

2017-06-08

In this work, the net power delivered to the grid from a nonideal power take-off (PTO) is introduced followed by a review of the pseudo-spectral control theory. A power-to-load ratio, used to evaluate the pseudo-spectral controller performance, is discussed, and the results obtained from optimizing a multiterm objective function are compared against results obtained from maximizing the net output power to the grid. Simulation results are then presented for four different oscillating wave energy converter geometries to highlight the potential of combing both geometry and PTO control to maximize power while minimizing loads.

Optimizing the financial structure and maximizing the future value of your generation project

International Nuclear Information System (INIS)

Arulampalam, G.; Letellier, M.

2004-01-01

This paper discusses ways of optimizing the financial structure and maximizing the future value of an electric power generation project. It outlines the project structure, the sponsor objectives, project finance lending criteria, project timeline, risk mitigation, bank and institutional financing, sponsor's role, impact of financing choices on project value, and impact of penalties and derivative products

Virtual power plant mid-term dispatch optimization

International Nuclear Information System (INIS)

Pandžić, Hrvoje; Kuzle, Igor; Capuder, Tomislav

2013-01-01

Highlights: ► Mid-term virtual power plant dispatching. ► Linear modeling. ► Mixed-integer linear programming applied to mid-term dispatch scheduling. ► Operation profit maximization combining bilateral contracts and the day-ahead market. -- Abstract: Wind power plants incur practically zero marginal costs during their operation. However, variable and uncertain nature of wind results in significant problems when trying to satisfy the contracted quantities of delivered electricity. For this reason, wind power plants and other non-dispatchable power sources are combined with dispatchable power sources forming a virtual power plant. This paper considers a weekly self-scheduling of a virtual power plant composed of intermittent renewable sources, storage system and a conventional power plant. On the one hand, the virtual power plant needs to fulfill its long-term bilateral contracts, while, on the other hand, it acts in the market trying to maximize its overall profit. The optimal dispatch problem is formulated as a mixed-integer linear programming model which maximizes the weekly virtual power plant profit subject to the long-term bilateral contracts and technical constraints. The self-scheduling procedure is based on stochastic programming. The uncertainty of the wind power and solar power generation is settled by using pumped hydro storage in order to provide flexible operation, as well as by having a conventional power plant as a backup. The efficiency of the proposed model is rendered through a realistic case study and analysis of the results is provided. Additionally, the impact of different storage capacities and turbine/pump capacities of pumped storage are analyzed.

Optimal optical communication terminal structure for maximizing the link budget

Science.gov (United States)

Huang, Jian; Jiang, Dagang; Deng, Ke; Zhang, Peng

2015-02-01

Ordinary inter-satellite optical includes at least three optical paths for acquisition, tracking and communication, the three optical paths work simultaneously and share the received power. An optimal structure of inter-satellite optical communication terminal with single working optical path at each of working stages of acquisition and communication is introduced. A space optical switch based on frustrated total internal reflection effect is applied to switch the received laser power between the acquisition sensor and the communication sensor between the stages of acquisition and communication, this is named as power fusion which means power is transferred for shutting down unused optical path. For the stages of tracking and communication, a multiple cells sensor is used to accomplish the operation of tracking while communication, this is named as function fusion which means accomplishing multiple functions by one device to reduce the redundant optical paths. For optical communication terminal with single working path structure, the total received laser power would be detected by one sensor for each different stages of acquisition, tracking and communication, the link budget would be maximized, and this design would help to enlarge the system tolerance and reduce the acquisition time.

A neural network based computational model to predict the output power of different types of photovoltaic cells.

Science.gov (United States)

Xiao, WenBo; Nazario, Gina; Wu, HuaMing; Zhang, HuaMing; Cheng, Feng

2017-01-01

In this article, we introduced an artificial neural network (ANN) based computational model to predict the output power of three types of photovoltaic cells, mono-crystalline (mono-), multi-crystalline (multi-), and amorphous (amor-) crystalline. The prediction results are very close to the experimental data, and were also influenced by numbers of hidden neurons. The order of the solar generation power output influenced by the external conditions from smallest to biggest is: multi-, mono-, and amor- crystalline silicon cells. In addition, the dependences of power prediction on the number of hidden neurons were studied. For multi- and amorphous crystalline cell, three or four hidden layer units resulted in the high correlation coefficient and low MSEs. For mono-crystalline cell, the best results were achieved at the hidden layer unit of 8.

A neural network based computational model to predict the output power of different types of photovoltaic cells.

Directory of Open Access Journals (Sweden)

WenBo Xiao

Full Text Available In this article, we introduced an artificial neural network (ANN based computational model to predict the output power of three types of photovoltaic cells, mono-crystalline (mono-, multi-crystalline (multi-, and amorphous (amor- crystalline. The prediction results are very close to the experimental data, and were also influenced by numbers of hidden neurons. The order of the solar generation power output influenced by the external conditions from smallest to biggest is: multi-, mono-, and amor- crystalline silicon cells. In addition, the dependences of power prediction on the number of hidden neurons were studied. For multi- and amorphous crystalline cell, three or four hidden layer units resulted in the high correlation coefficient and low MSEs. For mono-crystalline cell, the best results were achieved at the hidden layer unit of 8.

