Short-term wind power combined forecasting based on error forecast correction

International Nuclear Information System (INIS)

Liang, Zhengtang; Liang, Jun; Wang, Chengfu; Dong, Xiaoming; Miao, Xiaofeng

2016-01-01

Highlights: • The correlation relationships of short-term wind power forecast errors are studied. • The correlation analysis method of the multi-step forecast errors is proposed. • A strategy selecting the input variables for the error forecast models is proposed. • Several novel combined models based on error forecast correction are proposed. • The combined models have improved the short-term wind power forecasting accuracy. - Abstract: With the increasing contribution of wind power to electric power grids, accurate forecasting of short-term wind power has become particularly valuable for wind farm operators, utility operators and customers. The aim of this study is to investigate the interdependence structure of errors in short-term wind power forecasting that is crucial for building error forecast models with regression learning algorithms to correct predictions and improve final forecasting accuracy. In this paper, several novel short-term wind power combined forecasting models based on error forecast correction are proposed in the one-step ahead, continuous and discontinuous multi-step ahead forecasting modes. First, the correlation relationships of forecast errors of the autoregressive model, the persistence method and the support vector machine model in various forecasting modes have been investigated to determine whether the error forecast models can be established by regression learning algorithms. Second, according to the results of the correlation analysis, the range of input variables is defined and an efficient strategy for selecting the input variables for the error forecast models is proposed. Finally, several combined forecasting models are proposed, in which the error forecast models are based on support vector machine/extreme learning machine, and correct the short-term wind power forecast values. The data collected from a wind farm in Hebei Province, China, are selected as a case study to demonstrate the effectiveness of the proposed

Implementation of a Model Output Statistics based on meteorological variable screening for short‐term wind power forecast

DEFF Research Database (Denmark)

Ranaboldo, Matteo; Giebel, Gregor; Codina, Bernat

2013-01-01

A combination of physical and statistical treatments to post‐process numerical weather predictions (NWP) outputs is needed for successful short‐term wind power forecasts. One of the most promising and effective approaches for statistical treatment is the Model Output Statistics (MOS) technique....... The proposed MOS performed well in both wind farms, and its forecasts compare positively with an actual operative model in use at Risø DTU and other MOS types, showing minimum BIAS and improving NWP power forecast of around 15% in terms of root mean square error. Further improvements could be obtained...

Implementation of short-term prediction

Energy Technology Data Exchange (ETDEWEB)

Landberg, L; Joensen, A; Giebel, G [and others

1999-03-01

This paper will giver a general overview of the results from a EU JOULE funded project (`Implementing short-term prediction at utilities`, JOR3-CT95-0008). Reference will be given to specialised papers where applicable. The goal of the project was to implement wind farm power output prediction systems in operational environments at a number of utilities in Europe. Two models were developed, one by Risoe and one by the Technical University of Denmark (DTU). Both prediction models used HIRLAM predictions from the Danish Meteorological Institute (DMI). (au) EFP-94; EU-JOULE. 11 refs.

Short-Term Wind Speed Forecasting for Power System Operations

KAUST Repository

Zhu, Xinxin

2012-04-01

The emphasis on renewable energy and concerns about the environment have led to large-scale wind energy penetration worldwide. However, there are also significant challenges associated with the use of wind energy due to the intermittent and unstable nature of wind. High-quality short-term wind speed forecasting is critical to reliable and secure power system operations. This article begins with an overview of the current status of worldwide wind power developments and future trends. It then reviews some statistical short-term wind speed forecasting models, including traditional time series approaches and more advanced space-time statistical models. It also discusses the evaluation of forecast accuracy, in particular, the need for realistic loss functions. New challenges in wind speed forecasting regarding ramp events and offshore wind farms are also presented. © 2012 The Authors. International Statistical Review © 2012 International Statistical Institute.

Short-Term Planning of Hybrid Power System

Science.gov (United States)

Knežević, Goran; Baus, Zoran; Nikolovski, Srete

2016-07-01

In this paper short-term planning algorithm for hybrid power system consist of different types of cascade hydropower plants (run-of-the river, pumped storage, conventional), thermal power plants (coal-fired power plants, combined cycle gas-fired power plants) and wind farms is presented. The optimization process provides a joint bid of the hybrid system, and thus making the operation schedule of hydro and thermal power plants, the operation condition of pumped-storage hydropower plants with the aim of maximizing profits on day ahead market, according to expected hourly electricity prices, the expected local water inflow in certain hydropower plants, and the expected production of electrical energy from the wind farm, taking into account previously contracted bilateral agreement for electricity generation. Optimization process is formulated as hourly-discretized mixed integer linear optimization problem. Optimization model is applied on the case study in order to show general features of the developed model.

Grouping influences output interference in short-term memory: a mixture modeling study

Directory of Open Access Journals (Sweden)

Min-Suk eKang

2016-05-01

Full Text Available Output interference is a source of forgetting induced by recalling. We investigated how grouping influences output interference in short-term memory. In Experiment 1, the participants were asked to remember four colored items. Those items were grouped by temporal coincidence as well as spatial alignment: two items were presented in the first memory array and two were presented in the second, and the items in both arrays were either vertically or horizontally aligned as well. The participants then performed two recall tasks in sequence by selecting a color presented at a cued location from a color wheel. In the same-group condition, the participants reported both items from the same memory array; however, in the different-group condition, the participants reported one item from each memory array. We analyzed participant responses with a mixture model, which yielded two measures: guess rate and precision of recalled memories. The guess rate in the second recall was higher for the different-group condition than for the same-group condition; however, the memory precisions obtained for both conditions were similarly degraded in the second recall. In Experiment 2, we varied the probability of the same- and different-group conditions with a ratio of 3 to 7. We expected output interference to be higher in the same-group condition than in the different-group condition. This is because items of the other group are more likely to be probed in the second recall phase and, thus, protecting those items during the first recall phase leads to a better performance. Nevertheless, the same pattern of results was robustly reproduced, suggesting grouping shields the grouped items from output interference because of the secured accessibility. We discussed how grouping influences output interference.

Electricity generation and microbial community in response to short-term changes in stack connection of self-stacked submersible microbial fuel cell powered by glycerol

DEFF Research Database (Denmark)

Zhao, Nannan; Angelidaki, Irini; Zhang, Yifeng

2017-01-01

community. In this study, a self-stacked submersible microbial fuel cell (SSMFC) powered by glycerol was tested to elucidate this important issue. In series connection, the maximum voltage output reached to 1.15 V, while maximum current density was 5.73 mA in parallel. In both connections, the maximum power......Stack connection (i.e., in series or parallel) of microbial fuel cell (MFC) is an efficient way to boost the power output for practical application. However, there is little information available on short-term changes in stack connection and its effect on the electricity generation and microbial...... density increased with the initial glycerol concentration. However, the glycerol degradation was even faster in parallel connection. When the SSMFC was shifted from series to parallel connection, the reactor reached to a stable power output without any lag phase. Meanwhile, the anodic microbial community...

Short term Braking Capability during Power Interruptions for Integrated Matrix Converter-Motor Drives

DEFF Research Database (Denmark)

Klumpner, Christian; Blaabjerg, Frede

2002-01-01

attractive. Sinusoidal input currents and bi-directional power flow are other advantages of the matrix converter but it is less immune to power grid disturbances compared to a standard ASD. In hoisting applications, short-term braking capability during a power outage is needed until the mechanical brake...... engages or to perform more effective a combined braking.This paper proposes a new method to provide short-term braking capability during a power outage for matrix converters. A braking chopper is needed in the clamp circuit, which allows for a drastically reduction of the capacitor size. The power flow...

Language familiarity effects in short-term memory: the role of output delay and long-term knowledge.

Science.gov (United States)

Thorn, Annabel S C; Gathercole, Susan E; Frankish, Clive R

2002-10-01

Four experiments examined the origins of language familiarity effects in bilingual short-term recall. In Experiments 1A and 1B, bilingual adults were tested on serial recall and probed serial recall of words and nonwords in their first and second languages. A first-language advantage was obtained on both measures, indicating that the beneficial effects of language familiarity are not exclusively attributable to lesser output delay during overt recall. In Experiments 2A and 2B, the same group of bilinguals was tested on serial recall and serial recognition of word lists in both languages. Although a sizeable first-language advantage was obtained on the serial recall measure, recognition performance was comparable in the two languages. On the basis of these results it is suggested that language differences in bilingual immediate memory arise in large part as a consequence of the differential availability of language-specific long-term knowledge with which to support retrieval processes in serial recall.

Evaluating the quality of scenarios of short-term wind power generation

DEFF Research Database (Denmark)

Pinson, Pierre; Girard, R.

2012-01-01

Scenarios of short-term wind power generation are becoming increasingly popular as input to multi-stage decision-making problems e.g. multivariate stochastic optimization and stochastic programming. The quality of these scenarios is intuitively expected to substantially impact the benets from...... their use in decision-making. So far however, their verication is almost always focused on their marginal distributions for each individual lead time only, thus overlooking their temporal interdependence structure. The shortcomings of such an approach are discussed. Multivariate verication tools, as well...... as diagnostic approaches based on event-based verication are then presented. Their application to the evaluation of various sets of scenarios of short-term wind power generation demonstrates them as valuable discrimination tools....

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...

Short-Term Wind Power Interval Forecasting Based on an EEMD-RT-RVM Model

Directory of Open Access Journals (Sweden)

Haixiang Zang

2016-01-01

Full Text Available Accurate short-term wind power forecasting is important for improving the security and economic success of power grids. Existing wind power forecasting methods are mostly types of deterministic point forecasting. Deterministic point forecasting is vulnerable to forecasting errors and cannot effectively deal with the random nature of wind power. In order to solve the above problems, we propose a short-term wind power interval forecasting model based on ensemble empirical mode decomposition (EEMD, runs test (RT, and relevance vector machine (RVM. First, in order to reduce the complexity of data, the original wind power sequence is decomposed into a plurality of intrinsic mode function (IMF components and residual (RES component by using EEMD. Next, we use the RT method to reconstruct the components and obtain three new components characterized by the fine-to-coarse order. Finally, we obtain the overall forecasting results (with preestablished confidence levels by superimposing the forecasting results of each new component. Our results show that, compared with existing methods, our proposed short-term interval forecasting method has less forecasting errors, narrower interval widths, and larger interval coverage percentages. Ultimately, our forecasting model is more suitable for engineering applications and other forecasting methods for new energy.

Accurate Short-Term Power Forecasting of Wind Turbines: The Case of Jeju Island’s Wind Farm

OpenAIRE

BeomJun Park; Jin Hur

2017-01-01

Short-term wind power forecasting is a technique which tells system operators how much wind power can be expected at a specific time. Due to the increasing penetration of wind generating resources into the power grids, short-term wind power forecasting is becoming an important issue for grid integration analysis. The high reliability of wind power forecasting can contribute to the successful integration of wind generating resources into the power grids. To guarantee the reliability of forecas...

Analysing the Possible Ways for Short-Term Forcing Gas Turbine Engines in Auxiliary Power Unit

Directory of Open Access Journals (Sweden)

N. I. Trotskii

2016-01-01

Full Text Available Using a gas turbine energy unit as an example, the article discusses possible ways for forcing the short-term gas turbine engines (GTE. The introduction explains the need for forcing the air transport and marine GTE in specific driving conditions and offers the main methods. Then it analyzes the three main short-term forcing methods according to GTE power, namely: precompressor water injection, a short-term rise in temperature after the combustion chamber, and feeding an additional compressed air into combustion chamber from the reserve cylinders.The analysis of the water injection method to force a GTE presents the main provisions and calculation results of the cycle, as a function of engine power on the amount of water injected into compressor inlet. It is shown that with water injection into compressor inlet in an amount of 1% of the total airflow there is a 17% power increase in the compressor. It also lists the main implementation problems of this method and makes a comparison with the results of other studies on the water injection into compressor.Next, the article concerns the GTE short-term forcing method through the pre-turbine short-term increase in the gas temperature. The article presents the calculation results of the cycle as a function of the power and the fuel-flow rate on the gas temperature at the turbine inlet. It is shown that with increasing temperature by 80 degrees the engine power increases by 11.2% and requires 11% more fuel. In the analysis of this method arises an issue of thermal barrier coating on the blade surface. The article discusses the most common types of coatings and their main shortcomings. It lists the main challenges and some ways of their solving when using this method to implement the short-term forcing.The last method under consideration is GTE short-term forcing by feeding the compressed air into the combustion chamber from the additional reserve cylinders. It should be noted that this method is

Evaluating the quality of scenarios of short-term wind power generation

International Nuclear Information System (INIS)

Pinson, P.; Girard, R.

2012-01-01

Highlights: ► Presentation of the desirable properties of wind power generation scenarios. ► Description of various evaluation frameworks (univariate, multivariate, diagnostic). ► Highlighting of the properties of current approaches to scenario generation. ► Guidelines for future evaluation/benchmark exercises. -- Abstract: Scenarios of short-term wind power generation are becoming increasingly popular as input to multistage decision-making problems e.g. multivariate stochastic optimization and stochastic programming. The quality of these scenarios is intuitively expected to substantially impact the benefits from their use in decision-making. So far however, their verification is almost always focused on their marginal distributions for each individual lead time only, thus overlooking their temporal interdependence structure. The shortcomings of such an approach are discussed. Multivariate verification tools, as well as diagnostic approaches based on event-based verification are then presented. Their application to the evaluation of various sets of scenarios of short-term wind power generation demonstrates them as valuable discrimination tools.

Short term load forecasting using neuro-fuzzy networks

Energy Technology Data Exchange (ETDEWEB)

Hoffman, M.; Hassan, A. [South Dakota School of Mines and Technology, Rapid City, SD (United States); Martinez, D. [Black Hills Power and Light, Rapid City, SD (United States)

2005-07-01

Details of a neuro-fuzzy network-based short term load forecasting system for power utilities were presented. The fuzzy logic controller was used to fuzzify inputs representing historical temperature and load curves. The fuzzified inputs were then used to develop the fuzzy rules matrix. Output membership function values were determined by evaluating the fuzzified inputs with the fuzzy rules. Output membership function values were used as inputs for the neural network portion of the system. The training process used a back propagation gradient descent algorithm to adjust the weight values of the neural network in order to reduce the error between the neural network output and the desired output. The neural network was then used to predict future load values. Sample data were taken from a local power company's daily load curve to validate the system. A 10 per cent forecast error was introduced in the temperature values to determine the effect on load prediction. Results of the study suggest that the combined use of fuzzy logic and neural networks provide greater accuracy than studies where either approach is used alone. 6 refs., 6 figs.

Short Term Energy Storage for Grid Support in Wind Power Applications

DEFF Research Database (Denmark)

Stroe, Daniel Ioan; Stan, Ana-Irina; Diosi, Robert

2012-01-01

The penetration of wind power into the power system has been increasing in the recent years. Therefore, a lot of concerns related to the reliable operation of the power system have been addressed. An attractive solution to minimize the limitations faced by the wind power grid integration, and thus...... to increase the power system stability and the energy quality, is to integrate energy storage devices into wind power plants. This paper gives an overview of the state-of-the-art short-term energy storage devices and presents several applications which can be provided by the energy storage device - wind power...

Short-Term Solar Collector Power Forecasting

DEFF Research Database (Denmark)

Bacher, Peder; Madsen, Henrik; Perers, Bengt

2011-01-01

This paper describes a new approach to online forecasting of power output from solar thermal collectors. The method is suited for online forecasting in many applications and in this paper it is applied to predict hourly values of power from a standard single glazed large area flat plate collector...... enabling tracking of changes in the system and in the surrounding conditions, such as decreasing performance due to wear and dirt, and seasonal changes such as leaves on trees. This furthermore facilitates remote monitoring and check of the system....

Comparing the Effectiveness of a Short-Term Vertical Jump vs. Weightlifting Program on Athletic Power Development.

Science.gov (United States)

Teo, Shaun Y M; Newton, Michael J; Newton, Robert U; Dempsey, Alasdair R; Fairchild, Timothy J

2016-10-01

Teo, SYM, Newton, MJ, Newton, RU, Dempsey, AR, and Fairchild, TJ. Comparing the effectiveness of a short-term vertical jump vs. weightlifting program on athletic power development. J Strength Cond Res 30(10): 2741-2748, 2016-Efficient training of neuromuscular power and the translation of this power to sport-specific tasks is a key objective in the preparation of athletes involved in team-based sports. The purpose of this study was to compare changes in center of mass (COM) neuromuscular power and performance of sport-specific tasks after short-term (6-week) training adopting either Olympic-style weightlifting (WL) exercises or vertical jump (VJ) exercises. Twenty-six recreationally active men (18-30 years; height: 178.7 ± 8.3 cm; mass: 78.6 ± 12.2 kg) were randomly allocated to either a WL or VJ training group and performance during the countermovement jump (CMJ), squat jump (SJ), depth jump (DJ), 20-m sprint, and the 5-0-5 agility test-assessed pre and posttraining. Despite the WL group demonstrating larger increases in peak power output during the CMJ (WL group: 10% increase, d = 0.701; VJ group: 5.78% increase, d = 0.328) and SJ (WL group: 12.73% increase, d = 0.854; VJ group: 7.27% increase, d = 0.382), no significant between-group differences were observed in any outcome measure studied. There was a significant main effect of time observed for the 3 VJs (CMJ, SJ, and DJ), 0- to 5-m and 0- to 20-m sprint times, and the 5-0-5 agility test time, which were all shown to improve after the training (all main effects of time p sports, even in athletes with limited preseason training periods.

Short-Term Power Plant GHG Emissions Forecasting Model

International Nuclear Information System (INIS)

Vidovic, D.

2016-01-01

In 2010, the share of greenhouse gas (GHG) emissions from power generation in the total emissions at the global level was about 25 percent. From January 1st, 2013 Croatian facilities have been involved in the European Union Emissions Trading System (EU ETS). The share of the ETS sector in total GHG emissions in Croatia in 2012 was about 30 percent, where power plants and heat generation facilities contributed to almost 50 percent. Since 2013 power plants are obliged to purchase all emission allowances. The paper describes the short-term climate forecasting model of greenhouse gas emissions from power plants while covering the daily load diagram of the system. Forecasting is done on an hourly domain typically for one day, it is possible and more days ahead. Forecasting GHG emissions in this way would enable power plant operators to purchase additional or sell surplus allowances on the market at the time. Example that describes the operation of the above mentioned forecasting model is given at the end of the paper.(author).

Short term memory in echo state networks

OpenAIRE

Jaeger, H.

2001-01-01

The report investigates the short-term memory capacity of echo state recurrent neural networks. A quantitative measure MC of short-term memory capacity is introduced. The main result is that MC 5 N for networks with linear Output units and i.i.d. input, where N is network size. Conditions under which these maximal memory capacities are realized are described. Several theoretical and practical examples demonstrate how the short-term memory capacities of echo state networks can be exploited for...

Comparative Study on KNN and SVM Based Weather Classification Models for Day Ahead Short Term Solar PV Power Forecasting

Directory of Open Access Journals (Sweden)

Fei Wang

2017-12-01

Full Text Available Accurate solar photovoltaic (PV power forecasting is an essential tool for mitigating the negative effects caused by the uncertainty of PV output power in systems with high penetration levels of solar PV generation. Weather classification based modeling is an effective way to increase the accuracy of day-ahead short-term (DAST solar PV power forecasting because PV output power is strongly dependent on the specific weather conditions in a given time period. However, the accuracy of daily weather classification relies on both the applied classifiers and the training data. This paper aims to reveal how these two factors impact the classification performance and to delineate the relation between classification accuracy and sample dataset scale. Two commonly used classification methods, K-nearest neighbors (KNN and support vector machines (SVM are applied to classify the daily local weather types for DAST solar PV power forecasting using the operation data from a grid-connected PV plant in Hohhot, Inner Mongolia, China. We assessed the performance of SVM and KNN approaches, and then investigated the influences of sample scale, the number of categories, and the data distribution in different categories on the daily weather classification results. The simulation results illustrate that SVM performs well with small sample scale, while KNN is more sensitive to the length of the training dataset and can achieve higher accuracy than SVM with sufficient samples.

Short-term wind power forecasting: probabilistic and space-time aspects

DEFF Research Database (Denmark)

Tastu, Julija

work deals with the proposal and evaluation of new mathematical models and forecasting methods for short-term wind power forecasting, accounting for space-time dynamics based on geographically distributed information. Different forms of power predictions are considered, starting from traditional point...... into the corresponding models are analysed. As a final step, emphasis is placed on generating space-time trajectories: this calls for the prediction of joint multivariate predictive densities describing wind power generation at a number of distributed locations and for a number of successive lead times. In addition......Optimal integration of wind energy into power systems calls for high quality wind power predictions. State-of-the-art forecasting systems typically provide forecasts for every location individually, without taking into account information coming from the neighbouring territories. It is however...

An accident diagnosis algorithm using long short-term memory

Directory of Open Access Journals (Sweden)

Jaemin Yang

2018-05-01

Full Text Available Accident diagnosis is one of the complex tasks for nuclear power plant (NPP operators. In abnormal or emergency situations, the diagnostic activity of the NPP states is burdensome though necessary. Numerous computer-based methods and operator support systems have been suggested to address this problem. Among them, the recurrent neural network (RNN has performed well at analyzing time series data. This study proposes an algorithm for accident diagnosis using long short-term memory (LSTM, which is a kind of RNN, which improves the limitation for time reflection. The algorithm consists of preprocessing, the LSTM network, and postprocessing. In the LSTM-based algorithm, preprocessed input variables are calculated to output the accident diagnosis results. The outputs are also postprocessed using softmax to determine the ranking of accident diagnosis results with probabilities. This algorithm was trained using a compact nuclear simulator for several accidents: a loss of coolant accident, a steam generator tube rupture, and a main steam line break. The trained algorithm was also tested to demonstrate the feasibility of diagnosing NPP accidents. Keywords: Accident Diagnosis, Long Short-term Memory, Recurrent Neural Network, Softmax

A New Neural Network Approach to Short Term Load Forecasting of Electrical Power Systems

Directory of Open Access Journals (Sweden)

Farshid Keynia

2011-03-01

Full Text Available Short-term load forecast (STLF is an important operational function in both regulated power systems and deregulated open electricity markets. However, STLF is not easy to handle due to the nonlinear and random-like behaviors of system loads, weather conditions, and social and economic environment variations. Despite the research work performed in the area, more accurate and robust STLF methods are still needed due to the importance and complexity of STLF. In this paper, a new neural network approach for STLF is proposed. The proposed neural network has a novel learning algorithm based on a new modified harmony search technique. This learning algorithm can widely search the solution space in various directions, and it can also avoid the overfitting problem, trapping in local minima and dead bands. Based on this learning algorithm, the suggested neural network can efficiently extract the input/output mapping function of the forecast process leading to high STLF accuracy. The proposed approach is tested on two practical power systems and the results obtained are compared with the results of several other recently published STLF methods. These comparisons confirm the validity of the developed approach.

The “Weather Intelligence for Renewable Energies” Benchmarking Exercise on Short-Term Forecasting of Wind and Solar Power Generation

Directory of Open Access Journals (Sweden)

Simone Sperati

2015-09-01

Full Text Available A benchmarking exercise was organized within the framework of the European Action Weather Intelligence for Renewable Energies (“WIRE” with the purpose of evaluating the performance of state of the art models for short-term renewable energy forecasting. The exercise consisted in forecasting the power output of two wind farms and two photovoltaic power plants, in order to compare the merits of forecasts based on different modeling approaches and input data. It was thus possible to obtain a better knowledge of the state of the art in both wind and solar power forecasting, with an overview and comparison of the principal and the novel approaches that are used today in the field, and to assess the evolution of forecast performance with respect to previous benchmarking exercises. The outcome of this exercise consisted then in proposing new challenges in the renewable power forecasting field and identifying the main areas for improving accuracy in the future.

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.

Investigation of solar photovoltaic module power output by various models

International Nuclear Information System (INIS)

Jakhrani, A.Q.; Othman, A.K.; Rigit, A.R.H.; Baini, R.

2012-01-01

This paper aims to investigate the power output of a solar photovoltaic module by various models and to formulate a suitable model for predicting the performance of solar photovoltaic modules. The model was used to correct the configurations of solar photovoltaic systems for sustainable power supply. Different types of models namely the efficiency, power, fill factor and current-voltage characteristic curve models have been reviewed. It was found that the examined models predicted a 40% yield of the rated power in cloudy weather conditions and up to 80% in clear skies. The models performed well in terms of electrical efficiency in cloudy days if the influence of low irradiance were incorporated. Both analytical and numerical methods were employed in the formulation of improved model which gave +- 2% error when compared with the rated power output of solar photovoltaic module. The proposed model is more practical in terms of number of variables used and acceptable performance in humid atmospheres. Therefore, it could be useful for the estimation of power output of the solar photovoltaic systems in Sarawak region. (author)

From probabilistic forecasts to statistical scenarios of short-term wind power production

DEFF Research Database (Denmark)

Pinson, Pierre; Papaefthymiou, George; Klockl, Bernd

2009-01-01

on the development of the forecast uncertainty through forecast series. However, this additional information may be paramount for a large class of time-dependent and multistage decision-making problems, e.g. optimal operation of combined wind-storage systems or multiple-market trading with different gate closures......Short-term (up to 2-3 days ahead) probabilistic forecasts of wind power provide forecast users with highly valuable information on the uncertainty of expected wind generation. Whatever the type of these probabilistic forecasts, they are produced on a per horizon basis, and hence do not inform....... This issue is addressed here by describing a method that permits the generation of statistical scenarios of short-term wind generation that accounts for both the interdependence structure of prediction errors and the predictive distributions of wind power production. The method is based on the conversion...

Comparison of two new short-term wind-power forecasting systems

Energy Technology Data Exchange (ETDEWEB)

Ramirez-Rosado, Ignacio J. [Department of Electrical Engineering, University of Zaragoza, Zaragoza (Spain); Fernandez-Jimenez, L. Alfredo [Department of Electrical Engineering, University of La Rioja, Logrono (Spain); Monteiro, Claudio; Sousa, Joao; Bessa, Ricardo [FEUP, Fac. Engenharia Univ. Porto (Portugal)]|[INESC - Instituto de Engenharia de Sistemas e Computadores do Porto, Porto (Portugal)

2009-07-15

This paper presents a comparison of two new advanced statistical short-term wind-power forecasting systems developed by two independent research teams. The input variables used in both systems were the same: forecasted meteorological variable values obtained from a numerical weather prediction model; and electric power-generation registers from the SCADA system of the wind farm. Both systems are described in detail and the forecasting results compared, revealing great similarities, although the proposed structures of the two systems are different. The forecast horizon for both systems is 72 h, allowing the use of the forecasted values in electric market operations, as diary and intra-diary power generation bid offers, and in wind-farm maintenance planning. (author)

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)

Modelling and short-term forecasting of daily peak power demand in Victoria using two-dimensional wavelet based SDP models

International Nuclear Information System (INIS)

Truong, Nguyen-Vu; Wang, Liuping; Wong, Peter K.C.

2008-01-01

Power demand forecasting is of vital importance to the management and planning of power system operations which include generation, transmission, distribution, as well as system's security analysis and economic pricing processes. This paper concerns the modeling and short-term forecast of daily peak power demand in the state of Victoria, Australia. In this study, a two-dimensional wavelet based state dependent parameter (SDP) modelling approach is used to produce a compact mathematical model for this complex nonlinear dynamic system. In this approach, a nonlinear system is expressed by a set of linear regressive input and output terms (state variables) multiplied by the respective state dependent parameters that carry the nonlinearities in the form of 2-D wavelet series expansions. This model is identified based on historical data, descriptively representing the relationship and interaction between various components which affect the peak power demand of a certain day. The identified model has been used to forecast daily peak power demand in the state of Victoria, Australia in the time period from the 9th of August 2007 to the 24th of August 2007. With a MAPE (mean absolute prediction error) of 1.9%, it has clearly implied the effectiveness of the identified model. (author)

Multi-decadal Variability of the Wind Power Output

Science.gov (United States)

Kirchner Bossi, Nicolas; García-Herrera, Ricardo; Prieto, Luis; Trigo, Ricardo M.

2014-05-01

The knowledge of the long-term wind power variability is essential to provide a realistic outlook on the power output during the lifetime of a planned wind power project. In this work, the Power Output (Po) of a market wind turbine is simulated with a daily resolution for the period 1871-2009 at two different locations in Spain, one at the Central Iberian Plateau and another at the Gibraltar Strait Area. This is attained through a statistical downscaling of the daily wind conditions. It implements a Greedy Algorithm as classificator of a geostrophic-based wind predictor, which is derived by considering the SLP daily field from the 56 ensemble members of the longest homogeneous reanalysis available (20CR, 1871-2009). For calibration and validation purposes we use 10 years of wind observations (the predictand) at both sites. As a result, a series of 139 annual wind speed Probability Density Functions (PDF) are obtained, with a good performance in terms of wind speed uncertainty reduction (average daily wind speed MAE=1.48 m/s). The obtained centennial series allow to investigate the multi-decadal variability of wind power from different points of view. Significant periodicities around the 25-yr frequency band, as well as long-term linear trends are detected at both locations. In addition, a negative correlation is found between annual Po at both locations, evidencing the differences in the dynamical mechanisms ruling them (and possible complementary behavior). Furthermore, the impact that the three leading large-scale circulation patterns over Iberia (NAO, EA and SCAND) exert over wind power output is evaluated. Results show distinct (and non-stationary) couplings to these forcings depending on the geographical position and season or month. Moreover, significant non-stationary correlations are observed with the slow varying Atlantic Multidecadal Oscillation (AMO) index for both case studies. Finally, an empirical relationship is explored between the annual Po and the

European Short-term Electricity Market Designs under High Penetration of Wind Power

NARCIS (Netherlands)

Chaves Avila, J.P.

2014-01-01

The EU has ambitious policies for decarbonization of the electricity sector. Due to recent technological developments, wind power already represents a significant share of the generation mix in some European countries. As a result, short-term electricity markets and balancing arrangements must be

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.

Developing a Local Neurofuzzy Model for Short-Term Wind Power Forecasting

Directory of Open Access Journals (Sweden)

E. Faghihnia

2014-01-01

Full Text Available Large scale integration of wind generation capacity into power systems introduces operational challenges due to wind power uncertainty and variability. Therefore, accurate wind power forecast is important for reliable and economic operation of the power systems. Complexities and nonlinearities exhibited by wind power time series necessitate use of elaborative and sophisticated approaches for wind power forecasting. In this paper, a local neurofuzzy (LNF approach, trained by the polynomial model tree (POLYMOT learning algorithm, is proposed for short-term wind power forecasting. The LNF approach is constructed based on the contribution of local polynomial models which can efficiently model wind power generation. Data from Sotavento wind farm in Spain was used to validate the proposed LNF approach. Comparison between performance of the proposed approach and several recently published approaches illustrates capability of the LNF model for accurate wind power forecasting.

Estimation of the Maximum Output Power of Double-Clad Photonic Crystal Fiber Laser

International Nuclear Information System (INIS)

Chen Yue-E; Wang Yong; Qu Xi-Long

2012-01-01

Compared with traditional optical fiber lasers, double-clad photonic crystal fiber (PCF) lasers have larger surface-area-to-volume ratios. With an increase of output power, thermal effects may severely restrict output power and deteriorate beam quality of fiber lasers. We utilize the heat-conduction equations to estimate the maximum output power of a double-clad PCF laser under natural-convection, air-cooling, and water-cooling conditions in terms of a certain surface-volume heat ratio of the PCF. The thermal effects hence define an upper power limit of double-clad PCF lasers when scaling output power. (fundamental areas of phenomenology(including applications))

Short-Term Forecasting of Loads and Wind Power for Latvian Power System: Accuracy and Capacity of the Developed Tools

Directory of Open Access Journals (Sweden)

Radziukynas V.

2016-04-01

Full Text Available The paper analyses the performance results of the recently developed short-term forecasting suit for the Latvian power system. The system load and wind power are forecasted using ANN and ARIMA models, respectively, and the forecasting accuracy is evaluated in terms of errors, mean absolute errors and mean absolute percentage errors. The investigation of influence of additional input variables on load forecasting errors is performed. The interplay of hourly loads and wind power forecasting errors is also evaluated for the Latvian power system with historical loads (the year 2011 and planned wind power capacities (the year 2023.

Short-Term Forecasting of Loads and Wind Power for Latvian Power System: Accuracy and Capacity of the Developed Tools

Science.gov (United States)

Radziukynas, V.; Klementavičius, A.

2016-04-01

The paper analyses the performance results of the recently developed short-term forecasting suit for the Latvian power system. The system load and wind power are forecasted using ANN and ARIMA models, respectively, and the forecasting accuracy is evaluated in terms of errors, mean absolute errors and mean absolute percentage errors. The investigation of influence of additional input variables on load forecasting errors is performed. The interplay of hourly loads and wind power forecasting errors is also evaluated for the Latvian power system with historical loads (the year 2011) and planned wind power capacities (the year 2023).

Short-term load forecasting of power system

Science.gov (United States)

Xu, Xiaobin

2017-05-01

In order to ensure the scientific nature of optimization about power system, it is necessary to improve the load forecasting accuracy. Power system load forecasting is based on accurate statistical data and survey data, starting from the history and current situation of electricity consumption, with a scientific method to predict the future development trend of power load and change the law of science. Short-term load forecasting is the basis of power system operation and analysis, which is of great significance to unit combination, economic dispatch and safety check. Therefore, the load forecasting of the power system is explained in detail in this paper. First, we use the data from 2012 to 2014 to establish the partial least squares model to regression analysis the relationship between daily maximum load, daily minimum load, daily average load and each meteorological factor, and select the highest peak by observing the regression coefficient histogram Day maximum temperature, daily minimum temperature and daily average temperature as the meteorological factors to improve the accuracy of load forecasting indicators. Secondly, in the case of uncertain climate impact, we use the time series model to predict the load data for 2015, respectively, the 2009-2014 load data were sorted out, through the previous six years of the data to forecast the data for this time in 2015. The criterion for the accuracy of the prediction is the average of the standard deviations for the prediction results and average load for the previous six years. Finally, considering the climate effect, we use the BP neural network model to predict the data in 2015, and optimize the forecast results on the basis of the time series model.

A diode-pumped continuous-wave Nd:YAG laser with an average output power of 1 kW

International Nuclear Information System (INIS)

Lee, Sung Man; Cha, Byung Heon; Kim, Cheol Jung

2004-01-01

A diode-pumped Nd:YAG laser with an average output power of 1 kW is developed for industrial applications, such as metal cutting, precision welding, etc. To develop such a diode-pumped high power solid-state laser, a series of laser modules have been used in general with and without thermal birefringence compensation. For example, Akiyama et al. used three laser modules to obtain a output power of 5.4 kW CW.1 In the side-pumped Nd:YAG laser, which is a commonly used pump scheme to obtain high output power, the crystal rod has a short thermal focal length at a high input pump power, and the short thermal focal length in turn leads to beam distortion within a laser resonator. Therefore, to achieve a high output power with good stability, isotropic beam profile, and high optical efficiency, the detailed analysis of the resonator stability condition depending on both mirror distances and a crystal separation is essential

Short-Term Wind Power Forecasting Using the Enhanced Particle Swarm Optimization Based Hybrid Method

OpenAIRE

Wen-Yeau Chang

2013-01-01

High penetration of wind power in the electricity system provides many challenges to power system operators, mainly due to the unpredictability and variability of wind power generation. Although wind energy may not be dispatched, an accurate forecasting method of wind speed and power generation can help power system operators reduce the risk of an unreliable electricity supply. This paper proposes an enhanced particle swarm optimization (EPSO) based hybrid forecasting method for short-term wi...

A review on the young history of the wind power short-term prediction

DEFF Research Database (Denmark)

Costa, A.; Crespo, A.; Navarro, J.

2008-01-01

This paper makes a brief review on 30 years of history of the wind power short-term prediction, since the first ideas and sketches on the theme to the actual state of the art oil models and tools, giving emphasis to the most significant proposals and developments. The two principal lines of thought...... on short-term prediction (mathematical and physical) are indistinctly treated here and comparisons between models and tools are avoided, mainly because, on the one hand, a standard for a measure of performance is still not adopted and, on the other hand, it is very important that the data are exactly...

Wind Power Forecasting Based on Echo State Networks and Long Short-Term Memory

Directory of Open Access Journals (Sweden)

Erick López

2018-02-01

Full Text Available Wind power generation has presented an important development around the world. However, its integration into electrical systems presents numerous challenges due to the variable nature of the wind. Therefore, to maintain an economical and reliable electricity supply, it is necessary to accurately predict wind generation. The Wind Power Prediction Tool (WPPT has been proposed to solve this task using the power curve associated with a wind farm. Recurrent Neural Networks (RNNs model complex non-linear relationships without requiring explicit mathematical expressions that relate the variables involved. In particular, two types of RNN, Long Short-Term Memory (LSTM and Echo State Network (ESN, have shown good results in time series forecasting. In this work, we present an LSTM+ESN architecture that combines the characteristics of both networks. An architecture similar to an ESN is proposed, but using LSTM blocks as units in the hidden layer. The training process of this network has two key stages: (i the hidden layer is trained with a descending gradient method online using one epoch; (ii the output layer is adjusted with a regularized regression. In particular, the case is proposed where Step (i is used as a target for the input signal, in order to extract characteristics automatically as the autoencoder approach; and in the second stage (ii, a quantile regression is used in order to obtain a robust estimate of the expected target. The experimental results show that LSTM+ESN using the autoencoder and quantile regression outperforms the WPPT model in all global metrics used.

Implications of Wide-Area Geographic Diversity for Short- Term Variability of Solar Power

Energy Technology Data Exchange (ETDEWEB)

Mills, Andrew; Wiser, Ryan

2010-08-23

Worldwide interest in the deployment of photovoltaic generation (PV) is rapidly increasing. Operating experience with large PV plants, however, demonstrates that large, rapid changes in the output of PV plants are possible. Early studies of PV grid impacts suggested that short-term variability could be a potential limiting factor in deploying PV. Many of these early studies, however, lacked high-quality data from multiple sites to assess the costs and impacts of increasing PV penetration. As is well known for wind, accounting for the potential for geographic diversity can significantly reduce the magnitude of extreme changes in aggregated PV output, the resources required to accommodate that variability, and the potential costs of managing variability. We use measured 1-min solar insolation for 23 time-synchronized sites in the Southern Great Plains network of the Atmospheric Radiation Measurement program and wind speed data from 10 sites in the same network to characterize the variability of PV with different degrees of geographic diversity and to compare the variability of PV to the variability of similarly sited wind. The relative aggregate variability of PV plants sited in a dense 10 x 10 array with 20 km spacing is six times less than the variability of a single site for variability on time scales less than 15-min. We find in our analysis of wind and PV plants similarly sited in a 5 x 5 grid with 50 km spacing that the variability of PV is only slightly more than the variability of wind on time scales of 5-15 min. Over shorter and longer time scales the level of variability is nearly identical. Finally, we use a simple approximation method to estimate the cost of carrying additional reserves to manage sub-hourly variability. We conclude that the costs of managing the short-term variability of PV are dramatically reduced by geographic diversity and are not substantially different from the costs for managing the short-term variability of similarly sited wind in

Effects of massive wind power integration on short-term water resource management in central Chile - a grid-wide study

Science.gov (United States)

Haas, J.; Olivares, M. A.; Palma, R.

2013-12-01

In central Chile, water from reservoirs and streams is mainly used for irrigation and power generation. Hydropower reservoirs operation is particularly challenging because: i) decisions at each plant impact the entire power system, and ii) the existence of large storage capacity implies inter-temporal ties. An Independent System Operator (ISO) decides the grid-wide optimal allocation of water for power generation, under irrigation-related constraints. To account for the long-term opportunity cost of water, a future cost function is determined and used in the short term planning. As population growth and green policies demand increasing levels of renewable energy in power systems, deployment of wind farms and solar plants is rising quickly. However, their power output is highly fluctuating on short time scales, affecting the operation of power plants, particularly those fast responding units as hydropower reservoirs. This study addresses these indirect consequences of massive introduction of green energy sources on reservoir operations. Short-term reservoir operation, under different wind penetration scenarios, is simulated using a replica of Chile's ISO's scheduling optimization tools. Furthermore, an ongoing study is exploring the potential to augment the capacity the existing hydro-power plants to better cope with the balancing needs due to a higher wind power share in the system. As reservoir releases determine to a great extent flows at downstream locations, hourly time series of turbined flows for 24-hour periods were computed for selected combinations between new wind farms and increased capacity of existing hydropower plants. These time series are compiled into subdaily hydrologic alteration (SDHA) indexes (Zimmerman et al, 2010). The resulting sample of indexes is then analyzed using duration curves. Results show a clear increase in the SDHA for every reservoir of the system as more fluctuating renewables are integrated into the system. High

Aerobic capacity and peak power output of elite quadriplegic games players

Science.gov (United States)

Goosey‐Tolfrey, V; Castle, P; Webborn, N

2006-01-01

Background Participation in wheelchair sports such as tennis and rugby enables people with quadriplegia to compete both individually and as a team at the highest level. Both sports are dominated by frequent, intermittent, short term power demands superimposed on a background of aerobic activity. Objective To gain physiological profiles of highly trained British quadriplegic athletes, and to examine the relation between aerobic and sprint capacity. Methods Eight male quadriplegic athletes performed an arm crank exercise using an ergometer fitted with a Schoberer Rad Messtechnik (SRM) powermeter. The sprint test consisted of three maximum‐effort sprints of five seconds duration against a resistance of 2%, 3%, and 4% of body mass. The highest power output obtained was recorded (PPO). Peak oxygen consumption (V̇o2peak), peak heart rate (HRpeak), and maximal power output (POaer) were determined. Results Mean POaer was 67.7 (16.2) W, mean V̇o2peak was 0.96 (0.17) litres/min, and HRpeak was 134 (19) beats/min for the group. There was high variability among subjects. Peak power over the five second sprint for the group was 220 (62) W. There was a significant correlation between V̇o2peak (litres/min) and POaer (W) (r  =  0.74, p<0.05). Conclusions These British quadriplegic athletes have relatively high aerobic fitness when compared with the available literature. Moreover, the anaerobic capacity of these athletes appeared to be relatively high compared with paraplegic participants. PMID:16611721

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.

Generation of statistical scenarios of short-term wind power production

DEFF Research Database (Denmark)

Pinson, Pierre; Papaefthymiou, George; Klockl, Bernd

2007-01-01

Short-term (up to 2-3 days ahead) probabilistic forecasts of wind power provide forecast users with a paramount information on the uncertainty of expected wind generation. Whatever the type of these probabilistic forecasts, they are produced on a per horizon basis, and hence do not inform...... on the development of the forecast uncertainty through forecast series. This issue is addressed here by describing a method that permits to generate statistical scenarios of wind generation that accounts for the interdependence structure of prediction errors, in plus of respecting predictive distributions of wind...

Real-Time Wavelet-Based Coordinated Control of Hybrid Energy Storage Systems for Denoising and Flattening Wind Power Output

Directory of Open Access Journals (Sweden)

Tran Thai Trung

2014-10-01

Full Text Available Since the penetration level of wind energy is continuously increasing, the negative impact caused by the fluctuation of wind power output needs to be carefully managed. This paper proposes a novel real-time coordinated control algorithm based on a wavelet transform to mitigate both short-term and long-term fluctuations by using a hybrid energy storage system (HESS. The short-term fluctuation is eliminated by using an electric double-layer capacitor (EDLC, while the wind-HESS system output is kept constant during each 10-min period by a Ni-MH battery (NB. State-of-charge (SOC control strategies for both EDLC and NB are proposed to maintain the SOC level of storage within safe operating limits. A ramp rate limitation (RRL requirement is also considered in the proposed algorithm. The effectiveness of the proposed algorithm has been tested by using real time simulation. The simulation model of the wind-HESS system is developed in the real-time digital simulator (RTDS/RSCAD environment. The proposed algorithm is also implemented as a user defined model of the RSCAD. The simulation results demonstrate that the HESS with the proposed control algorithm can indeed assist in dealing with the variation of wind power generation. Moreover, the proposed method shows better performance in smoothing out the fluctuation and managing the SOC of battery and EDLC than the simple moving average (SMA based method.

Short-term marginal costs in French agriculture

OpenAIRE

Latruffe, Laure; LETORT, Elodie

2011-01-01

The paper investigates short-term marginal costs in French agriculture for field cropping, beef cattle, and dairy farms during the period 1995-2006. The multi-input multi-output Symmetric Generalised MacFadden cost function is used, with three variable inputs (crop-specific, animal-specific, energy costs), four outputs and three quasi-fixed inputs. Results indicate that marginal costs are on average lower for crop farms than for livestock samples. However, for crop farms, Common Agricultural ...

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)

Short-Term Wind Speed Forecasting Using Decomposition-Based Neural Networks Combining Abnormal Detection Method

Directory of Open Access Journals (Sweden)

Xuejun Chen

2014-01-01

Full Text Available As one of the most promising renewable resources in electricity generation, wind energy is acknowledged for its significant environmental contributions and economic competitiveness. Because wind fluctuates with strong variation, it is quite difficult to describe the characteristics of wind or to estimate the power output that will be injected into the grid. In particular, short-term wind speed forecasting, an essential support for the regulatory actions and short-term load dispatching planning during the operation of wind farms, is currently regarded as one of the most difficult problems to be solved. This paper contributes to short-term wind speed forecasting by developing two three-stage hybrid approaches; both are combinations of the five-three-Hanning (53H weighted average smoothing method, ensemble empirical mode decomposition (EEMD algorithm, and nonlinear autoregressive (NAR neural networks. The chosen datasets are ten-minute wind speed observations, including twelve samples, and our simulation indicates that the proposed methods perform much better than the traditional ones when addressing short-term wind speed forecasting problems.

EDM - A model for optimising the short-term power operation of a complex hydroelectric network

International Nuclear Information System (INIS)

Tremblay, M.; Guillaud, C.

1996-01-01

In order to optimize the short-term power operation of a complex hydroelectric network, a new model called EDM was added to PROSPER, a water management analysis system developed by SNC-Lavalin. PROSPER is now divided into three parts: an optimization model (DDDP), a simulation model (ESOLIN), and an economic dispatch model (EDM) for the short-term operation. The operation of the KSEB hydroelectric system (located in southern India) with PROSPER was described. The long-term analysis with monthly time steps is assisted by the DDDP, and the daily analysis with hourly or half-hourly time steps is performed with the EDM model. 3 figs

Short circuit protection for a power distribution system

Science.gov (United States)

Owen, J. R., III

1969-01-01

Sensing circuit detects when the output from a matrix is present and when it should be present. The circuit provides short circuit protection for a power distribution system where the selection of the driven load is accomplished by digital logic.

Short-term wind power forecasting in Portugal by neural networks and wavelet transform

Energy Technology Data Exchange (ETDEWEB)

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); 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)

2011-04-15

This paper proposes artificial neural networks in combination with wavelet transform for short-term wind power forecasting in Portugal. The increased integration of wind power into the electric grid, as nowadays occurs in Portugal, poses new challenges due to its intermittency and volatility. Hence, good forecasting tools play a key role in tackling these challenges. Results from a real-world case study are presented. A comparison is carried out, taking into account the results obtained with other approaches. Finally, conclusions are duly drawn. (author)

An analysis of the performance benefits of short-term energy storage in wind-diesel hybrid power systems

International Nuclear Information System (INIS)

Shirazi, M.; Drouilhet, S.

1996-01-01

A variety of prototype high penetration wind-diesel hybrid power systems have been implemented with different amounts of energy storage. They range from systems with no energy storage to those with many hours worth of energy storage. There has been little consensus among wind-diesel system developers as to the appropriate role and amount of energy storage in such systems. Some researchers advocate providing only enough storage capacity to supply power during the time it takes the diesel genset to start. Others install large battery banks to allow the diesel(s) to operate at full load and/or to time-shift the availability of wind-generated electricity to match the demand. Prior studies indicate that for high penetration wind-diesel systems, short-term energy storage provides the largest operational and economic benefit. This study uses data collected in Deering, Alaska, a small diesel-powered village, and the hybrid systems modeling software Hybrid2 to determine the optimum amount of short-term storage for a particular high penetration wind-diesel system. These findings were then generalized by determining how wind penetration, turbulence intensity, and load variability affect the value of short term energy storage as measured in terms of fuel savings, total diesel run time, and the number of diesel starts

Improving short-term forecasting during ramp events by means of Regime-Switching Artificial Neural Networks

Science.gov (United States)

Gallego, C.; Costa, A.; Cuerva, A.

2010-09-01

Since nowadays wind energy can't be neither scheduled nor large-scale storaged, wind power forecasting has been useful to minimize the impact of wind fluctuations. In particular, short-term forecasting (characterised by prediction horizons from minutes to a few days) is currently required by energy producers (in a daily electricity market context) and the TSO's (in order to keep the stability/balance of an electrical system). Within the short-term background, time-series based models (i.e., statistical models) have shown a better performance than NWP models for horizons up to few hours. These models try to learn and replicate the dynamic shown by the time series of a certain variable. When considering the power output of wind farms, ramp events are usually observed, being characterized by a large positive gradient in the time series (ramp-up) or negative (ramp-down) during relatively short time periods (few hours). Ramp events may be motivated by many different causes, involving generally several spatial scales, since the large scale (fronts, low pressure systems) up to the local scale (wind turbine shut-down due to high wind speed, yaw misalignment due to fast changes of wind direction). Hence, the output power may show unexpected dynamics during ramp events depending on the underlying processes; consequently, traditional statistical models considering only one dynamic for the hole power time series may be inappropriate. This work proposes a Regime Switching (RS) model based on Artificial Neural Nets (ANN). The RS-ANN model gathers as many ANN's as different dynamics considered (called regimes); a certain ANN is selected so as to predict the output power, depending on the current regime. The current regime is on-line updated based on a gradient criteria, regarding the past two values of the output power. 3 Regimes are established, concerning ramp events: ramp-up, ramp-down and no-ramp regime. In order to assess the skillness of the proposed RS-ANN model, a single

An Improved Mathematical Model for Computing Power Output of Solar Photovoltaic Modules

Directory of Open Access Journals (Sweden)

Abdul Qayoom Jakhrani

2014-01-01

Full Text Available It is difficult to determine the input parameters values for equivalent circuit models of photovoltaic modules through analytical methods. Thus, the previous researchers preferred to use numerical methods. Since, the numerical methods are time consuming and need long term time series data which is not available in most developing countries, an improved mathematical model was formulated by combination of analytical and numerical methods to overcome the limitations of existing methods. The values of required model input parameters were computed analytically. The expression for output current of photovoltaic module was determined explicitly by Lambert W function and voltage was determined numerically by Newton-Raphson method. Moreover, the algebraic equations were derived for the shape factor which involves the ideality factor and the series resistance of a single diode photovoltaic module power output model. The formulated model results were validated with rated power output of a photovoltaic module provided by manufacturers using local meteorological data, which gave ±2% error. It was found that the proposed model is more practical in terms of precise estimations of photovoltaic module power output for any required location and number of variables used.

Estimation of monthly wind power outputs of WECS with limited record period using artificial neural networks

International Nuclear Information System (INIS)

Tu, Yi-Long; Chang, Tsang-Jung; Chen, Cheng-Lung; Chang, Yu-Jung

2012-01-01

Highlights: ► ANN with short record training data is used to estimate power outputs in an existing station. ► The suitable numbers/parameters of input neurons for ANN are presented. ► Current wind speeds and previous power outputs are the most important input neurons. ► Choosing suitable input parameters is more important than choosing multiple parameters. - Abstract: For the brand new wind power industry, online recordings of wind power data are always in a relatively limited period. The aim of the study is to investigate the suitable numbers/parameters of input neurons for artificial neural networks under a short record of measured data. Measured wind speeds, wind directions (yaw angles) and power outputs with 10-min resolution at an existing wind power station, located at Jhongtun, Taiwan, are integrated to form three types of input neuron numbers and sixteen cases of input neurons. The first-10 days of each month in 2006 are used for data training to simulate the following 20-day power generation of the same month. The performance of various input neuron cases is evaluated. The simulated results show that using the first 10-day training data with adequate input neurons can estimate energy outputs well except the weak wind regime (May, June, and July). Among the input neuron parameters used, current wind speeds V(t) and previous power outputs P(t − 1) are the most important. Individually using one of them into input neurons can only provide satisfactory estimation. However, simultaneously using these two parameters into input neurons can give the best estimation. Thus, choosing suitable input parameters is more important than choosing multiple parameters.

Human power output during repeated sprint cycle exercise: the influence of thermal stress

NARCIS (Netherlands)

Ball, D.; Burrows, C.; Sargeant, A.J.

1999-01-01

Thermal stress is known to impair endurance capacity during moderate prolonged exercise. However, there is relatively little available information concerning the effects of thermal stress on the performance of high-intensity short-duration exercise. The present experiment examined human power output

The state-of-the-art in short-term prediction of wind power. A literature overview

Energy Technology Data Exchange (ETDEWEB)

Giebel, G.; Brownsword, R.; Kariniotakis, G.

2003-08-01

Based on an appropriate questionnaire (WP1.1) and some other works already in progress, this report details the state-of-the-art in short term prediction of wind power, mostly summarising nearly all existing literature on the topic. (au)

Benefits for wind energy in electricity markets from using short term wind power prediction tools: a simulation study

International Nuclear Information System (INIS)

Usaola, J.; Ravelo, O.; Gonzalez, G.; Soto, F.; Davila, M.C.; Diaz-Guerra, B.

2004-01-01

One of the characteristics of wind energy, from the grid point of view, is its non-dispatchability, i.e. generation cannot be ordered, hence integration in electrical networks may be difficult. Short-term wind power prediction-tools could make this integration easier, either by their use by the grid System Operator, or by promoting the participation of wind farms in the electricity markets and using prediction tools to make their bids in the market. In this paper, the importance of a short-term wind power-prediction tool for the participation of wind energy systems in electricity markets is studied. Simulations, according to the current Spanish market rules, have been performed to the production of different wind farms, with different degrees of accuracy in the prediction tool. It may be concluded that income from participation in electricity markets is increased using a short-term wind power prediction-tool of average accuracy. This both marginally increases income and also reduces the impact on system operation with the improved forecasts. (author)

Short-Term Solar Forecasting Performance of Popular Machine Learning Algorithms: Preprint

Energy Technology Data Exchange (ETDEWEB)

Florita, Anthony R [National Renewable Energy Laboratory (NREL), Golden, CO (United States); Elgindy, Tarek [National Renewable Energy Laboratory (NREL), Golden, CO (United States); Hodge, Brian S [National Renewable Energy Laboratory (NREL), Golden, CO (United States); Dobbs, Alex [National Renewable Energy Laboratory (NREL), Golden, CO (United States)

2017-10-03

A framework for assessing the performance of short-term solar forecasting is presented in conjunction with a range of numerical results using global horizontal irradiation (GHI) from the open-source Surface Radiation Budget (SURFRAD) data network. A suite of popular machine learning algorithms is compared according to a set of statistically distinct metrics and benchmarked against the persistence-of-cloudiness forecast and a cloud motion forecast. Results show significant improvement compared to the benchmarks with trade-offs among the machine learning algorithms depending on the desired error metric. Training inputs include time series observations of GHI for a history of years, historical weather and atmospheric measurements, and corresponding date and time stamps such that training sensitivities might be inferred. Prediction outputs are GHI forecasts for 1, 2, 3, and 4 hours ahead of the issue time, and they are made for every month of the year for 7 locations. Photovoltaic power and energy outputs can then be made using the solar forecasts to better understand power system impacts.

The Effects of Music on High-intensity Short-term Exercise in Well Trained Athletes.

Science.gov (United States)

Jarraya, Mohamed; Chtourou, Hamdi; Aloui, Asma; Hammouda, Omar; Chamari, Karim; Chaouachi, Anis; Souissi, Nizar

2012-12-01

The purpose of this investigation was to assess the effects of listening to music during warm-up on short-term supramaximal performances during the 30-s Wingate test in highly trained athletes. Twelve young male athletes (20.6±1.8 yrs, 177±4.4 cm and 72.3±5.3 kg) underwent two Wingate tests in separate sessions with a recovery period of 48 h in-between, either after a 10 min of warm-up with (MWU) or without (NMWU) music. High tempo music (>120 to 140bpm) was selected for the study. Heart rate (HR) and rate of perceived exertion (RPE) were recorded after the warm-up (for HR = average of warm-up) and immediately after the Wingate test. HR, RPE and the fatigue index during the Wingate test are not affected by the incorporation of music during warm-up. However, power output (P(peak) and P(mean)) was significantly higher after MWU than NMWU (Peffect of music during warm-up on short-term supramaximal performances. As it's a legal method and an additional aid, music may be used during warm-up before performing activities requiring powerful lower limbs' muscles contractions during short-term supramaximal exercises.

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.

Very-short-term wind power probabilistic forecasts by sparse vector autoregression

DEFF Research Database (Denmark)

Dowell, Jethro; Pinson, Pierre

2016-01-01

A spatio-temporal method for producing very-shortterm parametric probabilistic wind power forecasts at a large number of locations is presented. Smart grids containing tens, or hundreds, of wind generators require skilled very-short-term forecasts to operate effectively, and spatial information...... is highly desirable. In addition, probabilistic forecasts are widely regarded as necessary for optimal power system management as they quantify the uncertainty associated with point forecasts. Here we work within a parametric framework based on the logit-normal distribution and forecast its parameters....... The location parameter for multiple wind farms is modelled as a vector-valued spatiotemporal process, and the scale parameter is tracked by modified exponential smoothing. A state-of-the-art technique for fitting sparse vector autoregressive models is employed to model the location parameter and demonstrates...

An Artificial Neural Network Based Short-term Dynamic Prediction of Algae Bloom

Directory of Open Access Journals (Sweden)

Yao Junyang

2014-06-01

Full Text Available This paper proposes a method of short-term prediction of algae bloom based on artificial neural network. Firstly, principal component analysis is applied to water environmental factors in algae bloom raceway ponds to get main factors that influence the formation of algae blooms. Then, a model of short-term dynamic prediction based on neural network is built with the current chlorophyll_a values as input and the chlorophyll_a values in the next moment as output to realize short-term dynamic prediction of algae bloom. Simulation results show that the model can realize short-term prediction of algae bloom effectively.

Short time ahead wind power production forecast

International Nuclear Information System (INIS)

Sapronova, Alla; Meissner, Catherine; Mana, Matteo

2016-01-01

An accurate prediction of wind power output is crucial for efficient coordination of cooperative energy production from different sources. Long-time ahead prediction (from 6 to 24 hours) of wind power for onshore parks can be achieved by using a coupled model that would bridge the mesoscale weather prediction data and computational fluid dynamics. When a forecast for shorter time horizon (less than one hour ahead) is anticipated, an accuracy of a predictive model that utilizes hourly weather data is decreasing. That is because the higher frequency fluctuations of the wind speed are lost when data is averaged over an hour. Since the wind speed can vary up to 50% in magnitude over a period of 5 minutes, the higher frequency variations of wind speed and direction have to be taken into account for an accurate short-term ahead energy production forecast. In this work a new model for wind power production forecast 5- to 30-minutes ahead is presented. The model is based on machine learning techniques and categorization approach and using the historical park production time series and hourly numerical weather forecast. (paper)

Short time ahead wind power production forecast

Science.gov (United States)

Sapronova, Alla; Meissner, Catherine; Mana, Matteo

2016-09-01

An accurate prediction of wind power output is crucial for efficient coordination of cooperative energy production from different sources. Long-time ahead prediction (from 6 to 24 hours) of wind power for onshore parks can be achieved by using a coupled model that would bridge the mesoscale weather prediction data and computational fluid dynamics. When a forecast for shorter time horizon (less than one hour ahead) is anticipated, an accuracy of a predictive model that utilizes hourly weather data is decreasing. That is because the higher frequency fluctuations of the wind speed are lost when data is averaged over an hour. Since the wind speed can vary up to 50% in magnitude over a period of 5 minutes, the higher frequency variations of wind speed and direction have to be taken into account for an accurate short-term ahead energy production forecast. In this work a new model for wind power production forecast 5- to 30-minutes ahead is presented. The model is based on machine learning techniques and categorization approach and using the historical park production time series and hourly numerical weather forecast.

Economic evaluation of short-term wind power forecast in ERCOT. Preliminary results

Energy Technology Data Exchange (ETDEWEB)

Orwig, Kirsten D.; Hodge, Bri-Mathias; Brinkman, Greg; Ela, Erik; Milligan, Michael [National Renewable Energy Laboratory (NREL), Golden, CO (United States); Banunarayanan, Venkat; Nasir, Saleh [ICF International, Fairfax, VA (United States); Freedman, Jeff [AWS Truepower, Albany, NY (United States)

2012-07-01

A number of wind energy integration studies have investigated the monetary value of using day-ahead wind power forecasts for grid operation decisions. Historically, these studies have shown that large cost savings could be gained by grid operators implementing the forecasts in their system operations. To date, none of these studies have investigated the value of shorter term (0- to 6-h ahead) wind power forecasts. In 2010, the Department of Energy and the National Oceanic and Atmospheric Administration partnered to form the Wind Forecasting Improvement Project (WFIP) to fund improvements in short-term wind forecasts and determine the economic value of these improvements to grid operators. In this work, we discuss the preliminary results of the economic benefit analysis portion of the WFIP for the Electric Reliability Council of Texas. The improvements seen in the wind forecasts are examined and the economic results of a production cost model simulation are analyzed. (orig.)

Simulation of Distributed PV Power Output in Oahu Hawaii

Energy Technology Data Exchange (ETDEWEB)

Lave, Matthew Samuel [Sandia National Lab. (SNL-CA), Livermore, CA (United States)

2016-08-01

Distributed solar photovoltaic (PV) power generation in Oahu has grown rapidly since 2008. For applications such as determining the value of energy storage, it is important to have PV power output timeseries. Since these timeseries of not typically measured, here we produce simulated distributed PV power output for Oahu. Simulated power output is based on (a) satellite-derived solar irradiance, (b) PV permit data by neighborhood, and (c) population data by census block. Permit and population data was used to model locations of distributed PV, and irradiance data was then used to simulate power output. PV power output simulations are presented by sub-neighborhood polygons, neighborhoods, and for the whole island of Oahu. Summary plots of annual PV energy and a sample week timeseries of power output are shown, and a the files containing the entire timeseries are described.

Output power analyses for the thermodynamic cycles of thermal power plants

International Nuclear Information System (INIS)

Sun Chen; Cheng Xue-Tao; Liang Xin-Gang

2014-01-01

Thermal power plant is one of the important thermodynamic devices, which is very common in all kinds of power generation systems. In this paper, we use a new concept, entransy loss, as well as exergy destruction, to analyze the single reheating Rankine cycle unit and the single stage steam extraction regenerative Rankine cycle unit in power plants. This is the first time that the concept of entransy loss is applied to the analysis of the power plant Rankine cycles with reheating and steam extraction regeneration. In order to obtain the maximum output power, the operating conditions under variant vapor mass flow rates are optimized numerically, as well as the combustion temperatures and the off-design flow rates of the flue gas. The relationship between the output power and the exergy destruction rate and that between the output power and the entransy loss rate are discussed. It is found that both the minimum exergy destruction rate and the maximum entransy loss rate lead to the maximum output power when the combustion temperature and heat capacity flow rate of the flue gas are prescribed. Unlike the minimum exergy destruction rate, the maximum entransy loss rate is related to the maximum output power when the highest temperature and heat capacity flow rate of the flue gas are not prescribed. (general)

Intra-Minute Cloud Passing Forecasting Based on a Low Cost IoT Sensor—A Solution for Smoothing the Output Power of PV Power Plants

Science.gov (United States)

Sukič, Primož; Štumberger, Gorazd

2017-01-01

Clouds moving at a high speed in front of the Sun can cause step changes in the output power of photovoltaic (PV) power plants, which can lead to voltage fluctuations and stability problems in the connected electricity networks. These effects can be reduced effectively by proper short-term cloud passing forecasting and suitable PV power plant output power control. This paper proposes a low-cost Internet of Things (IoT)-based solution for intra-minute cloud passing forecasting. The hardware consists of a Raspberry PI Model B 3 with a WiFi connection and an OmniVision OV5647 sensor with a mounted wide-angle lens, a circular polarizing (CPL) filter and a natural density (ND) filter. The completely new algorithm for cloud passing forecasting uses the green and blue colors in the photo to determine the position of the Sun, to recognize the clouds, and to predict their movement. The image processing is performed in several stages, considering selectively only a small part of the photo relevant to the movement of the clouds in the vicinity of the Sun in the next minute. The proposed algorithm is compact, fast and suitable for implementation on low cost processors with low computation power. The speed of the cloud parts closest to the Sun is used to predict when the clouds will cover the Sun. WiFi communication is used to transmit this data to the PV power plant control system in order to decrease the output power slowly and smoothly. PMID:28505078

On the interplay between short and long term memory in the power-law cross-correlations setting

Czech Academy of Sciences Publication Activity Database

Krištoufek, Ladislav

2015-01-01

Roč. 421, č. 1 (2015), s. 218-222 ISSN 0378-4371 R&D Projects: GA ČR(CZ) GP14-11402P Institutional support: RVO:67985556 Keywords : Power-law cross-correlations * Long term memory * Short term memory Subject RIV: AH - Economics Impact factor: 1.785, year: 2015 http://library.utia.cas.cz/separaty/2015/E/kristoufek-0452316.pdf

Wavelet decomposition and neuro-fuzzy hybrid system applied to short-term wind power

Energy Technology Data Exchange (ETDEWEB)

Fernandez-Jimenez, L.A.; Mendoza-Villena, M. [La Rioja Univ., Logrono (Spain). Dept. of Electrical Engineering; Ramirez-Rosado, I.J.; Abebe, B. [Zaragoza Univ., Zaragoza (Spain). Dept. of Electrical Engineering

2010-03-09

Wind energy has become increasingly popular as a renewable energy source. However, the integration of wind farms in the electrical power systems presents several problems, including the chaotic fluctuation of wind flow which results in highly varied power generation from a wind farm. An accurate forecast of wind power generation has important consequences in the economic operation of the integrated power system. This paper presented a new statistical short-term wind power forecasting model based on wavelet decomposition and neuro-fuzzy systems optimized with a genetic algorithm. The paper discussed wavelet decomposition; the proposed wind power forecasting model; and computer results. The original time series, the mean electric power generated in a wind farm, was decomposing into wavelet coefficients that were utilized as inputs for the forecasting model. The forecasting results obtained with the final models were compared to those obtained with traditional forecasting models showing a better performance for all the forecasting horizons. 13 refs., 1 tab., 4 figs.

Short-term economics of virtual power plants

International Nuclear Information System (INIS)

Kok, J.K.

2009-08-01

The Virtual Power Plant (VPP) has gained an increasing interest over the last few years. A VPP is a flexible representation of a portfolio of Distributed Energy Resources (DER: distributed generation, demand response and electricity storage). One of the key activities of a VPP is the delivery of (near-)real-time balancing services. In order to operate such a (near-)real-time coordination activity optimally, the VPP needs to maintain a dynamic merit-order list of all DER participating in the VPP. In order to make optimal decisions based on this list, the merit order needs to be based on the true marginal cost (or marginal benefit in case of demand response) of the individual DER units. The marginal electricity costs of most types of DER are highly dependent on local context and, hence, change over time. From analysis of the short-term bid strategies of various DER units, the existence of a bid strategy spectrum becomes clear. On one end of the spectrum, bidding strategies are based straightforwardly on true marginal cost or benefit. Further along the spectrum, optimal bidding strategies become less dependent on marginal cost levels and more on the price dynamics in the (VPP) market context. These results are relevant for VPP operations both from business and technical perspectives.

Fuzzy approach for short term load forecasting

Energy Technology Data Exchange (ETDEWEB)

Chenthur Pandian, S.; Duraiswamy, K.; Kanagaraj, N. [Electrical and Electronics Engg., K.S. Rangasamy College of Technology, Tiruchengode 637209, Tamil Nadu (India); Christober Asir Rajan, C. [Department of Electrical and Electronics Engineering, Pondicherry Engineering College, Pondicherry (India)

2006-04-15

The main objective of short term load forecasting (STLF) is to provide load predictions for generation scheduling, economic load dispatch and security assessment at any time. The STLF is needed to supply necessary information for the system management of day-to-day operations and unit commitment. In this paper, the 'time' and 'temperature' of the day are taken as inputs for the fuzzy logic controller and the 'forecasted load' is the output. The input variable 'time' has been divided into eight triangular membership functions. The membership functions are Mid Night, Dawn, Morning, Fore Noon, After Noon, Evening, Dusk and Night. Another input variable 'temperature' has been divided into four triangular membership functions. They are Below Normal, Normal, Above Normal and High. The 'forecasted load' as output has been divided into eight triangular membership functions. They are Very Low, Low, Sub Normal, Moderate Normal, Normal, Above Normal, High and Very High. Case studies have been carried out for the Neyveli Thermal Power Station Unit-II (NTPS-II) in India. The fuzzy forecasted load values are compared with the conventional forecasted values. The forecasted load closely matches the actual one within +/-3%. (author)

Effect of material constants on power output in piezoelectric vibration-based generators.

Science.gov (United States)

Takeda, Hiroaki; Mihara, Kensuke; Yoshimura, Tomohiro; Hoshina, Takuya; Tsurumi, Takaaki

2011-09-01

A possible power output estimation based on material constants in piezoelectric vibration-based generators is proposed. A modified equivalent circuit model of the generator was built and was validated by the measurement results in the generator fabricated using potassium sodium niobate-based and lead zirconate titanate (PZT) ceramics. Subsequently, generators with the same structure using other PZT-based and bismuth-layered structure ferroelectrics ceramics were fabricated and tested. The power outputs of these generators were expressed as a linear functions of the term composed of electromechanical coupling coefficients k(sys)(2) and mechanical quality factors Q*(m) of the generator. The relationship between device constants (k(sys)(2) and Q*(m)) and material constants (k(31)(2) and Q(m)) was clarified. Estimation of the power output using material constants is demonstrated and the appropriate piezoelectric material for the generator is suggested.

Short-term Power Load Forecasting Based on Balanced KNN

Science.gov (United States)

Lv, Xianlong; Cheng, Xingong; YanShuang; Tang, Yan-mei

2018-03-01

To improve the accuracy of load forecasting, a short-term load forecasting model based on balanced KNN algorithm is proposed; According to the load characteristics, the historical data of massive power load are divided into scenes by the K-means algorithm; In view of unbalanced load scenes, the balanced KNN algorithm is proposed to classify the scene accurately; The local weighted linear regression algorithm is used to fitting and predict the load; Adopting the Apache Hadoop programming framework of cloud computing, the proposed algorithm model is parallelized and improved to enhance its ability of dealing with massive and high-dimension data. The analysis of the household electricity consumption data for a residential district is done by 23-nodes cloud computing cluster, and experimental results show that the load forecasting accuracy and execution time by the proposed model are the better than those of traditional forecasting algorithm.

Stirling engine with hydraulic power output for powering artificial hearts

International Nuclear Information System (INIS)

Johnston, R.P.; Noble, J.E.; Emigh, S.G.; White, M.A.; Griffith, W.R.; Perrone, R.E.

1975-01-01

The DWDL heart power source combines the high efficiency of Stirling engines with the reliability, efficiency, and flexibility of hydraulic power transfer and control to ensure long system life and physiological effectiveness. Extended life testing has already been achieved with an engine module; animal in-vivo tests with an assist heart have consistently demonstrated required performance by biological synchronization and effective ventricle relief. The present System 5 can reliably meet near-term thousand-hour animal in-vivo test goals as far as the durability and efficacy of the power source are concerned. Carefully planned development of System 6 has produced major reductions in size and required input power. Research engine tests have provided the basis for achieving performance goals and the approach for further improvement is well established. The near term goal is 33 W heat input with 16 W input projected for normal physical activity. The goal of reduction of engine module volume to 0.9 liter has been achieved. Demonstrated reliability of 292 d for the engine and 35 d for the full system, as well as effectiveness of the artificial heart power source in short-term in-vivo tests indicate that life-limiting problems are now blood pump reliability and the machine-animal interface

915 MHz microwave ablation with high output power in in vivo porcine spleens

International Nuclear Information System (INIS)

Gao Yongyan; Wang Yang; Duan Yaqi; Li Chunling; Sun Yuanyuan; Zhang Dakun; Lu Tong; Liang Ping

2010-01-01

Objective: The purpose of this study was to evaluate the efficacy of 915 MHz microwave (MW) ablation with high output power in in vivo porcine spleens. Materials and methods: MW ablations were performed in 9 porcine spleens with an internally cooled 915 MHz antenna. Thermocouples were placed at 5, 10, 15, 20 mm away from the antenna to measure temperatures in real-time during MW emission. The energy was applied for 10 min at high output power of 60 W, 70 W or 80 W. Gross specimens were sectioned and measured to determine ablation size. Representative areas were examined by light microscopy and electron microscopy. Coagulation sizes and temperatures were compared among the three power groups. Results: Hematoxylin-eosin staining showed irreversible necrosis in the splenic coagulation area after MW ablation. As the power was increased, long-axis diameter enlarged significantly (p .05). The coagulation size of long-axis and short-axis diameter with 80 W in vivo spleen ablation was 6.43 ± 0.52 and 4.95 ± 0.30 cm, respectively. With the increase of output power, maximum temperatures at 5, 10, 15, 20 mm from the antenna were increased accordingly (p o C respectively. Conclusion: With internally cooled antenna and high output power, 915 MHz MW ablation in the spleen could produce irreversible tissue necrosis of clinical significance. MW ablation may be used as a promising minimally invasive method for the treatment of splenic diseases.

Short-term optimal wind power generation capacity in liberalized electricity markets

International Nuclear Information System (INIS)

Olsina, Fernando; Roescher, Mark; Larisson, Carlos; Garces, Francisco

2007-01-01

Mainly because of environmental concerns and fuel price uncertainties, considerable amounts of wind-based generation capacity are being added to some deregulated power systems. The rapid wind development registered in some countries has essentially been driven by strong subsidizing programs. Since wind investments are commonly isolated from market signals, installed wind capacity can be higher than optimal, leading to distortions of the power prices with a consequent loss of social welfare. In this work, the influence of wind generation on power prices in the framework of a liberalized electricity market has been assessed by means of stochastic simulation techniques. The developed methodology allows investigating the maximal wind capacity that would be profitably deployed if wind investments were subject to market conditions only. For this purpose, stochastic variables determining power prices are accurately modeled. A test system resembling the size and characteristics of the German power system has been selected for this study. The expected value of the optimal, short-term wind capacity is evaluated for a considerable number of random realizations of power prices. The impact of dispersing the wind capacity over statistical independent wind sites has also been evaluated. The simulation results reveal that fuel prices, installation and financing costs of wind investments are very influential parameters on the maximal wind capacity that might be accommodated in a market-based manner

Power profiles and short-term visual performance of soft contact lenses.

Science.gov (United States)

Papas, Eric; Dahms, Anne; Carnt, Nicole; Tahhan, Nina; Ehrmann, Klaus

2009-04-01

To investigate the manner in which contemporary soft contact lenses differ in the distribution of optical power within their optic zones and establish if these variations affect the vision of wearers or the prescribing procedure for back vertex power (BVP). By using a Visionix VC 2001 contact lens power analyzer, power profiles were measured across the optic zones of the following contemporary contact lenses ACUVUE 2, ACUVUE ADVANCE, O2OPTIX, NIGHT & DAY and PureVision. Single BVP measures were obtained using a Nikon projection lensometer. Visual performance was assessed in 28 masked subjects who wore each lens type in random order. Measurements taken were high and low contrast visual acuity in normal illumination (250 Cd/m), high contrast acuity in reduced illumination (5 Cd/m), subjective visual quality using a numerical rating scale, and visual satisfaction rating using a Likert scale. Marked differences in the distribution of optical power across the optic zone were evident among the lens types. No significant differences were found for any of the visual performance variables (p > 0.05, analysis of variance with repeated measures and Friedman test). Variations in power profile between contemporary soft lens types exist but do not, in general, result in measurable visual performance differences in the short term, nor do they substantially influence the BVP required for optimal correction.

Short term economic emission power scheduling of hydrothermal energy systems using improved water cycle algorithm

International Nuclear Information System (INIS)

Haroon, S.S.; Malik, T.N.

2017-01-01

Due to the increasing environmental concerns, the demand of clean and green energy and concern of atmospheric pollution is increasing. Hence, the power utilities are forced to limit their emissions within the prescribed limits. Therefore, the minimization of fuel cost as well as exhaust gas emissions is becoming an important and challenging task in the short-term scheduling of hydro-thermal energy systems. This paper proposes a novel algorithm known as WCA-ER (Water Cycle Algorithm with Evaporation Rate) to inspect the short term EEPSHES (Economic Emission Power Scheduling of Hydrothermal Energy Systems). WCA has its ancestries from the natural hydrologic cycle i.e. the raining process forms streams and these streams start flowing towards the rivers which finally flow towards the sea. The worth of WCA-ER has been tested on the standard economic emission power scheduling of hydrothermal energy test system consisting of four hydropower and three thermal plants. The problem has been investigated for the three case studies (i) ECS (Economic Cost Scheduling), (ii) ES (Economic Emission Scheduling) and (iii) ECES (Economic Cost and Emission Scheduling). The results obtained show that WCA-ER is superior to many other methods in the literature in bringing lower fuel cost and emissions. (author)

Implementing a short-term loyalty program : case: Bosch Lawn & Garden and the Ventum short-term loyalty program

OpenAIRE

Logvinova, Veronika

2015-01-01

In 2015, one of the Bosch Home and Garden divisions, Bosch Lawn and Garden, has made a strategic decision to adopt a points-based short-term loyalty program called Ventum LG in the German supermarkets and petrol stations. It was decided that the base of this program will be completed Ventum PT short-term loyalty program which was managed by another division, Bosch Power Tools, and proved to be successful. This thesis aims to evaluate the worthiness of the Ventum LG loyalty program for Bosch L...

Short-Term and Working Memory Impairments in Early-Implanted, Long-Term Cochlear Implant Users Are Independent of Audibility and Speech Production.

Science.gov (United States)

AuBuchon, Angela M; Pisoni, David B; Kronenberger, William G

2015-01-01

To determine whether early-implanted, long-term cochlear implant (CI) users display delays in verbal short-term and working memory capacity when processes related to audibility and speech production are eliminated. Twenty-three long-term CI users and 23 normal-hearing controls each completed forward and backward digit span tasks under testing conditions that differed in presentation modality (auditory or visual) and response output (spoken recall or manual pointing). Normal-hearing controls reproduced more lists of digits than the CI users, even when the test items were presented visually and the responses were made manually via touchscreen response. Short-term and working memory delays observed in CI users are not due to greater demands from peripheral sensory processes such as audibility or from overt speech-motor planning and response output organization. Instead, CI users are less efficient at encoding and maintaining phonological representations in verbal short-term memory using phonological and linguistic strategies during memory tasks.

Ultra-Short-Term Wind-Power Forecasting Based on the Weighted Random Forest Optimized by the Niche Immune Lion Algorithm

Directory of Open Access Journals (Sweden)

Dongxiao Niu

2018-04-01

Full Text Available The continuous increase in energy consumption has made the potential of wind-power generation tremendous. However, the obvious intermittency and randomness of wind speed results in the fluctuation of the output power in a wind farm, seriously affecting the power quality. Therefore, the accurate prediction of wind power in advance can improve the ability of wind-power integration and enhance the reliability of the power system. In this paper, a model of wavelet decomposition (WD and weighted random forest (WRF optimized by the niche immune lion algorithm (NILA-WRF is presented for ultra-short-term wind power prediction. Firstly, the original serials of wind speed and power are decomposed into several sub-serials by WD because the original serials have no obvious day characteristics. Then, the model parameters are set and the model trained with the sub-serials of wind speed and wind power decomposed. Finally, the WD-NILA-WRF model is used to predict the wind power of the relative sub-serials and the result is reconstructed to obtain the final prediction result. The WD-NILA-WRF model combines the advantage of each single model, which uses WD for signal de-noising, and uses the niche immune lion algorithm (NILA to improve the model’s optimization efficiency. In this paper, two empirical analyses are carried out to prove the accuracy of the model, and the experimental results verify the proposed model’s validity and superiority compared with the back propagation neural network (BP neural network, support vector machine (SVM, RF and NILA-RF, indicating that the proposed method is superior in cases influenced by noise and unstable factors, and possesses an excellent generalization ability and robustness.

Variable Power, Short Microwave Pulses Generation using a CW Magnetron

Directory of Open Access Journals (Sweden)

CIUPA, R.

2011-05-01

Full Text Available Fine control of microwave power radiation in medical and scientific applications is a challenging task. Since a commercial Continuous Wave (CW magnetron is the most inexpensive microwave device available today on the market, it becomes the best candidate for a microwave power generator used in medical diathermy and hyperthermia treatments or high efficiency chemical reactions using microwave reactors as well. This article presents a new method for driving a CW magnetron with short pulses, using a modified commercial Zero Voltage Switching (ZVS inverter, software driven by a custom embedded system. The microwave power generator designed with this method can be programmed for output microwave pulses down to 1% of the magnetron's power and allows microwave low frequency pulse modulation in the range of human brain electrical activity, intended for medical applications. Microwave output power continuous control is also possible with the magnetron running in the oscillating area, using a dual frequency Pulse Width Modulation (PWM, where the low frequency PWM pulse is modulating a higher resonant frequency required by the ZVS inverter's transformer. The method presented allows a continuous control of both power and energy (duty-cycle at the inverter's output.

Intelligent and robust prediction of short term wind power using genetic programming based ensemble of neural networks

International Nuclear Information System (INIS)

Zameer, Aneela; Arshad, Junaid; Khan, Asifullah; Raja, Muhammad Asif Zahoor

2017-01-01

Highlights: • Genetic programming based ensemble of neural networks is employed for short term wind power prediction. • Proposed predictor shows resilience against abrupt changes in weather. • Genetic programming evolves nonlinear mapping between meteorological measures and wind-power. • Proposed approach gives mathematical expressions of wind power to its independent variables. • Proposed model shows relatively accurate and steady wind-power prediction performance. - Abstract: The inherent instability of wind power production leads to critical problems for smooth power generation from wind turbines, which then requires an accurate forecast of wind power. In this study, an effective short term wind power prediction methodology is presented, which uses an intelligent ensemble regressor that comprises Artificial Neural Networks and Genetic Programming. In contrast to existing series based combination of wind power predictors, whereby the error or variation in the leading predictor is propagated down the stream to the next predictors, the proposed intelligent ensemble predictor avoids this shortcoming by introducing Genetical Programming based semi-stochastic combination of neural networks. It is observed that the decision of the individual base regressors may vary due to the frequent and inherent fluctuations in the atmospheric conditions and thus meteorological properties. The novelty of the reported work lies in creating ensemble to generate an intelligent, collective and robust decision space and thereby avoiding large errors due to the sensitivity of the individual wind predictors. The proposed ensemble based regressor, Genetic Programming based ensemble of Artificial Neural Networks, has been implemented and tested on data taken from five different wind farms located in Europe. Obtained numerical results of the proposed model in terms of various error measures are compared with the recent artificial intelligence based strategies to demonstrate the

A review on the young history of the wind power short-term prediction

Energy Technology Data Exchange (ETDEWEB)

Costa, Alexandre; Navarro, Jorge [Wind Energy, Division of Renewable Energies, Department of Energy, CIEMAT, Av. Complutense, 22, Ed. 42, 28044 Madrid (Spain); Crespo, Antonio [Laboratorio de Mecanica de Fluidos, Departmento de Ingenieria Energetica y Fluidomecanica, ETSII, Universidad Politecnica de Madrid, C/Jose Gutierrez Abascal, 2-28006 Madrid (Spain); Lizcano, Gil [Oxford University Centre for the Environment, University of Oxford, South Parks Road, Oxford OX1 3QY (United Kingdom); Madsen, Henrik [Informatics and Mathematical Modelling - IMM, Technical University of Denmark, Richard Petersens Plads, Building 321, Office 019, 2800 Kgs. Lyngby (Denmark); Feitosa, Everaldo [Brazilian Wind Energy Centre - CBEE, Centro de Tecnologia e Geociencias, UFPE-50.740-530 Recife, PE (Brazil)

2008-08-15

This paper makes a brief review on 30 years of history of the wind power short-term prediction, since the first ideas and sketches on the theme to the actual state of the art on models and tools, giving emphasis to the most significant proposals and developments. The two principal lines of thought on short-term prediction (mathematical and physical) are indistinctly treated here and comparisons between models and tools are avoided, mainly because, on the one hand, a standard for a measure of performance is still not adopted and, on the other hand, it is very important that the data are exactly the same in order to compare two models (this fact makes it almost impossible to carry out a quantitative comparison between a huge number of models and methods). In place of a quantitative description, a qualitative approach is preferred for this review, remarking the contribution (and innovative aspect) of each model. On the basis of the review, some topics for future research are pointed out. (author)

An adaptive short-term prediction scheme for wind energy storage management

International Nuclear Information System (INIS)

Blonbou, Ruddy; Monjoly, Stephanie; Dorville, Jean-Francois

2011-01-01

Research highlights: → We develop a real time algorithm for grid-connected wind energy storage management. → The method aims to guarantee, with ±5% error margin, the power sent to the grid. → Dynamic scheduling of energy storage is based on short-term energy prediction. → Accurate predictions reduce the need in storage capacity. -- Abstract: Efficient forecasting scheme that includes some information on the likelihood of the forecast and based on a better knowledge of the wind variations characteristics along with their influence on power output variation is of key importance for the optimal integration of wind energy in island's power system. In the Guadeloupean archipelago (French West-Indies), with a total wind power capacity of 25 MW; wind energy can represent up to 5% of the instantaneous electricity production. At this level, wind energy contribution can be equivalent to the current network primary control reserve, which causes balancing difficult. The share of wind energy is due to grow even further since the objective is set to reach 118 MW by 2020. It is an absolute evidence for the network operator that due to security concerns of the electrical grid, the share of wind generation should not increase unless solutions are found to solve the prediction problem. The University of French West-Indies and Guyana has developed a short-term wind energy prediction scheme that uses artificial neural networks and adaptive learning procedures based on Bayesian approach and Gaussian approximation. This paper reports the results of the evaluation of the proposed approach; the improvement with respect to the simple persistent prediction model was globally good. A discussion on how such a tool combined with energy storage capacity could help to smooth the wind power variation and improve the wind energy penetration rate into island utility network is also proposed.

LOAD THAT MAXIMIZES POWER OUTPUT IN COUNTERMOVEMENT JUMP

Directory of Open Access Journals (Sweden)

Pedro Jimenez-Reyes

2016-02-01

Full Text Available ABSTRACT Introduction: One of the main problems faced by strength and conditioning coaches is the issue of how to objectively quantify and monitor the actual training load undertaken by athletes in order to maximize performance. It is well known that performance of explosive sports activities is largely determined by mechanical power. Objective: This study analysed the height at which maximal power output is generated and the corresponding load with which is achieved in a group of male-trained track and field athletes in the test of countermovement jump (CMJ with extra loads (CMJEL. Methods: Fifty national level male athletes in sprinting and jumping performed a CMJ test with increasing loads up to a height of 16 cm. The relative load that maximized the mechanical power output (Pmax was determined using a force platform and lineal encoder synchronization and estimating the power by peak power, average power and flight time in CMJ. Results: The load at which the power output no longer existed was at a height of 19.9 ± 2.35, referring to a 99.1 ± 1% of the maximum power output. The load that maximizes power output in all cases has been the load with which an athlete jump a height of approximately 20 cm. Conclusion: These results highlight the importance of considering the height achieved in CMJ with extra load instead of power because maximum power is always attained with the same height. We advise for the preferential use of the height achieved in CMJEL test, since it seems to be a valid indicative of an individual's actual neuromuscular potential providing a valid information for coaches and trainers when assessing the performance status of our athletes and to quantify and monitor training loads, measuring only the height of the jump in the exercise of CMJEL.

Short-term regulation of hydro powerplants. Studies on the environmental effects

International Nuclear Information System (INIS)

Sinisalmi, T.; Riihimaeki, J.; Vehanen, T.; Yrjaenae, T.

1997-01-01

The publication is a final report on a project studying effects of short-term regulation of hydro power plants. The project consists of two parts: (1) examining and developing methods for evaluation, (2) applying methods in a case study at the Oulujoki River. The economic value of short-term regulation was studied with a model consisting of an optimization model and a river simulation model. Constraints on water level or discharge variations could be given to the power plants and their economical influence could be studied. Effects on shoreline recreation use due to water level fluctuation were studied with a model where various effects are made commensurable and expressed in monetary terms. A literature survey and field experiments were used to study the methods for assessing effects of short-term regulation on river habitats. The state and development needs of fish stocks and fisheries in large regulated rivers were studied and an environmental classification was made. Remedial measures for the short-term regulated rivers were studied with a literature survey and enquiries. A comprehensive picture of the various effects of short-term regulation was gained in the case study in Oulujoki River (110 km long, 7 power plants). Harmful effects can be reduced with the given recommendations of remedial measures on environment and the usage of the hydro power plants. (orig.) 52 refs

Short-term regulation of hydro powerplants. Studies on the environmental effects

Energy Technology Data Exchange (ETDEWEB)

Sinisalmi, T. [ed.; Forsius, J.; Muotka, J.; Soimakallio, H. [Imatran Voima Oy, Vantaa (Finland); Riihimaeki, J. [VTT, Espoo (Finland); Vehanen, T. [Finnish Game and Fisheries Research Inst. (Finland); Yrjaenae, T. [North Ostrobothnia Regional Environmental Centre, Oulu (Finland)

1997-12-31

The publication is a final report on a project studying effects of short-term regulation of hydro power plants. The project consists of two parts: (1) examining and developing methods for evaluation, (2) applying methods in a case study at the Oulujoki River. The economic value of short-term regulation was studied with a model consisting of an optimization model and a river simulation model. Constraints on water level or discharge variations could be given to the power plants and their economical influence could be studied. Effects on shoreline recreation use due to water level fluctuation were studied with a model where various effects are made commensurable and expressed in monetary terms. A literature survey and field experiments were used to study the methods for assessing effects of short-term regulation on river habitats. The state and development needs of fish stocks and fisheries in large regulated rivers were studied and an environmental classification was made. Remedial measures for the short-term regulated rivers were studied with a literature survey and enquiries. A comprehensive picture of the various effects of short-term regulation was gained in the case study in Oulujoki River (110 km long, 7 power plants). Harmful effects can be reduced with the given recommendations of remedial measures on environment and the usage of the hydro power plants. (orig.) 52 refs.