Research Design and the Predictive Power of Measures of Self-Efficacy

Science.gov (United States)

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…

Prediction of critical flow rates through power-operated relief valves

International Nuclear Information System (INIS)

Abdollahian, D.; Singh, A.

1983-01-01

Existing single-phase and two-phase critical flow models are used to predict the flow rates through the power-operated relief valves tested in the EPRI Safety and Relief Valve test program. For liquid upstream conditions, Homogeneous Equilibrium Model, Moody, Henry-Fauske and Burnell two-phase critical flow models are used for comparison with data. Under steam upstream conditions, the flow rates are predicted either by the single-phase isentropic equations or the Homogeneous Equilibrium Model, depending on the thermodynamic condition of the fluid at the choking plane. The results of the comparisons are used to specify discharge coefficients for different valves under steam and liquid upstream conditions and evaluate the existing approximate critical flow relations for a wide range of subcooled water and steam conditions

Inclusive fitness maximization: An axiomatic approach.

Science.gov (United States)

Okasha, Samir; Weymark, John A; Bossert, Walter

2014-06-07

Kin selection theorists argue that evolution in social contexts will lead organisms to behave as if maximizing their inclusive, as opposed to personal, fitness. The inclusive fitness concept allows biologists to treat organisms as akin to rational agents seeking to maximize a utility function. Here we develop this idea and place it on a firm footing by employing a standard decision-theoretic methodology. We show how the principle of inclusive fitness maximization and a related principle of quasi-inclusive fitness maximization can be derived from axioms on an individual׳s 'as if preferences' (binary choices) for the case in which phenotypic effects are additive. Our results help integrate evolutionary theory and rational choice theory, help draw out the behavioural implications of inclusive fitness maximization, and point to a possible way in which evolution could lead organisms to implement it. Copyright © 2014 Elsevier Ltd. All rights reserved.

Conceptual Software Reliability Prediction Models for Nuclear Power Plant Safety Systems

International Nuclear Information System (INIS)

Johnson, G.; Lawrence, D.; Yu, H.

2000-01-01

The objective of this project is to develop a method to predict the potential reliability of software to be used in a digital system instrumentation and control system. The reliability prediction is to make use of existing measures of software reliability such as those described in IEEE Std 982 and 982.2. This prediction must be of sufficient accuracy to provide a value for uncertainty that could be used in a nuclear power plant probabilistic risk assessment (PRA). For the purposes of the project, reliability was defined to be the probability that the digital system will successfully perform its intended safety function (for the distribution of conditions under which it is expected to respond) upon demand with no unintended functions that might affect system safety. The ultimate objective is to use the identified measures to develop a method for predicting the potential quantitative reliability of a digital system. The reliability prediction models proposed in this report are conceptual in nature. That is, possible prediction techniques are proposed and trial models are built, but in order to become a useful tool for predicting reliability, the models must be tested, modified according to the results, and validated. Using methods outlined by this project, models could be constructed to develop reliability estimates for elements of software systems. This would require careful review and refinement of the models, development of model parameters from actual experience data or expert elicitation, and careful validation. By combining these reliability estimates (generated from the validated models for the constituent parts) in structural software models, the reliability of the software system could then be predicted. Modeling digital system reliability will also require that methods be developed for combining reliability estimates for hardware and software. System structural models must also be developed in order to predict system reliability based upon the reliability

Deterministic and probabilistic interval prediction for short-term wind power generation based on variational mode decomposition and machine learning methods

International Nuclear Information System (INIS)

Zhang, Yachao; Liu, Kaipei; Qin, Liang; An, Xueli

2016-01-01

Highlights: • Variational mode decomposition is adopted to process original wind power series. • A novel combined model based on machine learning methods is established. • An improved differential evolution algorithm is proposed for weight adjustment. • Probabilistic interval prediction is performed by quantile regression averaging. - Abstract: Due to the increasingly significant energy crisis nowadays, the exploitation and utilization of new clean energy gains more and more attention. As an important category of renewable energy, wind power generation has become the most rapidly growing renewable energy in China. However, the intermittency and volatility of wind power has restricted the large-scale integration of wind turbines into power systems. High-precision wind power forecasting is an effective measure to alleviate the negative influence of wind power generation on the power systems. In this paper, a novel combined model is proposed to improve the prediction performance for the short-term wind power forecasting. Variational mode decomposition is firstly adopted to handle the instability of the raw wind power series, and the subseries can be reconstructed by measuring sample entropy of the decomposed modes. Then the base models can be established for each subseries respectively. On this basis, the combined model is developed based on the optimal virtual prediction scheme, the weight matrix of which is dynamically adjusted by a self-adaptive multi-strategy differential evolution algorithm. Besides, a probabilistic interval prediction model based on quantile regression averaging and variational mode decomposition-based hybrid models is presented to quantify the potential risks of the wind power series. The simulation results indicate that: (1) the normalized mean absolute errors of the proposed combined model from one-step to three-step forecasting are 4.34%, 6.49% and 7.76%, respectively, which are much lower than those of the base models and the hybrid

Epileptic seizure prediction based on a bivariate spectral power methodology.