A fast network solution by the decoupled procedure during short-term dynamic processes in power systems

Energy Technology Data Exchange (ETDEWEB)

Popovic, D P; Stefanovic, M D [Nikola Tesla Inst., Belgrade (YU). Power System Dept.

1990-01-01

A simple, fast and reliable decoupled procedure for solving the network problems during short-term dynamic processes in power systems is presented. It is based on the Newton-Raphson method applied to the power balance equations, which include the effects of generator saliency and non-impedance loads, with further modifications resulting from the physical properties of the phenomena under study. The good convergence characteristics of the developed procedure are demonstrated, and a comparison is made with the traditional method based on the current equation and the triangularized admittance matrix, using the example of stability analysis of the Yugoslav power grid. (author).

Short-Term Wind Power Forecasting Using the Enhanced Particle Swarm Optimization Based Hybrid Method

Directory of Open Access Journals (Sweden)

Wen-Yeau Chang

2013-09-01

Full Text Available High penetration of wind power in the electricity system provides many challenges to power system operators, mainly due to the unpredictability and variability of wind power generation. Although wind energy may not be dispatched, an accurate forecasting method of wind speed and power generation can help power system operators reduce the risk of an unreliable electricity supply. This paper proposes an enhanced particle swarm optimization (EPSO based hybrid forecasting method for short-term wind power forecasting. The hybrid forecasting method combines the persistence method, the back propagation neural network, and the radial basis function (RBF neural network. The EPSO algorithm is employed to optimize the weight coefficients in the hybrid forecasting method. To demonstrate the effectiveness of the proposed method, the method is tested on the practical information of wind power generation of a wind energy conversion system (WECS installed on the Taichung coast of Taiwan. Comparisons of forecasting performance are made with the individual forecasting methods. Good agreements between the realistic values and forecasting values are obtained; the test results show the proposed forecasting method is accurate and reliable.

Measuring nuclear power plant output by neutrino detection

International Nuclear Information System (INIS)

Korovkin, V.A.; Kodanev, S.A.; Panashchenko, N.S.; Sokolov, D.A.; Solov'yanov, O.M.; Tverdovskii, N.D.; Yarichin, A.D.; Ketov, S.N.; Kopeikin, V.I.; Machulin, I.N.; Mikaelyan, L.A.; Sinev, V.V.

1989-01-01

Neutrino emission from a reactor is inseparably linked with the fission process of heavy nuclei: each fission contributes a specific amount to the overall power output and gives rise to neutrinos which are emitted by the fission fragments created. Using a detector to record the neutrino flux gives a curve for the number of nuclei undergoing fission and the reactor power output. The question of whether it is practically possible to make use of neutrino emission from reactors was first posed in the mid-70s in connection with preparations for neutrino research at the Roven nuclear power plant (RAES) and in 1986 at an IAEA symposium on the topic of guarantees. Since 1982, research has been carried on at RAES on the fundamental properties and interactions of neutrinos. Based on this research and in parallel with it, in 1983 specialists from the Kurchatov Nuclear Power Institute and RAES jointly conducted an experiment which demonstrated in principle the possibility of remotely measuring reactor power output using the neutrino emission. This experiment had extremely limited statistics and is of interest today as the first demonstration of practical usage of neutrino emission from a reactor. At present the statistics for detecting neutrino events have increased tenfold and experience in lengthy measurements has been accumulated. This allows better analysis for the possibilities of the method. This paper reviews neutrino detection, theoretical bases of the method, determining the fission scale values for converting a number of neutrinos into power output, and measuring the power output

Controlling output pulse and prepulse in a resonant microwave pulse compressor

International Nuclear Information System (INIS)

Shlapakovski, A.; Artemenko, S.; Chumerin, P.; Yushkov, Yu.

2013-01-01

A resonant microwave pulse compressor with a waveguide H-plane-tee-based energy extraction unit was studied in terms of its capability to produce output pulses that comprise a low-power long-duration (prepulse) and a high-power short-duration part. The application of such combined pulses with widely variable prepulse and high-power pulse power and energy ratios is of interest in the research area of electronic hardware vulnerability. The characteristics of output radiation pulses are controlled by the variation of the H-plane tee transition attenuation at the stage of microwave energy storage in the compressor cavity. Results of theoretical estimations of the parameters tuning range and experimental investigations of the prototype S-band compressor (1.5 MW, 12 ns output pulse; ∼13.2 dB gain) are presented. The achievable maximum in the prepulse power is found to be about half the power of the primary microwave source. It has been shown that the energy of the prepulse becomes comparable with that of the short-duration (nanosecond) pulse, while the power of the latter decreases insignificantly. The possible range of variation of the prepulse power and energy can be as wide as 40 dB. In the experiments, the prepulse level control within the range of ∼10 dB was demonstrated.

Short-Term Wind Speed Forecasting for Power System Operations

KAUST Repository

Zhu, Xinxin; Genton, Marc G.

2012-01-01

some statistical short-term wind speed forecasting models, including traditional time series approaches and more advanced space-time statistical models. It also discusses the evaluation of forecast accuracy, in particular, the need for realistic loss

Short-term electric power demand forecasting based on economic-electricity transmission model

Science.gov (United States)

Li, Wenfeng; Bai, Hongkun; Liu, Wei; Liu, Yongmin; Wang, Yubin Mao; Wang, Jiangbo; He, Dandan

2018-04-01

Short-term electricity demand forecasting is the basic work to ensure safe operation of the power system. In this paper, a practical economic electricity transmission model (EETM) is built. With the intelligent adaptive modeling capabilities of Prognoz Platform 7.2, the econometric model consists of three industrial added value and income levels is firstly built, the electricity demand transmission model is also built. By multiple regression, moving averages and seasonal decomposition, the problem of multiple correlations between variables is effectively overcome in EETM. The validity of EETM is proved by comparison with the actual value of Henan Province. Finally, EETM model is used to forecast the electricity consumption of the 1-4 quarter of 2018.

Reactive Power Pricing Model Considering the Randomness of Wind Power Output

Science.gov (United States)

Dai, Zhong; Wu, Zhou

2018-01-01

With the increase of wind power capacity integrated into grid, the influence of the randomness of wind power output on the reactive power distribution of grid is gradually highlighted. Meanwhile, the power market reform puts forward higher requirements for reasonable pricing of reactive power service. Based on it, the article combined the optimal power flow model considering wind power randomness with integrated cost allocation method to price reactive power. Meanwhile, considering the advantages and disadvantages of the present cost allocation method and marginal cost pricing, an integrated cost allocation method based on optimal power flow tracing is proposed. The model realized the optimal power flow distribution of reactive power with the minimal integrated cost and wind power integration, under the premise of guaranteeing the balance of reactive power pricing. Finally, through the analysis of multi-scenario calculation examples and the stochastic simulation of wind power outputs, the article compared the results of the model pricing and the marginal cost pricing, which proved that the model is accurate and effective.

Short-term LNG-markets

International Nuclear Information System (INIS)

Eldegard, Tom; Lund, Arne-Christian; Miltersen, Kristian; Rud, Linda

2005-01-01

The global Liquefied Natural Gas (LNG) industry has experienced substantial growth in the past decades. In the traditional trade patterns of LNG the product has typically been handled within a dedicated chain of plants and vessels fully committed by long term contracts or common ownership, providing risk sharing of large investments in a non-liquid market. Increasing gas prices and substantial cost reductions in all parts of the LNG chain have made LNG projects viable even if only part of the capacity is secured by long-term contracts, opening for more flexible trade of the remainder. Increasing gas demand, especially in power generation, combined with cost reductions in the cost of LNG terminals, open new markets for LNG. For the LNG supplier, the flexibility of shifting volumes between regions represents an additional value. International trade in LNG has been increasing, now accounting for more than one fifth of the world's cross-border gas trade. Despite traditional vertical chain bonds, increased flexibility has contributed in fact to an increasing LNG spot trade, representing 8% of global trade in 2002. The focus of this paper is on the development of global short-term LNG markets, and their role with respect to efficiency and security of supply in European gas markets. Arbitrage opportunities arising from price differences between regional markets (such as North America versus Europe) are important impetuses for flexible short-term trade. However, the short-term LNG trade may suffer from problems related to market access, e.g. limited access to terminals and regulatory issues, as well as rigidities connected to vertical binding within the LNG chain. Important issues related to the role of short-term LNG-trade in the European gas market are: Competition, flexibility in meeting peak demand, security of supply and consequences of differences in pricing policies (oil-linked prices in Europe and spot market prices in North America). (Author)

High Average Power, High Energy Short Pulse Fiber Laser System

Energy Technology Data Exchange (ETDEWEB)

Messerly, M J

2007-11-13

Recently continuous wave fiber laser systems with output powers in excess of 500W with good beam quality have been demonstrated [1]. High energy, ultrafast, chirped pulsed fiber laser systems have achieved record output energies of 1mJ [2]. However, these high-energy systems have not been scaled beyond a few watts of average output power. Fiber laser systems are attractive for many applications because they offer the promise of high efficiency, compact, robust systems that are turn key. Applications such as cutting, drilling and materials processing, front end systems for high energy pulsed lasers (such as petawatts) and laser based sources of high spatial coherence, high flux x-rays all require high energy short pulses and two of the three of these applications also require high average power. The challenge in creating a high energy chirped pulse fiber laser system is to find a way to scale the output energy while avoiding nonlinear effects and maintaining good beam quality in the amplifier fiber. To this end, our 3-year LDRD program sought to demonstrate a high energy, high average power fiber laser system. This work included exploring designs of large mode area optical fiber amplifiers for high energy systems as well as understanding the issues associated chirped pulse amplification in optical fiber amplifier systems.

Modelling short and long-term risks in power markets: Empirical evidence from Nord Pool

International Nuclear Information System (INIS)

Nomikos, Nikos K.; Soldatos, Orestes A.

2010-01-01

In this paper we propose a three-factor spike model that accounts for different speeds of mean reversion between normal and spiky shocks in the Scandinavian power market. In this model both short and long-run factors are unobservable and are hence estimated as latent variables using the Kalman filter. The proposed model has several advantages. First, it seems to capture in a parsimonious way the most important risks that practitioners face in the market, such as spike risk, short-term risk and long-term risk. Second, it explains the seasonal risk premium observed in the market and improves the fit between theoretical and observed forward prices, particularly for long-dated forward contracts. Finally, closed-form solutions for forward contracts, derived from the model, are consistent with the fact that the correlation between contracts of different maturities is imperfect. The resulting model is very promising, providing a very useful policy analysis and financial engineering tool to market participants for risk management and derivative pricing particularly for long-dated contracts.

Stochastic Dynamic AC Optimal Power Flow Based on a Multivariate Short-Term Wind Power Scenario Forecasting Model

Directory of Open Access Journals (Sweden)

Wenlei Bai

2017-12-01

Full Text Available The deterministic methods generally used to solve DC optimal power flow (OPF do not fully capture the uncertainty information in wind power, and thus their solutions could be suboptimal. However, the stochastic dynamic AC OPF problem can be used to find an optimal solution by fully capturing the uncertainty information of wind power. That uncertainty information of future wind power can be well represented by the short-term future wind power scenarios that are forecasted using the generalized dynamic factor model (GDFM—a novel multivariate statistical wind power forecasting model. Furthermore, the GDFM can accurately represent the spatial and temporal correlations among wind farms through the multivariate stochastic process. Fully capturing the uncertainty information in the spatially and temporally correlated GDFM scenarios can lead to a better AC OPF solution under a high penetration level of wind power. Since the GDFM is a factor analysis based model, the computational time can also be reduced. In order to further reduce the computational time, a modified artificial bee colony (ABC algorithm is used to solve the AC OPF problem based on the GDFM forecasting scenarios. Using the modified ABC algorithm based on the GDFM forecasting scenarios has resulted in better AC OPF’ solutions on an IEEE 118-bus system at every hour for 24 h.

Simple and reliable procedure for the evaluation of short-term dynamic processes in power systems

Energy Technology Data Exchange (ETDEWEB)

Popovic, D P

1986-10-01

An efficient approach is presented to the solution of the short-term dynamics model in power systems. It consists of an adequate algebraic treatment of the original system of nonlinear differential equations, using linearization, decomposition and Cauchy's formula. The simple difference equations obtained in this way are incorporated into a model of the electrical network, which is of a low order compared to the ones usually used. Newton's method is applied to the model formed in this way, which leads to a simple and reliable iterative procedure. The characteristics of the procedure developed are demonstrated on examples of transient stability analysis of real power systems. 12 refs.

A short-run solution to the power crisis of Pakistan

International Nuclear Information System (INIS)

Imran, Muhammad; Amir, Namra

2015-01-01

Pakistan is in a deep power crisis since 2008 which the government is trying to control by adding new generation capacity. This strategy, however, will not be helpful in the short-run. The only way, the power crisis can be controlled or mitigated in the short-run, is to efficiently utilize the available resources. Government lacks such a strategy at this point. The paper provides such a strategy by setting up a power sector model with multiple modules of generation, transmission and distribution. The model provides an efficient way of utilizing the available resources and can be used to perform simulations at different stages of the supply-chain. The results of model show that, if the given resources are utilized efficiently, the power generation increases by 3222 GWh or 5 percent of the current output and the revenue increases by $945 million or 12 percent. The extra generated power decrease the cost of power production by 0.52 ¢/KWh cents and reduces the power load-shedding for 2–3 h. These outcomes can significantly relieve the sector and the people of Pakistan. The results of the model have important policy implications on working of the sector and circular debt reduction. - Highlights: • Government needs a new strategy to come out of the power crisis along with adding new power generation. • Because one major reason of current power crisis is the inefficient use of available resources. • Focus of this paper is to provide such a strategy by setting up a power sector supply-chain model. • When resources are utilized efficiently, power generation and revenue increases by 5 and 12 percent respectively. • These outputs decreases cost of power production by 0.52¢/KWh and power load-shedding by 2–3 h.

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

Complementary power output characteristics of electromagnetic generators and triboelectric generators.

Science.gov (United States)

Fan, Feng-Ru; Tang, Wei; Yao, Yan; Luo, Jianjun; Zhang, Chi; Wang, Zhong Lin

2014-04-04

Recently, a triboelectric generator (TEG) has been invented to convert mechanical energy into electricity by a conjunction of triboelectrification and electrostatic induction. Compared to the traditional electromagnetic generator (EMG) that produces a high output current but low voltage, the TEG has different output characteristics of low output current but high output voltage. In this paper, we present a comparative study regarding the fundamentals of TEGs and EMGs. The power output performances of the EMG and the TEG have a special complementary relationship, with the EMG being a voltage source and the TEG a current source. Utilizing a power transformed and managed (PTM) system, the current output of a TEG can reach as high as ∼3 mA, which can be coupled with the output signal of an EMG to enhance the output power. We also demonstrate a design to integrate a TEG and an EMG into a single device for simultaneously harvesting mechanical energy. In addition, the integrated NGs can independently output a high voltage and a high current to meet special needs.

Oil price shocks and their short- and long-term effects on the Chinese economy

International Nuclear Information System (INIS)

Tang, Weiqi; Wu, Libo; Zhang, ZhongXiang

2010-01-01

A considerable body of economic literature shows the adverse economic impacts of oil-price shocks for the developed economies. However, there has been a lack of similar empirical study on China and other developing countries. This paper attempts to fill this gap by answering how and to what extent oil-price shocks impact China's economy, emphasizing on the price transmission mechanisms. To that end, we develop a structural vector auto-regressive model. Our results show that an oil-price increase negatively affects output and investment, but positively affects inflation rate and interest rate. However, with price control policies in China, the impact on real economy, represented by real output and real investment, lasts much longer than that to price/monetary variables. Our decomposition results also show that the short-term impact, namely output decrease induced by the cut in capacity-utilization rate, is greater in the first 6 periods (namely half a year), but the portion of the long-term impact, defined as the impact realized through an investment change, increases steadily and exceeds that of short-term impact in the 7th period. Afterwards, the long-term impact dominates, and maintains for quite some time. (author)

Effect of kinesthetic illusion induced by visual stimulation on muscular output function after short-term immobilization.

Science.gov (United States)

Inada, Toru; Kaneko, Fuminari; Hayami, Tatsuya

2016-04-01

Kinesthetic illusions by visual stimulation (KiNVIS) enhances corticomotor excitability and activates motor association areas. The purpose of this study was to investigate the effect of KiNVIS induction on muscular output function after short-term immobilization. Thirty subjects were assigned to 3 groups: an immobilization group, with the left hand immobilized for 12h (immobilization period); an illusion group, with the left hand immobilized and additionally subjected to KiNVIS of the immobilized part during the immobilization period; and a control group with no manipulation. The maximum voluntary contraction (MVC), fluctuation of force (force fluctuation) during a force modulation task, and twitch force were measured both before (pre-test) and after (post-test) the immobilization period. Data were analyzed by performing two-way (TIME×GROUP) repeated measures ANOVA. The MVC decreased in the immobilization group only (pre-test; 37.8±6.1N, post-test; 32.8±6.9N, p<0.0005) after the immobilization period. The force fluctuation increased only in the immobilization group (pre-test; 2.19±0.54%, post-test; 2.78±0.87%, p=0.007) after the immobilization period. These results demonstrate that induction of KiNVIS prevents negative effect on MVC and force fluctuation after 12h of immobilization. Copyright © 2016 Elsevier Ltd. All rights reserved.

Auxetic piezoelectric energy harvesters for increased electric power output

Directory of Open Access Journals (Sweden)

Qiang Li

2017-01-01

Full Text Available This letter presents a piezoelectric bimorph with auxetic (negative Poisson’s ratio behaviors for increased power output in vibration energy harvesting. The piezoelectric bimorph comprises a 2D auxetic substrate sandwiched between two piezoelectric layers. The auxetic substrate is capable of introducing auxetic behaviors and thus increasing the transverse stress in the piezoelectric layers when the bimorph is subjected to a longitudinal stretching load. As a result, both 31- and 32-modes are simultaneously exploited to generate electric power, leading to an increased power output. The increasing power output principle was theoretically analyzed and verified by finite element (FE modelling. The FE modelling results showed that the auxetic substrate can increase the transverse stress of a bimorph by 16.7 times. The average power generated by the auxetic bimorph is 2.76 times of that generated by a conventional bimorph.

Short-Term Wind Power Forecasting Based on Clustering Pre-Calculated CFD Method

Directory of Open Access Journals (Sweden)

Yimei Wang

2018-04-01

Full Text Available To meet the increasing wind power forecasting (WPF demands of newly built wind farms without historical data, physical WPF methods are widely used. The computational fluid dynamics (CFD pre-calculated flow fields (CPFF-based WPF is a promising physical approach, which can balance well the competing demands of computational efficiency and accuracy. To enhance its adaptability for wind farms in complex terrain, a WPF method combining wind turbine clustering with CPFF is first proposed where the wind turbines in the wind farm are clustered and a forecasting is undertaken for each cluster. K-means, hierarchical agglomerative and spectral analysis methods are used to establish the wind turbine clustering models. The Silhouette Coefficient, Calinski-Harabaz index and within-between index are proposed as criteria to evaluate the effectiveness of the established clustering models. Based on different clustering methods and schemes, various clustering databases are built for clustering pre-calculated CFD (CPCC-based short-term WPF. For the wind farm case studied, clustering evaluation criteria show that hierarchical agglomerative clustering has reasonable results, spectral clustering is better and K-means gives the best performance. The WPF results produced by different clustering databases also prove the effectiveness of the three evaluation criteria in turn. The newly developed CPCC model has a much higher WPF accuracy than the CPFF model without using clustering techniques, both on temporal and spatial scales. The research provides supports for both the development and improvement of short-term physical WPF systems.

Short-term forecasting model for aggregated regional hydropower generation

International Nuclear Information System (INIS)

Monteiro, Claudio; Ramirez-Rosado, Ignacio J.; Fernandez-Jimenez, L. Alfredo

2014-01-01

Highlights: • Original short-term forecasting model for the hourly hydropower generation. • The use of NWP forecasts allows horizons of several days. • New variable to represent the capacity level for generating hydroelectric energy. • The proposed model significantly outperforms the persistence model. - Abstract: This paper presents an original short-term forecasting model of the hourly electric power production for aggregated regional hydropower generation. The inputs of the model are previously recorded values of the aggregated hourly production of hydropower plants and hourly water precipitation forecasts using Numerical Weather Prediction tools, as well as other hourly data (load demand and wind generation). This model is composed of three modules: the first one gives the prediction of the “monthly” hourly power production of the hydropower plants; the second module gives the prediction of hourly power deviation values, which are added to that obtained by the first module to achieve the final forecast of the hourly hydropower generation; the third module allows a periodic adjustment of the prediction of the first module to improve its BIAS error. The model has been applied successfully to the real-life case study of the short-term forecasting of the aggregated hydropower generation in Spain and Portugal (Iberian Peninsula Power System), achieving satisfactory results for the next-day forecasts. The model can be valuable for agents involved in electricity markets and useful for power system operations

Entropy method combined with extreme learning machine method for the short-term photovoltaic power generation forecasting

International Nuclear Information System (INIS)

Tang, Pingzhou; Chen, Di; Hou, Yushuo

2016-01-01

As the world’s energy problem becomes more severe day by day, photovoltaic power generation has opened a new door for us with no doubt. It will provide an effective solution for this severe energy problem and meet human’s needs for energy if we can apply photovoltaic power generation in real life, Similar to wind power generation, photovoltaic power generation is uncertain. Therefore, the forecast of photovoltaic power generation is very crucial. In this paper, entropy method and extreme learning machine (ELM) method were combined to forecast a short-term photovoltaic power generation. First, entropy method is used to process initial data, train the network through the data after unification, and then forecast electricity generation. Finally, the data results obtained through the entropy method with ELM were compared with that generated through generalized regression neural network (GRNN) and radial basis function neural network (RBF) method. We found that entropy method combining with ELM method possesses higher accuracy and the calculation is faster.

A Novel Short-Term Maintenance Strategy for Power Transmission and Transformation Equipment Based on Risk-Cost-Analysis

Directory of Open Access Journals (Sweden)

Hang Yang

2017-11-01

Full Text Available Current studies on preventive condition-based maintenance of power transmission and transformation equipment mainly focus on mid-term or long-term maintenance, and cannot meet the requirements of short-term especially temporary maintenance. In order to solve the defects of the present preventive maintenance strategies, according to the engineering application and based on risk-cost analysis, a short-term maintenance strategy is proposed in this manuscript. For the equipment working in bad health condition, its active maintenance costs and operation risk costs are evaluated, respectively. Then the latest maintenance time is calculated in accordance with the principle that its operation risk costs are no higher than active maintenance costs. Utilizing the latest maintenance time, the best maintenance time is calculated by setting the maximum relative earnings of postponing maintenance as the target, which provides the operation staffs with comprehensive maintenance-decision support. In the end, different cases on the IEEE 24-bus system are simulated. The effectiveness and advantages of the proposed strategy are demonstrated by the simulation results.

Robust short-term memory without synaptic learning.

Directory of Open Access Journals (Sweden)

Samuel Johnson

Full Text Available Short-term memory in the brain cannot in general be explained the way long-term memory can--as a gradual modification of synaptic weights--since it takes place too quickly. Theories based on some form of cellular bistability, however, do not seem able to account for the fact that noisy neurons can collectively store information in a robust manner. We show how a sufficiently clustered network of simple model neurons can be instantly induced into metastable states capable of retaining information for a short time (a few seconds. The mechanism is robust to different network topologies and kinds of neural model. This could constitute a viable means available to the brain for sensory and/or short-term memory with no need of synaptic learning. Relevant phenomena described by neurobiology and psychology, such as local synchronization of synaptic inputs and power-law statistics of forgetting avalanches, emerge naturally from this mechanism, and we suggest possible experiments to test its viability in more biological settings.

Robust short-term memory without synaptic learning.

Science.gov (United States)

Johnson, Samuel; Marro, J; Torres, Joaquín J

2013-01-01

Short-term memory in the brain cannot in general be explained the way long-term memory can--as a gradual modification of synaptic weights--since it takes place too quickly. Theories based on some form of cellular bistability, however, do not seem able to account for the fact that noisy neurons can collectively store information in a robust manner. We show how a sufficiently clustered network of simple model neurons can be instantly induced into metastable states capable of retaining information for a short time (a few seconds). The mechanism is robust to different network topologies and kinds of neural model. This could constitute a viable means available to the brain for sensory and/or short-term memory with no need of synaptic learning. Relevant phenomena described by neurobiology and psychology, such as local synchronization of synaptic inputs and power-law statistics of forgetting avalanches, emerge naturally from this mechanism, and we suggest possible experiments to test its viability in more biological settings.

Robust Short-Term Memory without Synaptic Learning

Science.gov (United States)

Johnson, Samuel; Marro, J.; Torres, Joaquín J.

2013-01-01

Short-term memory in the brain cannot in general be explained the way long-term memory can – as a gradual modification of synaptic weights – since it takes place too quickly. Theories based on some form of cellular bistability, however, do not seem able to account for the fact that noisy neurons can collectively store information in a robust manner. We show how a sufficiently clustered network of simple model neurons can be instantly induced into metastable states capable of retaining information for a short time (a few seconds). The mechanism is robust to different network topologies and kinds of neural model. This could constitute a viable means available to the brain for sensory and/or short-term memory with no need of synaptic learning. Relevant phenomena described by neurobiology and psychology, such as local synchronization of synaptic inputs and power-law statistics of forgetting avalanches, emerge naturally from this mechanism, and we suggest possible experiments to test its viability in more biological settings. PMID:23349664

Output power distributions of terminals in a 3G mobile communication network.

Science.gov (United States)

Persson, Tomas; Törnevik, Christer; Larsson, Lars-Eric; Lovén, Jan

2012-05-01

The objective of this study was to examine the distribution of the output power of mobile phones and other terminals connected to a 3G network in Sweden. It is well known that 3G terminals can operate with very low output power, particularly for voice calls. Measurements of terminal output power were conducted in the Swedish TeliaSonera 3G network in November 2008 by recording network statistics. In the analysis, discrimination was made between rural, suburban, urban, and dedicated indoor networks. In addition, information about terminal output power was possible to collect separately for voice and data traffic. Information from six different Radio Network Controllers (RNCs) was collected during at least 1 week. In total, more than 800000 h of voice calls were collected and in addition to that a substantial amount of data traffic. The average terminal output power for 3G voice calls was below 1 mW for any environment including rural, urban, and dedicated indoor networks. This is <1% of the maximum available output power. For data applications the average output power was about 6-8 dB higher than for voice calls. For rural areas the output power was about 2 dB higher, on average, than in urban areas. Copyright © 2011 Wiley Periodicals, Inc.

Short-Term Forecasting of Electric Loads Using Nonlinear Autoregressive Artificial Neural Networks with Exogenous Vector Inputs

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Jaime Buitrago

2017-01-01

Full Text Available Short-term load forecasting is crucial for the operations planning of an electrical grid. Forecasting the next 24 h of electrical load in a grid allows operators to plan and optimize their resources. The purpose of this study is to develop a more accurate short-term load forecasting method utilizing non-linear autoregressive artificial neural networks (ANN with exogenous multi-variable input (NARX. The proposed implementation of the network is new: the neural network is trained in open-loop using actual load and weather data, and then, the network is placed in closed-loop to generate a forecast using the predicted load as the feedback input. Unlike the existing short-term load forecasting methods using ANNs, the proposed method uses its own output as the input in order to improve the accuracy, thus effectively implementing a feedback loop for the load, making it less dependent on external data. Using the proposed framework, mean absolute percent errors in the forecast in the order of 1% have been achieved, which is a 30% improvement on the average error using feedforward ANNs, ARMAX and state space methods, which can result in large savings by avoiding commissioning of unnecessary power plants. The New England electrical load data are used to train and validate the forecast prediction.

Short-Term Photovoltaic Power Generation Forecasting Based on Multivariable Grey Theory Model with Parameter Optimization

Directory of Open Access Journals (Sweden)

Zhifeng Zhong

2017-01-01

Full Text Available Owing to the environment, temperature, and so forth, photovoltaic power generation volume is always fluctuating and subsequently impacts power grid planning and operation seriously. Therefore, it is of great importance to make accurate prediction of the power generation of photovoltaic (PV system in advance. In order to improve the prediction accuracy, in this paper, a novel particle swarm optimization algorithm based multivariable grey theory model is proposed for short-term photovoltaic power generation volume forecasting. It is highlighted that, by integrating particle swarm optimization algorithm, the prediction accuracy of grey theory model is expected to be highly improved. In addition, large amounts of real data from two separate power stations in China are being employed for model verification. The experimental results indicate that, compared with the conventional grey model, the mean relative error in the proposed model has been reduced from 7.14% to 3.53%. The real practice demonstrates that the proposed optimization model outperforms the conventional grey model from both theoretical and practical perspectives.

Optimization of output power and transmission efficiency of magnetically coupled resonance wireless power transfer system

Science.gov (United States)

Yan, Rongge; Guo, Xiaoting; Cao, Shaoqing; Zhang, Changgeng

2018-05-01

Magnetically coupled resonance (MCR) wireless power transfer (WPT) system is a promising technology in electric energy transmission. But, if its system parameters are designed unreasonably, output power and transmission efficiency will be low. Therefore, optimized parameters design of MCR WPT has important research value. In the MCR WPT system with designated coil structure, the main parameters affecting output power and transmission efficiency are the distance between the coils, the resonance frequency and the resistance of the load. Based on the established mathematical model and the differential evolution algorithm, the change of output power and transmission efficiency with parameters can be simulated. From the simulation results, it can be seen that output power and transmission efficiency of the two-coil MCR WPT system and four-coil one with designated coil structure are improved. The simulation results confirm the validity of the optimization method for MCR WPT system with designated coil structure.

Intermittent Smoothing Approaches for Wind Power Output: A Review

Directory of Open Access Journals (Sweden)

Muhammad Jabir

2017-10-01

Full Text Available Wind energy is one of the most common types of renewable energy resource. Due to its sustainability and environmental benefits, it is an emerging source for electric power generation. Rapid and random changes of wind speed makes it an irregular and inconsistent power source when connected to the grid, causing different technical problems in protection, power quality and generation dispatch control. Due to these problems, effective intermittent smoothing approaches for wind power output are crucially needed to minimize such problems. This paper reviews various intermittent smoothing approaches used in smoothing the output power fluctuations caused by wind energy. Problems associated with the inclusion of wind energy resources to grid are also briefly reviewed. From this review, it has been found that battery energy storage system is the most suitable and effective smoothing approach, provided that an effective control strategy is available for optimal utilization of battery energy system. This paper further demonstrates different control strategies built for battery energy storage system to obtain the smooth output wind power.

An Operational Short-Term Forecasting System for Regional Hydropower Management

Science.gov (United States)

Gronewold, A.; Labuhn, K. A.; Calappi, T. J.; MacNeil, A.

2017-12-01

The Niagara River is the natural outlet of Lake Erie and drains four of the five Great lakes. The river is used to move commerce and is home to both sport fishing and tourism industries. It also provides nearly 5 million kilowatts of hydropower for approximately 3.9 million homes. Due to a complex international treaty and the necessity of balancing water needs for an extensive tourism industry, the power entities operating on the river require detailed and accurate short-term river flow forecasts to maximize power output. A new forecast system is being evaluated that takes advantage of several previously independent components including the NOAA Lake Erie operational Forecast System (LEOFS), a previously developed HEC-RAS model, input from the New York Power Authority(NYPA) and Ontario Power Generation (OPG) and lateral flow forecasts for some of the tributaries provided by the NOAA Northeast River Forecast Center (NERFC). The Corps of Engineers updated the HEC-RAS model of the upper Niagara River to use the output forcing from LEOFS and a planned Grass Island Pool elevation provided by the power entities. The entire system has been integrated at the NERFC; it will be run multiple times per day with results provided to the Niagara River Control Center operators. The new model helps improve discharge forecasts by better accounting for dynamic conditions on Lake Erie. LEOFS captures seiche events on the lake that are often several meters of displacement from still water level. These seiche events translate into flow spikes that HEC-RAS routes downstream. Knowledge of the peak arrival time helps improve operational decisions at the Grass Island Pool. This poster will compare and contrast results from the existing operational flow forecast and the new integrated LEOFS/HEC-RAS forecast. This additional model will supply the Niagara River Control Center operators with multiple forecasts of flow to help improve forecasting under a wider variety of conditions.

Audit of long-term and short-term liabilities

Directory of Open Access Journals (Sweden)

Korinko M.D.

2017-03-01

Full Text Available The article determines the importance of long-term and short-term liabilities for the management of financial and material resources of an enterprise. It reviews the aim, objects and information generators for realization of audit of short-term and long-term obligations. The organizing and methodical providing of audit of long-term and short-term liabilities of an enterprise are generalized. The authors distinguish the stages of realization of audit of long-term and short-term liabilities, the aim of audit on each of the presented stages, and recommend methodical techniques. It is fixed that it is necessary to conduct the estimation of the systems of internal control and record-keeping of an enterprise by implementation of public accountant procedures for determination of volume and maintenance of selection realization. After estimating the indicated systems, a public accountant determines the methodology for realization of public accountant verification of long-term and short-term liabilities. The analytical procedures that public accountants are expedient to use for realization of audit of short-term and long-term obligations are determined. The authors suggest the classification of the educed defects on the results of the conducted public accountant verification of short-term and long-term obligations.

Short-Term Forecasting of Electric Energy Generation for a Photovoltaic System

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Dinh V.T.

2018-01-01

Full Text Available This article presents a short-term forecast of electric energy output of a photovoltaic (PV system towards Tomsk city, Russia climate variations (module temperature and solar irradiance. The system is located at Institute of Non-destructive Testing, Tomsk Polytechnic University. The obtained results show good agreement between actual data and prediction values.

Calculation of the output power in self-amplified spontaneous radiation using scaling of power with number of simulation particles

International Nuclear Information System (INIS)

Yu, L.H.

1998-01-01

Recent advances in self-amplified spontaneous emission (SASE) experiments stimulate interest in quantitative comparison of measurements with theory. In this paper we show that the widely used simulation code TDA3D, developed by Tran and Wurtele [Comput. Phys. Commun. 54, 263 (1989)] even though a single frequency code, can be used to determine the output power in the SASE process with excellent approximation in the exponential growth regime. The method applies when the gain is not very high, which is a special advantage, because when the gain is not very high, the analytical calculation is particularly difficult since the exponential growing term does not dominate. The analysis utilizes a scaling relation between the output power and the number of simulation particles in the code TDA3D: left-angle P right-angle=N λ ' /N λ left-angle P ' right-angle, where left-angle P right-angle is the output power and N λ is the line density of the electrons, while left-angle P ' right-angle is the calculated output power using a line density N λ ' of the number of simulation particles in the code TDA3D. Because of the scaling property, the number of simulation particles can be taken to be many orders of magnitude less than the actual experiment. Comparison of our results with experiment yields new insight into the SASE process. copyright 1998 The American Physical Society

FFT transformed quantitative EEG analysis of short term memory load.

Science.gov (United States)

Singh, Yogesh; Singh, Jayvardhan; Sharma, Ratna; Talwar, Anjana

2015-07-01

The EEG is considered as building block of functional signaling in the brain. The role of EEG oscillations in human information processing has been intensively investigated. To study the quantitative EEG correlates of short term memory load as assessed through Sternberg memory test. The study was conducted on 34 healthy male student volunteers. The intervention consisted of Sternberg memory test, which runs on a version of the Sternberg memory scanning paradigm software on a computer. Electroencephalography (EEG) was recorded from 19 scalp locations according to 10-20 international system of electrode placement. EEG signals were analyzed offline. To overcome the problems of fixed band system, individual alpha frequency (IAF) based frequency band selection method was adopted. The outcome measures were FFT transformed absolute powers in the six bands at 19 electrode positions. Sternberg memory test served as model of short term memory load. Correlation analysis of EEG during memory task was reflected as decreased absolute power in Upper alpha band in nearly all the electrode positions; increased power in Theta band at Fronto-Temporal region and Lower 1 alpha band at Fronto-Central region. Lower 2 alpha, Beta and Gamma band power remained unchanged. Short term memory load has distinct electroencephalographic correlates resembling the mentally stressed state. This is evident from decreased power in Upper alpha band (corresponding to Alpha band of traditional EEG system) which is representative band of relaxed mental state. Fronto-temporal Theta power changes may reflect the encoding and execution of memory task.

Short-term high intensity plyometric training program improves strength, power and agility in male soccer players.

Science.gov (United States)

Váczi, Márk; Tollár, József; Meszler, Balázs; Juhász, Ivett; Karsai, István

2013-03-01

The aim of the present study was to investigate the effects of a short-term in-season plyometric training program on power, agility and knee extensor strength. Male soccer players from a third league team were assigned into an experimental and a control group. The experimental group, beside its regular soccer training sessions, performed a periodized plyometric training program for six weeks. The program included two training sessions per week, and maximal intensity unilateral and bilateral plyometric exercises (total of 40 - 100 foot contacts/session) were executed. Controls participated only in the same soccer training routine, and did not perform plyometrics. Depth vertical jump height, agility (Illinois Agility Test, T Agility Test) and maximal voluntary isometric torque in knee extensors using Multicont II dynamometer were evaluated before and after the experiment. In the experimental group small but significant improvements were found in both agility tests, while depth jump height and isometric torque increments were greater. The control group did not improve in any of the measures. Results of the study indicate that plyometric training consisting of high impact unilateral and bilateral exercises induced remarkable improvements in lower extremity power and maximal knee extensor strength, and smaller improvements in soccer-specific agility. Therefore, it is concluded that short-term plyometric training should be incorporated in the in-season preparation of lower level players to improve specific performance in soccer.

Short-Term High Intensity Plyometric Training Program Improves Strength, Power and Agility in Male Soccer Players

Science.gov (United States)

Váczi, Márk; Tollár, József; Meszler, Balázs; Juhász, Ivett; Karsai, István

2013-01-01

The aim of the present study was to investigate the effects of a short-term in-season plyometric training program on power, agility and knee extensor strength. Male soccer players from a third league team were assigned into an experimental and a control group. The experimental group, beside its regular soccer training sessions, performed a periodized plyometric training program for six weeks. The program included two training sessions per week, and maximal intensity unilateral and bilateral plyometric exercises (total of 40 – 100 foot contacts/session) were executed. Controls participated only in the same soccer training routine, and did not perform plyometrics. Depth vertical jump height, agility (Illinois Agility Test, T Agility Test) and maximal voluntary isometric torque in knee extensors using Multicont II dynamometer were evaluated before and after the experiment. In the experimental group small but significant improvements were found in both agility tests, while depth jump height and isometric torque increments were greater. The control group did not improve in any of the measures. Results of the study indicate that plyometric training consisting of high impact unilateral and bilateral exercises induced remarkable improvements in lower extremity power and maximal knee extensor strength, and smaller improvements in soccer-specific agility. Therefore, it is concluded that short-term plyometric training should be incorporated in the in-season preparation of lower level players to improve specific performance in soccer. PMID:23717351

Output power distributions of mobile radio base stations based on network measurements

International Nuclear Information System (INIS)

Colombi, D; Thors, B; Persson, T; Törnevik, C; Wirén, N; Larsson, L-E

2013-01-01

In this work output power distributions of mobile radio base stations have been analyzed for 2G and 3G telecommunication systems. The approach is based on measurements in selected networks using performance surveillance tools part of the network Operational Support System (OSS). For the 3G network considered, direct measurements of output power levels were possible, while for the 2G networks, output power levels were estimated from measurements of traffic volumes. Both voice and data services were included in the investigation. Measurements were conducted for large geographical areas, to ensure good overall statistics, as well as for smaller areas to investigate the impact of different environments. For high traffic hours, the 90th percentile of the averaged output power was found to be below 65% and 45% of the available output power for the 2G and 3G systems, respectively.

Output power distributions of mobile radio base stations based on network measurements

Science.gov (United States)

Colombi, D.; Thors, B.; Persson, T.; Wirén, N.; Larsson, L.-E.; Törnevik, C.

2013-04-01

In this work output power distributions of mobile radio base stations have been analyzed for 2G and 3G telecommunication systems. The approach is based on measurements in selected networks using performance surveillance tools part of the network Operational Support System (OSS). For the 3G network considered, direct measurements of output power levels were possible, while for the 2G networks, output power levels were estimated from measurements of traffic volumes. Both voice and data services were included in the investigation. Measurements were conducted for large geographical areas, to ensure good overall statistics, as well as for smaller areas to investigate the impact of different environments. For high traffic hours, the 90th percentile of the averaged output power was found to be below 65% and 45% of the available output power for the 2G and 3G systems, respectively.

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.

The Short-Term Power Load Forecasting Based on Sperm Whale Algorithm and Wavelet Least Square Support Vector Machine with DWT-IR for Feature Selection

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Jin-peng Liu

2017-07-01

Full Text Available Short-term power load forecasting is an important basis for the operation of integrated energy system, and the accuracy of load forecasting directly affects the economy of system operation. To improve the forecasting accuracy, this paper proposes a load forecasting system based on wavelet least square support vector machine and sperm whale algorithm. Firstly, the methods of discrete wavelet transform and inconsistency rate model (DWT-IR are used to select the optimal features, which aims to reduce the redundancy of input vectors. Secondly, the kernel function of least square support vector machine LSSVM is replaced by wavelet kernel function for improving the nonlinear mapping ability of LSSVM. Lastly, the parameters of W-LSSVM are optimized by sperm whale algorithm, and the short-term load forecasting method of W-LSSVM-SWA is established. Additionally, the example verification results show that the proposed model outperforms other alternative methods and has a strong effectiveness and feasibility in short-term power load forecasting.

Carnot efficiency at divergent power output

Science.gov (United States)

Polettini, Matteo; Esposito, Massimiliano

2017-05-01

The widely debated feasibility of thermodynamic machines achieving Carnot efficiency at finite power has been convincingly dismissed. Yet, the common wisdom that efficiency can only be optimal in the limit of infinitely slow processes overlooks the dual scenario of infinitely fast processes. We corroborate that efficient engines at divergent power output are not theoretically impossible, framing our claims within the theory of Stochastic Thermodynamics. We inspect the case of an electronic quantum dot coupled to three particle reservoirs to illustrate the physical rationale.

Modeling the power output of piezoelectric energy harvesters

KAUST Repository

Al Ahmad, Mahmoud

2011-04-30

Design of experiments and multiphysics analyses were used to develop a parametric model for a d 33-based cantilever. The analysis revealed that the most significant parameters influencing the resonant frequency are the supporting layer thickness, piezoelectric layer thickness, and cantilever length. On the other hand, the most important factors affecting the charge output arethe piezoelectric thickness and the interdigitated electrode dimensions. The accuracy of the developed model was confirmed and showed less than 1% estimation error compared with a commercial simulation package. To estimate the power delivered to a load, the electric current output from the piezoelectric generator was calculated. A circuit model was built and used to estimate the power delivered to a load, which compared favorably to experimentally published power data on actual cantilevers of similar dimensions. © 2011 TMS.

Modeling the power output of piezoelectric energy harvesters

KAUST Repository

Al Ahmad, Mahmoud; Alshareef, Husam N.

2011-01-01

Design of experiments and multiphysics analyses were used to develop a parametric model for a d 33-based cantilever. The analysis revealed that the most significant parameters influencing the resonant frequency are the supporting layer thickness, piezoelectric layer thickness, and cantilever length. On the other hand, the most important factors affecting the charge output arethe piezoelectric thickness and the interdigitated electrode dimensions. The accuracy of the developed model was confirmed and showed less than 1% estimation error compared with a commercial simulation package. To estimate the power delivered to a load, the electric current output from the piezoelectric generator was calculated. A circuit model was built and used to estimate the power delivered to a load, which compared favorably to experimentally published power data on actual cantilevers of similar dimensions. © 2011 TMS.

A three-stage short-term electric power planning procedure for a generation company in a liberalized market

International Nuclear Information System (INIS)

Nabona, Narcis; Pages, Adela

2007-01-01

In liberalized electricity markets, generation companies bid their hourly generation in order to maximize their profit. The optimization of the generation bids over a short-term weekly period must take into account the action of the competing generation companies and the market-price formation rules and must be coordinated with long-term planning results. This paper presents a three stage optimization process with a data analysis and parameter calculation, a linearized unit commitment, and a nonlinear generation scheduling refinement. Although the procedure has been developed from the experience with the Spanish power market, with minor adaptations it is also applicable to any generation company participating in a competitive market system. (author)

PI and Fuzzy Control Strategies for High Voltage Output DC-DC Boost Power Converter - Hardware Implementation and Analysis

DEFF Research Database (Denmark)

Padmanaban, Sanjeevi Kumar; Blaabjerg, Frede; Siano, Pierluigi

2016-01-01

This paper presents the control strategies by Proportional-Integral (P-I) and Fuzzy Logic (FL) for a DC-DC boost power converter for high output voltage configuration. Standard DC-DC converters are traditionally used for high voltage direct current (HVDC) power transmission systems. But, lack its...... converter with inbuilt voltage-lift technique and overcome the aforementioned deficiencies. Further, the control strategy is adapted based on proportional-integral (P-I) and fuzzy logic, closed-loop controller to regulate the outputs and ensure the performances. Complete hardware prototype of EHV converter...... performances in terms of efficiency, reduced transfer gain and increased cost with sensor units. Moreover, the internal self-parasitic components reduce the output voltage and efficiency of classical high voltage converters (HVC). This investigation focused on extra high-voltage (EHV) DC-DC boost power...

S-Band AlGaN/GaN Power Amplifier MMIC with over 20 Watt Output Power

NARCIS (Netherlands)

Heijningen, M. van; Visser, G.C.; Wuerfl, J.; Vliet, F.E. van

2008-01-01

This paper presents the design of an S-band HPA MMIC in AlGaN/GaN CPW technology for radar TR-module application. The trade-offs of using an MMIC solution versus discrete power devices are discussed. The MMIC shows a maximum output power of 38 Watt at 37% Power Added Efficiency at 3.1 GHz. An output

Power output of field-based downhill mountain biking.

Science.gov (United States)

Hurst, Howard Thomas; Atkins, Stephen

2006-10-01

The purpose of this study was to assess the power output of field-based downhill mountain biking. Seventeen trained male downhill cyclists (age 27.1 +/- 5.1 years) competing nationally performed two timed runs of a measured downhill course. An SRM powermeter was used to simultaneously record power, cadence, and speed. Values were sampled at 1-s intervals. Heart rates were recorded at 5-s intervals using a Polar S710 heart rate monitor. Peak and mean power output were 834 +/- 129 W and 75 +/- 26 W respectively. Mean power accounted for only 9% of peak values. Paradoxically, mean heart rate was 168 +/- 9 beats x min(-1) (89% of age-predicted maximum heart rate). Mean cadence (27 +/- 5 rev x min(-1)) was significantly related to speed (r = 0.51; P biking. The poor relationships between power and run time and between cadence and run time suggest they are not essential pre-requisites to downhill mountain biking performance and indicate the importance of riding dynamics to overall performance.

Ensemble Nonlinear Autoregressive Exogenous Artificial Neural Networks for Short-Term Wind Speed and Power Forecasting.

Science.gov (United States)

Men, Zhongxian; Yee, Eugene; Lien, Fue-Sang; Yang, Zhiling; Liu, Yongqian

2014-01-01

Short-term wind speed and wind power forecasts (for a 72 h period) are obtained using a nonlinear autoregressive exogenous artificial neural network (ANN) methodology which incorporates either numerical weather prediction or high-resolution computational fluid dynamics wind field information as an exogenous input. An ensemble approach is used to combine the predictions from many candidate ANNs in order to provide improved forecasts for wind speed and power, along with the associated uncertainties in these forecasts. More specifically, the ensemble ANN is used to quantify the uncertainties arising from the network weight initialization and from the unknown structure of the ANN. All members forming the ensemble of neural networks were trained using an efficient particle swarm optimization algorithm. The results of the proposed methodology are validated using wind speed and wind power data obtained from an operational wind farm located in Northern China. The assessment demonstrates that this methodology for wind speed and power forecasting generally provides an improvement in predictive skills when compared to the practice of using an "optimal" weight vector from a single ANN while providing additional information in the form of prediction uncertainty bounds.

An Advanced Bayesian Method for Short-Term Probabilistic Forecasting of the Generation of Wind Power

Directory of Open Access Journals (Sweden)

Antonio Bracale

2015-09-01

Full Text Available Currently, among renewable distributed generation systems, wind generators are receiving a great deal of interest due to the great economic, technological, and environmental incentives they involve. However, the uncertainties due to the intermittent nature of wind energy make it difficult to operate electrical power systems optimally and make decisions that satisfy the needs of all the stakeholders of the electricity energy market. Thus, there is increasing interest determining how to forecast wind power production accurately. Most the methods that have been published in the relevant literature provided deterministic forecasts even though great interest has been focused recently on probabilistic forecast methods. In this paper, an advanced probabilistic method is proposed for short-term forecasting of wind power production. A mixture of two Weibull distributions was used as a probability function to model the uncertainties associated with wind speed. Then, a Bayesian inference approach with a particularly-effective, autoregressive, integrated, moving-average model was used to determine the parameters of the mixture Weibull distribution. Numerical applications also are presented to provide evidence of the forecasting performance of the Bayesian-based approach.

Word-length effect in verbal short-term memory in individuals with Down's syndrome.

Science.gov (United States)

Kanno, K; Ikeda, Y

2002-11-01

Many studies have indicated that individuals with Down's syndrome (DS) show a specific deficit in short-term memory for verbal information. The aim of the present study was to investigate the influence of the length of words on verbal short-term memory in individuals with DS. Twenty-eight children with DS and 10 control participants matched for memory span were tested on verbal serial recall and speech rate, which are thought to involve rehearsal and output speed. Although a significant word-length effect was observed in both groups for the recall of a larger number of items with a shorter spoken duration than for those with a longer spoken duration, the number of correct recalls in the group with DS was reduced compared to the control subjects. The results demonstrating poor short-term memory in children with DS were irrelevant to speech rate. In addition, the proportion of repetition-gained errors in serial recall was higher in children with DS than in control subjects. The present findings suggest that poor access to long-term lexical knowledge, rather than overt articulation speed, constrains verbal short-term memory functions in individuals with DS.

A method for short term electricity spot price forecasting

International Nuclear Information System (INIS)

Koreneff, G.; Seppaelae, A.; Lehtonen, M.; Kekkonen, V.; Laitinen, E.; Haekli, J.; Antila, E.

1998-01-01

In Finland, the electricity market was de-regulated in November 1995. For the electricity purchase of power companies this has caused big changes, since the old tariff based contracts of bulk power supply have been replaced by negotiated bilateral short term contracts and by power purchase from the spot market. In the spot market, in turn, there are at the present two strong actors: The electricity exchange of Finland and the Nordic power pool which is run by the Swedish and Norwegian companies. Today, the power companies in Finland have short term trade with both of the electricity exchanges. The aim of this chapter is to present methods for spot price forecasting in the electricity exchange. The main focus is given to the Finnish circumstances. In the beginning of the presentation, the practices of the electricity exchange of Finland are described, and a brief presentation is given on the different contracts, or electricity products, available in the spot market. For comparison, the practices of the Nordic electricity exchange are also outlined. A time series technique for spot price forecasting is presented. The structure of the model is presented, and its validity is tested using real case data obtained from the Finnish power market. The spot price forecasting model is a part of a computer system for distribution energy management (DEM) in a de-regulated power market

A method for short term electricity spot price forecasting

Energy Technology Data Exchange (ETDEWEB)

Koreneff, G; Seppaelae, A; Lehtonen, M; Kekkonen, V [VTT Energy, Espoo (Finland); Laitinen, E; Haekli, J [Vaasa Univ. (Finland); Antila, E [ABB Transmit Oy (Finland)

1998-08-01

In Finland, the electricity market was de-regulated in November 1995. For the electricity purchase of power companies this has caused big changes, since the old tariff based contracts of bulk power supply have been replaced by negotiated bilateral short term contracts and by power purchase from the spot market. In the spot market, in turn, there are at the present two strong actors: The electricity exchange of Finland and the Nordic power pool which is run by the Swedish and Norwegian companies. Today, the power companies in Finland have short term trade with both of the electricity exchanges. The aim of this chapter is to present methods for spot price forecasting in the electricity exchange. The main focus is given to the Finnish circumstances. In the beginning of the presentation, the practices of the electricity exchange of Finland are described, and a brief presentation is given on the different contracts, or electricity products, available in the spot market. For comparison, the practices of the Nordic electricity exchange are also outlined. A time series technique for spot price forecasting is presented. The structure of the model is presented, and its validity is tested using real case data obtained from the Finnish power market. The spot price forecasting model is a part of a computer system for distribution energy management (DEM) in a de-regulated power market

Increased alpha-band power during the retention of shapes and shape-location associations in visual short-term memory

Directory of Open Access Journals (Sweden)

Jeffrey S. Johnson

2011-06-01

Full Text Available Studies exploring the role of neural oscillations in cognition have revealed sustained increases in alpha-band (~8-14 Hz power during the delay period of delayed-recognition short-term memory tasks. These increases have been proposed to reflect the inhibition, for example, of cortical areas representing task-irrelevant information, or of potentially interfering representations from previous trials. Another possibility, however, is that elevated delay-period alpha-band power reflects the selection and maintenance of information, rather than, or in addition to, the inhibition of task-irrelevant information. In the present study, we explored these possibilities using a delayed-recognition paradigm in which the presence and task-relevance of shape information was systematically manipulated across trial blocks and EEG was used to measure alpha-band power. In the first trial block, participants remembered locations marked by identical black circles. The second block featured the same instructions, but locations were marked by unique shapes. The third block featured the same stimulus presentation as the second, but with pretrial instructions indicating, on a trial-by-trial basis, whether memory for shape or location was required, the other dimension being irrelevant. In the final block, participants remembered the unique pairing of shape and location for each stimulus. Results revealed minimal delay-period alpha-band power in each of the location-memory conditions, whether locations were marked with identical circles or with unique task-irrelevant shapes. In contrast, alpha-band power increases were observed in both the shape-memory condition, in which location was task irrelevant, and in the critical final condition, in which both shape and location were task relevant. These results provide support for the proposal that alpha-band oscillations reflect the retention of shape information and/or shape-location associations in short-term memory.

Short-Term Optimal Operation of a Wind-PV-Hydro Complementary Installation: Yalong River, Sichuan Province, China

Directory of Open Access Journals (Sweden)

Xinshuo Zhang

2018-04-01

Full Text Available How to effectively use clean renewable energy to improve the capacity of the power grid to absorb new energy and optimize the power grid structure has become one of China’s current issues. The Yalong River Wind-PV-Hydro complementary clean energy base was chosen as the research object from which to analyze the output complementarity principle and characteristics of wind farms, photovoltaic power plants, and hydropower stations. Then, an optimization scheduling model was established with the objective of minimizing the amount of abandoned wind and photovoltaic power and maximizing the stored energy in cascade hydropower stations. A Progress Optimality Algorithm (POA was used for the short-term optimal operation of Wind-PV-Hydro combinations. The results show that use of cascaded hydropower storage capacity can compensate for large-scale wind power and photovoltaic power, provide a relatively sustained and stable power supply for the grid. Wind-PV-Hydro complementary operation not only promotes wind power and photovoltaic power consumption but also improves the efficiency of using the original transmission channel of hydropower. This is of great significance to many developing countries in formatting a new green approach, realizing low-carbon power dispatch and trade and promoting regional economic development.

Determinants of mobile phone output power in a multinational study: implications for exposure assessment

DEFF Research Database (Denmark)

Vrijheid, M; Madsen, Stine Mann; di Vecchia, Paolo

2009-01-01

OBJECTIVES: The output power of a mobile phone is directly related to its radiofrequency (RF) electromagnetic field strength, and may theoretically vary substantially in different networks and phone use circumstances due to power control technologies. To improve indices of RF exposure for epidemi......OBJECTIVES: The output power of a mobile phone is directly related to its radiofrequency (RF) electromagnetic field strength, and may theoretically vary substantially in different networks and phone use circumstances due to power control technologies. To improve indices of RF exposure...... on the average output power and the percentage call time at maximum power for each call. RESULTS: Measurements of over 60,000 phone calls showed that the average output power was approximately 50% of the maximum, and that output power varied by a factor of up to 2 to 3 between study centres and network operators...

Pediatric polytrauma : Short-term and long-term outcomes

NARCIS (Netherlands)

vanderSluis, CK; Kingma, J; Eisma, WH; tenDuis, HJ

Objective: To assess the short-term and long-term outcomes of pediatric polytrauma patients and to analyze the extent to which short-term outcomes can predict long-term outcomes. Materials and Methods: Ail pediatric polytrauma patients (Injury Severity Score of greater than or equal to 16, less than

Analysis of losses within SMES system for compensating output fluctuation of wind power farm

Energy Technology Data Exchange (ETDEWEB)

Park, S. I.; Kim, J. H.; Le, T. D.; Lee, D. H.; Kim, H. M. [Jeju National University, Jeju (Korea, Republic of); Yoon, Y. S. [Dept. of Electrical Engineering, Shin Ansan University, Ansan (Korea, Republic of); Yoon, K. Y. [Dept. of lectrical and Electronic Engineering, Yonsei University, Seoul (Korea, Republic of)

2014-12-15

Output fluctuation which is generated in wind power farm can hinder stability of total power system. The electric energy storage (EES) reduces unstable output, and superconducting magnetic energy storage (SMES) of various EESs has the proper performance for output compensation of wind power farm since it charges and discharges large scale power quickly with high efficiency. However, because of the change of current within SMES, the electromagnetic losses occur in the process of output compensation. In this paper, the thermal effect of the losses that occur in SMES system while compensating in wind power farm is analyzed. The output analysis of wind power farm is processed by numerical analysis, and the losses of SMES system is analyzed by 3D finite element analysis (FEA) simulation tool.

Analysis of losses within SMES system for compensating output fluctuation of wind power farm

International Nuclear Information System (INIS)

Park, S. I.; Kim, J. H.; Le, T. D.; Lee, D. H.; Kim, H. M.; Yoon, Y. S.; Yoon, K. Y.

2014-01-01

Output fluctuation which is generated in wind power farm can hinder stability of total power system. The electric energy storage (EES) reduces unstable output, and superconducting magnetic energy storage (SMES) of various EESs has the proper performance for output compensation of wind power farm since it charges and discharges large scale power quickly with high efficiency. However, because of the change of current within SMES, the electromagnetic losses occur in the process of output compensation. In this paper, the thermal effect of the losses that occur in SMES system while compensating in wind power farm is analyzed. The output analysis of wind power farm is processed by numerical analysis, and the losses of SMES system is analyzed by 3D finite element analysis (FEA) simulation tool.

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.

High power, short pulses ultraviolet laser for the development of a new x-ray laser

International Nuclear Information System (INIS)

Meixler, L.; Nam, C.H.; Robinson, J.; Tighe, W.; Krushelnick, K.; Suckewer, S.; Goldhar, J.; Seely, J.; Feldman, U.

1989-04-01

A high power, short pulse ultraviolet laser system (Powerful Picosecond-Laser) has been developed at the Princeton Plasma Physics Laboratory (PPPL) as part of experiments designed to generate shorter wavelength x-ray lasers. With the addition of pulse compression and a final KrF amplifier the laser output is expected to have reached 1/3-1/2 TW (10 12 watts) levels. The laser system, particularly the final amplifier, is described along with some initial soft x-ray spectra from laser-target experiments. The front end of the PP-Laser provides an output of 20--30 GW (10 9 watts) and can be focussed to intensities of /approximately/10 16 W/cm 2 . Experiments using this output to examine the effects of a prepulse on laser-target interaction are described. 19 refs., 14 figs

Output regularization of SVM seizure predictors: Kalman Filter versus the "Firing Power" method.

Science.gov (United States)

Teixeira, Cesar; Direito, Bruno; Bandarabadi, Mojtaba; Dourado, António

2012-01-01

Two methods for output regularization of support vector machines (SVMs) classifiers were applied for seizure prediction in 10 patients with long-term annotated data. The output of the classifiers were regularized by two methods: one based on the Kalman Filter (KF) and other based on a measure called the "Firing Power" (FP). The FP is a quantification of the rate of the classification in the preictal class in a past time window. In order to enable the application of the KF, the classification problem was subdivided in a two two-class problem, and the real-valued output of SVMs was considered. The results point that the FP method raise less false alarms than the KF approach. However, the KF approach presents an higher sensitivity, but the high number of false alarms turns their applicability negligible in some situations.

Phonological, visual, and semantic coding strategies and children's short-term picture memory span

OpenAIRE

Henry, L.; Messer, D. J.; Luger-Klein, S.; Crane, L.

2012-01-01

Three experiments addressed controversies in the previous literature on the development of phonological and other forms of short-term memory coding in children, using assessments of picture memory span that ruled out potentially confounding effects of verbal input and output. Picture materials were varied in terms of phonological similarity, visual similarity, semantic similarity, and word length. Older children (6/8-year-olds), but not younger children (4/5-year-olds), demonstrated robust an...

Control strategies to optimise power output in heave buoy energy convertors

International Nuclear Information System (INIS)

Abu Zarim, M A U A; Sharip, R M

2013-01-01

Wave energy converter (WEC) designs are always discussed in order to obtain an optimum design to generate the power from the wave. Output power from wave energy converter can be improved by controlling the oscillation in order to acquire the interaction between the WEC and the incident wave.The purpose of this research is to study the heave buoys in the interest to generate an optimum power output by optimising the phase control and amplitude in order to maximise the active power. In line with the real aims of this study which investigate the theory and function and hence optimise the power generation of heave buoys as renewable energy sources, the condition that influence the heave buoy must be understand in which to propose the control strategies that can be use to control parameters to obtain optimum power output. However, this research is in an early stage, and further analysis and technical development is require

Gradient decent based multi-objective cultural differential evolution for short-term hydrothermal optimal scheduling of economic emission with integrating wind power and photovoltaic power

International Nuclear Information System (INIS)

Zhang, Huifeng; Yue, Dong; Xie, Xiangpeng; Dou, Chunxia; Sun, Feng

2017-01-01

With the integration of wind power and photovoltaic power, optimal operation of hydrothermal power system becomes great challenge due to its non-convex, stochastic and complex-coupled constrained characteristics. This paper extends short-term hydrothermal system optimal model into short-term hydrothermal optimal scheduling of economic emission while considering integrated intermittent energy resources (SHOSEE-IIER). For properly solving SHOSEE-IIER problem, a gradient decent based multi-objective cultural differential evolution (GD-MOCDE) is proposed to improve the optimal efficiency of SHOSEE-IIER combined with three designed knowledge structures, which mainly enhances search ability of differential evolution in the shortest way. With considering those complex-coupled and stochastic constraints, a heuristic constraint-handling measurement is utilized to tackle with them both in coarse and fine tuning way, and probability constraint-handling procedures are taken to properly handle those stochastic constraints combined with their probability density functions. Ultimately, those approaches are implemented on five test systems, which testify the optimization efficiency of proposed GD-MOCDE and constraint-handling efficiency for system load balance, water balance and stochastic constraint-handling measurements, those obtained results reveal that the proposed GD-MOCDE can properly solve the SHOSEE-IIER problem combined with those constraint-handling approaches. - Highlights: • Gradient decent method is proposed to improve mutation operator. • Hydrothermal system is extended to hybrid energy system. • The uncertainty constraint is converted into deterministic constraint. • The results show the viability and efficiency of proposed algorithm.

Forecasting short-term wind farm production in complex terrain. Volume 1

International Nuclear Information System (INIS)

LeBlanc, M.

2005-01-01

Wind energy forecasting adds financial value to wind farms and may soon become a regulatory requirement. A robust information technology system is essential for addressing industry demands. Various forecasting methodologies for short-term wind production in complex terrain were presented. Numerical weather predictions were discussed with reference to supervisory control and data acquisition (SCADA) system site measurements. Forecasting methods using wind speed, direction, temperature and pressure, as well as issues concerning statistical modelling were presented. Model output statistics and neural networks were reviewed, as well as significant components of error. Results from a Garrad Hassan forecaster with a European wind farm were presented, including wind speed evaluation, and forecast horizon for T + 1 hours, T + 12 hours, and T + 36 hours. It was suggested that buy prices often reflect the cost of under-prediction, and that forecasting has more potential where the spread is greatest. Accurate T + 19 hours to T + 31 hours could enable participation in the day-ahead market, which is less volatile and prices are usually better. Estimates of possible profits per annum through the use of GH forecaster power predictions were presented, calculated over and above spilling power to the grid. It was concluded that accurate forecasts combined with certainty evaluation enables the optimization of wind energy in the market, and is applicable to a wide range of weather regimes and terrain types. It was suggested that site feedback is essential for good forecasts at short horizons, and that the value of forecasting is dependent on the market. refs., tabs., figs

Modelling and Prediction of Photovoltaic Power Output Using Artificial Neural Networks

Directory of Open Access Journals (Sweden)

Aminmohammad Saberian

2014-01-01

Full Text Available This paper presents a solar power modelling method using artificial neural networks (ANNs. Two neural network structures, namely, general regression neural network (GRNN feedforward back propagation (FFBP, have been used to model a photovoltaic panel output power and approximate the generated power. Both neural networks have four inputs and one output. The inputs are maximum temperature, minimum temperature, mean temperature, and irradiance; the output is the power. The data used in this paper started from January 1, 2006, until December 31, 2010. The five years of data were split into two parts: 2006–2008 and 2009-2010; the first part was used for training and the second part was used for testing the neural networks. A mathematical equation is used to estimate the generated power. At the end, both of these networks have shown good modelling performance; however, FFBP has shown a better performance comparing with GRNN.

Standardizing the performance evaluation of short-term wind prediction models

DEFF Research Database (Denmark)

Madsen, Henrik; Pinson, Pierre; Kariniotakis, G.

2005-01-01

Short-term wind power prediction is a primary requirement for efficient large-scale integration of wind generation in power systems and electricity markets. The choice of an appropriate prediction model among the numerous available models is not trivial, and has to be based on an objective...... evaluation of model performance. This paper proposes a standardized protocol for the evaluation of short-term wind-poser preciction systems. A number of reference prediction models are also described, and their use for performance comparison is analysed. The use of the protocol is demonstrated using results...... from both on-shore and off-shore wind forms. The work was developed in the frame of the Anemos project (EU R&D project) where the protocol has been used to evaluate more than 10 prediction systems....

High Power Tm3+-Doped Fiber Lasers Tuned by a Variable Reflective Output Coupler

Directory of Open Access Journals (Sweden)

Yulong Tang

2008-01-01

Full Text Available Wide wavelength tuning by a variable reflective output coupler is demonstrated in high-power double-clad Tm3+-doped silica fiber lasers diode-pumped at ∼790  nm. Varying the output coupling from 96% to 5%, the laser wavelength is tuned over a range of 106  nm from 1949 to 2055  nm. The output power exceeds 20  W over 90-nm range and the maximum output power is 32  W at 1949  nm for 51-W launched pump power, corresponding to a slope efficiency of ∼70%. Assisted with different fiber lengths, the tuning range is expanded to 240  nm from 1866 to 2107  nm with the output power larger than 10  W.

Long-term associative learning predicts verbal short-term memory performance

OpenAIRE

Jones, Gary; Macken, Bill

2017-01-01

Studies using tests such as digit span and nonword repetition have implicated short-term memory across a range of developmental domains. Such tests ostensibly assess specialized processes for the short-term manipulation and maintenance of information that are often argued to enable long-term learning. However, there is considerable evidence for an influence of long-term linguistic learning on performance in short-term memory tasks that brings into question the role of a specialized short-term...

Long-term associative learning predicts verbal short-term memory performance.

Science.gov (United States)

Jones, Gary; Macken, Bill

2018-02-01

Studies using tests such as digit span and nonword repetition have implicated short-term memory across a range of developmental domains. Such tests ostensibly assess specialized processes for the short-term manipulation and maintenance of information that are often argued to enable long-term learning. However, there is considerable evidence for an influence of long-term linguistic learning on performance in short-term memory tasks that brings into question the role of a specialized short-term memory system separate from long-term knowledge. Using natural language corpora, we show experimentally and computationally that performance on three widely used measures of short-term memory (digit span, nonword repetition, and sentence recall) can be predicted from simple associative learning operating on the linguistic environment to which a typical child may have been exposed. The findings support the broad view that short-term verbal memory performance reflects the application of long-term language knowledge to the experimental setting.

Speech Timing and Verbal Short-Term Memory: Evidence for Contrasting Deficits in Down Syndrome and Williams Syndrome

Science.gov (United States)

Jarrold, Christopher; Cowan, Nelson; Hewes, Alexa K.; Riby, Deborah M.

2004-01-01

This study explored the degree of verbal short-term memory deficit among individuals with Down syndrome and Williams syndrome, and the extent to which any such impairment could be accounted for by a relative slowing of rehearsal and output processes. Measures of serial recall and detailed assessments of speeded articulation for short and long…

Flexible, transparent and exceptionally high power output nanogenerators based on ultrathin ZnO nanoflakes

Science.gov (United States)

van Ngoc, Huynh; Kang, Dae Joon

2016-02-01

Novel nanogenerator structures composed of ZnO nanoflakes of less than 10 nm thickness were fabricated using a novel method involving a facile synthetic route and a rational design. The fabricated nanogenerators exhibited a short-circuit current density of 67 μA cm-2, a peak-to-peak open-circuit voltage of 110 V, and an overall output power density exceeding 1.2 mW cm-2, and to the best of our knowledge, these are the best values that have been reported so far in the literature on ZnO-based nanogenerators. We demonstrated that our nanogenerator design could instantaneously power 20 commercial green light-emitting diodes without any additional energy storage processes. Both the facile synthetic route for the ZnO nanoflakes and the straightforward device fabrication process present great scaling potential in order to power mobile and personal electronics that can be used in smart wearable systems, transparent and flexible devices, implantable telemetric energy receivers, electronic emergency equipment, and other self-powered nano/micro devices.Novel nanogenerator structures composed of ZnO nanoflakes of less than 10 nm thickness were fabricated using a novel method involving a facile synthetic route and a rational design. The fabricated nanogenerators exhibited a short-circuit current density of 67 μA cm-2, a peak-to-peak open-circuit voltage of 110 V, and an overall output power density exceeding 1.2 mW cm-2, and to the best of our knowledge, these are the best values that have been reported so far in the literature on ZnO-based nanogenerators. We demonstrated that our nanogenerator design could instantaneously power 20 commercial green light-emitting diodes without any additional energy storage processes. Both the facile synthetic route for the ZnO nanoflakes and the straightforward device fabrication process present great scaling potential in order to power mobile and personal electronics that can be used in smart wearable systems, transparent and flexible

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

Laser fiber cleaving techniques: effects on tip morphology and power output.

Science.gov (United States)

Vassantachart, Janna M; Lightfoot, Michelle; Yeo, Alexander; Maldonado, Jonathan; Li, Roger; Alsyouf, Muhannad; Martin, Jacob; Lee, Michael; Olgin, Gaudencio; Baldwin, D Duane

2015-01-01

Proper cleaving of reusable laser fibers is needed to maintain optimal functionality. This study quantifies the effect of different cleaving tools on power output of the holmium laser fiber and demonstrates morphologic changes using microscopy. The uncleaved tips of new 272 μm reusable laser fibers were used to obtain baseline power transmission values at 3 W (0.6 J, 5 Hz). Power output for each of four cleaving techniques-11-blade scalpel, scribe pen cleaving tool, diamond cleaving wheel, and suture scissors-was measured in a single-blinded fashion. Dispersion of light from the fibers was compared with manufacturer specifications and rated as "ideal," "acceptable," or "unacceptable" by blinded reviewers. The fiber tips were also imaged using confocal and scanning electron microscopy. Independent samples Kruskal-Wallis test and chi square were used for statistical analysis (αtrend that was highly significant (Ptrend as the power output results (P<0.001). Microscopy showed that the scribe pen produced small defects along the fiber cladding but maintained a smooth, flat core surface. The other cleaving techniques produced defects on both the core and cladding. Cleaving techniques produce a significant effect on the initial power transmitted by reusable laser fibers. The scribe pen cleaving tool produced the most consistent and highest average power output.

Development of Compact Ozonizer with High Ozone Output by Pulsed Power

Science.gov (United States)

Tanaka, Fumiaki; Ueda, Satoru; Kouno, Kanako; Sakugawa, Takashi; Akiyama, Hidenori; Kinoshita, Youhei

Conventional ozonizer with a high ozone output using silent or surface discharges needs a cooling system and a dielectric barrier, and therefore becomes a large machine. A compact ozonizer without the cooling system and the dielectric barrier has been developed by using a pulsed power generated discharge. The wire to plane electrodes made of metal have been used. However, the ozone output was low. Here, a compact and high repetition rate pulsed power generator is used as an electric source of a compact ozonizer. The ozone output of 6.1 g/h and the ozone yield of 86 g/kWh are achieved at 500 pulses per second, input average power of 280 W and an air flow rate of 20 L/min.

A study on electric power management for power producer-suppliers utilizing output of megawatt-solar power plants

Directory of Open Access Journals (Sweden)

Hirotaka Takano

2016-01-01

Full Text Available The growth in penetration of photovoltaic generation units (PVs has brought new power management ideas, which achieve more profitable operation, to Power Producer-Suppliers (PPSs. The expected profit for the PPSs will improve if they appropriately operate their controllable generators and sell the generated electricity to contracted customers and Power Exchanges together with the output of Megawatt-Solar Power Plants (MSPPs. Moreover, we can expect that the profitable cooperation between the PPSs and the MSPPs decreases difficulties in the supply-demand balancing operation for the main power grids. However, it is necessary that the PPSs treat the uncertainty in output prediction of PVs carefully. This is because there is a risk for them to pay a heavy imbalance penalty. This paper presents a problem framework and its solution to make the optimal power management plan for the PPSs in consideration with the electricity procurement from the MSPPs. The validity of the authors’ proposal is verified through numerical simulations and discussions of their results.

Technique for enhancing the power output of an electrostatic generator employing parametric resonance

Science.gov (United States)

Post, Richard F.

2016-02-23

A circuit-based technique enhances the power output of electrostatic generators employing an array of axially oriented rods or tubes or azimuthal corrugated metal surfaces for their electrodes. During generator operation, the peak voltage across the electrodes occurs at an azimuthal position that is intermediate between the position of minimum gap and maximum gap. If this position is also close to the azimuthal angle where the rate of change of capacity is a maximum, then the highest rf power output possible for a given maximum allowable voltage at the minimum gap can be attained. This rf power output is then coupled to the generator load through a coupling condenser that prevents suppression of the dc charging potential by conduction through the load. Optimized circuit values produce phase shifts in the rf output voltage that allow higher power output to occur at the same voltage limit at the minimum gap position.

Short-term load forecasting by a neuro-fuzzy based approach

Energy Technology Data Exchange (ETDEWEB)

Ruey-Hsun Liang; Ching-Chi Cheng [National Yunlin University of Science and Technology (China). Dept. of Electrical Engineering

2002-02-01

An approach based on an artificial neural network (ANN) combined with a fuzzy system is proposed for short-term load forecasting. This approach was developed in order to reach the desired short-term load forecasting in an efficient manner. Over the past few years, ANNs have attained the ability to manage a great deal of system complexity and are now being proposed as powerful computational tools. In order to select the appropriate load as the input for the desired forecasting, the Pearson analysis method is first applied to choose two historical record load patterns that are similar to the forecasted load pattern. These two load patterns and the required weather parameters are then fuzzified and input into a neural network for training or testing the network. The back-propagation (BP) neural network is applied to determine the preliminary forecasted load. In addition, the rule base for the fuzzy inference machine contains important linguistic membership function terms with knowledge in the form of fuzzy IF-THEN rules. This produces the load correction inference from the historical information and past forecasted load errors to obtain an inferred load error. Adding the inferred load error to the preliminary forecasted load, we can obtain the finial forecasted load. The effectiveness of the proposed approach to the short-term load-forecasting problem is demonstrated using practical data from the Taiwan Power Company (TPC). (Author)

Pigeon visual short-term memory directly compared to primates.

Science.gov (United States)

Wright, Anthony A; Elmore, L Caitlin

2016-02-01

Three pigeons were trained to remember arrays of 2-6 colored squares and detect which of two squares had changed color to test their visual short-term memory. Procedures (e.g., stimuli, displays, viewing times, delays) were similar to those used to test monkeys and humans. Following extensive training, pigeons performed slightly better than similarly trained monkeys, but both animal species were considerably less accurate than humans with the same array sizes (2, 4 and 6 items). Pigeons and monkeys showed calculated memory capacities of one item or less, whereas humans showed a memory capacity of 2.5 items. Despite the differences in calculated memory capacities, the pigeons' memory results, like those from monkeys and humans, were all well characterized by an inverse power-law function fit to d' values for the five display sizes. This characterization provides a simple, straightforward summary of the fundamental processing of visual short-term memory (how visual short-term memory declines with memory load) that emphasizes species similarities based upon similar functional relationships. By closely matching pigeon testing parameters to those of monkeys and humans, these similar functional relationships suggest similar underlying processes of visual short-term memory in pigeons, monkeys and humans. Copyright © 2015 Elsevier B.V. All rights reserved.

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...

Online Short-term Solar Power Forecasting

DEFF Research Database (Denmark)

Bacher, Peder; Madsen, Henrik; Nielsen, Henrik Aalborg

2011-01-01

This poster presents two approaches to online forecasting of power production from PV systems. The methods are suited for online forecasting in many applications and here they are used to predict hourly values of solar power for horizons up to 32 hours.......This poster presents two approaches to online forecasting of power production from PV systems. The methods are suited for online forecasting in many applications and here they are used to predict hourly values of solar power for horizons up to 32 hours....

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 ...

Very short-term rainfall forecasting by effectively using the ensemble outputs of numerical weather prediction models

Science.gov (United States)

Wu, Ming-Chang; Lin, Gwo-Fong; Feng, Lei; Hwang, Gong-Do

2017-04-01

In Taiwan, heavy rainfall brought by typhoons often causes serious disasters and leads to loss of life and property. In order to reduce the impact of these disasters, accurate rainfall forecasts are always important for civil protection authorities to prepare proper measures in advance. In this study, a methodology is proposed for providing very short-term (1- to 6-h ahead) rainfall forecasts in a basin-scale area. The proposed methodology is developed based on the use of analogy reasoning approach to effectively integrate the ensemble precipitation forecasts from a numerical weather prediction system in Taiwan. To demonstrate the potential of the proposed methodology, an application to a basin-scale area (the Choshui River basin located in west-central Taiwan) during five typhoons is conducted. The results indicate that the proposed methodology yields more accurate hourly rainfall forecasts, especially the forecasts with a lead time of 1 to 3 hours. On average, improvement of the Nash-Sutcliffe efficiency coefficient is about 14% due to the effective use of the ensemble forecasts through the proposed methodology. The proposed methodology is expected to be useful for providing accurate very short-term rainfall forecasts during typhoons.

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.

Investigation on the integral output power model of a large-scale wind farm

Institute of Scientific and Technical Information of China (English)

BAO Nengsheng; MA Xiuqian; NI Weidou

2007-01-01

The integral output power model of a large-scale wind farm is needed when estimating the wind farm's output over a period of time in the future.The actual wind speed power model and calculation method of a wind farm made up of many wind turbine units are discussed.After analyzing the incoming wind flow characteristics and their energy distributions,and after considering the multi-effects among the wind turbine units and certain assumptions,the incoming wind flow model of multi-units is built.The calculation algorithms and steps of the integral output power model of a large-scale wind farm are provided.Finally,an actual power output of the wind farm is calculated and analyzed by using the practical measurement wind speed data.The characteristics of a large-scale wind farm are also discussed.

Committing to coal and gas: Long-term contracts, regulation, and fuel switching in power generation

Science.gov (United States)

Rice, Michael

short-term fuel switching in power production. During the era prior to shale gas and electricity market deregulation, I do not find evidence that gas generation substituted for coal in response to fuel price changes. However, I do find evidence that coal plant operations are constrained by fuel contracts. As the min-take commitment to coal increases, changes to annual coal plant output decrease. My conclusions are robust in spite of bias due to the selective reporting of proprietary coal delivery contracts by utilities.

High Output Piezo/Triboelectric Hybrid Generator

Science.gov (United States)

Jung, Woo-Suk; Kang, Min-Gyu; Moon, Hi Gyu; Baek, Seung-Hyub; Yoon, Seok-Jin; Wang, Zhong-Lin; Kim, Sang-Woo; Kang, Chong-Yun

2015-03-01

Recently, piezoelectric and triboelectric energy harvesting devices have been developed to convert mechanical energy into electrical energy. Especially, it is well known that triboelectric nanogenerators have a simple structure and a high output voltage. However, whereas nanostructures improve the output of triboelectric generators, its fabrication process is still complicated and unfavorable in term of the large scale and long-time durability of the device. Here, we demonstrate a hybrid generator which does not use nanostructure but generates much higher output power by a small mechanical force and integrates piezoelectric generator into triboelectric generator, derived from the simultaneous use of piezoelectric and triboelectric mechanisms in one press-and-release cycle. This hybrid generator combines high piezoelectric output current and triboelectric output voltage, which produces peak output voltage of ~370 V, current density of ~12 μA.cm-2, and average power density of ~4.44 mW.cm-2. The output power successfully lit up 600 LED bulbs by the application of a 0.2 N mechanical force and it charged a 10 μF capacitor to 10 V in 25 s. Beyond energy harvesting, this work will provide new opportunities for developing a small, built-in power source in self-powered electronics such as mobile electronics.

High Output Piezo/Triboelectric Hybrid Generator

Science.gov (United States)

Jung, Woo-Suk; Kang, Min-Gyu; Moon, Hi Gyu; Baek, Seung-Hyub; Yoon, Seok-Jin; Wang, Zhong-Lin; Kim, Sang-Woo; Kang, Chong-Yun

2015-01-01

Recently, piezoelectric and triboelectric energy harvesting devices have been developed to convert mechanical energy into electrical energy. Especially, it is well known that triboelectric nanogenerators have a simple structure and a high output voltage. However, whereas nanostructures improve the output of triboelectric generators, its fabrication process is still complicated and unfavorable in term of the large scale and long-time durability of the device. Here, we demonstrate a hybrid generator which does not use nanostructure but generates much higher output power by a small mechanical force and integrates piezoelectric generator into triboelectric generator, derived from the simultaneous use of piezoelectric and triboelectric mechanisms in one press-and-release cycle. This hybrid generator combines high piezoelectric output current and triboelectric output voltage, which produces peak output voltage of ~370 V, current density of ~12 μA·cm−2, and average power density of ~4.44 mW·cm−2. The output power successfully lit up 600 LED bulbs by the application of a 0.2 N mechanical force and it charged a 10 μF capacitor to 10 V in 25 s. Beyond energy harvesting, this work will provide new opportunities for developing a small, built-in power source in self-powered electronics such as mobile electronics. PMID:25791299

Online short-term solar power forecasting

DEFF Research Database (Denmark)

Bacher, Peder; Madsen, Henrik; Nielsen, Henrik Aalborg

2009-01-01

This paper describes a new approach to online forecasting of power production from PV systems. The method is suited to online forecasting in many applications and in this paper it is used to predict hourly values of solar power for horizons of up to 36 hours. The data used is fifteen......-minute observations of solar power from 21 PV systems located on rooftops in a small village in Denmark. The suggested method is a two-stage method where first a statistical normalization of the solar power is obtained using a clear sky model. The clear sky model is found using statistical smoothing techniques....... Then forecasts of the normalized solar power are calculated using adaptive linear time series models. Both autoregressive (AR) and AR with exogenous input (ARX) models are evaluated, where the latter takes numerical weather predictions (NWPs) as input. The results indicate that for forecasts up to two hours...

Analysis of the spontaneous variations in wind power and necessary continuous regulation of hydro-electric and thermal power, related to a future Swedish power system

Energy Technology Data Exchange (ETDEWEB)

Holm, J O; Lindstrom, P O

1982-09-01

Wind power is unlike conventional electric power generation, since the output fluctuates uncontrollably. These fluctuations must be balanced by controlled generation from other power sources. This will create new and interesting demands on the reserves in the power system. The short-term fluctuations have a low simultaneity factor and must be balanced by an automatic frequency control reserve. In Sweden, this consists of automatically controlled hydro-electric power. The report contains calculations of the amount by which the demand on reserves will increase when wind power is introduced.

Short-term variability of CYG X-1

International Nuclear Information System (INIS)

Oda, M.; Doi, K.; Ogawara, Y.; Takagishi, K.; Wada, M.

1975-01-01

The short-term X-ray variability distinguishes Cyg X-1, which is the most likely candidate of the black hole, from other X-ray sources. Present status of our knowledge on this short-term variation mainly from the Uhuru, the MIT and the GSFC observations is reviewed. The nature of impulsive variations which compose the time variation exceeding the statistical fluctuation is discussed. There are indications that the energy spectrum of large pulses is harder than the average spectrum or the large pulses are the characteristics of the hard component of the spectrum if it is composed of two, soft and hard, components. Features of the variations may be partly simulated by the superposition of random short-noise pulses with a fraction of a second duration. However, the autocorrelation analysis and the dynamic spectrum analysis indicate that the correlation lasts for several seconds and in the variation buried are some regularities which exhibit power concentrations in several frequency bands; 0.2 -- 0.3, 0.4 -- 0.5, 0.8, 1.2 -- 1.5 Hz. There are several possible interpretation of these results in terms of: e.g. a) a mixture of short-noise pulses with two or more constant durations, b) the shape of the basic shot-noise pulse, c) bunching of the pulses, d) superposition of wave-packets or temporal oscillations. But we have not yet reached any definite understandings in the nature of the variabilities. The sub-structure of the fluctuations on a time scale of milli-second suggested by two investigations is also discussed. (auth.)

INFLUENCE OF FISCAL POLICY DYNAMICS ON OUTPUT MANAGEMENT

Directory of Open Access Journals (Sweden)

Predescu Antoniu

2013-04-01

Full Text Available Dynamics of fiscal policy, more specific rise in fiscal pressure, increase which can be obtained either through enforcing one or more taxes, or by augmenting at least a tax, has a powerful impact on output management – visible, in the first place, in the realm of output size. But, not only output size will vary, after an increase in fiscal pressure, at least because output management is dealing with more than issue of producing a certain quantity of products, material or not, goods and/or services. Products are made for selling, but selling is impossible but through price and with a price; price is an essential economic variable, both in microeconomic and macroeconomic spheres. Thus, on one side rise in fiscal pressure determines, at least in short term, and, of course, if producers pay, or even support, a tax, be it newly enforced or (newly augmented, a rise of prices for sold products, and, on the other side, this results in a variation in output size, e.g. a reduced output volume, but, though, not in a linear trend. The dynamics, in this case of economic mechanism whose yield is a reduced volume of goods and/or services, in not linear, because essential are, too, the characteristics of products, from which effects of demand price elasticity and offer price elasticity influence significantly, in this framework, output management.

Power-Combined GaN Amplifier with 2.28-W Output Power at 87 GHz

Science.gov (United States)

Fung, King Man; Ward, John; Chattopadhyay, Goutam; Lin, Robert H.; Samoska, Lorene A.; Kangaslahti, Pekka P.; Mehdi, Imran; Lambrigtsen, Bjorn H.; Goldsmith, Paul F.; Soria, Mary M.;

Maximum Power Output of Quantum Heat Engine with Energy Bath

Directory of Open Access Journals (Sweden)

Shengnan Liu

2016-05-01

Full Text Available The difference between quantum isoenergetic process and quantum isothermal process comes from the violation of the law of equipartition of energy in the quantum regime. To reveal an important physical meaning of this fact, here we study a special type of quantum heat engine consisting of three processes: isoenergetic, isothermal and adiabatic processes. Therefore, this engine works between the energy and heat baths. Combining two engines of this kind, it is possible to realize the quantum Carnot engine. Furthermore, considering finite velocity of change of the potential shape, here an infinite square well with moving walls, the power output of the engine is discussed. It is found that the efficiency and power output are both closely dependent on the initial and final states of the quantum isothermal process. The performance of the engine cycle is shown to be optimized by control of the occupation probability of the ground state, which is determined by the temperature and the potential width. The relation between the efficiency and power output is also discussed.

Short-term trends in the gas industry - Panorama 2008

International Nuclear Information System (INIS)

2008-01-01

In a context of high investment costs and rising energy prices, and recurring unseasonably warm temperatures in recent years, the growth of natural gas demand is slowing. On the supply side, and on the demand side too, new trends are emerging, with potentially powerful impact on the short-and long-term development of the industry

An integrated control method for a wind farm to reduce frequency deviations in a small power system

International Nuclear Information System (INIS)

Kaneko, Toshiaki; Uehara, Akie; Senjyu, Tomonobu; Yona, Atsushi; Urasaki, Naomitsu

2011-01-01

Output power of wind turbine generator (WTG) is not constant and fluctuates due to wind speed changes. To reduce the adverse effects of the power system introducing WTGs, there are several published reports on output power control of WTGs detailing various researches based on pitch angle control, variable speed wind turbines, energy storage systems, and so on. In this context, this paper presents an integrated control method for a WF to reduce frequency deviations in a small power system. In this study, the WF achieves the frequency control with two control schemes: load estimation and short-term ahead wind speed prediction. For load estimation in the small power system, a minimal-order observer is used as disturbance observer. The estimated load is utilized to determine the output power command of the WF. To regulate the output power command of the WF according to wind speed changing, short-term ahead wind speed is predicted by using least-squares method. The predicted wind speed adjusts the output power command of the WF as a multiplying factor with fuzzy reasoning. By means of the proposed method, the WF can operate according to the wind and load conditions. In the WF system, each output power of the WTGs is controlled by regulating each pitch angle. For increasing acquisition power of the WF, a dispatch control method also is proposed. In the pitch angle control system of each WTG, generalized predictive control (GPC) is applied to enhance the control performance. Effectiveness of the proposed method is verified by the numerical simulations.