Science.gov (United States)

Bandarabadi, Mojtaba; Teixeira, Cesar A; Direito, Bruno; Dourado, Antonio

2012-01-01

The spectral power of 5 frequently considered frequency bands (Alpha, Beta, Gamma, Theta and Delta) for 6 EEG channels is computed and then all the possible pairwise combinations among the 30 features set, are used to create a 435 dimensional feature space. Two new feature selection methods are introduced to choose the best candidate features among those and to reduce the dimensionality of this feature space. The selected features are then fed to Support Vector Machines (SVMs) that classify the cerebral state in preictal and non-preictal classes. The outputs of the SVM are regularized using a method that accounts for the classification dynamics of the preictal class, also known as "Firing Power" method. The results obtained using our feature selection approaches are compared with the ones obtained using minimum Redundancy Maximum Relevance (mRMR) feature selection method. The results in a group of 12 patients of the EPILEPSIAE database, containing 46 seizures and 787 hours multichannel recording for out-of-sample data, indicate the efficiency of the bivariate approach as well as the two new feature selection methods. The best results presented sensitivity of 76.09% (35 of 46 seizures predicted) and a false prediction rate of 0.15(-1).

Real-time control strategy to maximize hybrid electric vehicle powertrain efficiency

International Nuclear Information System (INIS)

Shabbir, Wassif; Evangelou, Simos A.

2014-01-01

Highlights: • An off-line local control is proposed for real-time HEV energy management. • Powertrain efficiencies are studied to produce a unified objective function. • Penalty function is designed to ensure charge sustaining operation. • Implementation by storing optimal power share in a two-dimensional control map. • Proposed control improved fuel economy by up to 20% compared to conventional control. - Abstract: The proposed supervisory control system (SCS) uses a control map to maximize the powertrain efficiency of a hybrid electric vehicle (HEV) in real-time. The paper presents the methodology and structure of the control, including a novel, comprehensive and unified expression for the overall powertrain efficiency that considers the engine-generator set and the battery in depth as well as the power electronics. A control map is then produced with instructions for the optimal power share between the engine branch and battery branch of the vehicle such that the powertrain efficiency is maximized. This map is computed off-line and can thereafter be operated in real-time at very low computational cost. A charge sustaining factor is also developed and introduced to ensure the SCS operates the vehicle within desired SOC bounds. This SCS is then tested and benchmarked against two conventional control strategies in a high-fidelity vehicle model, representing a series HEV. Extensive simulation results are presented for repeated cycles of a diverse range of standard driving cycles, showing significant improvements in fuel economy (up to 20%) and less aggressive use of the battery

Using molecular classification to predict gains in maximal aerobic capacity following endurance exercise training in humans

DEFF Research Database (Denmark)

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...

Mixed maximal and explosive strength training in recreational endurance runners.

Science.gov (United States)

Taipale, Ritva S; Mikkola, Jussi; Salo, Tiina; Hokka, Laura; Vesterinen, Ville; Kraemer, William J; Nummela, Ari; Häkkinen, Keijo

2014-03-01

Supervised periodized mixed maximal and explosive strength training added to endurance training in recreational endurance runners was examined during an 8-week intervention preceded by an 8-week preparatory strength training period. Thirty-four subjects (21-45 years) were divided into experimental groups: men (M, n = 9), women (W, n = 9), and control groups: men (MC, n = 7), women (WC, n = 9). The experimental groups performed mixed maximal and explosive exercises, whereas control subjects performed circuit training with body weight. Endurance training included running at an intensity below lactate threshold. Strength, power, endurance performance characteristics, and hormones were monitored throughout the study. Significance was set at p ≤ 0.05. Increases were observed in both experimental groups that were more systematic than in the control groups in explosive strength (12 and 13% in men and women, respectively), muscle activation, maximal strength (6 and 13%), and peak running speed (14.9 ± 1.2 to 15.6 ± 1.2 and 12.9 ± 0.9 to 13.5 ± 0.8 km Ł h). The control groups showed significant improvements in maximal and explosive strength, but Speak increased only in MC. Submaximal running characteristics (blood lactate and heart rate) improved in all groups. Serum hormones fluctuated significantly in men (testosterone) and in women (thyroid stimulating hormone) but returned to baseline by the end of the study. Mixed strength training combined with endurance training may be more effective than circuit training in recreational endurance runners to benefit overall fitness that may be important for other adaptive processes and larger training loads associated with, e.g., marathon training.

Neural Network Ensemble Based Approach for 2D-Interval Prediction of Solar Photovoltaic Power

Directory of Open Access Journals (Sweden)

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.

Estimation of maximal oxygen uptake via submaximal exercise testing in sports, clinical, and home settings