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.

Design and optimization of G-band extended interaction klystron with high output power

Science.gov (United States)

Li, Renjie; Ruan, Cunjun; Zhang, Huafeng

2018-03-01

A ladder-type Extended Interaction Klystron (EIK) with unequal-length slots in the G-band is proposed and designed. The key parameters of resonance cavities working in the π mode are obtained based on the theoretical analysis and 3D simulation. The influence of the device fabrication tolerance on the high-frequency performance is analyzed in detail, and it is found that at least 5 μm of machining precision is required. Thus, the dynamic tuning is required to compensate for the frequency shift and increase the bandwidth. The input and output coupling hole dimensions are carefully designed to achieve high output power along with a broad bandwidth. The effect of surface roughness of the metallic material on the output power has been investigated, and it is proposed that lower surface roughness leads to higher output power. The focusing magnetic field is also optimized to 0.75 T in order to maintain the beam transportation and achieve high output power. With 16.5 kV operating voltage and 0.30 A beam current, the output power of 360 W, the efficiency of 7.27%, the gain of 38.6 dB, and the 3 dB bandwidth of 500 MHz are predicted. The output properties of the EIK show great stability with the effective suppression of oscillation and mode competition. Moreover, small-signal theory analysis and 1D code AJDISK calculations are carried out to verify the results of 3D PIC simulations. A close agreement among the three methods proves the relative validity and the reliability of the designed EIK. Thus, it is indicated that the EIK with unequal-length slots has potential for power improvement and bandwidth extension.

Quantifying and Reducing Uncertainty in Correlated Multi-Area Short-Term Load Forecasting

Energy Technology Data Exchange (ETDEWEB)

Sun, Yannan; Hou, Zhangshuan; Meng, Da; Samaan, Nader A.; Makarov, Yuri V.; Huang, Zhenyu

2016-07-17

In this study, we represent and reduce the uncertainties in short-term electric load forecasting by integrating time series analysis tools including ARIMA modeling, sequential Gaussian simulation, and principal component analysis. The approaches are mainly focusing on maintaining the inter-dependency between multiple geographically related areas. These approaches are applied onto cross-correlated load time series as well as their forecast errors. Multiple short-term prediction realizations are then generated from the reduced uncertainty ranges, which are useful for power system risk analyses.

Modeling Long-Term Fluvial Incision : Shall we Care for the Details of Short-Term Fluvial Dynamics?

Science.gov (United States)

Lague, D.; Davy, P.

2008-12-01

Fluvial incision laws used in numerical models of coupled climate, erosion and tectonics systems are mainly based on the family of stream power laws for which the rate of local erosion E is a power function of the topographic slope S and the local mean discharge Q : E = K Qm Sn. The exponents m and n are generally taken as (0.35, 0.7) or (0.5, 1), and K is chosen such that the predicted topographic elevation given the prevailing rates of precipitation and tectonics stay within realistic values. The resulting topographies are reasonably realistic, and the coupled system dynamics behaves somehow as expected : more precipitation induces increased erosion and localization of the deformation. Yet, if we now focus on smaller scale fluvial dynamics (the reach scale), recent advances have suggested that discharge variability, channel width dynamics or sediment flux effects may play a significant role in controlling incision rates. These are not factored in the simple stream power law model. In this work, we study how these short- term details propagate into long-term incision dynamics within the framework of surface/tectonics coupled numerical models. To upscale the short term dynamics to geological timescales, we use a numerical model of a trapezoidal river in which vertical and lateral incision processes are computed from fluid shear stress at a daily timescale, sediment transport and protection effects are factored in, as well as a variable discharge. We show that the stream power law model might still be a valid model but that as soon as realistic effects are included such as a threshold for sediment transport, variable discharge and dynamic width the resulting exponents m and n can be as high as 2 and 4. This high non-linearity has a profound consequence on the sensitivity of fluvial relief to incision rate. We also show that additional complexity does not systematically translates into more non-linear behaviour. For instance, considering only a dynamical width

Regulation of the output power at the resonant converter

Energy Technology Data Exchange (ETDEWEB)

Stefanov, Goce G.; Sarac, Vasilija J. [University Goce Delecev-Stip, Faculty of Electrical Engineering, Radovis (Macedonia, The Former Yugoslav Republic of); Karadzinov, Ljupco V., E-mail: goce.stefanov@ugd.edu.mk [University Kiril and Methodyus-Skopje, FEIT Skopje(Macedonia, The Former Yugoslav Republic of)

2011-07-01

In this paper a method for regulating an alternating current voltage source with pair of IGBT transistor’s modules, in a full bridge configuration with series resonant converter is given. With the developed method a solution is obtained which can regulate the phase difference between output voltage and current through the inductor, in order to maintain maximum output power. Control electronic via feedback signals regulates the energy transfer to the tank by changing the pulse width of signals which are used as inputs to the gates of the IGBTs. By increasing or decreasing the pulse width transmitted to the various gates of the IGBT the energy transfer to the tank is increased or decreased . PowerSim simulations program is used for development of controlling methodology. Developed method is practically implemented in a prototype of the device for phase control of resonant converter with variable the resonant load. Key words: pulse width method, phase regulation , power converter.

Wind power generation and dispatch in competitive power markets

Science.gov (United States)

Abreu, Lisias

Wind energy is currently the fastest growing type of renewable energy. The main motivation is led by more strict emission constraints and higher fuel prices. In addition, recent developments in wind turbine technology and financial incentives have made wind energy technically and economically viable almost anywhere. In restructured power systems, reliable and economical operation of power systems are the two main objectives for the ISO. The ability to control the output of wind turbines is limited and the capacity of a wind farm changes according to wind speeds. Since this type of generation has no production costs, all production is taken by the system. Although, insufficient operational planning of power systems considering wind generation could result in higher system operation costs and off-peak transmission congestions. In addition, a GENCO can participate in short-term power markets in restructured power systems. The goal of a GENCO is to sell energy in such a way that would maximize its profitability. However, due to market price fluctuations and wind forecasting errors, it is essential for the wind GENCO to keep its financial risk at an acceptable level when constituting market bidding strategies. This dissertation discusses assumptions, functions, and methodologies that optimize short-term operations of power systems considering wind energy, and that optimize bidding strategies for wind producers in short-term markets. This dissertation also discusses uncertainties associated with electricity market environment and wind power forecasting that can expose market participants to a significant risk level when managing the tradeoff between profitability and risk.

Brushless power generating system having reduced conducted emissions in output power

International Nuclear Information System (INIS)

Walton, D.N.; Dolan, C.F.; Shah, M.J.

1991-01-01

This patent describes a brushless electrical power generating system. It comprises an exciter for producing alternating current from an exciter rotor; a rectifier mounted for rotation with the rotor for producing a rectified control current from the alternating current; a common mode inductor, coupled to the rectifier, for cancelling common mode noise components within the rectified control current; and a main generator, having a rotating field winding mounted on a main generator rotor excited by the control current and producing an alternating current power output from a stator

Anaerobic power output and propulsion technique in spinal cord injured subjects during wheelchair ergometry

NARCIS (Netherlands)

Dallmeijer, A J; Kappe, Y J; Veeger, DirkJan (H. E. J.); Janssen, T W; van der Woude, L H

1994-01-01

In order to investigate the influence of the level of the spinal cord injury (SCI) on anaerobic or short-term power production and propulsion technique, 23 male SCI subjects performed a 30-second sprint test on a stationary wheelchair ergometer. Kinematic parameters were studied both inter- and

Short-Term Load Forecasting Based on Wavelet Transform and Least Squares Support Vector Machine Optimized by Fruit Fly Optimization Algorithm

Directory of Open Access Journals (Sweden)

Wei Sun

2015-01-01

Full Text Available Electric power is a kind of unstorable energy concerning the national welfare and the people’s livelihood, the stability of which is attracting more and more attention. Because the short-term power load is always interfered by various external factors with the characteristics like high volatility and instability, a single model is not suitable for short-term load forecasting due to low accuracy. In order to solve this problem, this paper proposes a new model based on wavelet transform and the least squares support vector machine (LSSVM which is optimized by fruit fly algorithm (FOA for short-term load forecasting. Wavelet transform is used to remove error points and enhance the stability of the data. Fruit fly algorithm is applied to optimize the parameters of LSSVM, avoiding the randomness and inaccuracy to parameters setting. The result of implementation of short-term load forecasting demonstrates that the hybrid model can be used in the short-term forecasting of the power system.

Short, medium and long term consequences of inadequate defect fuel management

Energy Technology Data Exchange (ETDEWEB)

Roberts, J.G. [CANTECH Associates Limited, Burlington, Ontario (Canada); Nashiem, R.; McQueen, M.; Ma, G. [Bruce Power, Tiverton, Ontario (Canada)

2011-07-01

Defect fuel pencils result in short, medium and long term consequences to the environment within and external to the nuclear power station. The paper will describe these consequences and specify the Defect Fuel Management Practices required to avoid these consequences. (author)

Short, medium and long term consequences of inadequate defect fuel management

International Nuclear Information System (INIS)

Roberts, J.G.; Nashiem, R.; McQueen, M.; Ma, G.

2011-01-01

Defect fuel pencils result in short, medium and long term consequences to the environment within and external to the nuclear power station. The paper will describe these consequences and specify the Defect Fuel Management Practices required to avoid these consequences. (author)

Short, medium and long term consequences of inadequate defect fuel management

International Nuclear Information System (INIS)

Roberts, J.G.; McQueen, M.; Nashiem, R.; Ma, G.

2011-01-01

Defect fuel pencils result in short, medium and long term consequences to the environment within and external to the nuclear power station. The paper will describe these consequences and specify the Defect Fuel Management Practices required to avoid these consequences.

Short, medium and long term consequences of inadequate defect fuel management

Energy Technology Data Exchange (ETDEWEB)

Roberts, J.G. [CANTECH Associates Ltd., Burlington, ON (Canada); McQueen, M.; Nashiem, R.; Ma, G. [Bruce Power, Tiverton, ON (Canada)

2011-07-01

Defect fuel pencils result in short, medium and long term consequences to the environment within and external to the nuclear power station. The paper will describe these consequences and specify the Defect Fuel Management Practices required to avoid these consequences.

Short, medium and long term consequences of inadequate defect fuel management

Energy Technology Data Exchange (ETDEWEB)

Roberts, J.G., E-mail: alchemy@tnt21.com [CANTECH Associates Ltd., Burlington, Ontario (Canada); Nashiem, R.; McQueen, M.; Ma, G., E-mail: Rod.nashiem@brucepower.com, E-mail: Maureen.mcqueen@brucepower.com, E-mail: guoping.ma@brucepower.com [Bruce Power, Tiverton (Canada)

2010-07-01

Defect fuel pencils result in short, medium and long term consequences to the environment within and external to the nuclear power station. The paper will describe these consequences and specify the Defect Fuel Management Practices required to avoid these consequences. (author)

Short, medium and long term consequences of inadequate defect fuel management

International Nuclear Information System (INIS)

Roberts, J.G.; Nashiem, R.; McQueen, M.; Ma, G.

2010-01-01

Defect fuel pencils result in short, medium and long term consequences to the environment within and external to the nuclear power station. The paper will describe these consequences and specify the Defect Fuel Management Practices required to avoid these consequences. (author)

The “Weather Intelligence for Renewable Energies” Benchmarking Exercise on Short-Term Forecasting of Wind and Solar Power Generation

DEFF Research Database (Denmark)

Sperati, Simone; Alessandrini, Stefano; Pinson, Pierre

2015-01-01

the power output of two wind farms and two photovoltaic power plants, in order to compare the merits of forecasts based on different modeling approaches and input data. It was thus possible to obtain a better knowledge of the state of the art in both wind and solar power forecasting, with an overview...

What are the differences between long-term, short-term, and working memory?

Science.gov (United States)

Cowan, Nelson

2008-01-01

In the recent literature there has been considerable confusion about the three types of memory: long-term, short-term, and working memory. This chapter strives to reduce that confusion and makes up-to-date assessments of these types of memory. Long- and short-term memory could differ in two fundamental ways, with only short-term memory demonstrating (1) temporal decay and (2) chunk capacity limits. Both properties of short-term memory are still controversial but the current literature is rather encouraging regarding the existence of both decay and capacity limits. Working memory has been conceived and defined in three different, slightly discrepant ways: as short-term memory applied to cognitive tasks, as a multi-component system that holds and manipulates information in short-term memory, and as the use of attention to manage short-term memory. Regardless of the definition, there are some measures of memory in the short term that seem routine and do not correlate well with cognitive aptitudes and other measures (those usually identified with the term "working memory") that seem more attention demanding and do correlate well with these aptitudes. The evidence is evaluated and placed within a theoretical framework depicted in Fig. 1.

Short-term memory of motor network performance via activity-dependent potentiation of Na+/K+ pump function.

Science.gov (United States)

Zhang, Hong-Yan; Sillar, Keith T

2012-03-20

Brain networks memorize previous performance to adjust their output in light of past experience. These activity-dependent modifications generally result from changes in synaptic strengths or ionic conductances, and ion pumps have only rarely been demonstrated to play a dynamic role. Locomotor behavior is produced by central pattern generator (CPG) networks and modified by sensory and descending signals to allow for changes in movement frequency, intensity, and duration, but whether or how the CPG networks recall recent activity is largely unknown. In Xenopus frog tadpoles, swim bout duration correlates linearly with interswim interval, suggesting that the locomotor network retains a short-term memory of previous output. We discovered an ultraslow, minute-long afterhyperpolarization (usAHP) in network neurons following locomotor episodes. The usAHP is mediated by an activity- and sodium spike-dependent enhancement of electrogenic Na(+)/K(+) pump function. By integrating spike frequency over time and linking the membrane potential of spinal neurons to network performance, the usAHP plays a dynamic role in short-term motor memory. Because Na(+)/K(+) pumps are ubiquitously expressed in neurons of all animals and because sodium spikes inevitably accompany network activity, the usAHP may represent a phylogenetically conserved but largely overlooked mechanism for short-term memory of neural network function. Copyright © 2012 Elsevier Ltd. All rights reserved.

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)

Electric power from near-term fusion reactors

International Nuclear Information System (INIS)

Longhurst, G.R.; Deis, G.A.; Miller, L.G.

1981-01-01

This paper examines requirements and possbilities of electric power production on near-term fusion reactors using low temperature cycle technology similar to that used in some geothermal power systems. Requirements include the need for a working fluid with suitable thermodynamics properties and which is free of oxygen and hydrogen to facilitate tritium management. Thermal storage will also be required due to the short system thermal time constants on near-time reactors. It is possbile to use the FED shield in a binary power cycle, and results are presented of thermodynamic analyses of this system

Advanced Output Coupling for High Power Gyrotrons

Energy Technology Data Exchange (ETDEWEB)

Read, Michael [Calabazas Creek Research, Inc., San Mateo, CA (United States); Ives, Robert Lawrence [Calabazas Creek Research, Inc., San Mateo, CA (United States); Marsden, David [Calabazas Creek Research, Inc., San Mateo, CA (United States); Collins, George [Calabazas Creek Research, Inc., San Mateo, CA (United States); Temkin, Richard [Massachusetts Inst. of Technology (MIT), Cambridge, MA (United States); Guss, William [Massachusetts Inst. of Technology (MIT), Cambridge, MA (United States); Lohr, John [General Atomics, La Jolla, CA (United States); Neilson, Jeffrey [Lexam Research, Redwood City, CA (United States); Bui, Thuc [Calabazas Creek Research, Inc., San Mateo, CA (United States)

2016-11-28

The Phase II program developed an internal RF coupler that transforms the whispering gallery RF mode produced in gyrotron cavities to an HE11 waveguide mode propagating in corrugated waveguide. This power is extracted from the vacuum using a broadband, chemical vapor deposited (CVD) diamond, Brewster angle window capable of transmitting more than 1.5 MW CW of RF power over a broad range of frequencies. This coupling system eliminates the Mirror Optical Units now required to externally couple Gaussian output power into corrugated waveguide, significantly reducing system cost and increasing efficiency. The program simulated the performance using a broad range of advanced computer codes to optimize the design. Both a direct coupler and Brewster angle window were built and tested at low and high power. Test results confirmed the performance of both devices and demonstrated they are capable of achieving the required performance for scientific, defense, industrial, and medical applications.

The interdependence of Ca2+ activation, sarcomere length, and power output in the heart.

Science.gov (United States)

McDonald, Kerry S

2011-07-01

Myocardium generates power to perform external work on the circulation; yet, many questions regarding intermolecular mechanisms regulating power output remain unresolved. Power output equals force × shortening velocity, and some interesting new observations regarding control of these two factors have arisen. While it is well established that sarcomere length tightly controls myocyte force, sarcomere length-tension relationships also appear to be markedly modulated by PKA-mediated phosphorylation of myofibrillar proteins. Concerning loaded shortening, historical models predict independent cross-bridge mechanics; however, it seems that the mechanical state of one population of cross-bridges affects the activity of other cross-bridges by, for example, recruitment of cross-bridges from the non-cycling pool to the cycling force-generating pool during submaximal Ca(2+) activation. This is supported by the findings that Ca(2+) activation levels, myofilament phosphorylation, and sarcomere length are all modulators of loaded shortening and power output independent of their effects on force. This fine tuning of power output probably helps optimize myocardial energetics and to match ventricular supply with peripheral demand; yet, the discernment of the chemo-mechanical signals that modulate loaded shortening needs further clarification since power output may be a key convergent point and feedback regulator of cytoskeleton and cellular signals that control myocyte growth and survival.

Adaptive short-term electricity price forecasting using artificial neural networks in the restructured power markets

International Nuclear Information System (INIS)

Yamin, H.Y.; Shahidehpour, S.M.; Li, Z.

2004-01-01

This paper proposes a comprehensive model for the adaptive short-term electricity price forecasting using Artificial Neural Networks (ANN) in the restructured power markets. The model consists: price simulation, price forecasting, and performance analysis. The factors impacting the electricity price forecasting, including time factors, load factors, reserve factors, and historical price factor are discussed. We adopted ANN and proposed a new definition for the MAPE using the median to study the relationship between these factors and market price as well as the performance of the electricity price forecasting. The reserve factors are included to enhance the performance of the forecasting process. The proposed model handles the price spikes more efficiently due to considering the median instead of the average. The IEEE 118-bus system and California practical system are used to demonstrate the superiority of the proposed model. (author)

A long-term stable power supply μDMFC stack for wireless sensor node applications

International Nuclear Information System (INIS)

Wu, Z L; Wang, X H; Teng, F; Li, X Z; Wu, X M; Liu, L T

2013-01-01

A passive, air-breathing 4-cell micro direct methanol fuel cell (μDMFC) stack is presented featured by a fuel delivery structure for a long-term and stable power supply. The fuel is reserved in a T shape tank and diffuses through the porous diffusion layer to the catalyst at anode. The stack has a maximum power output of 110mW with 3M methanol at room temperature and output a stable power even thought 5% fuel is the remained in reservoir. Its performance decreases less than 3% for 100 hours continuous work. As such, it is believed to be more applicable for powering the wireless sensor nodes

Influence of Intra-cell Traffic on the Output Power of Base Station in GSM

Directory of Open Access Journals (Sweden)

M. Mileusnic

2014-06-01

Full Text Available In this paper we analyze the influence of intracell traffic in a GSM cell on the base station output power. It is proved that intracell traffic increases this power. If offered traffic is small, the increase of output power is equal to the part of intracell traffic. When the offered traffic and, as the result, call loss increase, the increase of output power becomes less. The results of calculation are verified by the computer simulation of traffic process in the GSM cell. The calculation and the simulation consider the uniform distribution of mobile users in the cell, but the conclusions are of a general nature.

A comprehensive analysis and hardware implementation of control strategies for high output voltage DC-DC boost power converter

OpenAIRE

Padmanaban, Sanjeevikumar; Grandi, Gabriele; Blaabjerg, Frede; Wheeler, Patrick; Siano, Pierluigi; Hammami, Manel

2017-01-01

Classical DC-DC converters used in high voltage direct current (HVDC) power transmission systems, lack in terms of efficiency, reduced transfer gain and increased cost with sensor (voltage/current) numbers. Besides, the internal self-parasitic behavior of the power components reduces the output voltage and efficiency of classical HV converters. This paper deals with extra high-voltage (EHV) dc-dc boost converter by the application of voltage-lift technique to overcome the aforementioned defic...

Revisiting short-term price and volatility dynamics in day-ahead electricity markets with rising wind power

International Nuclear Information System (INIS)

Li, Yuanjing

2015-01-01

This paper revisits the short-term price and volatility dynamics in day-ahead electricity markets in consideration of an increasing share of wind power, using an example of the Nord Pool day-ahead market and the Danish wind generation. To do so, a GARCH process is applied, and market coupling and the counterbalance effect of hydropower in the Scandinavian countries are additionally accounted for. As results, we found that wind generation weakly dampens spot prices with an elasticity of 0.008 and also reduces price volatility with an elasticity of 0.02 in the Nordic day-ahead market. The results shed lights on the importance of market coupling and interactions between wind power and hydropower in the Nordic system through cross-border exchanges, which play an essential role in price stabilization. Additionally, an EGARCH specification confirms an asymmetric influence of the price innovations, whereby negative shocks produce larger volatility in the Nordic spot market. While considering heavy tails in error distributions can improve model fits significantly, the EGARCH model outperforms the GARCH model on forecast evaluations. (author)

The Demonstration of Short-Term Consolidation.

Science.gov (United States)

Jolicoeur, Pierre; Dell'Acqua, Roberto

1998-01-01

Results of seven experiments involving 112 college students or staff using a dual-task approach provide evidence that encoding information into short-term memory involves a distinct process termed short-term consolidation (STC). Results suggest that STC has limited capacity and that it requires central processing mechanisms. (SLD)

Power Spectral Analysis of Short-Term Heart Rate Variability in Healthy and Arrhythmia Subjects by the Adaptive Continuous Morlet Wavelet Transform

Directory of Open Access Journals (Sweden)

Ram Sewak SINGH

2017-12-01

Full Text Available Power spectral analysis of short-term heart rate variability (HRV can provide instant valuable information to understand the functioning of autonomic control over the cardiovascular system. In this study, an adaptive continuous Morlet wavelet transform (ACMWT method has been used to describe the time-frequency characteristics of the HRV using band power spectra and the median value of interquartile range. Adaptation of the method was based on the measurement of maximum energy concentration. The ACMWT has been validated on synthetic signals (i.e. stationary, non-stationary as slow varying and fast changing frequency with time modeled as closest to dynamic changes in HRV signals. This method has been also tested in the presence of additive white Gaussian noise (AWGN to show its robustness towards the noise. From the results of testing on synthetic signals, the ACMWT was found to be an enhanced energy concentration estimator for assessment of power spectral of short-term HRV time series compared to adaptive Stockwell transform (AST, adaptive modified Stockwell transform (AMST, standard continuous Morlet wavelet transform (CMWT and Stockwell transform (ST estimators at statistical significance level of 5%. Further, the ACMWT was applied to real HRV data from Fantasia and MIT-BIH databases, grouped as healthy young group (HYG, healthy elderly group (HEG, arrhythmia controlled medication group (ARCMG, and supraventricular tachycardia group (SVTG subjects. The global results demonstrate that spectral indices of low frequency power (LFp and high frequency power (HFp of HRV were decreased in HEG compared to HYG subjects (p<0.0001. While LFp and HFp indices were increased in ARCMG compared to HEG (p<0.00001. The LFp and HFp components of HRV obtained from SVTG were reduced compared to other group subjects (p<0.00001.

Output power characteristics of the neutral xenon long laser

Energy Technology Data Exchange (ETDEWEB)

Linford, G.J. [TRW Space and Electronics Group, Redondo Beach, CA (United States). Space and Technology Div.

1994-12-31

Lasers which oscillate within inhomogeneously broadened gain media exhibit spectral hole burning and concomitant reduction in output power compared with equivalent homogeneously-broadened laser gain media. By increasing the cavity length, it may be possible to demonstrate at least a partial transition from an inhomogeneous laser cavity mode spectrum to a homogeneous spectrum. There are a number of high gain laser lines which are inhomogeneously-broadened transitions in electric discharges of neutral xenon. In neutral xenon lasers, as in the cases of many other gas lasers, the inhomogeneous spectral broadening mechanism arises from Doppler shifts, {Delta}{nu}{sub D}, of individual atoms in thermal motion within the electric discharge comprising the laser gain medium. Optical transitions corresponding to these noble gas atoms have natural linewidths, {Delta}{nu}{sub n}{lt}{Delta}{nu}{sub D}. Simulations of the output power characteristics of the xenon laser were carried out as a function of laser cavity parameters, including the cavity length, L. These calculations showed that when the intracavity mode spacing frequency, c/2L{lt}{Delta}{nu}{sub n}, the inhomogeneously broadened xenon mode spectrum converted to a homogeneously broadened oscillation spectrum with an increase in output power. These simulations are compared with experimental results obtained for the long laser oscillation characteristics of the (5d[5/2]{degree}{sub 2}{r_arrow}6p[3/2]{sub 1}) transition corresponding to the strong, high-gain 3.508 {mu} line in xenon.

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.

Combined heat and power production planning in a waste-to-energy plant on a short-term basis

International Nuclear Information System (INIS)

Touš, Michal; Pavlas, Martin; Putna, Ondřej; Stehlík, Petr; Crha, Lukáš

2015-01-01

In many cases, WtE (waste-to-energy) plants are CHP (combined heat and power) producers. They are often integrated into a central heating system and they also export electricity to the grid. Therefore, they have to plan their operation on a long-term basis (months, years) as well as on a short-term basis (hours, days). Simulation models can effectively support decision making in CHP production planning. In general, CHP production planning on a short-term basis is a challenging task for WtE plants. This article presents a simulation based support. It is demonstrated on an example involving a real WtE plant. Most of the models of relevant WtE sub-systems (boilers, steam turbine) are developed using operational data and applying linear regression and artificial neural network technique. The process randomness given mainly by fluctuating heating value of waste leads to uncertainty in a calculation of CHP production and a stochastic approach is appropriate. The models of the sub-systems are, therefore, extended of a stochastic part and Monte-Carlo simulation is applied. Compared to the current planning strategy in the involved WtE plant, the stochastic simulation based planning provides increased CHP production resulting in better net thermal efficiency and increased revenue. This is demonstrated through a comparison using real operational data. - Highlights: • Introduction of a stochastic model of a CHP production in a waste-to-energy plant. • An application of the model for the next day CHP production planning. • Better net thermal efficiency and therefore increased revenue achieved.

A Free-Piston Linear Generator Control Strategy for Improving Output Power

Directory of Open Access Journals (Sweden)

Chi Zhang

2018-01-01

Full Text Available This paper presents a control strategy to improve the output power for a single-cylinder two-stroke free-piston linear generator (FPLG. The comprehensive simulation model of this FPLG is established and the operation principle is introduced. The factors that affect the output power are analyzed theoretically. The characteristics of the piston motion are studied. Considering the different features of the piston motion respectively in acceleration and deceleration phases, a ladder-like electromagnetic force control strategy is proposed. According to the status of the linear electric machine, the reference profile of the electromagnetic force is divided into four ladder-like stages during one motion cycle. The piston motions, especially the dead center errors, are controlled by regulating the profile of the electromagnetic force. The feasibility and advantage of the proposed control strategy are verified through comparison analyses with two conventional control strategies via MatLab/Simulink. The results state that the proposed control strategy can improve the output power by around 7–10% with the same fuel cycle mass.

Onboard Short Term Plan Viewer

Science.gov (United States)

Hall, Tim; LeBlanc, Troy; Ulman, Brian; McDonald, Aaron; Gramm, Paul; Chang, Li-Min; Keerthi, Suman; Kivlovitz, Dov; Hadlock, Jason

2011-01-01

Onboard Short Term Plan Viewer (OSTPV) is a computer program for electronic display of mission plans and timelines, both aboard the International Space Station (ISS) and in ISS ground control stations located in several countries. OSTPV was specifically designed both (1) for use within the limited ISS computing environment and (2) to be compatible with computers used in ground control stations. OSTPV supplants a prior system in which, aboard the ISS, timelines were printed on paper and incorporated into files that also contained other paper documents. Hence, the introduction of OSTPV has both reduced the consumption of resources and saved time in updating plans and timelines. OSTPV accepts, as input, the mission timeline output of a legacy, print-oriented, UNIX-based program called "Consolidated Planning System" and converts the timeline information for display in an interactive, dynamic, Windows Web-based graphical user interface that is used by both the ISS crew and ground control teams in real time. OSTPV enables the ISS crew to electronically indicate execution of timeline steps, launch electronic procedures, and efficiently report to ground control teams on the statuses of ISS activities, all by use of laptop computers aboard the ISS.

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.

Short-term moderate intensive high volume training program provides aerobic endurance benefit in wheelchair basketball players.

Science.gov (United States)

Skucas, Kestutis; Pokvytyte, Vaida

2017-04-01

The aim of this paper was to investigate the effect of short-term period, moderate intensity and high volume endurance training on physiological variables in elite wheelchair basketball players. Eight wheelchair basketball players were examined. The subjects participated in a two-week intervention program of mainly two training types: wheelchair basketball and wheelchair driving endurance training. The subjects performed the continuously increasing cycling exercise (CCE) at the constant 60 rpm arm cranking speed at the beginning of the program and after two weeks of the program. The initial workload was 20 W, then the workload was increased by 2 W every 5 seconds until fatigue. The post training of the wheelchair basketball group in the study showed a significant improvement in the peak oxygen uptake (VO2peak) and the peak power output (POpeak). VO2peak increased by 9% from 2.32±0.16 L/min to 2.53±0.2 L/min (Pbasketball squad had relatively high levels of aerobic fitness prior to participating in the endurance training program. Nevertheless, the high-volume, moderate-intensity, short-term training program, which evolved over the two-weeks period, resulted in the improvement of the athlete's aerobic endurance. The ventilatory threshold (VT) and the second ventilatory threshold (VT2) are good markers for aerobic capacity of wheelchair athletes.

What are the differences between long-term, short-term, and working memory?

OpenAIRE

Cowan, Nelson

2008-01-01

In the recent literature there has been considerable confusion about the three types of memory: long-term, short-term, and working memory. This chapter strives to reduce that confusion and makes up-to-date assessments of these types of memory. Long- and short-term memory could differ in two fundamental ways, with only short-term memory demonstrating (1) temporal decay and (2) chunk capacity limits. Both properties of short-term memory are still controversial but the current literature is rath...

Long-term contracts vs. short-term trade of natural gas - a European perspective

International Nuclear Information System (INIS)

Neuhoff, Karsten; Hirschhausen, Christian von

2005-01-01

This paper analyses the economics of long-term gas contracts under changing institutional conditions, mainly gas sector liberalisation. The paper is motivated by the increasingly tense debate in continental Europe, UK and the US on the security of long-term gas supply. We discuss the main issues regarding long-term contracts, i.e. the changing role of the flexibility clause, the effect of abandoning the destination clause, and the strategic behaviour of producers between long-term sales and spot-sales. The literature suggests consumers and producers benefit from risk hedging through long-term contracts. Furthermore long-term contracts may reduce exercise of market power. Our analysis adds an additional benefit if the long-run demand elasticity is significantly lower than the short-run elasticity, both strategic producers and consumers benefit from lower prices and larger market volume. Some policy implications of the findings are also discussed. (Author)

The effects of training with loads that maximise power output and individualised repetitions vs. traditional power training.

Directory of Open Access Journals (Sweden)

J M Sarabia

Full Text Available It has been suggested that strength training effects (i.e. neural or structural vary, depending on the total repetitions performed and velocity loss in each training set.The aim of this study is to compare the effects of two training programmes (i.e. one with loads that maximise power output and individualised repetitions, and the other following traditional power training.Twenty-five males were divided into three groups (optimum power [OP = 10], traditional training [TT = 9] and control group [CG = 6]. The training load used for OP was individualised using loads that maximised power output (41.7% ± 5.8 of one repetition maximum [1RM] and repetitions at maximum power (4 to 9 repetitions, or 'reps'. Volume (sets x repetitions was the same for both experimental groups, while intensity for TT was that needed to perform only 50% of the maximum number of possible repetitions (i.e. 61.1%-66.6% of 1RM. The training programme ran over 11 weeks (2 sessions per week; 4-5 sets per session; 3-minute rests between sets, with pre-, intermediate and post-tests which included: anthropometry, 1RM, peak power output (PPO with 30%, 40% and 50% of 1RM in the bench press throw, and salivary testosterone (ST and cortisol (SC concentrations. Rate of perceived exertion (RPE and power output were recorded in all sessions.Following the intermediate test, PPO was increased in the OP group for each load (10.9%-13.2%. Following the post-test, both experimental groups had increased 1RM (11.8%-13.8% and PPO for each load (14.1%-19.6%. Significant decreases in PPO were found for the TT group during all sets (4.9%-15.4%, along with significantly higher RPE (37%.OP appears to be a more efficient method of training, with less neuromuscular fatigue and lower RPE.

Short-term memory across eye blinks.

Science.gov (United States)

Irwin, David E

2014-01-01

The effect of eye blinks on short-term memory was examined in two experiments. On each trial, participants viewed an initial display of coloured, oriented lines, then after a retention interval they viewed a test display that was either identical or different by one feature. Participants kept their eyes open throughout the retention interval on some blocks of trials, whereas on others they made a single eye blink. Accuracy was measured as a function of the number of items in the display to determine the capacity of short-term memory on blink and no-blink trials. In separate blocks of trials participants were instructed to remember colour only, orientation only, or both colour and orientation. Eye blinks reduced short-term memory capacity by approximately 0.6-0.8 items for both feature and conjunction stimuli. A third, control, experiment showed that a button press during the retention interval had no effect on short-term memory capacity, indicating that the effect of an eye blink was not due to general motoric dual-task interference. Eye blinks might instead reduce short-term memory capacity by interfering with attention-based rehearsal processes.

Short-term spatio-temporal wind power forecast in robust look-ahead power system dispatch

KAUST Repository

Xie, Le

2014-01-01

We propose a novel statistical wind power forecast framework, which leverages the spatio-temporal correlation in wind speed and direction data among geographically dispersed wind farms. Critical assessment of the performance of spatio-temporal wind power forecast is performed using realistic wind farm data from West Texas. It is shown that spatio-temporal wind forecast models are numerically efficient approaches to improving forecast quality. By reducing uncertainties in near-term wind power forecasts, the overall cost benefits on system dispatch can be quantified. We integrate the improved forecast with an advanced robust look-ahead dispatch framework. This integrated forecast and economic dispatch framework is tested in a modified IEEE RTS 24-bus system. Numerical simulation suggests that the overall generation cost can be reduced by up to 6% using a robust look-ahead dispatch coupled with spatio-temporal wind forecast as compared with persistent wind forecast models. © 2013 IEEE.

Short-term memory and dual task performance

Science.gov (United States)

Regan, J. E.

1982-01-01

Two hypotheses concerning the way in which short-term memory interacts with another task in a dual task situation are considered. It is noted that when two tasks are combined, the activity of controlling and organizing performance on both tasks simultaneously may compete with either task for a resource; this resource may be space in a central mechanism or general processing capacity or it may be some task-specific resource. If a special relationship exists between short-term memory and control, especially if there is an identity relationship between short-term and a central controlling mechanism, then short-term memory performance should show a decrement in a dual task situation. Even if short-term memory does not have any particular identity with a controlling mechanism, but both tasks draw on some common resource or resources, then a tradeoff between the two tasks in allocating resources is possible and could be reflected in performance. The persistent concurrence cost in memory performance in these experiments suggests that short-term memory may have a unique status in the information processing system.

Energy Harvesting by Subcutaneous Solar Cells: A Long-Term Study on Achievable Energy Output.

Science.gov (United States)

Bereuter, L; Williner, S; Pianezzi, F; Bissig, B; Buecheler, S; Burger, J; Vogel, R; Zurbuchen, A; Haeberlin, A

2017-05-01

Active electronic implants are powered by primary batteries, which induces the necessity of implant replacement after battery depletion. This causes repeated interventions in a patients' life, which bears the risk of complications and is costly. By using energy harvesting devices to power the implant, device replacements may be avoided and the device size may be reduced dramatically. Recently, several groups presented prototypes of implants powered by subcutaneous solar cells. However, data about the expected real-life power output of subcutaneously implanted solar cells was lacking so far. In this study, we report the first real-life validation data of energy harvesting by subcutaneous solar cells. Portable light measurement devices that feature solar cells (cell area = 3.6 cm 2 ) and continuously measure a subcutaneous solar cell's output power were built. The measurement devices were worn by volunteers in their daily routine in summer, autumn and winter. In addition to the measured output power, influences such as season, weather and human activity were analyzed. The obtained mean power over the whole study period was 67 µW (=19 µW cm -2 ), which is sufficient to power e.g. a cardiac pacemaker.

The Interdependence of Long- and Short-Term Components in Unmasked Repetition Priming: An Indication of Shared Resources.

Science.gov (United States)

Merema, Matt R; Speelman, Craig P

2015-01-01

It has been suggested that unmasked repetition priming is composed of distinct long-and short-term priming components. The current study sought to clarify the relationship between these components by examining the relationship between them. A total of 60 people (45 females, 15 males) participated in a computer-based lexical decision task designed to measure levels of short-term priming across different levels of long-term priming. The results revealed an interdependent relationship between the two components, whereby an increase in long-term priming prompted a decrease in short-term priming. Both long-term and short-term priming were accurately captured by a single power function over seven minutes post repetition, suggesting the two components may draw on the same resources. This interdependence between long- and short-term priming may serve to improve fluency in reading.

The Interdependence of Long- and Short-Term Components in Unmasked Repetition Priming: An Indication of Shared Resources.

Directory of Open Access Journals (Sweden)

Matt R Merema

Full Text Available It has been suggested that unmasked repetition priming is composed of distinct long-and short-term priming components. The current study sought to clarify the relationship between these components by examining the relationship between them. A total of 60 people (45 females, 15 males participated in a computer-based lexical decision task designed to measure levels of short-term priming across different levels of long-term priming. The results revealed an interdependent relationship between the two components, whereby an increase in long-term priming prompted a decrease in short-term priming. Both long-term and short-term priming were accurately captured by a single power function over seven minutes post repetition, suggesting the two components may draw on the same resources. This interdependence between long- and short-term priming may serve to improve fluency in reading.

Dangerous dream: Nuclear power. With an attached short dictionary of terms in nuclear energy. Der gefaehrliche Traum: Atomkraft. Mit kleinem Lexikon der Atom-Energie

Energy Technology Data Exchange (ETDEWEB)

Paul, R

1986-01-01

After Chernobyl: Necessary basic knowledge and information, data on safety hazards and risks, sketches of all German nuclear power plants and brief accounts of incidents reported so far, consequences of the Chernobyl and Harrisburg accidents for man and the environment, emergency control plans. With an attached short dictionary of terms in nuclear energy.

A new cascade NN based method to short-term load forecast in deregulated electricity market

International Nuclear Information System (INIS)

Kouhi, Sajjad; Keynia, Farshid

2013-01-01

Highlights: • We are proposed a new hybrid cascaded NN based method and WT to short-term load forecast in deregulated electricity market. • An efficient preprocessor consist of normalization and shuffling of signals is presented. • In order to select the best inputs, a two-stage feature selection is presented. • A new cascaded structure consist of three cascaded NNs is used as forecaster. - Abstract: Short-term load forecasting (STLF) is a major discussion in efficient operation of power systems. The electricity load is a nonlinear signal with time dependent behavior. The area of electricity load forecasting has still essential need for more accurate and stable load forecast algorithm. To improve the accuracy of prediction, a new hybrid forecast strategy based on cascaded neural network is proposed for STLF. This method is consists of wavelet transform, an intelligent two-stage feature selection, and cascaded neural network. The feature selection is used to remove the irrelevant and redundant inputs. The forecast engine is composed of three cascaded neural network (CNN) structure. This cascaded structure can be efficiently extract input/output mapping function of the nonlinear electricity load data. Adjustable parameters of the intelligent feature selection and CNN is fine-tuned by a kind of cross-validation technique. The proposed STLF is tested on PJM and New York electricity markets. It is concluded from the result, the proposed algorithm is a robust forecast method

High-power direct diode laser output by spectral beam combining

Science.gov (United States)

Tan, Hao; Meng, Huicheng; Ruan, Xu; Du, Weichuan; Wang, Zhao

2018-03-01

We demonstrate a spectral beam combining scheme based on multiple mini-bar stacks, which have more diode laser combining elements, to increase the combined diode laser power and realize equal beam quality in both the fast and slow axes. A spectral beam combining diode laser output of 1130 W is achieved with an operating current of 75 A. When a 9.6 X de-magnifying telescope is introduced between the output mirror and the diffraction grating, to restrain cross-talk among diode laser emitters, a 710 W spectral beam combining diode laser output is achieved at the operating current of 70 A, and the beam quality on the fast and slow axes of the combined beam is about 7.5 mm mrad and 7.3 mm mrad respectively. The power reduction is caused by the existence of a couple resonator between the rear facet of the diode laser and the fast axis collimation lens, and it should be eliminated by using diode laser chips with higher front facet transmission efficiency and a fast axis collimation lens with lower residual reflectivity.

Call-related factors influencing output power from mobile phones.

Science.gov (United States)

Hillert, Lena; Ahlbom, Anders; Neasham, David; Feychting, Maria; Järup, Lars; Navin, Roshan; Elliott, Paul

2006-11-01

Mobile phone use is increasing but there is also concern for adverse health effects. Well-designed prospective studies to assess several health outcomes are required. In designing a study of mobile phone use, it is important to assess which factors need to be considered in classifying the exposure to radiofrequency fields (RF). A pilot study was performed in Sweden and in the UK 2002 to 2003 to test the feasibility of recruiting a cohort of mobile phone users from a random population sample and from mobile phone subscription lists for a prospective study. As one part of this pilot study, different factors were evaluated regarding possible influence on the output power of the phones. By local switch logging, information on calls made from predefined subscriptions or dedicated handsets were obtained and the output power of phones during calls made indoors and outdoors, in moving and stationary mode, and in rural as well in urban areas were compared. In this experiment, calls were either 1, 1.5 or 5 min long. The results showed that high mobile phone output power is more frequent in rural areas whereas the other factors (length of call, moving/stationary, indoor/outdoor) were of less importance. Urban and rural area should be considered in an exposure index for classification of the exposure to RF from mobile phones and may be assessed by first base station during mobile phone calls or, if this information is not available, possibly by using home address as a proxy.

Effect of argon plasma treatment on the output performance of triboelectric nanogenerator

Energy Technology Data Exchange (ETDEWEB)

Cheng, Guang-Gui, E-mail: ggcheng@ujs.edu.cn [Research Center of Micro/Nano Science and Technology, Jiangsu University, Zhenjiang (China); Jiangsu Collaborative Innovation Center of Photovoltaic Science and Engineering, Changzhou University, Changzhou (China); Jiang, Shi-Yu; Li, Kai [Research Center of Micro/Nano Science and Technology, Jiangsu University, Zhenjiang (China); Zhang, Zhong-Qiang [Research Center of Micro/Nano Science and Technology, Jiangsu University, Zhenjiang (China); Jiangsu Collaborative Innovation Center of Photovoltaic Science and Engineering, Changzhou University, Changzhou (China); Wang, Ying; Yuan, Ning-Yi [Jiangsu Collaborative Innovation Center of Photovoltaic Science and Engineering, Changzhou University, Changzhou (China); Ding, Jian-Ning, E-mail: dingjn@ujs.edu.cn [Research Center of Micro/Nano Science and Technology, Jiangsu University, Zhenjiang (China); Jiangsu Collaborative Innovation Center of Photovoltaic Science and Engineering, Changzhou University, Changzhou (China); Zhang, Wei [Research Center of Micro/Nano Science and Technology, Jiangsu University, Zhenjiang (China)

2017-08-01

Highlights: • Two different kinds of PDMS films were prepared by spin-coated. • The PDMS surface was plasma treated with different power and time. • The output performance of TENG was significantly enhanced by plasma treatment. • Plasma treatment effect has time-efficient, the output declines with store time. - Abstract: Physical and chemical properties of the polymer surface play great roles in the output performance of triboelectric nanogenerator (TENG). Specific texture on the surface of polymer can enlarge the contact area and enhance the power output performance of TENG. In this paper, polydimethylsiloxane (PDMS) films with smooth and micro pillar arrays on the surface were prepared respectively. The surfaces were treated by argon plasma before testing their output performance. By changing treatment parameters such as treating time and plasma power, surfaces with different roughness and their relationship were achieved. The electrical output performances of the assembled TENG for each specimen showed that argon plasma treatment has a significant etching effect on the PDMS surface and greatly strengthen its output performance. The average surface roughness of PDMS film increases with the etching time from 5 mins to 15 mins when the argon plasma power is 60 W. Nevertheless, the average surface roughness is inversely proportional to the treatment time for the power of 90W. When treated with 90 W and 5 mins, many uniform micro pillars appeared on the both PDMS surface, and the output performance of the TENG for plasma treated smooth surface is 2.6 times larger than that before treatment. The output voltage increases from 42 V to 72 V, and the short circuit current increases from 4.2 μA to 8.3 μA after plasma treatment of the micro pillar array surface. However, this plasma treatment has time-efficient due to the hydrophobic recovery property of Ar plasma treated PDMS surface, both output voltage and short circuit current decrease significantly after 3

Effects of Short-Term Jump Squat Training With and Without Chains on Strength and Power in Recreational Lifters

Directory of Open Access Journals (Sweden)

David C. Archer

2016-10-01

Full Text Available Background: The use of chains in resistance training is a way to accommodate the muscular strength curve. Short-term training and jump squats have been shown to increase back squat strength, but not in conjunction with each other or with chains. Jump squats have also been used to increase jump height and power. Objectives: The purpose of this study was to investigate the effects of short-term jump squat training with and without chains on strength and power. Methods: Thirty-one resistance-trained men volunteered to participate (age = 23.87 ± 2.2 years, height=174.87 ± 6.94 cm, mass = 82.74 ± 14.95 kg and were randomly assigned to one of three groups [control (C = 10, no chains (NC =10, or chains (CH = 11]. Participants had their jump height (VJ and back squat strength (BS tested before and after a week of training. The NC and CH groups performed three training sessions consisting of five sets of three reps of jump squats at 30% 1RM with 30s rest between sets. The CH group had 20% of their load added by chains when standing erect. The C group did not train. Results: A 3 (group: CH, NC, C x 2 (time: pre, post mixed factor ANOVA revealed a significant (p = 0.006 interaction for back squat 1RM. Both the CH (pre 142.56 ± 20.40 kg; post 145.66 ± 19.59 kg and NC (pre 150.00 ± 15.23 kg; post 154.77 ± 15.09 kg groups significantly increased while the C (pre 157.27 ± 25.35 kg; post 156.36 ± 24.85 kg group showed no difference. There were no significant interactions (p =0.32 or main effects for VJ (C = pre 50.59 ± 9.39cm; post 51.29 ± 9.68cm; NC = pre 55.29 ± 5.23cm; post 57.39 ± 5.22cm; CH = pre 46.19 ± 5.02; post 47.45 ± 4.62. Conclusions: The CH group was able to increase strength while lifting less overall weight. Coaches may use short-term training with chains to yield a similar increase in back squat strength as without chains. Keywords: variable resistance, back squats, novel, vertical jump

Short-term incentive schemes for hospital managers

Directory of Open Access Journals (Sweden)

Lucas Malambe

2013-10-01

Full Text Available Orientation: Short-term incentives, considered to be an extrinsic motivation, are commonly used to motivate performance. This study explored hospital managers’ perceptions of short term incentives in maximising performance and retention. Research purpose: The study explored the experiences, views and perceptions of private hospital managers in South Africa regarding the use of short-term incentives to maximise performance and retention, as well as the applicability of the findings to public hospitals. Motivation for the study: Whilst there is an established link between performance reward schemes and organisational performance, there is little understanding of the effects of short term incentives on the performance and retention of hospital managers within the South African context. Research design, approach, and method: The study used a qualitative research design: interviews were conducted with a purposive sample of 19 hospital managers, and a thematic content analysis was performed. Main findings: Short-term incentives may not be the primary motivator for hospital managers, but they do play a critical role in sustaining motivation. Participants indicated that these schemes could also be applicable to public hospitals. Practical/managerial implications: Hospital managers are inclined to be more motivated by intrinsic than extrinsic factors. However, hospital managers (as middle managers also seem to be motivated by short-term incentives. A combination of intrinsic and extrinsic motivators should thus be used to maximise performance and retention. Contribution/value-add: Whilst the study sought to explore hospital managers’ perceptions of short-term incentives, it also found that an adequate balance between internal and external motivators is key to implementing an effective short-term incentive scheme.

Short-Term Intercultural Psychotherapy: Ethnographic Inquiry

Science.gov (United States)

Seeley, Karen M.

2004-01-01

This article examines the challenges specific to short-term intercultural treatments and recently developed approaches to intercultural treatments based on notions of cultural knowledge and cultural competence. The article introduces alternative approaches to short-term intercultural treatments based on ethnographic inquiry adapted for clinical…

S-Band AlGaN/GaN power amplifier MMIC with over 20 Watt output power

NARCIS (Netherlands)

van Heijningen, M; Visser, G.C.; Wurfl, J.; van Vliet, Frank Edward

2008-01-01

Abstract This paper presents the design of an S-band HPA MMIC in AlGaN/GaN CPW technology for radar TR-module application. The trade-offs of using an MMIC solution versus discrete power devices are discussed. The MMIC shows a maximum output power of 38 Watt at 37% Power Added Efficiency at 3.1 GHz.

Why do short term workers have high mortality?

DEFF Research Database (Denmark)

Kolstad, Henrik; Olsen, Jørn

1999-01-01

or violence, the rate ratios for short term employment were 2.30 (95% Cl 1.74-3.06) and 1.86 (95% Cl 1.35-2.56), respectively. An unhealthy lifestyle may also be a determinant of short term employment. While it is possible in principle to adjust for lifestyle factors if proper data are collected, the health......Increased mortality is often reported among workers in short term employment. This may indicate either a health-related selection process or the presence of different lifestyle or social conditions among short term workers. The authors studied these two aspects of short term employment among 16...

Design and characterization of a high-power ultrasound driver with ultralow-output impedance

Science.gov (United States)

Lewis, George K.; Olbricht, William L.

2009-11-01

We describe a pocket-sized ultrasound driver with an ultralow-output impedance amplifier circuit (less than 0.05 Ω) that can transfer more than 99% of the voltage from a power supply to the ultrasound transducer with minimal reflections. The device produces high-power acoustical energy waves while operating at lower voltages than conventional ultrasound driving systems because energy losses owing to mismatched impedance are minimized. The peak performance of the driver is measured experimentally with a PZT-4, 1.54 MHz, piezoelectric ceramic, and modeled using an adjusted Mason model over a range of transducer resonant frequencies. The ultrasound driver can deliver a 100 Vpp (peak to peak) square-wave signal across 0-8 MHz ultrasound transducers in 5 ms bursts through continuous wave operation, producing acoustic powers exceeding 130 W. Effects of frequency, output impedance of the driver, and input impedance of the transducer on the maximum acoustic output power of piezoelectric transducers are examined. The small size, high power, and efficiency of the ultrasound driver make this technology useful for research, medical, and industrial ultrasonic applications.

Improving the Output Power Stability of a High Concentration Photovoltaic System with Supercapacitors: A Preliminary Evaluation

Directory of Open Access Journals (Sweden)

Yu-Pei Huang

2015-01-01

Full Text Available The output power of a high concentration photovoltaic (HCPV system is very sensitive to fluctuating tracking errors and weather patterns. To help compensate this shortcoming, supercapacitors have been successfully incorporated into photovoltaic systems to improve their output power stability. This study examined the output power stability improvement of an HCPV module with a supercapacitor integrated into its circuit. Furthermore, the equivalent model of the experimental circuit is presented and analyzed. Experimental results suggest that integrating a supercapacitor into an HCPV module could improve its output power stability and further extend its acceptance angle. This paper provides preliminary data of the improvement and its evaluation method, which could be utilized for further improvements to an HCPV system.

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.

Solar Power Station Output Inverter Control Design

Directory of Open Access Journals (Sweden)

J. Bauer

2011-04-01

Full Text Available The photovoltaic applications spreads in these days fast, therefore they also undergo great development. Because the amount of the energy obtained from the panel depends on the surrounding conditions, as intensity of the sun exposure or the temperature of the solar array, the converter must be connected to the panel output. The Solar system equipped with inverter can supply small loads like notebooks, mobile chargers etc. in the places where the supplying network is not present. Or the system can be used as a generator and it shall deliver energy to the supply network. Each type of the application has different requirements on the converter and its control algorithm. But for all of them the one thing is common – the maximal efficiency. The paper focuses on design and simulation of the low power inverter that acts as output part of the whole converter. In the paper the design of the control algorithm of the inverter for both types of inverter application – for islanding mode and for operation on the supply grid – is discussed. Attention is also paid to the design of the output filter that should reduce negative side effects of the converter on the supply network.

Measuring power output intermittency and unsteady loading in a micro wind farm model

OpenAIRE

Bossuyt, Juliaan; Howland, Michael; Meneveau, Charles; Meyers, Johan

2016-01-01

In this study porous disc models are used as a turbine model for a wind-tunnel wind farm experiment, allowing the measurement of the power output, thrust force and spatially averaged incoming velocity for every turbine. The model's capabilities for studying the unsteady turbine loading, wind farm power output intermittency and spatio temporal correlations between wind turbines are demonstrated on an aligned wind farm, consisting of 100 wind turbine models.

Greenhouse gas emissions from operating reserves used to backup large-scale wind power.

Science.gov (United States)

Fripp, Matthias

2011-11-01

Wind farms provide electricity with no direct emissions. However, their output cannot be forecasted perfectly, even a short time ahead. Consequently, power systems with large amounts of wind power may need to keep extra fossil-fired generators turned on and ready to provide power if wind farm output drops unexpectedly. In this work, I introduce a new model for estimating the uncertainty in short-term wind power forecasts, and how this uncertainty varies as wind power is aggregated over larger regions. I then use this model to estimate the reserve requirements in order to compensate for wind forecast errors to a 99.999% level of reliability, and an upper limit on the amount of carbon dioxide that would be emitted if natural gas power plants are used for this purpose. I find that for regions larger than 500 km across, operating reserves will undo 6% or less of the greenhouse gas emission savings that would otherwise be expected from wind power.

A fuzzy inference model for short-term load forecasting

International Nuclear Information System (INIS)

Mamlook, Rustum; Badran, Omar; Abdulhadi, Emad

2009-01-01

This paper is concerned with the short-term load forecasting (STLF) in power system operations. It provides load prediction for generation scheduling and unit commitment decisions, and therefore precise load forecasting plays an important role in reducing the generation cost and the spinning reserve capacity. Short-term electricity demand forecasting (i.e., the prediction of hourly loads (demand)) is one of the most important tools by which an electric utility/company plans, dispatches the loading of generating units in order to meet system demand. The accuracy of the dispatching system, which is derived from the accuracy of the forecasting algorithm used, will determine the economics of the operation of the power system. The inaccuracy or large error in the forecast simply means that load matching is not optimized and consequently the generation and transmission systems are not being operated in an efficient manner. In the present study, a proposed methodology has been introduced to decrease the forecasted error and the processing time by using fuzzy logic controller on an hourly base. Therefore, it predicts the effect of different conditional parameters (i.e., weather, time, historical data, and random disturbances) on load forecasting in terms of fuzzy sets during the generation process. These parameters are chosen with respect to their priority and importance. The forecasted values obtained by fuzzy method were compared with the conventionally forecasted ones. The results showed that the STLF of the fuzzy implementation have more accuracy and better outcomes

Wind Power Forecasting Based on Echo State Networks and Long Short-Term Memory

DEFF Research Database (Denmark)

López, Erick; Allende, Héctor; Gil, Esteban

2018-01-01

involved. In particular, two types of RNN, Long Short-Term Memory (LSTM) and Echo State Network (ESN), have shown good results in time series forecasting. In this work, we present an LSTM+ESN architecture that combines the characteristics of both networks. An architecture similar to an ESN is proposed...

Methodological concerns for determining power output in the jump squat.

Science.gov (United States)

Cormie, Prue; Deane, Russell; McBride, Jeffrey M

2007-05-01

The purpose of this study was to investigate the validity of power measurement techniques during the jump squat (JS) utilizing various combinations of a force plate and linear position transducer (LPT) devices. Nine men with at least 6 months of prior resistance training experience participated in this acute investigation. One repetition maximums (1RM) in the squat were determined, followed by JS testing under 2 loading conditions (30% of 1RM [JS30] and 90% of 1RM [JS90]). Three different techniques were used simultaneously in data collection: (a) 1 linear position transducer (1-LPT); (b) 1 linear position transducer and a force plate (1-LPT + FP); and (c) 2 linear position transducers and a force place (2-LPT + FP). Vertical velocity-, force-, and power-time curves were calculated for each lift using these methodologies and were compared. Peak force and peak power were overestimated by 1-LPT in both JS30 and JS90 compared with 2-LPT + FP and 1-LPT + FP (p squat varies according to the measurement technique utilized. The 1-LPT methodology is not a valid means of determining power output in the jump squat. Furthermore, the 1-LPT + FP method may not accurately represent power output in free weight movements that involve a significant amount of horizontal motion.

Short-term mechanisms influencing volumetric brain dynamics

Directory of Open Access Journals (Sweden)

Nikki Dieleman

2017-01-01

Full Text Available With the use of magnetic resonance imaging (MRI and brain analysis tools, it has become possible to measure brain volume changes up to around 0.5%. Besides long-term brain changes caused by atrophy in aging or neurodegenerative disease, short-term mechanisms that influence brain volume may exist. When we focus on short-term changes of the brain, changes may be either physiological or pathological. As such determining the cause of volumetric dynamics of the brain is essential. Additionally for an accurate interpretation of longitudinal brain volume measures by means of neurodegeneration, knowledge about the short-term changes is needed. Therefore, in this review, we discuss the possible mechanisms influencing brain volumes on a short-term basis and set-out a framework of MRI techniques to be used for volumetric changes as well as the used analysis tools. 3D T1-weighted images are the images of choice when it comes to MRI of brain volume. These images are excellent to determine brain volume and can be used together with an analysis tool to determine the degree of volume change. Mechanisms that decrease global brain volume are: fluid restriction, evening MRI measurements, corticosteroids, antipsychotics and short-term effects of pathological processes like Alzheimer's disease, hypertension and Diabetes mellitus type II. Mechanisms increasing the brain volume include fluid intake, morning MRI measurements, surgical revascularization and probably medications like anti-inflammatory drugs and anti-hypertensive medication. Exercise was found to have no effect on brain volume on a short-term basis, which may imply that dehydration caused by exercise differs from dehydration by fluid restriction. In the upcoming years, attention should be directed towards studies investigating physiological short-term changes within the light of long-term pathological changes. Ultimately this may lead to a better understanding of the physiological short-term effects of

Somatotype variables related to strength and power output in male basketball players.

Science.gov (United States)

Buśko, Krzysztof; Pastuszak, Anna; Lipińska, Monika; Lipińska, Marta; Gryko, Karol

2017-01-01

The purpose of this study was to investigate the relationship between somatotype, muscular strength, power output measured in maximal cycle ergometer exercise bouts, and maximal power output and height of rise of the body mass centre (jump height) measured in akimbo counter movement jump (ACMJ), counter movement jump (CMJ) and spike jump (SPJ), in male basketball players. Thirteen male basketball players (second division, age 19.4 ± 0.8 years, body height 192.9 ± 5.6 cm, body mass 88.8 ± 8.6 kg, training experience 9.3 ± 0.8 years) participated in the study. Somatotype was determined using the Heath-Carter method. Maximal joint torques were measured under static conditions. Power output was measured in 2 maximal cycle ergometer exercise bouts, 10 seconds each, with increasing external loads equal to 7.5 and 10.0% of the body weight (BW). All jump trials (ACMJ, CMJ and SPJ) were performed on a force plate. The mean somatotype of basketball players amounted to: 2.8-4.2-3.2. The sum of the joint torques for left and right lower extremities (0.613), trunk (0.631) and all six measured muscle groups (0.647) were significantly correlated (p jump during ACMJ, CMJ and SPJ trials. The power output measured in maximal cycle ergometer exercise bouts with increasing external loads was significantly correlated (p basketball players' anthropometric characteristics can influence their level of performance but it is not a decisive factor.

Modulating wind power plant output using different frequency modulation components for damping grid oscillations

DEFF Research Database (Denmark)

2017-01-01

A method, controller, wind power plant, and computer program product are disclosed for operating a wind power plant comprising a plurality of wind turbines, the wind power plant producing a plant power output. The method comprises receiving a modulation request signal indicating a requested...... modulation of the plant power output, the requested modulation specifying a modulation frequency. The method further comprises generating a respective power reference signal for each of at least two wind turbines of the plurality of wind turbines selected to fulfill the requested modulation, Each generated...... power reference signal includes a respective modulation component corresponding to a portion of the requested modulation and having a frequency different than the modulation frequency....

Verbal Short-Term Memory Span in Speech-Disordered Children: Implications for Articulatory Coding in Short-Term Memory.

Science.gov (United States)

Raine, Adrian; And Others

1991-01-01

Children with speech disorders had lower short-term memory capacity and smaller word length effect than control children. Children with speech disorders also had reduced speech-motor activity during rehearsal. Results suggest that speech rate may be a causal determinant of verbal short-term memory capacity. (BC)

A Simplified Short Term Load Forecasting Method Based on Sequential Patterns

DEFF Research Database (Denmark)

Kouzelis, Konstantinos; Bak-Jensen, Birgitte; Mahat, Pukar

2014-01-01

Load forecasting is an essential part of a power system both for planning and daily operation purposes. As far as the latter is concerned, short term load forecasting has been broadly used at the transmission level. However, recent technological advancements and legislation have facilitated the i...... in comparison with an ARIMA model....

Real-time energy resources scheduling considering short-term and very short-term wind forecast

Energy Technology Data Exchange (ETDEWEB)

Silva, Marco; Sousa, Tiago; Morais, Hugo; Vale, Zita [Polytechnic of Porto (Portugal). GECAD - Knowledge Engineering and Decision Support Research Center

2012-07-01

This paper proposes an energy resources management methodology based on three distinct time horizons: day-ahead scheduling, hour-ahead scheduling, and real-time scheduling. In each scheduling process the update of generation and consumption operation and of the storage and electric vehicles storage status are used. Besides the new operation conditions, the most accurate forecast values of wind generation and of consumption using results of short-term and very short-term methods are used. A case study considering a distribution network with intensive use of distributed generation and electric vehicles is presented. (orig.)

An analog ensemble for short-term probabilistic solar power forecast

International Nuclear Information System (INIS)

Alessandrini, S.; Delle Monache, L.; Sperati, S.; Cervone, G.

2015-01-01

Highlights: • A novel method for solar power probabilistic forecasting is proposed. • The forecast accuracy does not depend on the nominal power. • The impact of climatology on forecast accuracy is evaluated. - Abstract: The energy produced by photovoltaic farms has a variable nature depending on astronomical and meteorological factors. The former are the solar elevation and the solar azimuth, which are easily predictable without any uncertainty. The amount of liquid water met by the solar radiation within the troposphere is the main meteorological factor influencing the solar power production, as a fraction of short wave solar radiation is reflected by the water particles and cannot reach the earth surface. The total cloud cover is a meteorological variable often used to indicate the presence of liquid water in the troposphere and has a limited predictability, which is also reflected on the global horizontal irradiance and, as a consequence, on solar photovoltaic power prediction. This lack of predictability makes the solar energy integration into the grid challenging. A cost-effective utilization of solar energy over a grid strongly depends on the accuracy and reliability of the power forecasts available to the Transmission System Operators (TSOs). Furthermore, several countries have in place legislation requiring solar power producers to pay penalties proportional to the errors of day-ahead energy forecasts, which makes the accuracy of such predictions a determining factor for producers to reduce their economic losses. Probabilistic predictions can provide accurate deterministic forecasts along with a quantification of their uncertainty, as well as a reliable estimate of the probability to overcome a certain production threshold. In this paper we propose the application of an analog ensemble (AnEn) method to generate probabilistic solar power forecasts (SPF). The AnEn is based on an historical set of deterministic numerical weather prediction (NWP) model

Short-Term Wind Electric Power Forecasting Using a Novel Multi-Stage Intelligent Algorithm

Directory of Open Access Journals (Sweden)

Haoran Zhao

2018-03-01

Full Text Available As the most efficient renewable energy source for generating electricity in a modern electricity network, wind power has the potential to realize sustainable energy supply. However, owing to its random and intermittent instincts, a high permeability of wind power into a power network demands accurate and effective wind energy prediction models. This study proposes a multi-stage intelligent algorithm for wind electric power prediction, which combines the Beveridge–Nelson (B-N decomposition approach, the Least Square Support Vector Machine (LSSVM, and a newly proposed intelligent optimization approach called the Grasshopper Optimization Algorithm (GOA. For data preprocessing, the B-N decomposition approach was employed to disintegrate the hourly wind electric power data into a deterministic trend, a cyclic term, and a random component. Then, the LSSVM optimized by the GOA (denoted GOA-LSSVM was applied to forecast the future 168 h of the deterministic trend, the cyclic term, and the stochastic component, respectively. Finally, the future hourly wind electric power values can be obtained by multiplying the forecasted values of these three trends. Through comparing the forecasting performance of this proposed method with the LSSVM, the LSSVM optimized by the Fruit-fly Optimization Algorithm (FOA-LSSVM, and the LSSVM optimized by Particle Swarm Optimization (PSO-LSSVM, it is verified that the established multi-stage approach is superior to other models and can increase the precision of wind electric power prediction effectively.

Theory Study and Application of the BP-ANN Method for Power Grid Short-Term Load Forecasting

Institute of Scientific and Technical Information of China (English)

Xia Hua; Gang Zhang; Jiawei Yang; Zhengyuan Li

2015-01-01

Aiming at the low accuracy problem of power system short⁃term load forecasting by traditional methods, a back⁃propagation artifi⁃cial neural network (BP⁃ANN) based method for short⁃term load forecasting is presented in this paper. The forecast points are re⁃lated to prophase adjacent data as well as the periodical long⁃term historical load data. Then the short⁃term load forecasting model of Shanxi Power Grid (China) based on BP⁃ANN method and correlation analysis is established. The simulation model matches well with practical power system load, indicating the BP⁃ANN method is simple and with higher precision and practicality.

The Mind and Brain of Short-Term Memory

OpenAIRE

Jonides, John; Lewis, Richard L.; Nee, Derek Evan; Lustig, Cindy A.; Berman, Marc G.; Moore, Katherine Sledge

2008-01-01

The past 10 years have brought near-revolutionary changes in psychological theories about short-term memory, with similarly great advances in the neurosciences. Here, we critically examine the major psychological theories (the “mind”) of short-term memory and how they relate to evidence about underlying brain mechanisms. We focus on three features that must be addressed by any satisfactory theory of short-term memory. First, we examine the evidence for the architecture of short-term memory, w...

Very-long-term and short-term chromatic adaptation: are their influences cumulative?

Science.gov (United States)

Belmore, Suzanne C; Shevell, Steven K

2011-02-09

Very-long-term (VLT) chromatic adaptation results from exposure to an altered chromatic environment for days or weeks. Color shifts from VLT adaptation are observed hours or days after leaving the altered environment. Short-term chromatic adaptation, on the other hand, results from exposure for a few minutes or less, with color shifts measured within seconds or a few minutes after the adapting light is extinguished; recovery to the pre-adapted state is complete in less than an hour. Here, both types of adaptation were combined. All adaptation was to reddish-appearing long-wavelength light. Shifts in unique yellow were measured following adaptation. Previous studies demonstrate shifts in unique yellow due to VLT chromatic adaptation, but shifts from short-term chromatic adaptation to comparable adapting light can be far greater than from VLT adaptation. The question considered here is whether the color shifts from VLT adaptation are cumulative with large shifts from short-term adaptation or, alternatively, does simultaneous short-term adaptation eliminate color shifts caused by VLT adaptation. The results show the color shifts from VLT and short-term adaptation together are cumulative, which indicates that both short-term and very-long-term chromatic adaptation affect color perception during natural viewing. Copyright © 2010 Elsevier Ltd. All rights reserved.

The effects of training with loads that maximise power output and individualised repetitions vs. traditional power training

Science.gov (United States)

Moya-Ramón, M.; Hernández-Davó, J. L.; Fernandez-Fernandez, J.; Sabido, R.

2017-01-01

Background It has been suggested that strength training effects (i.e. neural or structural) vary, depending on the total repetitions performed and velocity loss in each training set. Purpose The aim of this study is to compare the effects of two training programmes (i.e. one with loads that maximise power output and individualised repetitions, and the other following traditional power training). Methods Twenty-five males were divided into three groups (optimum power [OP = 10], traditional training [TT = 9] and control group [CG = 6]). The training load used for OP was individualised using loads that maximised power output (41.7% ± 5.8 of one repetition maximum [1RM]) and repetitions at maximum power (4 to 9 repetitions, or ‘reps’). Volume (sets x repetitions) was the same for both experimental groups, while intensity for TT was that needed to perform only 50% of the maximum number of possible repetitions (i.e. 61.1%–66.6% of 1RM). The training programme ran over 11 weeks (2 sessions per week; 4–5 sets per session; 3-minute rests between sets), with pre-, intermediate and post-tests which included: anthropometry, 1RM, peak power output (PPO) with 30%, 40% and 50% of 1RM in the bench press throw, and salivary testosterone (ST) and cortisol (SC) concentrations. Rate of perceived exertion (RPE) and power output were recorded in all sessions. Results Following the intermediate test, PPO was increased in the OP group for each load (10.9%–13.2%). Following the post-test, both experimental groups had increased 1RM (11.8%–13.8%) and PPO for each load (14.1%–19.6%). Significant decreases in PPO were found for the TT group during all sets (4.9%–15.4%), along with significantly higher RPE (37%). Conclusion OP appears to be a more efficient method of training, with less neuromuscular fatigue and lower RPE. PMID:29053725

Periodization of Carbohydrate Intake: Short-Term Effect on Performance

Directory of Open Access Journals (Sweden)

Laurie-Anne Marquet

2016-11-01

Full Text Available Background: “Sleep-low” consists of a sequential periodization of carbohydrate (CHO availability—low glycogen recovery after “train high” glycogen-depleting interval training, followed by an overnight-fast and light intensity training (“train low” the following day. This strategy leads to an upregulation of several exercise-responsive signaling proteins, but the chronic effect on performance has received less attention. We investigated the effects of short-term exposure to this strategy on endurance performance. Methods: Following training familiarization, 11 trained cyclists were divided into two groups for a one-week intervention—one group implemented three cycles of periodized CHO intake to achieve the sleep-low strategy over six training sessions (SL, CHO intake: 6 g·kg−1·day−1, whereas the control group consumed an even distribution of CHO over the day (CON. Tests were a 2 h submaximal ride and a 20 km time trial. Results: SL improved their performance (mean: +3.2%; p < 0.05 compared to CON. The improvement was associated with a change in pacing strategy with higher power output during the second part of the test. No change in substrate utilization was observed after the training period for either group. Conclusion: Implementing the “sleep-low” strategy for one week improved performance by the same magnitude previously seen in a three-week intervention, without any significant changes in selected markers of metabolism.

Periodization of Carbohydrate Intake: Short-Term Effect on Performance

Science.gov (United States)

Marquet, Laurie-Anne; Hausswirth, Christophe; Molle, Odeline; Hawley, John A.; Burke, Louise M.; Tiollier, Eve; Brisswalter, Jeanick

2016-01-01

Background: “Sleep-low” consists of a sequential periodization of carbohydrate (CHO) availability—low glycogen recovery after “train high” glycogen-depleting interval training, followed by an overnight-fast and light intensity training (“train low”) the following day. This strategy leads to an upregulation of several exercise-responsive signaling proteins, but the chronic effect on performance has received less attention. We investigated the effects of short-term exposure to this strategy on endurance performance. Methods: Following training familiarization, 11 trained cyclists were divided into two groups for a one-week intervention—one group implemented three cycles of periodized CHO intake to achieve the sleep-low strategy over six training sessions (SL, CHO intake: 6 g·kg−1·day−1), whereas the control group consumed an even distribution of CHO over the day (CON). Tests were a 2 h submaximal ride and a 20 km time trial. Results: SL improved their performance (mean: +3.2%; p < 0.05) compared to CON. The improvement was associated with a change in pacing strategy with higher power output during the second part of the test. No change in substrate utilization was observed after the training period for either group. Conclusion: Implementing the “sleep-low” strategy for one week improved performance by the same magnitude previously seen in a three-week intervention, without any significant changes in selected markers of metabolism. PMID:27897989

Short-term load and wind power forecasting using neural network-based prediction intervals.

Science.gov (United States)

Quan, Hao; Srinivasan, Dipti; Khosravi, Abbas

2014-02-01

Electrical power systems are evolving from today's centralized bulk systems to more decentralized systems. Penetrations of renewable energies, such as wind and solar power, significantly increase the level of uncertainty in power systems. Accurate load forecasting becomes more complex, yet more important for management of power systems. Traditional methods for generating point forecasts of load demands cannot properly handle uncertainties in system operations. To quantify potential uncertainties associated with forecasts, this paper implements a neural network (NN)-based method for the construction of prediction intervals (PIs). A newly introduced method, called lower upper bound estimation (LUBE), is applied and extended to develop PIs using NN models. A new problem formulation is proposed, which translates the primary multiobjective problem into a constrained single-objective problem. Compared with the cost function, this new formulation is closer to the primary problem and has fewer parameters. Particle swarm optimization (PSO) integrated with the mutation operator is used to solve the problem. Electrical demands from Singapore and New South Wales (Australia), as well as wind power generation from Capital Wind Farm, are used to validate the PSO-based LUBE method. Comparative results show that the proposed method can construct higher quality PIs for load and wind power generation forecasts in a short time.

Predicting short-term weight loss using four leading health behavior change theories

Directory of Open Access Journals (Sweden)

Barata José T

2007-04-01

Full Text Available Abstract Background This study was conceived to analyze how exercise and weight management psychosocial variables, derived from several health behavior change theories, predict weight change in a short-term intervention. The theories under analysis were the Social Cognitive Theory, the Transtheoretical Model, the Theory of Planned Behavior, and Self-Determination Theory. Methods Subjects were 142 overweight and obese women (BMI = 30.2 ± 3.7 kg/m2; age = 38.3 ± 5.8y, participating in a 16-week University-based weight control program. Body weight and a comprehensive psychometric battery were assessed at baseline and at program's end. Results Weight decreased significantly (-3.6 ± 3.4%, p Conclusion The present models were able to predict 20–30% of variance in short-term weight loss and changes in weight management self-efficacy accounted for a large share of the predictive power. As expected from previous studies, exercise variables were only moderately associated with short-term outcomes; they are expected to play a larger explanatory role in longer-term results.

A combined compensation method for the output voltage of an insulated core transformer power supply

Energy Technology Data Exchange (ETDEWEB)

Yang, L.; Yang, J., E-mail: jyang@mail.hust.edu.cn; Liu, K. F.; Qin, B.; Chen, D. Z. [State Key Laboratory of Advanced Electromagnetic Engineering and Technology, Huazhong University of Science and Technology, Wuhan 430074 (China)

2014-06-15

An insulated core transformer (ICT) power supply is an ideal high-voltage generator for irradiation accelerators with energy lower than 3 MeV. However, there is a significant problem that the structure of the segmented cores leads to an increase in the leakage flux and voltage differences between rectifier disks. A high level of consistency in the output of the disks helps to achieve a compact structure by improving the utilization of both the rectifier components and the insulation distances, and consequently increase the output voltage of the power supply. The output voltages of the disks which are far away from the primary coils need to be improved to reduce their inhomogeneity. In this study, by investigating and comparing the existing compensation methods, a new combined compensation method is proposed, which increases the turns on the secondary coils and employs parallel capacitors to improve the consistency of the disks, while covering the entire operating range of the power supply. This method turns out to be both feasible and effective during the development of an ICT power supply. The non-uniformity of the output voltages of the disks is less than 3.5% from no-load to full-load, and the power supply reaches an output specification of 350 kV/60 mA.

Hypoxia triggers short term potentiation of phrenic motoneuron discharge after chronic cervical spinal cord injury

Science.gov (United States)

Lee, Kun-Ze; Sandhu, Milapjit S.; Dougherty, Brendan J.; Reier, Paul J.; Fuller, David D.

2014-01-01

Repeated exposure to hypoxia can induce spinal neuroplasticity as well as respiratory and somatic motor recovery after spinal cord injury (SCI). The purpose of the present study was to define the capacity for a single bout of hypoxia to trigger short-term plasticity in phrenic output after cervical SCI, and to determine the phrenic motoneuron (PhrMN) bursting and recruitment patterns underlying the response. Hypoxia-induced short term potentiation (STP) of phrenic motor output was quantified in anesthetized rats 11 wks following lateral spinal hemisection at C2 (C2Hx). A 3-min hypoxic episode (12–14% O2) always triggered STP of inspiratory burst amplitude, the magnitude of which was greater in phrenic bursting ipsilateral vs. contralateral to C2Hx. We next determined if STP could be evoked in recruited (silent) PhrMNs ipsilateral to C2Hx. Individual PhrMN action potentials were recorded during and following hypoxia using a “single fiber” approach. STP of bursting activity did not occur in cells initiating bursting at inspiratory onset, but was robust in recruited PhrMNs as well as previously active cells initiating bursting later in the inspiratory effort. We conclude that following chronic C2Hx, a single bout of hypoxia triggers recruitment of PhrMNs in the ipsilateral spinal cord with bursting that persists beyond the hypoxic exposure. The results provide further support for the use of short bouts of hypoxia as a neurorehabilitative training modality following SCI. PMID:25448009

Conduction Aphasia, Sensory-Motor Integration, and Phonological Short-Term Memory--An Aggregate Analysis of Lesion and fMRI Data

Science.gov (United States)

Buchsbaum, Bradley R.; Baldo, Juliana; Okada, Kayoko; Berman, Karen F.; Dronkers, Nina; D'Esposito, Mark; Hickok, Gregory

2011-01-01

Conduction aphasia is a language disorder characterized by frequent speech errors, impaired verbatim repetition, a deficit in phonological short-term memory, and naming difficulties in the presence of otherwise fluent and grammatical speech output. While traditional models of conduction aphasia have typically implicated white matter pathways,…

Smart Demand for Improving Short-term Voltage Control on Distribution Networks

DEFF Research Database (Denmark)

Garcia-Valle, Rodrigo; P. Da Silva, Luiz C.; Xu, Zhao

2009-01-01

customer integration to aid power system performance is almost inevitable. This study introduces a new type of smart demand side technology, denoted demand as voltage controlled reserve (DVR), to improve short-term voltage control, where customers are expected to play a more dynamic role to improve voltage...... control. The technology can be provided by thermostatically controlled loads as well as other types of load. This technology is proven to be effective in case of distribution systems with a large composition of induction motors, where the voltage presents a slow recovery characteristic due to deceleration...... of the motors during faults. This study presents detailed models, discussion and simulation tests to demonstrate the technical viability and effectiveness of the DVR technology for short-term voltage control....

Wind Farm Active Power Dispatch for Output Power Maximizing Based on a Wind Turbine Control Strategy for Load Minimizing

DEFF Research Database (Denmark)

Zhang, Baohua; Hu, Weihao; Hou, Peng

2015-01-01

Inclusion of the wake effect in the wind farm control design (WF) can increase the total captured power by wind turbines (WTs), which is usually implemented by derating upwind WTs. However, derating the WT without a proper control strategy will increase the structural loads, caused by operation...... in stall mode. Therefore, the WT control strategy for derating operation should be considered in the attempt at maximizing the total captured power while reducing structural loads. Moreover, electrical power loss on the transmission system inside a WF is also not negligible for maximizing the total output...... power of the WF. In this paper, an optimal active power dispatch strategy based on a WT derating strategy and considering the transmission loss is proposed for maximizing the total output power. The active power reference of each WT is chosen as the optimization variable. A partial swarm optimizing...

A short-term ensemble wind speed forecasting system for wind power applications

Science.gov (United States)

Baidya Roy, S.; Traiteur, J. J.; Callicutt, D.; Smith, M.

2011-12-01

This study develops an adaptive, blended forecasting system to provide accurate wind speed forecasts 1 hour ahead of time for wind power applications. The system consists of an ensemble of 21 forecasts with different configurations of the Weather Research and Forecasting Single Column Model (WRFSCM) and a persistence model. The ensemble is calibrated against observations for a 2 month period (June-July, 2008) at a potential wind farm site in Illinois using the Bayesian Model Averaging (BMA) technique. The forecasting system is evaluated against observations for August 2008 at the same site. The calibrated ensemble forecasts significantly outperform the forecasts from the uncalibrated ensemble while significantly reducing forecast uncertainty under all environmental stability conditions. The system also generates significantly better forecasts than persistence, autoregressive (AR) and autoregressive moving average (ARMA) models during the morning transition and the diurnal convective regimes. This forecasting system is computationally more efficient than traditional numerical weather prediction models and can generate a calibrated forecast, including model runs and calibration, in approximately 1 minute. Currently, hour-ahead wind speed forecasts are almost exclusively produced using statistical models. However, numerical models have several distinct advantages over statistical models including the potential to provide turbulence forecasts. Hence, there is an urgent need to explore the role of numerical models in short-term wind speed forecasting. This work is a step in that direction and is likely to trigger a debate within the wind speed forecasting community.

Linearised model for PV panel power output variation with changes ...

Indian Academy of Sciences (India)

PALLAVI BHARADWAJ

2017-10-26

Oct 26, 2017 ... change in system input, namely: irradiance and temperature, with its output, namely: array current and power. ... of a solar cell as shown in figure 1, with appropriate scaling according to ... measurement-based methods [8–13].

Ultra-Fast Tracking Power Supply with 4th order Output Filter and Fixed-Frequency Hysteretic Control

DEFF Research Database (Denmark)

Høyerby, Mikkel Christian Wendelboe; Andersen, Michael Andreas E.

2008-01-01

A practical solution is presented for the design of a non-isolated DC/DC power converter with very low output ripple voltage and very fast output voltage step response. The converter is intended for use as an envelope tracking power supply for an RFPA (Radio Frequency Power Amplifier) in a Tetra2...

The prediction of the impact of climatic factors on short-term electric power load based on the big data of smart city

Science.gov (United States)

Qiu, Yunfei; Li, Xizhong; Zheng, Wei; Hu, Qinghe; Wei, Zhanmeng; Yue, Yaqin

2017-08-01

The climate changes have great impact on the residents’ electricity consumption, so the study on the impact of climatic factors on electric power load is of significance. In this paper, the effects of the data of temperature, rainfall and wind of smart city on short-term power load is studied to predict power load. The authors studied the relation between power load and daily temperature, rainfall and wind in the 31 days of January of one year. In the research, the authors used the Matlab neural network toolbox to establish the combinational forecasting model. The authors trained the original input data continuously to get the internal rules inside the data and used the rules to predict the daily power load in the next January. The prediction method relies on the accuracy of weather forecasting. If the weather forecasting is different from the actual weather, we need to correct the climatic factors to ensure accurate prediction.

Trade credit supply, market power and the matching of trade credit terms

NARCIS (Netherlands)

Fabbri, D.; Klapper, L.F.

2008-01-01

This paper studies the decision of firms to extend trade credit to customers and its relation with their financing decisions. We use a novel firm-level database with unique information on market power in both output and input markets and on the amount, terms and payment history of trade credit

Smoothing of Grid-connected Wind-Diesel Power Output Using Energy Capacitor System

Directory of Open Access Journals (Sweden)

Adel A. Elbaset

2014-06-01

Full Text Available This paper presents a small hybrid power system consists of two types of power generation; wind turbine and diesel generation, DG connected to power distribution system. The fluctuations like random nature of wind power, turbulent wind, and sudden changes in load demand create imbalances in power distribution that can affect the frequency and the voltage in the power system. So, addition of Energy capacitor System, ECS is useful for compensation of fluctuating power, since it is capable of controlling both active and reactive power simultaneously and can smooth the output power flow. Hence, this paper proposes herein a dynamic model and simulation of a grid connected wind/DG based-ECS with power flow controllers between load and generation. Moreover, the paper presents a study to analyze the leveling of output fluctuation of wind power with the installation of ECS. To control the power exchanged between the ECS system and the AC grid, a load Following Control, LFC based supervisor is proposed with the aim to minimize variations of the power generated by the diesel generator. The interesting performance of the proposed supervisor is shown with the help of simulations. The computer simulation program is confirmed on a realistic circuit model which implemented in the Simulink environment of Matlab and works as if on line.

Output Power Smoothing Control for a Wind Farm Based on the Allocation of Wind Turbines

Directory of Open Access Journals (Sweden)

Ying Zhu

2018-06-01

Full Text Available This paper presents a new output power smoothing control strategy for a wind farm based on the allocation of wind turbines. The wind turbines in the wind farm are divided into control wind turbines (CWT and power wind turbines (PWT, separately. The PWTs are expected to output as much power as possible and a maximum power point tracking (MPPT control strategy combining the rotor inertia based power smoothing method is adopted. The CWTs are in charge of the output power smoothing for the whole wind farm by giving the calculated appropriate power. The battery energy storage system (BESS with small capacity is installed to be the support and its charge and discharge times are greatly reduced comparing with the traditional ESSs based power smoothing strategies. The simulation model of the permanent magnet synchronous generators (PMSG based wind farm by considering the wake effect is built in Matlab/Simulink to test the proposed power smoothing method. Three different working modes of the wind farm are given in the simulation and the simulation results verify the effectiveness of the proposed power smoothing control strategy.

Probabilistic Physics-Based Risk Tools Used to Analyze the International Space Station Electrical Power System Output

Science.gov (United States)

Patel, Bhogila M.; Hoge, Peter A.; Nagpal, Vinod K.; Hojnicki, Jeffrey S.; Rusick, Jeffrey J.

2004-01-01

This paper describes the methods employed to apply probabilistic modeling techniques to the International Space Station (ISS) power system. These techniques were used to quantify the probabilistic variation in the power output, also called the response variable, due to variations (uncertainties) associated with knowledge of the influencing factors called the random variables. These uncertainties can be due to unknown environmental conditions, variation in the performance of electrical power system components or sensor tolerances. Uncertainties in these variables, cause corresponding variations in the power output, but the magnitude of that effect varies with the ISS operating conditions, e.g. whether or not the solar panels are actively tracking the sun. Therefore, it is important to quantify the influence of these uncertainties on the power output for optimizing the power available for experiments.

Revolutionary interdisciplinary cooperation. Effects of short- term regulation studied in a river environment

Energy Technology Data Exchange (ETDEWEB)

Saimakallio, H.; Virsu, R.

1996-11-01

A three-year study on how short-term regulation affects the river environment provides power plant builders with new capabilities to meet the needs of the riverside population, recreational users and power plants. The study also opens up new perspectives to researchers. Interdisciplinary cooperation between experts on the living environment, vegetation, fish, recreational use and energy has been revolutionary even on the international scale. (orig.)

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.

Nine Criteria for a Measure of Scientific Output

OpenAIRE

Kreiman, Gabriel; Maunsell, John H. R.

2011-01-01

Scientific research produces new knowledge, technologies, and clinical treatments that can lead to enormous returns. Often, the path from basic research to new paradigms and direct impact on society takes time. Precise quantification of scientific output in the short-term is not an easy task but is critical for evaluating scientists, laboratories, departments, and institutions. While there have been attempts to quantifying scientific output, we argue that current methods are not ideal and suf...

Short-term Periodization Models: Effects on Strength and Speed-strength Performance.

Science.gov (United States)

Hartmann, Hagen; Wirth, Klaus; Keiner, Michael; Mickel, Christoph; Sander, Andre; Szilvas, Elena

2015-10-01

avoided because it does not provide an adequate training stimulus for gains in muscle cross-sectional area and strength performance. High-volume circuit strength training performed over 2 years negatively affected the development of the power output and maximal strength of the upper extremities in professional rugby players. Indeed, meta-analyses and results with weightlifters, American Football players, and throwers confirm the necessity of the habitual use of ≥80% 1 RM: (1) to improve maximal strength during the off-season and in-season in American Football, (2) to reach peak performance in maximal strength and vertical jump power during tapering in track-and-field, and (3) to produce hypertrophy and strength improvements in advanced athletes. The integration and extent of hypertrophy strength training in in-season conditioning depend on the duration of the contest period, the frequency of the contests, and the proportion of the conditioning program. Based on the literature, 72 h between hypertrophy strength training and strength-power training should be provided to allow for adequate regeneration times and therefore maximal stimulus intensities in training. This conclusion is only valid if the muscle is not trained otherwise during this regeneration phase. Thus, rotating hypertrophy and strength-power sessions in a microcycle during the season is a viable option. Comparative studies in competitive athletes who integrated strength training during pre-season conditioning confirm a tendency for gains in explosive strength and statistically significant improvements in medicine ball throw through SPP but not through daily undulating periodization. These findings indicate that to maximize the speed-strength in the short term (peaking), elite athletes should perform strength-power training twice per week. It is possible to perform a single strength-power session with the method of maximum explosive strength actions moving high-weight loads (90% 1 repetition maximum [RM]) at

Short term wind speed forecasting in La Venta, Oaxaca, Mexico, using artificial neural networks

Energy Technology Data Exchange (ETDEWEB)

Cadenas, Erasmo [Facultad de Ingenieria Mecanica, Universidad Michoacana de San Nicolas de Hidalgo, Santiago Tapia No. 403, Centro, 5000, Mor., Mich. (Mexico); Rivera, Wilfrido [Centro de Ivestigacion en Energia, Universidad Nacional Autonoma de Mexico, Apartado Postal 34, Temixco 62580, Morelos (Mexico)

2009-01-15

In this paper the short term wind speed forecasting in the region of La Venta, Oaxaca, Mexico, applying the technique of artificial neural network (ANN) to the hourly time series representative of the site is presented. The data were collected by the Comision Federal de Electricidad (CFE) during 7 years through a network of measurement stations located in the place of interest. Diverse configurations of ANN were generated and compared through error measures, guaranteeing the performance and accuracy of the chosen models. First a model with three layers and seven neurons was chosen, according to the recommendations of diverse authors, nevertheless, the results were not sufficiently satisfactory so other three models were developed, consisting of three layers and six neurons, two layers and four neurons and two layers and three neurons. The simplest model of two layers, with two input neurons and one output neuron, was the best for the short term wind speed forecasting, with mean squared error and mean absolute error values of 0.0016 and 0.0399, respectively. The developed model for short term wind speed forecasting showed a very good accuracy to be used by the Electric Utility Control Centre in Oaxaca for the energy supply. (author)

Possible factors determining the non-linearity in the VO2-power output relationship in humans: theoretical studies.

Science.gov (United States)

Korzeniewski, Bernard; Zoladz, Jerzy A

2003-08-01

At low power output exercise (below lactate threshold), the oxygen uptake increases linearly with power output, but at high power output exercise (above lactate threshold) some additional oxygen consumption causes a non-linearity in the overall VO(2) (oxygen uptake rate)-power output relationship. The functional significance of this phenomenon for human exercise tolerance is very important, but the mechanisms underlying it remain unknown. In the present work, a computer model of oxidative phosphorylation in intact skeletal muscle developed previously is used to examine the background of this relationship in different modes of exercise. Our simulations demonstrate that the non-linearity in the VO(2)-power output relationship and the difference in the magnitude of this non-linearity between incremental exercise mode and square-wave exercise mode (constant power output exercise) can be generated by introducing into the model some hypothetical factor F (group of associated factors) that accumulate(s) in time during exercise. The performed computer simulations, based on this assumption, give proper time courses of changes in VO(2) and [PCr] after an onset of work of different intensities, including the slow component in VO(2), well matching the experimental results. Moreover, if it is assumed that the exercise terminates because of fatigue when the amount/intensity of F exceed some threshold value, the model allows the generation of a proper shape of the well-known power-duration curve. This fact suggests that the phenomenon of the non-linearity of the VO(2)-power output relationship and the magnitude of this non-linearity in different modes of exercise is determined by some factor(s) responsible for muscle fatigue.

Investigating the Correlation Between Wind and Solar Power Forecast Errors in the Western Interconnection: Preprint

Energy Technology Data Exchange (ETDEWEB)

Zhang, J.; Hodge, B. M.; Florita, A.

2013-05-01

Wind and solar power generations differ from conventional energy generation because of the variable and uncertain nature of their power output. This variability and uncertainty can have significant impacts on grid operations. Thus, short-term forecasting of wind and solar generation is uniquely helpful for power system operations to balance supply and demand in an electricity system. This paper investigates the correlation between wind and solar power forecasting errors.

Forecasting the daily power output of a grid-connected photovoltaic system based on multivariate adaptive regression splines

International Nuclear Information System (INIS)

Li, Yanting; He, Yong; Su, Yan; Shu, Lianjie

2016-01-01

Highlights: • Suggests a nonparametric model based on MARS for output power prediction. • Compare the MARS model with a wide variety of prediction models. • Show that the MARS model is able to provide an overall good performance in both the training and testing stages. - Abstract: Both linear and nonlinear models have been proposed for forecasting the power output of photovoltaic systems. Linear models are simple to implement but less flexible. Due to the stochastic nature of the power output of PV systems, nonlinear models tend to provide better forecast than linear models. Motivated by this, this paper suggests a fairly simple nonlinear regression model known as multivariate adaptive regression splines (MARS), as an alternative to forecasting of solar power output. The MARS model is a data-driven modeling approach without any assumption about the relationship between the power output and predictors. It maintains simplicity of the classical multiple linear regression (MLR) model while possessing the capability of handling nonlinearity. It is simpler in format than other nonlinear models such as ANN, k-nearest neighbors (KNN), classification and regression tree (CART), and support vector machine (SVM). The MARS model was applied on the daily output of a grid-connected 2.1 kW PV system to provide the 1-day-ahead mean daily forecast of the power output. The comparisons with a wide variety of forecast models show that the MARS model is able to provide reliable forecast performance.

Wind Power accuracy and forecast. D3.1. Assumptions on accuracy of wind power to be considered at short and long term horizons

Energy Technology Data Exchange (ETDEWEB)

Morthorst, P.E.; Coulondre, J.M.; Schroeder, S.T.; Meibom, P.

2010-07-15

The main objective of the Optimate project (An Open Platform to Test Integration in new MArkeT designs of massive intermittent Energy sources dispersed in several regional power markets) is to develop a new tool for testing these new market designs with large introduction of variable renewable energy sources. In Optimate a novel network/system/market modelling approach is being developed, generating an open simulation platform able to exhibit the comparative benefits of several market design options. This report constitutes delivery 3.1 on the assumptions on accuracy of wind power to be considered at short and long term horizons. The report handles the issues of state-of-the-art prediction, how predictions for wind power enter into the Optimate model and a simple and a more advanced methodology of how to generate trajectories of prediction errors to be used in Optimate. The main conclusion is that undoubtedly, the advanced approach is to be preferred to the simple one seen from a theoretical viewpoint. However, the advanced approach was developed to the Wilmar-model with the purpose of describing the integration of large-scale wind power in Europe. As the main purpose of the Optimate model is not to test the integration of wind power, but to test new market designs assuming a strong growth in wind power production, a more simplified approach for describing wind power forecasts should be sufficient. Thus a further development of the simple approach is suggested, eventually including correlations between geographical areas. In this report the general methodologies for generating trajectories for wind power forecasts are outlined. However, the methods are not yet implemented. In the next phase of Optimate, the clusters will be defined and the needed data collected. Following this phase actual results will be generated to be used in Optimate. (LN)

Short-Term Memory and Aphasia: From Theory to Treatment.

Science.gov (United States)

Minkina, Irene; Rosenberg, Samantha; Kalinyak-Fliszar, Michelene; Martin, Nadine

2017-02-01

This article reviews existing research on the interactions between verbal short-term memory and language processing impairments in aphasia. Theoretical models of short-term memory are reviewed, starting with a model assuming a separation between short-term memory and language, and progressing to models that view verbal short-term memory as a cognitive requirement of language processing. The review highlights a verbal short-term memory model derived from an interactive activation model of word retrieval. This model holds that verbal short-term memory encompasses the temporary activation of linguistic knowledge (e.g., semantic, lexical, and phonological features) during language production and comprehension tasks. Empirical evidence supporting this model, which views short-term memory in the context of the processes it subserves, is outlined. Studies that use a classic measure of verbal short-term memory (i.e., number of words/digits correctly recalled in immediate serial recall) as well as those that use more intricate measures (e.g., serial position effects in immediate serial recall) are discussed. Treatment research that uses verbal short-term memory tasks in an attempt to improve language processing is then summarized, with a particular focus on word retrieval. A discussion of the limitations of current research and possible future directions concludes the review. Thieme Medical Publishers 333 Seventh Avenue, New York, NY 10001, USA.

Balancing Europe's wind power output through spatial deployment informed by weather regimes.

Science.gov (United States)

Grams, Christian M; Beerli, Remo; Pfenninger, Stefan; Staffell, Iain; Wernli, Heini

2017-08-01

As wind and solar power provide a growing share of Europe's electricity1, understanding and accommodating their variability on multiple timescales remains a critical problem. On weekly timescales, variability is related to long-lasting weather conditions, called weather regimes2-5, which can cause lulls with a loss of wind power across neighbouring countries6. Here we show that weather regimes provide a meteorological explanation for multi-day fluctuations in Europe's wind power and can help guide new deployment pathways which minimise this variability. Mean generation during different regimes currently ranges from 22 GW to 44 GW and is expected to triple by 2030 with current planning strategies. However, balancing future wind capacity across regions with contrasting inter-regime behaviour - specifically deploying in the Balkans instead of the North Sea - would almost eliminate these output variations, maintain mean generation, and increase fleet-wide minimum output. Solar photovoltaics could balance low-wind regimes locally, but only by expanding current capacity tenfold. New deployment strategies based on an understanding of continent-scale wind patterns and pan-European collaboration could enable a high share of wind energy whilst minimising the negative impacts of output variability.

Estimation of PV output power in moving and rocking hybrid energy marine ships

International Nuclear Information System (INIS)

Liu, Hongda; Zhang, Qing; Qi, Xiaoxia; Han, Yang; Lu, Fang

2017-01-01

Highlights: •A mathematical model for characterizing the ship PV output power is developed. •The impacts of the sea condition and ship type on the PV output power are analyzed. •The hybrid energy storage system is used to stabilize the PV fluctuation powers. •A SC configuration method based on maximum half period is applied. -- Abstract: In recent years, the application of solar energy and energy storage to ship power systems has shown promise as a method for both reducing annual carbon and nitrogen oxide emissions and improving ship energy efficiency in the maritime shipping industry. When a ship navigates at sea, it encounters a constant rocking motion that is affected by both the surrounding sea conditions and the ship’s navigation parameters. This motion increases the uncertainty involved in using solar energy and accelerates the aging of the ship’s energy storage battery to some extent. In this study, a universal mathematical model is established for the power generation by photovoltaic (PV) modules in which both the sea conditions and the ship’s integrated motion, including its basic movement along with the motion caused by rocking, are taken into account. Based on this model, the fluctuation characteristics of a ship’s PV output power are studied and determined using three different simulation scenarios. A binary energy storage scheme based on a decoupled PV output power is proposed in order to both stabilize the small-period PV power fluctuations and slow the aging of the actual battery caused by rocking. In addition, a super-capacitor (SC) configuration is constructed based on a maximum half cycle. Finally, the optimal energy storage capacities for this green ship are compared under both rocking and moving motion. In the case of rocking motion, the SCs are able to achieve an approximately 24.8–35.0% reduction in battery replacement. A shipping route between Shanghai, China and Sydney, Australia is considered to validate the practicality

A 25 W 70% Efficiency Doherty Power Amplifier at 6 dB Output Back-Off for 2.4 GHz Applications with VGS, PEAK

Directory of Open Access Journals (Sweden)

Jorge Moreno Rubio

2015-01-01

Full Text Available This paper shows the design and simulation results of a hybrid Doherty power amplifier. The amplifier has been designed at 2,4 GHz, obtaining power-added efficiency above 70 % for 6 dB output power back-off, together with a small signal gain of 17 dB. Design and analysis equations are presented considering class AB bias conditions for the main amplifier and class C for the peak one in back-off larger than 6 dB, and FET device assumption. An additional control on the bias point of the peak device has been carried out, in order to increase the gain on the Doherty region and ease the design of the peak branch. A Cree’s GaN-HEMT CGH40010F device has been used with a nonlinear model guarantied up to 6 GHz and with an expected output power of 10 W. The obtained output power is higher than 25-W. The simulation has been carried out using Agilent ADS CAD tools. The present design could present the state of the art in terms of continuous-wave (CW characterization

Tuning range and output power optimization of an external-cavity GaN diode laser at 455 nm

DEFF Research Database (Denmark)

Chi, Mingjun; Jensen, Ole Bjarlin; Petersen, Paul Michael

2016-01-01

In this paper we discuss how different feedback gratings affect the tuning range and the output power of external feedback diode laser systems. A tunable high-power narrow-spectrum external-cavity diode laser system around 455 nm is investigated. The laser system is based on a high-power GaN diode...... laser in a Littrow external-cavity. Both a holographic diffraction grating and a ruled diffraction grating are used as feedback elements in the external cavity. The output power, spectral bandwidth, and tunable range of the external cavity diode laser system are measured and compared with the two...... gratings at different injected currents. When the holographic grating is used, the laser system can be tuned over a range of 1.4 nm with an output power around 530 mW. When the ruled grating is used, the laser system can be tuned over a range of 6.0 nm with an output power around 80 mW. The results can...

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.

Non-linear relationship between O2 uptake and power output at high intensities of exercise in humans.

Science.gov (United States)

Zoladz, J A; Rademaker, A C; Sargeant, A J

1995-01-01

1. A slow component to pulmonary oxygen uptake (VO2) is reported during prolonged high power exercise performed at constant power output at, or above, approximately 60% of the maximal oxygen uptake. The magnitude of the slow component is reported to be associated with the intensity of exercise and to be largely accounted for by an increased VO2 across the exercising legs. 2. On the assumption that the control mechanism responsible for the increased VO2 is intensity dependent we hypothesized that it should also be apparent in multi-stage incremental exercise tests with the result that the VO2-power output relationship would be curvilinear. 3. We further hypothesized that the change in the VO2-power output relationship could be related to the hierarchical recruitment of different muscle fibre types with a lower mechanical efficiency. 4. Six subjects each performed five incremental exercise tests, at pedalling rates of 40, 60, 80, 100 and 120 rev min-1, over which range we expected to vary the proportional contribution of different fibre types to the power output. Pulmonary VO2 was determined continuously and arterialized capillary blood was sampled and analysed for blood lactate concentration ([lactate]b). 5. Below the level at which a sustained increase in [lactate]b was observed pulmonary VO2 showed a linear relationship with power output; at high power outputs, however, there was an additional increase in VO2 above that expected from the extrapolation of that linear relationship, leading to a positive curvilinear VO2-power output relationship. 6. No systematic effect on the magnitude or onset of the 'extra' VO2 was found in relation to pedalling rate, which suggests that it is not related to the pattern of motor unit recruitment in any simple way. PMID:8568657

Short-term memories with a stochastic perturbation

International Nuclear Information System (INIS)

Pontes, Jose C.A. de; Batista, Antonio M.; Viana, Ricardo L.; Lopes, Sergio R.

2005-01-01

We investigate short-term memories in linear and weakly nonlinear coupled map lattices with a periodic external input. We use locally coupled maps to present numerical results about short-term memory formation adding a stochastic perturbation in the maps and in the external input

Short-term variability of Cyg X-1

International Nuclear Information System (INIS)

Oda, M.; Doi, K.; Ogawara, Y.

1976-01-01

The short-term X-ray variability distinguishes Cyg X-1, which is the most likely candidate for a black hole, from other X-ray sources. The present status of our knowledge on this short-term variation, mainly from the UHURU, the MIT and the GSFC observations, is reviewed. The nature of impulsive variations which compose the time variation exceeding the statistical fluctuation is discussed. There are indications that the energy spectrum of large pulses is harder than the average spectrum, or that the large pulses are the characteristics of the hard component of the spectrum if it is composed of two, soft and hard, components. Features of the variations may be partly simulated by the superposition of random shot-noise pulses with a fraction of a second duration. However, the autocorrelation analysis and the dynamic spectrum analysis indicate that the correlation lasts for several seconds and in the variation are buried some regularities which exhibit power concentrations in several frequency bands; 0.2-0.3, 0.4-0.5, 0.8, 1.2-1.5 Hz. There are several possible interpretations of these results in terms of; e.g. (a) a mixture of shot-noise pulses with two or more constant durations, (b) the shape of the basic shot-noise pulse, (c) bunching of the pulses, (d) superposition of wave-packets or temporal oscillations. But we have not yet reached any definite understandings in the nature of the variabilities. The substructure of the fluctuations on a time scale of milliseconds suggested by two investigations is also discussed. (Auth.)

Short-term memory

Science.gov (United States)

Toulouse, G.

This is a rather bold attempt to bridge the gap between neuron structure and psychological data. We try to answer the question: Is there a relation between the neuronal connectivity in the human cortex (around 5,000) and the short-term memory capacity (7±2)? Our starting point is the Hopfield model (Hopfield 1982), presented in this volume by D.J. Amit.

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.

Enhanced normal short-term human myelopoiesis in mice engineered to express human-specific myeloid growth factors.

Science.gov (United States)

Miller, Paul H; Cheung, Alice M S; Beer, Philip A; Knapp, David J H F; Dhillon, Kiran; Rabu, Gabrielle; Rostamirad, Shabnam; Humphries, R Keith; Eaves, Connie J

2013-01-31

Better methods to characterize normal human hematopoietic cells with short-term repopulating activity cells (STRCs) are needed to facilitate improving recovery rates in transplanted patients.We now show that 5-fold more human myeloid cells are produced in sublethally irradiated NOD/SCID-IL-2Receptor-γchain-null (NSG) mice engineered to constitutively produce human interleukin-3, granulocyte-macrophage colony-stimulating factor and Steel factor (NSG-3GS mice) than in regular NSG mice 3 weeks after an intravenous injection of CD34 human cord blood cells. Importantly, the NSG-3GS mice also show a concomitant and matched increase in circulating mature human neutrophils. Imaging NSG-3GS recipients of lenti-luciferase-transduced cells showed that human cells being produced 3 weeks posttransplant were heterogeneously distributed, validating the blood as a more representative measure of transplanted STRC activity. Limiting dilution transplants further demonstrated that the early increase in human granulopoiesis in NSG-3GS mice reflects an expanded output of differentiated cells per STRC rather than an increase in STRC detection. NSG-3GS mice support enhanced clonal outputs from human short-term repopulating cells (STRCs) without affecting their engrafting efficiency. Increased human STRC clone sizes enable their more precise and efficient measurement by peripheral blood monitoring.

Competitive short-term and long-term memory processes in spatial habituation.

Science.gov (United States)

Sanderson, David J; Bannerman, David M

2011-04-01

Exposure to a spatial location leads to habituation of exploration such that, in a novelty preference test, rodents subsequently prefer exploring a novel location to the familiar location. According to Wagner's (1981) theory of memory, short-term and long-term habituation are caused by separate and sometimes opponent processes. In the present study, this dual-process account of memory was tested. Mice received a series of exposure training trials to a location before receiving a novelty preference test. The novelty preference was greater when tested after a short, rather than a long, interval. In contrast, the novelty preference was weaker when exposure training trials were separated by a short, rather than a long interval. Furthermore, it was found that long-term habituation was determined by the independent effects of the amount of exposure training and the number of exposure training trials when factors such as the intertrial interval and the cumulative intertrial interval were controlled. A final experiment demonstrated that a long-term reduction of exploration could be caused by a negative priming effect due to associations formed during exploration. These results provide evidence against a single-process account of habituation and suggest that spatial habituation is determined by both short-term, recency-based memory and long-term, incrementally strengthened memory.

Retrieval-Induced Inhibition in Short-Term Memory.

Science.gov (United States)

Kang, Min-Suk; Choi, Joongrul

2015-07-01

We used a visual illusion called motion repulsion as a model system for investigating competition between two mental representations. Subjects were asked to remember two random-dot-motion displays presented in sequence and then to report the motion directions for each. Remembered motion directions were shifted away from the actual motion directions, an effect similar to the motion repulsion observed during perception. More important, the item retrieved second showed greater repulsion than the item retrieved first. This suggests that earlier retrieval exerted greater inhibition on the other item being held in short-term memory. This retrieval-induced motion repulsion could be explained neither by reduced cognitive resources for maintaining short-term memory nor by continued inhibition between short-term memory representations. These results indicate that retrieval of memory representations inhibits other representations in short-term memory. We discuss mechanisms of retrieval-induced inhibition and their implications for the structure of memory. © The Author(s) 2015.

Short term hydroelectric power system scheduling with wind turbine generators using the multi-pass iteration particle swarm optimization approach

International Nuclear Information System (INIS)

Lee, T.-Y.

2008-01-01

This paper uses multi-pass iteration particle swarm optimization (MIPSO) to solve short term hydroelectric generation scheduling of a power system with wind turbine generators. MIPSO is a new algorithm for solving nonlinear optimal scheduling problems. A new index called iteration best (IB) is incorporated into particle swarm optimization (PSO) to improve solution quality. The concept of multi-pass dynamic programming is applied to modify PSO further and improve computation efficiency. The feasible operational regions of the hydro units and pumped storage plants over the whole scheduling time range must be determined before applying MIPSO to the problem. Wind turbine power generation then shaves the power system load curves. Next, MIPSO calculates hydroelectric generation scheduling. It begins with a coarse time stage and searching space and refines the time interval between two time stages and the search spacing pass by pass (iteration). With the cooperation of agents called particles, the near optimal solution of the scheduling problem can be effectively reached. The effects of wind speed uncertainty were also considered in this paper. The feasibility of the new algorithm is demonstrated by a numerical example, and MIPSO solution quality and computation efficiency are compared to those of other algorithms

Evaluation of Short Term Memory Span Function In Children

Directory of Open Access Journals (Sweden)

Barış ERGÜL

2016-12-01

Full Text Available Although details of the information encoded in the short-term memory where it is stored temporarily be recorded in the working memory in the next stage. Repeating the information mentally makes it remain in memory for a long time. Studies investigating the relationship between short-term memory and reading skills that are carried out to examine the relationship between short-term memory processes and reading comprehension. In this study information coming to short-term memory and the factors affecting operation of short term memory are investigated with regression model. The aim of the research is to examine the factors (age, IQ and reading skills that are expected the have an effect on short-term memory in children through regression analysis. One of the assumptions of regression analysis is to examine which has constant variance and normal distribution of the error term. In this study, because the error term is not normally distributed, robust regression techniques were applied. Also, for each technique; coefficient of determination is determined. According to the findings, the increase in age, IQ and reading skills caused the increase in short term memory in children. After applying robust regression techniques, the Winsorized Least Squares (WLS technique gives the highest coefficient of determination.

Research on Power Output Characteristics of Magnetic Core in Energy Harvesting Devices

Directory of Open Access Journals (Sweden)

Rong-Ping GUO

2014-07-01

Full Text Available Magnetic core is the dominant factor in the performance of current transformer energy harvesting devices. The power output model of the magnetic core is established and verified through experiments. According to the actual application requirements, the concept of power density is proposed. The relationships of power density to air gap, material and dimension of the magnetic core are analyzed and verified through experiments.

Reliability and Energy Output of Bifacial Modules

Energy Technology Data Exchange (ETDEWEB)

Van Aken, B.B.; Jansen, M.J.; Dekker, N.J.J. [ECN Solar Energy, Petten (Netherlands)

2013-06-15

Although flash tests under standard test conditions yields lower power due to transmittance of the back sheet, bifacial modules are expected to outperform their monofacial equivalents in terms of yearly energy output in the field. We compare flash tests for bifacial modules with and without a light scattering panel directly behind the modules: 3% more power output is obtained. We also report on the damp-heat reliability of modules with transparent back sheet. Finally we will present the results of an outdoor study comparing modules with transparent back sheet and modules with state-of-the-art AR coating on the front glass.

Phonological short-term memory impairment and the word length effect in children with intellectual disabilities.

Science.gov (United States)

Poloczek, Sebastian; Büttner, Gerhard; Hasselhorn, Marcus

2014-02-01

There is mounting evidence that children and adolescents with intellectual disabilities (ID) of nonspecific aetiology perform poorer on phonological short-term memory tasks than children matched for mental age indicating a structural deficit in a process contributing to short-term recall of verbal material. One explanation is that children with ID of nonspecific aetiology do not activate subvocal rehearsal to refresh degrading memory traces. However, existing research concerning this explanation is inconclusive since studies focussing on the word length effect (WLE) as indicator of rehearsal have revealed inconsistent results for samples with ID and because in several existing studies, it is unclear whether the WLE was caused by rehearsal or merely appeared during output of the responses. We assumed that in children with ID only output delays produce a small WLE while in typically developing 6- to 8-year-olds rehearsal and output contribute to the WLE. From this assumption we derived several predictions that were tested in an experiment including 34 children with mild or borderline ID and 34 typically developing children matched for mental age (MA). As predicted, results revealed a small but significant WLE for children with ID that was significantly smaller than the WLE in the control group. Additionally, for children with ID, a WLE was not found for the first word of each trial but the effect emerged only in later serial positions. The findings corroborate the notion that in children with ID subvocal rehearsal does not develop in line with their mental age and provide a potential explanation for the inconsistent results on the WLE in children with ID. Copyright © 2013 Elsevier Ltd. All rights reserved.

Evaluation of Short Term Memory Span Function In Children

OpenAIRE

Barış ERGÜL; Arzu ALTIN YAVUZ; Ebru GÜNDOĞAN AŞIK

2016-01-01

Although details of the information encoded in the short-term memory where it is stored temporarily be recorded in the working memory in the next stage. Repeating the information mentally makes it remain in memory for a long time. Studies investigating the relationship between short-term memory and reading skills that are carried out to examine the relationship between short-term memory processes and reading comprehension. In this study information coming to short-term memory and the factors ...

Short-term Memory as a Processing Shift

Science.gov (United States)

Lewis-Smith, Marion Quinn

1975-01-01

The series of experiments described here examined the predictions for free recall from sequential models and the shift formulation, focusing on the roles of short- and long-term memory in the primacy/recency shift and on the effects of expectancies on short- and long-term memory. (Author/RK)

Does increasing active warm-up duration affect afternoon short-term maximal performance during Ramadan?

Science.gov (United States)

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

2015-01-01

The purpose of this study was to examine the effect of active warm-up duration on short-term maximal performance assessed during Ramadan in the afternoon. Twelve healthy active men took part in the study. The experimental design consisted of four test sessions conducted at 5 p.m., before and during Ramadan, either with a 5-minute or a 15-minute 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. During each session, the subjects performed two vertical jump tests (squat jump and counter movement jump) for measurement of vertical jump height followed by a 30-second Wingate test for measurement of peak and mean power. Oral temperature was recorded at rest and after warming-up. Moreover, ratings of perceived exertion were obtained immediately after the Wingate test. Oral temperature was higher before Ramadan than during Ramadan at rest, and was higher after the 15-minute warm-up than the 5-minute warm-up both before and during Ramadan. In addition, vertical jump heights were not significantly different between the two warm-up conditions before and during Ramadan, and were lower during Ramadan than before Ramadan after both warm-up conditions. Peak and mean power were not significantly different between the two warm-up durations before Ramadan, but were significantly higher after the 5-minute warm-up than the 15-minute warm-up during Ramadan. Moreover, peak and mean power were lower during Ramadan than before Ramadan after both warm-up conditions. Furthermore, ratings of perceived exertion were higher after the 15-minute warm-up than the 5-minute warm-up only during Ramadan. The prolonged active warm-up has no effect on vertical jump height but impairs anaerobic power assessed during Ramadan in the afternoon.

Statistical downscaling of precipitation using long short-term memory recurrent neural networks

Science.gov (United States)

Misra, Saptarshi; Sarkar, Sudeshna; Mitra, Pabitra

2017-11-01

Hydrological impacts of global climate change on regional scale are generally assessed by downscaling large-scale climatic variables, simulated by General Circulation Models (GCMs), to regional, small-scale hydrometeorological variables like precipitation, temperature, etc. In this study, we propose a new statistical downscaling model based on Recurrent Neural Network with Long Short-Term Memory which captures the spatio-temporal dependencies in local rainfall. The previous studies have used several other methods such as linear regression, quantile regression, kernel regression, beta regression, and artificial neural networks. Deep neural networks and recurrent neural networks have been shown to be highly promising in modeling complex and highly non-linear relationships between input and output variables in different domains and hence we investigated their performance in the task of statistical downscaling. We have tested this model on two datasets—one on precipitation in Mahanadi basin in India and the second on precipitation in Campbell River basin in Canada. Our autoencoder coupled long short-term memory recurrent neural network model performs the best compared to other existing methods on both the datasets with respect to temporal cross-correlation, mean squared error, and capturing the extremes.

Empirical investigation on using wind speed volatility to estimate the operation probability and power output of wind turbines

International Nuclear Information System (INIS)

Liu, Heping; Shi, Jing; Qu, Xiuli

2013-01-01

Highlights: ► Ten-minute wind speed and power generation data of an offshore wind turbine are used. ► An ARMA–GARCH-M model is built to simultaneously forecast wind speed mean and volatility. ► The operation probability and expected power output of the wind turbine are predicted. ► The integrated approach produces more accurate wind power forecasting than other conventional methods. - Abstract: In this paper, we introduce a quantitative methodology that performs the interval estimation of wind speed, calculates the operation probability of wind turbine, and forecasts the wind power output. The technological advantage of this methodology stems from the empowered capability of mean and volatility forecasting of wind speed. Based on the real wind speed and corresponding wind power output data from an offshore wind turbine, this methodology is applied to build an ARMA–GARCH-M model for wind speed forecasting, and then to compute the operation probability and the expected power output of the wind turbine. The results show that the developed methodology is effective, the obtained interval estimation of wind speed is reliable, and the forecasted operation probability and expected wind power output of the wind turbine are accurate

Statistical Language Modeling for Historical Documents using Weighted Finite-State Transducers and Long Short-Term Memory

OpenAIRE

Al Azawi, Mayce

2015-01-01

The goal of this work is to develop statistical natural language models and processing techniques based on Recurrent Neural Networks (RNN), especially the recently introduced Long Short- Term Memory (LSTM). Due to their adapting and predicting abilities, these methods are more robust, and easier to train than traditional methods, i.e., words list and rule-based models. They improve the output of recognition systems and make them more accessible to users for browsing and reading...

On the relationship between short- and long-term memory

DEFF Research Database (Denmark)

Sørensen, Thomas Alrik

James (1890) divided memory into separate stores; primary and secondary – or short-term and long-term memory. The interaction between the two stores often assumes that information initially is represented in volatile short-term store before entering and consolidating in the more durable long-term......, accepted). Counter to popular beliefs this suggest that long-term memory precedes short-term memory and not vice versa....... memory system (e.g. Atkinson & Shiffrin, 1968). Short-term memory seems to provide a surprising processing bottleneck where only a very limited amount of information can be represented at any given moment (Miller, 1956; Cowan, 2001). A number of studies have investigated the nature of this processing...

Smoothing Control of Wind Farm Output by Using Kinetic Energy of Variable Speed Wind Power Generators

Science.gov (United States)

Sato, Daiki; Saitoh, Hiroumi

This paper proposes a new control method for reducing fluctuation of power system frequency through smoothing active power output of wind farm. The proposal is based on the modulation of rotaional kinetic energy of variable speed wind power generators through power converters between permanent magnet synchronous generators (PMSG) and transmission lines. In this paper, the proposed control is called Fluctuation Absorption by Flywheel Characteristics control (FAFC). The FAFC can be easily implemented by adding wind farm output signal to Maximum Power Point Tracking control signal through a feedback control loop. In order to verify the effectiveness of the FAFC control, a simulation study was carried out. In the study, it was assumed that the wind farm consisting of PMSG type wind power generator and induction machine type wind power generaotors is connected with a power sysem. The results of the study show that the FAFC control is a useful method for reducing the impacts of wind farm output fluctuation on system frequency without additional devices such as secondary battery.

Non-Fourier conduction model with thermal source term of ultra short high power pulsed laser ablation and temperature evolvement before melting

International Nuclear Information System (INIS)

Zhang Duanming; Li, Li; Li Zhihua; Guan Li; Tan Xinyu

2005-01-01

A non-Fourier conduction model with heat source term is presented to study the target temperature evolvement when the target is radiated by high power (the laser intensity is above 10 9 w/cm 2 ) and ultra short (the pulse width is less than 150 ps) pulsed laser. By Laplace transform, the analytical expression of the space- and time-dependence of temperature is derived. Then as an example of aluminum target, the target temperature evolvement is simulated. Compared with the results of Fourier conduction model and non-Fourier model without heat source term, it is found that the effect of non-Fourier conduction is notable and the heat source plays an important role during non-Fourier conduction which makes surface temperature ascending quickly with time. Meanwhile, the corresponding physical mechanism is analyzed theoretically

Short-term memory and long-term memory are still different.

Science.gov (United States)

Norris, Dennis

2017-09-01

A commonly expressed view is that short-term memory (STM) is nothing more than activated long-term memory. If true, this would overturn a central tenet of cognitive psychology-the idea that there are functionally and neurobiologically distinct short- and long-term stores. Here I present an updated case for a separation between short- and long-term stores, focusing on the computational demands placed on any STM system. STM must support memory for previously unencountered information, the storage of multiple tokens of the same type, and variable binding. None of these can be achieved simply by activating long-term memory. For example, even a simple sequence of digits such as "1, 3, 1" where there are 2 tokens of the digit "1" cannot be stored in the correct order simply by activating the representations of the digits "1" and "3" in LTM. I also review recent neuroimaging data that has been presented as evidence that STM is activated LTM and show that these data are exactly what one would expect to see based on a conventional 2-store view. (PsycINFO Database Record (c) 2017 APA, all rights reserved).

Fast Weight Long Short-Term Memory

OpenAIRE

Keller, T. Anderson; Sridhar, Sharath Nittur; Wang, Xin

2018-01-01

Associative memory using fast weights is a short-term memory mechanism that substantially improves the memory capacity and time scale of recurrent neural networks (RNNs). As recent studies introduced fast weights only to regular RNNs, it is unknown whether fast weight memory is beneficial to gated RNNs. In this work, we report a significant synergy between long short-term memory (LSTM) networks and fast weight associative memories. We show that this combination, in learning associative retrie...

Blue 450nm high power semiconductor continuous wave laser bars exceeding rollover output power of 80W

Science.gov (United States)

König, H.; Lell, A.; Stojetz, B.; Ali, M.; Eichler, C.; Peter, M.; Löffler, A.; Strauss, U.; Baumann, M.; Balck, A.; Malchus, J.; Krause, V.

2018-02-01

Industrial material processing like cutting or welding of metals is rather energy efficient using direct diode or diode pumped solid state lasers. However, many applications cannot be addressed by established infrared laser technology due to fundamental material properties of the workpiece: For example materials like copper or gold have too low absorption in the near infrared wavelength range to be processed efficiently by use of existing high power laser systems. The huge interest to enable high power kW systems with more suitable wavelengths in the blue spectral range triggered the German funded research project 'BLAULAS': Therein the feasibility and capability of CW operating high power laser bars based on the GaN material system was investigated by Osram and Laserline. High performance bars were enabled by defeating fundamental challenges like material quality as well as the chip processes, both of which differ significantly from well-known IR laser bars. The research samples were assembled on actively cooled heat sinks with hard solder technology. For the first time an output power of 98W per bar at 60A drive current was achieved. Conversion efficiency as high as 46% at 50W output power was demonstrated.

Theoretical and experimental investigations of the limits to the maximum output power of laser diodes

International Nuclear Information System (INIS)

Wenzel, H; Crump, P; Pietrzak, A; Wang, X; Erbert, G; Traenkle, G

2010-01-01

The factors that limit both the continuous wave (CW) and the pulsed output power of broad-area laser diodes driven at very high currents are investigated theoretically and experimentally. The decrease in the gain due to self-heating under CW operation and spectral holeburning under pulsed operation, as well as heterobarrier carrier leakage and longitudinal spatial holeburning, are the dominant mechanisms limiting the maximum achievable output power.

Increasing the solar cell power output by coating with transition metal-oxide nanorods

International Nuclear Information System (INIS)

Kuznetsov, I.A.; Greenfield, M.J.; Mehta, Y.U.; Merchan-Merchan, W.; Salkar, G.; Saveliev, A.V.

2011-01-01

Highlights: → Nanoparticles enhance solar cell efficiency. → Solar cell power increase by nanorod coating. → Metal-oxide nanorods are prepared in flames. → Molybdenum oxide nanorods effectively scatter light on solar cell surface. → Scattering efficiency depends on coating density. -- Abstract: Photovoltaic cells produce electric current through interactions among photons from an ambient light source and electrons in the semiconductor layer of the cell. However, much of the light incident on the panel is reflected or absorbed without inducing the photovoltaic effect. Transition metal-oxide nanoparticles, an inexpensive product of a process called flame synthesis, can cause scattering of light. Scattering can redirect photon flux, increasing the fraction of light absorbed in the thin active layer of silicon solar cells. This research aims to demonstrate that the application of transition metal-oxide nanorods to the surface of silicon solar panels can enhance the power output of the panels. Several solar panels were coated with a nanoparticle-methanol suspension, and the power outputs of the panels before and after the treatment were compared. The results demonstrate an increase in power output of up to 5% after the treatment. The presence of metal-oxide nanorods on the surface of the coated solar cells is confirmed by electron microscopy.

An analysis on the short-term sectoral competitiveness impact of carbon tax in China

International Nuclear Information System (INIS)

Wang Xin; Li Ji Feng; Zhang Yaxiong

2011-01-01

Market-based instruments, particularly carbon tax, have recently drawn the attention of Chinese government by their cost-effective contribution to the achievement of China's climate targets. Most of the recent policy proposals have focused on its long-term impact. However, particularly for policy makers, both long term and short term effects of carbon tax would be necessary when determining tax rates. We provided a detailed analysis of short-term impacts of carbon tax on sectoral competitiveness in this paper. We divided China's economy into 36 sectors, based on its 2007 input-output table, in order to examine the ratio of carbon tax added costs to sector GDP. We were thus able to determine the impact level of a carbon tax on each sector. We then divided the sectoral trade impact into domestic competitiveness with regards to foreign imported products and international competitiveness external to the Chinese domestic market. We found that a high tax level (100 yuan/t CO 2 ) may necessitate compensatory measures to certain highly affected industries, and that a low tax rate (10 yuan/t CO 2 ) would generate few competitiveness problems for all industries and may therefore be considered as an appropriate starting point. - Highlights: → We study short-term sectoral competitiveness impact of carbon tax in China. → For each sector, we study its carbon cost, GDP share and trade intensity. → A high rate (100 yuan/t CO 2 ) may require compensatory measures to certain industries. → A low rate (10 yuan/t CO 2 ) would generate few competitiveness problems.

High output power reluctance electric motors with bulk high-temperature superconductor elements

Energy Technology Data Exchange (ETDEWEB)

Kovalev, L.K. [Moscow State Aviation Institute (Technical University) (MAI), Moscow (Russian Federation)]. E-mail: kovalev@mail.sitek.net; Ilushin, K.V.; Penkin, V.T. [Moscow State Aviation Institute (Technical University) (MAI), Moscow (RU)] [and others

2002-05-01

We present new types of electric machines with the rotors containing bulk high-temperature superconductor (HTS)-YBCO and Bi-Ag-elements. We discuss different schematics of hysteresis, reluctance, 'trapped field' and composed synchronous HTS machines. The two-dimensional mathematical models describing the processes in such types of HTS machines were developed on the basis of the theoretical analysis of the electrodynamic and hysteresis processes in the single-domain and polycrystal YBCO ceramic samples and plate shape Bi-Ag elements. We give the test results of the series of hysteresis, reluctance, 'trapped field' and composed with permanent magnets HTS motors with an output power rating of 0.1-18 kW and current frequencies 50 Hz and 400 Hz. These results show that in the media of liquid nitrogen the specific output power per one unit weight of the HTS motor is four to seven times better than for conventional electric machines. A comparison of the theoretical and experimental characteristics of the developed HTS motors show that they are in good agreement. We discuss the test results for a liquid nitrogen cryogenic pump system with a hysteresis 500 W HTS motor. We describe several designs of new HTS motors operating in the media of liquid nitrogen with an output power 125 kW (and more) and a power factor of more than 0.8. We discuss future applications of new types of HTS motors for aerospace technology, on-land industry and transport systems. (author)

Variable gas spring for matching power output from FPSE to load of refrigerant compressor

Science.gov (United States)

Chen, Gong; Beale, William T.

1990-01-01

The power output of a free piston Stirling engine is matched to a gas compressor which it drives and its stroke amplitude is made relatively constant as a function of power by connecting a gas spring to the drive linkage from the engine to the compressor. The gas spring is connected to the compressor through a passageway in which a valve is interposed. The valve is linked to the drive linkage so it is opened when the stroke amplitude exceeds a selected limit. This allows compressed gas to enter the spring, increase its spring constant, thus opposing stroke increase and reducing the phase lead of the displacer ahead of the piston to reduce power output and match it to a reduced load power demand.

Detecting, categorizing and forecasting large romps in wind farm power output using meteorological observations and WPPT

DEFF Research Database (Denmark)

Cutler, N.; Kay, M.; Jacka, K.

2007-01-01

The Wind Power Prediction Tool (WPPT) has been installed in Australia for the first time, to forecast the power output from the 65MW Roaring 40s Renewable Energy P/L Woolnorth Bluff Point wind form. This article analyses the general performance of WPPT as well as its performance during large romps...... (swings) in power output. In addition to this, detected large ramps are studied in detail and categorized. WPPT combines wind speed and direction forecasts from the Australian Bureau of Meteorology regional numerical weather prediction model, MesoLAPS, with real-time wind power observations to make hourly...... forecasts of the wind farm power output. The general performances of MesoLAPS and WPPTore evaluated over I year using the root mean square error (RMSE). The errors are significantly lower than for basic benchmark forecasts but higher than for many other WPPT installations, where the site conditions...

Improving creativity performance by short-term meditation

Science.gov (United States)

2014-01-01

Background One form of meditation intervention, the integrative body-mind training (IBMT) has been shown to improve attention, reduce stress and change self-reports of mood. In this paper we examine whether short-term IBMT can improve performance related to creativity and determine the role that mood may play in such improvement. Methods Forty Chinese undergraduates were randomly assigned to short-term IBMT group or a relaxation training (RT) control group. Mood and creativity performance were assessed by the Positive and Negative Affect Schedule (PANAS) and Torrance Tests of Creative Thinking (TTCT) questionnaire respectively. Results As predicted, the results indicated that short-term (30 min per day for 7 days) IBMT improved creativity performance on the divergent thinking task, and yielded better emotional regulation than RT. In addition, cross-lagged analysis indicated that both positive and negative affect may influence creativity in IBMT group (not RT group). Conclusions Our results suggested that emotion-related creativity-promoting mechanism may be attributed to short-term meditation. PMID:24645871

Long vs. short-term energy storage:sensitivity analysis.

Energy Technology Data Exchange (ETDEWEB)

Schoenung, Susan M. (Longitude 122 West, Inc., Menlo Park, CA); Hassenzahl, William V. (,Advanced Energy Analysis, Piedmont, CA)

2007-07-01

This report extends earlier work to characterize long-duration and short-duration energy storage technologies, primarily on the basis of life-cycle cost, and to investigate sensitivities to various input assumptions. Another technology--asymmetric lead-carbon capacitors--has also been added. Energy storage technologies are examined for three application categories--bulk energy storage, distributed generation, and power quality--with significant variations in discharge time and storage capacity. Sensitivity analyses include cost of electricity and natural gas, and system life, which impacts replacement costs and capital carrying charges. Results are presented in terms of annual cost, $/kW-yr. A major variable affecting system cost is hours of storage available for discharge.

Photovoltaic systems: state of the art and short-medium term perspectives

International Nuclear Information System (INIS)

Brofferio, Sergio C.; Rota, Alberto

2006-01-01

The paper presents and discusses, from a technology and economic point of view, the characteristics, performances, issues and perspectives of the thin films and the solar concentrating photovoltaic systems in the short and medium terms. Both have well based motivations to be an evolutionary step of current wafer based Silicon systems: the former as Building Integrated Photovoltaic and the latter as high density and high power photovoltaic systems [it

The Structure and Content of Long-Term and Short-Term Mate Preferences

Directory of Open Access Journals (Sweden)

Peter K. Jonason

2013-12-01

Full Text Available This study addresses two limitations in the mate preferences literature. First, research all-too-often relies on single-item assessments of mate preferences precluding more advanced statistical techniques like factor analysis. Second, when factor analysis could be done, it exclusively has done for long-term mate preferences, at the exclusion of short-term mate preferences. In this study (N = 401, we subjected 20 items designed to measure short- and long-term mate preferences to both principle components (n = 200 and confirmatory factor analysis (n = 201. In the long-term context, we replicated previous findings that there are three different categories of preferences: physical attractiveness, interpersonal warmth, and social status. In the short-term context, physical attractiveness occupied two parts of the structure, social status dropped out, and interpersonal warmth remained. Across short- and long-term contexts, there were slight changes in what defined the shared dimensions (i.e., physical attractiveness and interpersonal warmth, suggesting prior work that applies the same inventory to each context might be flawed. We also replicated sex differences and similarities in mate preferences and correlates with sociosexuality and mate value. We adopt an evolutionary paradigm to understand our results.

Short-term energy outlook, annual supplement 1994

International Nuclear Information System (INIS)

1994-08-01

The Short-Term Energy Outlook Annual Supplement (Supplement) is published once a year as a complement to the Short-Term Energy Outlook (Outlook), Quarterly Projections. The purpose of the Supplement is to review the accuracy of the forecasts published in the Outlook, make comparisons with other independent energy forecasts, and examine current energy topics that affect the forecasts

Short-term energy outlook annual supplement, 1993

Energy Technology Data Exchange (ETDEWEB)

NONE

1993-08-06

The Short-Term Energy Outlook Annual Supplement (supplement) is published once a year as a complement to the Short-Term Energy Outlook (Outlook), Quarterly Projections. The purpose of the Supplement is to review the accuracy of the forecasts published in the Outlook, make comparisons with other independent energy forecasts, and examine current energy topics that affect the forecasts.

The Sources of Life Chances: Does Education, Class Category, Occupation, or Short-Term Earnings Predict 20-Year Long-Term Earnings?

Directory of Open Access Journals (Sweden)

ChangHwan Kim

2018-03-01

Full Text Available In sociological studies of economic stratification and intergenerational mobility, occupation has long been presumed to reflect lifetime earnings better than do short-term earnings. However, few studies have actually tested this critical assumption. In this study, we investigate the cross-sectional determinants of 20-year accumulated earnings using data that match respondents in the Survey of Income and Program Participation to their longitudinal earnings records based on administrative tax information from 1990 to 2009. Fit statistics of regression models are estimated to assess the predictive power of various proxy variables, including occupation, education, and short-term earnings, on cumulative earnings over the 20-year time period. Contrary to the popular assumption in sociology, our results find that cross-sectional earnings have greater predictive power on long-term earnings than occupation-based class classifications, including three-digit detailed occupations for both men and women. The model based on educational attainment, including field of study, has slightly better fit than models based on one-digit occupation or the Erikson, Goldthorpe, and Portocarero class scheme. We discuss the theoretical implications of these findings for the sociology of stratification and intergenerational mobility.

Enhancing the power output of the VA-955 UHF-TV klystron

International Nuclear Information System (INIS)

Bowen, O.N.; Lawson, J.Q.

1977-01-01

The Varian VA-955 UHF-TV klystron is rated at 50 kW CW, and four of these klystrons were used to provide 200 kW of RF power for lower hybrid heating experiments on the ATC machine at 800 MHz. These proven, production-type tubes were wanted to generate more power for larger type machines, such as the PDX. Varian was asked whether the tubes were capable of higher-power operation in pulsed applications. They replied that they had no experimental data but felt that the tubes were capable of greatly enhanced performance under pulsed conditions. By using cathode modulation instead of modulating anode control of the klystron, and thus limiting the time that high voltage is applied to the cathode, it was shown that the tube is capable of an output power of 200 kW for tens of milliseconds compared to its normal CW rating of 50 kW. A description is given of the experimental results, the required modifications to the klystron and output transmission circuit, the details of operation of the regulating modulator used to perform the experiment. Upgrade kits are now being fabricated to allow 200 kW operation of the two 50 kW units which were lent to General Atomic for Doublet II experiments

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.

A long-term stable power supply µDMFC stack for wireless sensor node applications

International Nuclear Information System (INIS)

Wu, Zonglin; Wang, Xiaohong; Li, Xiaozhao; Xu, Manqi; Liu, Litian

2014-01-01

In this paper, a passive, air-breathing four-cell micro direct methanol fuel cell (µDMFC) stack featuring a fuel delivery structure for long-term and stable power supply is designed, fabricated and tested. The fuel is reserved in a T-shaped tank and diffuses through the porous diffusion layer to the catalyst at the anode. A peak power density of 25.7 mW cm −2 and a maximum power output of 113 mW are achieved with 3 M methanol at room temperature, and the stack can produce 60 mW of power, even though only 5% fuel remains in the reservoir. Combined with a low-input dc–dc convertor, the stack can realize a stable and optional constant voltage output from 1 V–6 V. The stack successfully powered a heavy metal sensor node for water environment monitoring 12 d continuously, with consumption of 10 mL 5 M methanol solution. As such, it is believed to be applicable for powering wireless sensor nodes. (paper)

TMI-2 Lessons Learned Task Force status report and short-term recommendations

International Nuclear Information System (INIS)

1979-07-01

Review of the Three Mile Island accident by the TMI-2 Lessons Learned Task Force has disclosed a number of actions in the areas of design and analysis and plant operations that the Task Force recommends be required in the short term to provide substantial additional protection which is required for the public health and safety. All nuclear power plants in operation or in various stages of construction or licensing action are affected to varying degrees by the specific recommendations. The Task Force is continuing work in areas of general safety criteria, systems design requirements, nuclear power plant operations, and nuclear power plant licensing

Monitoring Linear Accelerator Output Constancy Using the PTW Linacheck

International Nuclear Information System (INIS)

McDermott, Garry M.; Buckle, Andrew H.

2011-01-01

The PTW-Linacheck was assessed for its ability to monitor linear accelerator radiation output constancy. The key issues that were considered were the setup for daily output measurements, e.g., requirements for build-up and backscatter material, and the reproducibility and linearity of the device with linear accelerator output. An appropriate measurement setup includes a 10 x 10 cm field at 100 cm FSD, 5 cm backscatter, and no added build-up for 4 MeV electron beams, 1 cm added build-up for 6-16 MeV electron beams and 5 cm added build-up for 6-15 MV photon beams. Using this measurement setup, the dose linearity and short-term reproducibility were acceptable; however, the Linacheck should be recalibrated on a monthly basis to ensure acceptable long-term reproducibility.

Short-term prediction of local wind conditions

DEFF Research Database (Denmark)

Landberg, L.

2001-01-01

This paper will describe a 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...

Multiple regression approach to predict turbine-generator output for Chinshan nuclear power plant

International Nuclear Information System (INIS)

Chan, Yea-Kuang; Tsai, Yu-Ching

2017-01-01

The objective of this study is to develop a turbine cycle model using the multiple regression approach to estimate the turbine-generator output for the Chinshan Nuclear Power Plant (NPP). The plant operating data was verified using a linear regression model with a corresponding 95% confidence interval for the operating data. In this study, the key parameters were selected as inputs for the multiple regression based turbine cycle model. The proposed model was used to estimate the turbine-generator output. The effectiveness of the proposed turbine cycle model was demonstrated by using plant operating data obtained from the Chinshan NPP Unit 2. The results show that this multiple regression based turbine cycle model can be used to accurately estimate the turbine-generator output. In addition, this study also provides an alternative approach with simple and easy features to evaluate the thermal performance for nuclear power plants.

Multiple regression approach to predict turbine-generator output for Chinshan nuclear power plant

Energy Technology Data Exchange (ETDEWEB)

Chan, Yea-Kuang; Tsai, Yu-Ching [Institute of Nuclear Energy Research, Taoyuan City, Taiwan (China). Nuclear Engineering Division

2017-03-15

The objective of this study is to develop a turbine cycle model using the multiple regression approach to estimate the turbine-generator output for the Chinshan Nuclear Power Plant (NPP). The plant operating data was verified using a linear regression model with a corresponding 95% confidence interval for the operating data. In this study, the key parameters were selected as inputs for the multiple regression based turbine cycle model. The proposed model was used to estimate the turbine-generator output. The effectiveness of the proposed turbine cycle model was demonstrated by using plant operating data obtained from the Chinshan NPP Unit 2. The results show that this multiple regression based turbine cycle model can be used to accurately estimate the turbine-generator output. In addition, this study also provides an alternative approach with simple and easy features to evaluate the thermal performance for nuclear power plants.

Prediction of Sea Surface Temperature Using Long Short-Term Memory

Science.gov (United States)

Zhang, Qin; Wang, Hui; Dong, Junyu; Zhong, Guoqiang; Sun, Xin

2017-10-01

This letter adopts long short-term memory(LSTM) to predict sea surface temperature(SST), which is the first attempt, to our knowledge, to use recurrent neural network to solve the problem of SST prediction, and to make one week and one month daily prediction. We formulate the SST prediction problem as a time series regression problem. LSTM is a special kind of recurrent neural network, which introduces gate mechanism into vanilla RNN to prevent the vanished or exploding gradient problem. It has strong ability to model the temporal relationship of time series data and can handle the long-term dependency problem well. The proposed network architecture is composed of two kinds of layers: LSTM layer and full-connected dense layer. LSTM layer is utilized to model the time series relationship. Full-connected layer is utilized to map the output of LSTM layer to a final prediction. We explore the optimal setting of this architecture by experiments and report the accuracy of coastal seas of China to confirm the effectiveness of the proposed method. In addition, we also show its online updated characteristics.

In Search of Decay in Verbal Short-Term Memory

Science.gov (United States)

Berman, Marc G.; Jonides, John; Lewis, Richard L.

2009-01-01

Is forgetting in the short term due to decay with the mere passage of time, interference from other memoranda, or both? Past research on short-term memory has revealed some evidence for decay and a plethora of evidence showing that short-term memory is worsened by interference. However, none of these studies has directly contrasted decay and…

16 W output power by high-efficient spectral beam combining of DBR-tapered diode lasers

DEFF Research Database (Denmark)

Müller, André; Vijayakumar, Deepak; Jensen, Ole Bjarlin

2011-01-01

output power achieved by spectral beam combining of two single element tapered diode lasers. Since spectral beam combining does not affect beam propagation parameters, M2-values of 1.8 (fast axis) and 3.3 (slow axis) match the M2- values of the laser with lowest spatial coherence. The principle......Up to 16 W output power has been obtained using spectral beam combining of two 1063 nm DBR-tapered diode lasers. Using a reflecting volume Bragg grating, a combining efficiency as high as 93.7% is achieved, resulting in a single beam with high spatial coherence. The result represents the highest...... of spectral beam combining used in our experiments can be expanded to combine more than two tapered diode lasers and hence it is expected that the output power may be increased even further in the future....

16 W output power by high-efficient spectral beam combining of DBR-tapered diode lasers.

Science.gov (United States)

Müller, André; Vijayakumar, Deepak; Jensen, Ole Bjarlin; Hasler, Karl-Heinz; Sumpf, Bernd; Erbert, Götz; Andersen, Peter E; Petersen, Paul Michael

2011-01-17

Up to 16 W output power has been obtained using spectral beam combining of two 1063 nm DBR-tapered diode lasers. Using a reflecting volume Bragg grating, a combining efficiency as high as 93.7% is achieved, resulting in a single beam with high spatial coherence. The result represents the highest output power achieved by spectral beam combining of two single element tapered diode lasers. Since spectral beam combining does not affect beam propagation parameters, M2-values of 1.8 (fast axis) and 3.3 (slow axis) match the M2-values of the laser with lowest spatial coherence. The principle of spectral beam combining used in our experiments can be expanded to combine more than two tapered diode lasers and hence it is expected that the output power may be increased even further in the future.

Attention Problems, Phonological Short-Term Memory, and Visuospatial Short-Term Memory: Differential Effects on Near- and Long-Term Scholastic Achievement

Science.gov (United States)

Sarver, Dustin E.; Rapport, Mark D.; Kofler, Michael J.; Scanlan, Sean W.; Raiker, Joseph S.; Altro, Thomas A.; Bolden, Jennifer

2012-01-01

The current study examined individual differences in children's phonological and visuospatial short-term memory as potential mediators of the relationship among attention problems and near- and long-term scholastic achievement. Nested structural equation models revealed that teacher-reported attention problems were associated negatively with…

Output Control Technologies for a Large-scale PV System Considering Impacts on a Power Grid

Science.gov (United States)

Kuwayama, Akira

The mega-solar demonstration project named “Verification of Grid Stabilization with Large-scale PV Power Generation systems” had been completed in March 2011 at Wakkanai, the northernmost city of Japan. The major objectives of this project were to evaluate adverse impacts of large-scale PV power generation systems connected to the power grid and develop output control technologies with integrated battery storage system. This paper describes the outline and results of this project. These results show the effectiveness of battery storage system and also proposed output control methods for a large-scale PV system to ensure stable operation of power grids. NEDO, New Energy and Industrial Technology Development Organization of Japan conducted this project and HEPCO, Hokkaido Electric Power Co., Inc managed the overall project.

Short-Term Load Forecasting-Based Automatic Distribution Network Reconfiguration

Energy Technology Data Exchange (ETDEWEB)

Jiang, Huaiguang [National Renewable Energy Laboratory (NREL), Golden, CO (United States); Ding, Fei [National Renewable Energy Laboratory (NREL), Golden, CO (United States); Zhang, Yingchen [National Renewable Energy Laboratory (NREL), Golden, CO (United States)

2017-08-23

In a traditional dynamic network reconfiguration study, the optimal topology is determined at every scheduled time point by using the real load data measured at that time. The development of the load forecasting technique can provide an accurate prediction of the load power that will happen in a future time and provide more information about load changes. With the inclusion of load forecasting, the optimal topology can be determined based on the predicted load conditions during a longer time period instead of using a snapshot of the load at the time when the reconfiguration happens; thus, the distribution system operator can use this information to better operate the system reconfiguration and achieve optimal solutions. This paper proposes a short-term load forecasting approach to automatically reconfigure distribution systems in a dynamic and pre-event manner. Specifically, a short-term and high-resolution distribution system load forecasting approach is proposed with a forecaster based on support vector regression and parallel parameters optimization. The network reconfiguration problem is solved by using the forecasted load continuously to determine the optimal network topology with the minimum amount of loss at the future time. The simulation results validate and evaluate the proposed approach.

Short-Term Reciprocity in Late Parent-Child Relationships

Science.gov (United States)

Leopold, Thomas; Raab, Marcel

2011-01-01

Long-term concepts of parent-child reciprocity assume that the amount of support given and received is only balanced in a generalized fashion over the life course. We argue that reciprocity in parent-child relationships also operates in the short term. Our analysis of short-term reciprocity focuses on concurrent exchange in its main upward and…

Decay uncovered in nonverbal short-term memory.

Science.gov (United States)

Mercer, Tom; McKeown, Denis

2014-02-01

Decay theory posits that memory traces gradually fade away over the passage of time unless they are actively rehearsed. Much recent work exploring verbal short-term memory has challenged this theory, but there does appear to be evidence for trace decay in nonverbal auditory short-term memory. Numerous discrimination studies have reported a performance decline as the interval separating two tones is increased, consistent with a decay process. However, most of this tone comparison research can be explained in other ways, without reference to decay, and these alternative accounts were tested in the present study. In Experiment 1, signals were employed toward the end of extended retention intervals to ensure that listeners were alert to the presence and frequency content of the memoranda. In Experiment 2, a mask stimulus was employed in an attempt to distinguish between a highly detailed sensory trace and a longer-lasting short-term memory, and the distinctiveness of the stimuli was varied. Despite these precautions, slow-acting trace decay was observed. It therefore appears that the mere passage of time can lead to forgetting in some forms of short-term memory.

Short-term energy outlook annual supplement, 1993

International Nuclear Information System (INIS)

1993-01-01

The Energy Information Administration (EIA) prepares quarterly, short-term energy supply, demand, and price projections for publication in February, May, August, and November in the Short-Term Energy Outlook (Outlook). An annual supplement analyzes the performance of previous forecasts, compares recent cases with those of other forecasting services, and discusses current topics related to the short-term energy markets. (See Short-Term Energy Outlook Annual Supplement, DOE/EIA-0202.) The forecast period for this issue of the Outlook extends from the third quarter of 1993 through the fourth quarter of 1994. Values for the second quarter of 1993, however, are preliminary EIA estimates (for example, some monthly values for petroleum supply and disposition are derived in part from weekly data reported in the Weekly Petroleum Status Report) or are calculated from model simulations using the latest exogenous information available (for example, electricity sales and generation are simulated using actual weather data). The historical energy data are EIA data published in the Monthly Energy Review, Petroleum Supply Monthly, and other EIA publications. Minor discrepancies between the data in these publications and the historical data in this Outlook are due to independent rounding

Towards shorter wavelength x-ray lasers using a high power, short pulse pump laser

International Nuclear Information System (INIS)

Tighe, W.; Krushelnick, K.; Valeo, E.; Suckewer, S.

1991-05-01

A near-terawatt, KrF* laser system, focussable to power densities >10 18 W/cm 2 has been constructed for use as a pump laser in various schemes aimed at the development of x-ray lasing below 5nm. The laser system along with output characteristics such as the pulse duration, the focal spot size, and the percentage of amplified spontaneous emission (ASE) emitted along with the laser pulse will be presented. Schemes intended to lead to shorter wavelength x-ray emission will be described. The resultant requirements on the pump laser characteristics and the target design will be outlined. Results from recent solid target experiments and two-laser experiments, showing the interaction of a high-power, short pulse laser with a preformed plasma, will be presented. 13 refs., 5 figs

Loss of power output and laser fibre degradation during 120 watt lithium-triborate HPS laser vaporisation of the prostate

Science.gov (United States)

Hermanns, Thomas; Sulser, Tullio; Hefermehl, Lukas J.; Strebel, Daniel; Michel, Maurice-Stephan; Müntener, Michael; Meier, Alexander H.; Seifert, Hans-Helge

2009-02-01

It has recently been shown that laser fibre deterioration leads to a significant decrease of power output during 80 W potassium titanyl phosphate (KTP) laser vaporisation (LV) of the prostate. This decrease results in inefficient vaporisation especially towards the end of the procedure. For the new 120 W lithium-triborate (LBO) High Performance System (HPS) laser not only higher power but also changes in beam characteristics and improved fibre quality have been advertised. However, high laser power has been identified as a risk factor for laser fibre degradation. Between July and September 2008 25 laser fibres were investigated during routine 120 W LBO-LV in 20 consecutive patients. Laser beam power was measured at baseline and after the application of every 25 kJ during the LV procedure. Postoperatively, the surgeon subjectively rated the performance of the respective fibre on a scale from 1 to 4 (1 indicating perfect and 4 insufficient performance). Additionally, microscopic examination of the fibre tip was performed. Median energy applied was 212 kJ. Changes of power output were similar for all fibres. Typically, a steep decrease of power output within the first 50 kJ was followed by a continuous mild decrease until the end of the procedure. After the application of 50 kJ the median power output was 63% (58-73% interquartile range) of the baseline value. The median power output at the end of the 275 kJ-lifespan of the fibres was 42% (40-47%). The median surgeons' rating of the overall performance of the laser fibres was 2 and the median estimated final decrease of power output 60%. Some degree of degradation at the emission window was microscopically detectable in all cases after the procedure. However, even after the application of 275 kJ, these structural changes were only moderate. Minor degradation of the laser fibre was associated with a significant decrease of power output during 120 W LBO-LV. However, following an early, steep decrease, power output

A Comprehensive Analysis and Hardware Implementation of Control Strategies for High Output Voltage DC-DC Boost Power Converter

Directory of Open Access Journals (Sweden)

Sanjeevikumar Padmanaban

2017-01-01

Full Text Available Classical DC-DC converters used in high voltage direct current (HVDC power transmission systems, lack in terms of efficiency, reduced transfer gain and increased cost with sensor (voltage/current numbers. Besides, the internal self-parasitic behavior of the power components reduces the output voltage and efficiency of classical HV converters. This paper deals with extra high-voltage (EHV dc-dc boost converter by the application of voltage-lift technique to overcome the aforementioned deficiencies. The control strategy is based on classical proportional-integral (P-I and fuzzy logic closed-loop controller to get high and stable output voltage. Complete hardware prototype of EHV is implemented and experimental tasks are carried out with digital signal processor (DSP TMS320F2812. The control algorithms P-I, fuzzy logic and the pulse-width modulation (PWM signals for N-channel MOSFET device are performed by the DSP. The experimental results provided show good conformity with developed hypothetical predictions. Additionally, the presented study confirms that the fuzzy logic controller provides better performance than classical P-I controller under different perturbation conditions.

Output power maximization of low-power wind energy conversion systems revisited: Possible control solutions

Energy Technology Data Exchange (ETDEWEB)

Vlad, Ciprian; Munteanu, Iulian; Bratcu, Antoneta Iuliana; Ceanga, Emil [' ' Dunarea de Jos' ' University of Galati, 47, Domneasca, 800008-Galati (Romania)

2010-02-15

This paper discusses the problem of output power maximization for low-power wind energy conversion systems operated in partial load. These systems are generally based on multi-polar permanent-magnet synchronous generators, who exhibit significant efficiency variations over the operating range. Unlike the high-power systems, whose mechanical-to-electrical conversion efficiency is high and practically does not modify the global optimum, the low-power systems global conversion efficiency is affected by the generator behavior and the electrical power optimization is no longer equivalent with the mechanical power optimization. The system efficiency has been analyzed by using both the maxima locus of the mechanical power versus the rotational speed characteristics, and the maxima locus of the electrical power delivered versus the rotational speed characteristics. The experimental investigation has been carried out by using a torque-controlled generator taken from a real-world wind turbine coupled to a physically simulated wind turbine rotor. The experimental results indeed show that the steady-state performance of the conversion system is strongly determined by the generator behavior. Some control solutions aiming at maximizing the energy efficiency are envisaged and thoroughly compared through experimental results. (author)

Output power maximization of low-power wind energy conversion systems revisited: Possible control solutions

International Nuclear Information System (INIS)

Vlad, Ciprian; Munteanu, Iulian; Bratcu, Antoneta Iuliana; Ceanga, Emil

2010-01-01

This paper discusses the problem of output power maximization for low-power wind energy conversion systems operated in partial load. These systems are generally based on multi-polar permanent-magnet synchronous generators, who exhibit significant efficiency variations over the operating range. Unlike the high-power systems, whose mechanical-to-electrical conversion efficiency is high and practically does not modify the global optimum, the low-power systems global conversion efficiency is affected by the generator behavior and the electrical power optimization is no longer equivalent with the mechanical power optimization. The system efficiency has been analyzed by using both the maxima locus of the mechanical power versus the rotational speed characteristics, and the maxima locus of the electrical power delivered versus the rotational speed characteristics. The experimental investigation has been carried out by using a torque-controlled generator taken from a real-world wind turbine coupled to a physically simulated wind turbine rotor. The experimental results indeed show that the steady-state performance of the conversion system is strongly determined by the generator behavior. Some control solutions aiming at maximizing the energy efficiency are envisaged and thoroughly compared through experimental results.

Parent-Offspring Conflict over Short-Term Mating Strategies

Directory of Open Access Journals (Sweden)

Spyroulla Georgiou

2011-12-01

Full Text Available Individuals engage in short-term mating strategies that enable them to obtain fitness benefits from casual relationships. These benefits, however, count for less and cost more to their parents. On this basis three hypotheses are tested. First, parents and offspring are likely to disagree over short-term mating strategies, with the former considering these as less acceptable than the latter. Second, parents are more likely to disapprove of the short-term mating strategies of their daughters than of their sons. Finally, mothers and fathers are expected to agree on how much they disagree over the short-term mating strategies of their children. Evidence from a sample of 148 Greek-Cypriot families (140 mothers, 105 fathers, 119 daughters, 77 sons provides support for the first two hypotheses and partial support for the third hypothesis. The implications of these findings for understanding family dynamics are further discussed.

Short-Term and Medium-Term Reliability Evaluation for Power Systems With High Penetration of Wind Power

DEFF Research Database (Denmark)

Ding, Yi; Singh, Chanan; Goel, Lalit

2014-01-01

reliability evaluation techniques for power systems are well developed. These techniques are more focused on steady-state (time-independent) reliability evaluation and have been successfully applied in power system planning and expansion. In the operational phase, however, they may be too rough......The expanding share of the fluctuating and less predictable wind power generation can introduce complexities in power system reliability evaluation and management. This entails a need for the system operator to assess the system status more accurately for securing real-time balancing. The existing...... an approximation of the time-varying behavior of power systems with high penetration of wind power. This paper proposes a time-varying reliability assessment technique. Time-varying reliability models for wind farms, conventional generating units, and rapid start-up generating units are developed and represented...

Short-term trends in the gas industry - Panorama 2008; Tendances a court terme de l'industrie gaziere - Panorama 2008

Energy Technology Data Exchange (ETDEWEB)

NONE

2008-07-01

In a context of high investment costs and rising energy prices, and recurring unseasonably warm temperatures in recent years, the growth of natural gas demand is slowing. On the supply side, and on the demand side too, new trends are emerging, with potentially powerful impact on the short-and long-term development of the industry.

Relative performance of different numerical weather prediction models for short term predition of wind wnergy

Energy Technology Data Exchange (ETDEWEB)

Giebel, G; Landberg, L [Risoe National Lab., Wind Energy and Atmospheric Physics Dept., Roskilde (Denmark); Moennich, K; Waldl, H P [Carl con Ossietzky Univ., Faculty of Physics, Dept. of Energy and Semiconductor, Oldenburg (Germany)

1999-03-01

In several approaches presented in other papers in this conference, short term forecasting of wind power for a time horizon covering the next two days is done on the basis of Numerical Weather Prediction (NWP) models. This paper explores the relative merits of HIRLAM, which is the model used by the Danish Meteorological Institute, the Deutschlandmodell from the German Weather Service and the Nested Grid Model used in the US. The performance comparison will be mainly done for a site in Germany which is in the forecasting area of both the Deutschlandmodell and HIRLAM. In addition, a comparison of measured data with the forecasts made for one site in Iowa will be included, which allows conclusions on the merits of all three models. Differences in the relative performances could be due to a better tailoring of one model to its country, or to a tighter grid, or could be a function of the distance between the grid points and the measuring site. Also the amount, in which the performance can be enhanced by the use of model output statistics (topic of other papers in this conference) could give insights into the performance of the models. (au)

Local and regional effects of large scale atmospheric circulation patterns on winter wind power output in Western Europe

Science.gov (United States)

Zubiate, Laura; McDermott, Frank; Sweeney, Conor; O'Malley, Mark

2014-05-01

Recent studies (Brayshaw, 2009, Garcia-Bustamante, 2010, Garcia-Bustamante, 2013) have drawn attention to the sensitivity of wind speed distributions and likely wind energy power output in Western Europe to changes in low-frequency, large scale atmospheric circulation patterns such as the North Atlantic Oscillation (NAO). Wind speed variations and directional shifts as a function of the NAO state can be larger or smaller depending on the North Atlantic region that is considered. Wind speeds in Ireland and the UK for example are approximately 20 % higher during NAO + phases, and up to 30 % lower during NAO - phases relative to the long-term (30 year) climatological means. By contrast, in southern Europe, wind speeds are 15 % lower than average during NAO + phases and 15 % higher than average during NAO - phases. Crucially however, some regions such as Brittany in N.W. France have been identified in which there is negligible variability in wind speeds as a function of the NAO phase, as observed in the ERA-Interim 0.5 degree gridded reanalysis database. However, the magnitude of these effects on wind conditions is temporally and spatially non-stationary. As described by Comas-Bru and McDermott (2013) for temperature and precipitation, such non-stationarity is caused by the influence of two other patterns, the East Atlantic pattern, (EA), and the Scandinavian pattern, (SCA), which modulate the position of the NAO dipole. This phenomenon has also implications for wind speeds and directions, which has been assessed using the ERA-Interim reanalysis dataset and the indices obtained from the PC analysis of sea level pressure over the Atlantic region. In order to study the implications for power production, the interaction of the NAO and the other teleconnection patterns with local topography was also analysed, as well as how these interactions ultimately translate into wind power output. The objective is to have a better defined relationship between wind speed and power

Circadian modulation of short-term memory in Drosophila.

Science.gov (United States)

Lyons, Lisa C; Roman, Gregg

2009-01-01

Endogenous biological clocks are widespread regulators of behavior and physiology, allowing for a more efficient allocation of efforts and resources over the course of a day. The extent that different processes are regulated by circadian oscillators, however, is not fully understood. We investigated the role of the circadian clock on short-term associative memory formation using a negatively reinforced olfactory-learning paradigm in Drosophila melanogaster. We found that memory formation was regulated in a circadian manner. The peak performance in short-term memory (STM) occurred during the early subjective night with a twofold performance amplitude after a single pairing of conditioned and unconditioned stimuli. This rhythm in memory is eliminated in both timeless and period mutants and is absent during constant light conditions. Circadian gating of sensory perception does not appear to underlie the rhythm in short-term memory as evidenced by the nonrhythmic shock avoidance and olfactory avoidance behaviors. Moreover, central brain oscillators appear to be responsible for the modulation as cryptochrome mutants, in which the antennal circadian oscillators are nonfunctional, demonstrate robust circadian rhythms in short-term memory. Together these data suggest that central, rather than peripheral, circadian oscillators modulate the formation of short-term associative memory and not the perception of the stimuli.

Critical neural networks with short- and long-term plasticity

Science.gov (United States)

Michiels van Kessenich, L.; Luković, M.; de Arcangelis, L.; Herrmann, H. J.

2018-03-01

In recent years self organized critical neuronal models have provided insights regarding the origin of the experimentally observed avalanching behavior of neuronal systems. It has been shown that dynamical synapses, as a form of short-term plasticity, can cause critical neuronal dynamics. Whereas long-term plasticity, such as Hebbian or activity dependent plasticity, have a crucial role in shaping the network structure and endowing neural systems with learning abilities. In this work we provide a model which combines both plasticity mechanisms, acting on two different time scales. The measured avalanche statistics are compatible with experimental results for both the avalanche size and duration distribution with biologically observed percentages of inhibitory neurons. The time series of neuronal activity exhibits temporal bursts leading to 1 /f decay in the power spectrum. The presence of long-term plasticity gives the system the ability to learn binary rules such as xor, providing the foundation of future research on more complicated tasks such as pattern recognition.

Relationship between government expenditure and output in the problematic regions in the European Union

Directory of Open Access Journals (Sweden)

Irena Szarowská

2013-12-01

Full Text Available Economic and debt crisis has increased the attention paid to the development of government expenditure in problematic regions in the European Union. The goal of the article is to provide direct empirical evidence on cyclicality and the long-term and short-term relationship between government expenditure and output in the Portugal, Ireland, Italy, Greece and Spain in a period 1995–2011. We have applied Johansen cointegration test and the error correction model on adjusted annual data of GDP and government expenditure in compliance with the COFOG international standard. Research confirms procyclical development of government expenditure functions on GDP in the selected countries; this procyclicality is in line with development typical for developing countries. Moreover, output and government expenditure are cointegrated for at least six of the expenditure categories in every country and it implies a long-term relationship between government expenditure and output consistent with Wagner’s law. The values of the coefficients for the short-run relationship between expenditure and output confirm the voracity hypothesis, as they suggest that in response to a given shock to real GDP, government expenditure rises by even more in percentage points.

The Role of Short-term Consolidation in Memory Persistence

OpenAIRE

Timothy J. Ricker

2015-01-01

Short-term memory, often described as working memory, is one of the most fundamental information processing systems of the human brain. Short-term memory function is necessary for language, spatial navigation, problem solving, and many other daily activities. Given its importance to cognitive function, understanding the architecture of short-term memory is of crucial importance to understanding human behavior. Recent work from several laboratories investigating the entry of information into s...

The interaction of short-term and long-term memory in phonetic category formation

Science.gov (United States)

Harnsberger, James D.

2002-05-01

This study examined the role that short-term memory capacity plays in the relationship between novel stimuli (e.g., non-native speech sounds, native nonsense words) and phonetic categories in long-term memory. Thirty native speakers of American English were administered five tests: categorial AXB discrimination using nasal consonants from Malayalam; categorial identification, also using Malayalam nasals, which measured the influence of phonetic categories in long-term memory; digit span; nonword span, a short-term memory measure mediated by phonetic categories in long-term memory; and paired-associate word learning (word-word and word-nonword pairs). The results showed that almost all measures were significantly correlated with one another. The strongest predictor for the discrimination and word-nonword learning results was nonword (r=+0.62) and digit span (r=+0.51), respectively. When the identification test results were partialed out, only nonword span significantly correlated with discrimination. The results show a strong influence of short-term memory capacity on the encoding of phonetic detail within phonetic categories and suggest that long-term memory representations regulate the capacity of short-term memory to preserve information for subsequent encoding. The results of this study will also be discussed with regards to resolving the tension between episodic and abstract models of phonetic category structure.

Prospective testing of Coulomb short-term earthquake forecasts

Science.gov (United States)

Jackson, D. D.; Kagan, Y. Y.; Schorlemmer, D.; Zechar, J. D.; Wang, Q.; Wong, K.

2009-12-01

Earthquake induced Coulomb stresses, whether static or dynamic, suddenly change the probability of future earthquakes. Models to estimate stress and the resulting seismicity changes could help to illuminate earthquake physics and guide appropriate precautionary response. But do these models have improved forecasting power compared to empirical statistical models? The best answer lies in prospective testing in which a fully specified model, with no subsequent parameter adjustments, is evaluated against future earthquakes. The Center of Study of Earthquake Predictability (CSEP) facilitates such prospective testing of earthquake forecasts, including several short term forecasts. Formulating Coulomb stress models for formal testing involves several practical problems, mostly shared with other short-term models. First, earthquake probabilities must be calculated after each “perpetrator” earthquake but before the triggered earthquakes, or “victims”. The time interval between a perpetrator and its victims may be very short, as characterized by the Omori law for aftershocks. CSEP evaluates short term models daily, and allows daily updates of the models. However, lots can happen in a day. An alternative is to test and update models on the occurrence of each earthquake over a certain magnitude. To make such updates rapidly enough and to qualify as prospective, earthquake focal mechanisms, slip distributions, stress patterns, and earthquake probabilities would have to be made by computer without human intervention. This scheme would be more appropriate for evaluating scientific ideas, but it may be less useful for practical applications than daily updates. Second, triggered earthquakes are imperfectly recorded following larger events because their seismic waves are buried in the coda of the earlier event. To solve this problem, testing methods need to allow for “censoring” of early aftershock data, and a quantitative model for detection threshold as a function of

Semantic and phonological contributions to short-term repetition and long-term cued sentence recall.

Science.gov (United States)

Meltzer, Jed A; Rose, Nathan S; Deschamps, Tiffany; Leigh, Rosie C; Panamsky, Lilia; Silberberg, Alexandra; Madani, Noushin; Links, Kira A

2016-02-01

The function of verbal short-term memory is supported not only by the phonological loop, but also by semantic resources that may operate on both short and long time scales. Elucidation of the neural underpinnings of these mechanisms requires effective behavioral manipulations that can selectively engage them. We developed a novel cued sentence recall paradigm to assess the effects of two factors on sentence recall accuracy at short-term and long-term stages. Participants initially repeated auditory sentences immediately following a 14-s retention period. After this task was complete, long-term memory for each sentence was probed by a two-word recall cue. The sentences were either concrete (high imageability) or abstract (low imageability), and the initial 14-s retention period was filled with either an undemanding finger-tapping task or a more engaging articulatory suppression task (Exp. 1, counting backward by threes; Exp. 2, repeating a four-syllable nonword). Recall was always better for the concrete sentences. Articulatory suppression reduced accuracy in short-term recall, especially for abstract sentences, but the sentences initially recalled following articulatory suppression were retained better at the subsequent cued-recall test, suggesting that the engagement of semantic mechanisms for short-term retention promoted encoding of the sentence meaning into long-term memory. These results provide a basis for using sentence imageability and subsequent memory performance as probes of semantic engagement in short-term memory for sentences.

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.

Probabilistic forecasting of wind power at the minute time-scale with Markov-switching autoregressive models

DEFF Research Database (Denmark)

Pinson, Pierre; Madsen, Henrik

2008-01-01

Better modelling and forecasting of very short-term power fluctuations at large offshore wind farms may significantly enhance control and management strategies of their power output. The paper introduces a new methodology for modelling and forecasting such very short-term fluctuations. The proposed...... consists in 1-step ahead forecasting exercise on time-series of wind generation with a time resolution of 10 minute. The quality of the introduced forecasting methodology and its interest for better understanding power fluctuations are finally discussed....... methodology is based on a Markov-switching autoregressive model with time-varying coefficients. An advantage of the method is that one can easily derive full predictive densities. The quality of this methodology is demonstrated from the test case of 2 large offshore wind farms in Denmark. The exercise...

Short-term and long-term sick-leave in Sweden

DEFF Research Database (Denmark)

Blank, N; Diderichsen, Finn

1995-01-01

The primary aim of the study was to analyse similarities and differences between repeated spells of short-term sick-leave (more than 3 spells of less than 7 days' duration in a 12-month period) and long-term absence through sickness (at least 1 spell of more than 59 days' duration in a 12-month p...

Hybrid wind power balance control strategy using thermal power, hydro power and flow batteries

OpenAIRE

Gelažanskas, Linas; Baranauskas, Audrius; Gamage, Kelum A.A.; Ažubalis, Mindaugas

2016-01-01

The increased number of renewable power plants pose threat to power system balance. Their intermittent nature makes it very difficult to predict power output, thus either additional reserve power plants or new storage and control technologies are required. Traditional spinning reserve cannot fully compensate sudden changes in renewable energy power generation. Using new storage technologies such as flow batteries, it is feasible to balance the variations in power and voltage within very short...

Dependability of wind energy generators with short-term energy storage.

Science.gov (United States)

Sørensen, B

1976-11-26

Power fluctuations and power duration curves for wind energy generators, including energy storage facilities of a certain capacity, are compared to those of typical nuclear reactors. A storage system capable of delivering the yearly average power output for about 10 hours already makes the dependability of the wind energy system comparable to that of a typical nuclear plant.

Improving power output of inertial energy harvesters by employing principal component analysis of input acceleration

Science.gov (United States)

Smilek, Jan; Hadas, Zdenek

2017-02-01

In this paper we propose the use of principal component analysis to process the measured acceleration data in order to determine the direction of acceleration with the highest variance on given frequency of interest. This method can be used for improving the power generated by inertial energy harvesters. Their power output is highly dependent on the excitation acceleration magnitude and frequency, but the axes of acceleration measurements might not always be perfectly aligned with the directions of movement, and therefore the generated power output might be severely underestimated in simulations, possibly leading to false conclusions about the feasibility of using the inertial energy harvester for the examined application.

Utilizing Maximum Power Point Trackers in Parallel to Maximize the Power Output of a Solar (Photovoltaic) Array

Science.gov (United States)

2012-12-01

completing the academic workload at NPS. Taking care of two toddlers all day, every day, is not an easy task. You make xxviii it seem effortless and...for the development of numerous thin-cell applications that meet the military’s requirements for ruggedness and power output. For example, the...2012, September 5). PV microinverters and power optimizers set for significant growth [PV Magazine Online]. Available: http://www.pv- magazine.com

Perceptual-gestural (mis)mapping in serial short-term memory: the impact of talker variability.

Science.gov (United States)

Hughes, Robert W; Marsh, John E; Jones, Dylan M

2009-11-01

The mechanisms underlying the poorer serial recall of talker-variable lists (e.g., alternating female-male voices) as compared with single-voice lists were examined. We tested the novel hypothesis that this talker variability effect arises from the tendency for perceptual organization to partition the list into streams based on voice such that the representation of order maps poorly onto the formation of a gestural sequence-output plan assembled in support of the reproduction of the true temporal order of the items. In line with the hypothesis, (a) the presence of a spoken lead-in designed to further promote by-voice perceptual partitioning accentuates the effect (Experiments 1 and 2); (b) the impairment is larger the greater the acoustic coherence is between nonadjacent items: Alternating-voice lists are more poorly recalled than four-voice lists (Experiment 3); and (c) talker variability combines nonadditively with phonological similarity, consistent with the view that both variables disrupt sequence output planning (Experiment 4). The results support the view that serial short-term memory performance reflects the action of sequencing processes embodied within general-purpose perceptual input-processing and gestural output-planning systems.

Control Strategies for Smoothing of Output Power of Wind Energy Conversion Systems

Science.gov (United States)

Pratap, Alok; Urasaki, Naomitsu; Senju, Tomonobu

2013-10-01

This article presents a control method for output power smoothing of a wind energy conversion system (WECS) with a permanent magnet synchronous generator (PMSG) using the inertia of wind turbine and the pitch control. The WECS used in this article adopts an AC-DC-AC converter system. The generator-side converter controls the torque of the PMSG, while the grid-side inverter controls the DC-link and grid voltages. For the generator-side converter, the torque command is determined by using the fuzzy logic. The inputs of the fuzzy logic are the operating point of the rotational speed of the PMSG and the difference between the wind turbine torque and the generator torque. By means of the proposed method, the generator torque is smoothed, and the kinetic energy stored by the inertia of the wind turbine can be utilized to smooth the output power fluctuations of the PMSG. In addition, the wind turbines shaft stress is mitigated compared to a conventional maximum power point tracking control. Effectiveness of the proposed method is verified by the numerical simulations.

Short-Term Power Load Point Prediction Based on the Sharp Degree and Chaotic RBF Neural Network

Directory of Open Access Journals (Sweden)

Dongxiao Niu

2015-01-01

Full Text Available In order to realize the predicting and positioning of short-term load inflection point, this paper made reference to related research in the field of computer image recognition. It got a load sharp degree sequence by the transformation of the original load sequence based on the algorithm of sharp degree. Then this paper designed a forecasting model based on the chaos theory and RBF neural network. It predicted the load sharp degree sequence based on the forecasting model to realize the positioning of short-term load inflection point. Finally, in the empirical example analysis, this paper predicted the daily load point of a region using the actual load data of the certain region to verify the effectiveness and applicability of this method. Prediction results showed that most of the test sample load points could be accurately predicted.

Short-term Consumer Benefits of Dynamic Pricing

OpenAIRE

Dupont, Benjamin; De Jonghe, Cedric; Kessels, Kris; Belmans, Ronnie

2011-01-01

Consumer benefits of dynamic pricing depend on a variety of factors. Consumer characteristics and climatic circumstances widely differ, which forces a regional comparison. This paper presents a general overview of demand response programs and focuses on the short-term benefits of dynamic pricing for an average Flemish residential consumer. It reaches a methodology to develop a cost reflective dynamic pricing program and to estimate short-term bill savings. Participating in a dynamic pricing p...

Very short-term probabilistic forecasting of wind power with generalized logit-Normal distributions

DEFF Research Database (Denmark)

Pinson, Pierre

2012-01-01

and probability masses at the bounds. Both auto-regressive and conditional parametric auto-regressive models are considered for the dynamics of their location and scale parameters. Estimation is performed in a recursive least squares framework with exponential forgetting. The superiority of this proposal over......Very-short-term probabilistic forecasts, which are essential for an optimal management of wind generation, ought to account for the non-linear and double-bounded nature of that stochastic process. They take here the form of discrete–continuous mixtures of generalized logit–normal distributions...

High power CW output from low confinement asymmetric structure diode laser

NARCIS (Netherlands)

Iordache, G.; Buda, M.; Acket, G.A.; Roer, van de T.G.; Kaufmann, L.M.F.; Karouta, F.; Jagadish, C.; Tan, H.H.

1999-01-01

High power continuous wave output from diode lasers using low loss, low confinement, asymmetric structures is demonstrated. An asymmetric structure with an optical trap layer was grown by metal organic vapour phase epitaxy. Gain guided 50 µm wide stripe 1-3 mm long diode lasers were studied. 1.8 W

Short-term hydro-thermal scheduling using particle swarm optimization method

International Nuclear Information System (INIS)

Yu, Binghui; Yuan, Xiaohui; Wang, Jinwen

2007-01-01

The approaches based on different particle swarm optimization (PSO) techniques are applied to solve the short-term hydro-thermal scheduling problem. In the proposed methods, many constraints of the hydro-thermal system, such as power balance, water balance, reservoir volume limits and the operation limits of hydro and thermal plants, are considered. The feasibility of the proposed algorithm is demonstrated through an example system, and the results are compared with the results of a genetic algorithm and evolutionary programming approaches. The experimental results show that all the PSO algorithms have the ability to achieve nearly global solutions, but a local version of PSO with inertia weight appears to be the best amongst all the PSOs in terms of high quality solution

Improvement of Output Power of ECF Micromotor

Science.gov (United States)

Yokota, Shinichi; Kawamura, Kiyomi; Takemura, Kenjiro; Edamura, Kazuya

Electro-conjugate fluid (ECF) is a kind of dielectric fluids, which produces jet-flow (ECF jet) when subjected to a high DC voltage. By using the ECF jet, a new type of micromotor with simple structure and lightweight can be realized. Up to now, we developed a disk-plate type ECF micromotor with inner diameter of 9 mm. In this study, we develope novel ECF micromotors with inner diameter of 5 mm in order to improve the output power density. First, we designed and produced the ECF micromotors with 4-layered and 8-layered disk plate rotors. Then, the performances of the motors are measured. The experimental results confirm the motor developed has a higher performance than the previous ones.

Musical and Verbal Memory in Alzheimer's Disease: A Study of Long-Term and Short-Term Memory

Science.gov (United States)

Menard, Marie-Claude; Belleville, Sylvie

2009-01-01

Musical memory was tested in Alzheimer patients and in healthy older adults using long-term and short-term memory tasks. Long-term memory (LTM) was tested with a recognition procedure using unfamiliar melodies. Short-term memory (STM) was evaluated with same/different judgment tasks on short series of notes. Musical memory was compared to verbal…

Effect of liraglutide treatment on jejunostomy output in patients with short bowel syndrome

DEFF Research Database (Denmark)

Hvistendahl, Mark; Brandt, Christopher Filtenborg; Tribler, Siri

2018-01-01

BACKGROUND: An impaired hormonal "ileo-colonic brake" may contribute to rapid gastric emptying, gastric hypersecretion, high ostomy losses, and the need for parenteral support in end-jejunostomy short bowel syndrome (SBS) patients with intestinal failure (IF). Liraglutide, a glucagon-like peptide 1...... ± SD) and with small bowel lengths of 110 ± 66 cm. The 72-hour metabolic balance studies were performed before and at the end of treatment. Food intake was unrestricted. Oral fluid intake and parenteral support volume were kept constant. The primary end point was change in the ostomy wet weight output....... RESULTS: Liraglutide reduced ostomy wet weight output by 474 ± 563 g/d from 3249 ± 1352 to 2775 ± 1187 g/d (P =049, Student t test). Intestinal wet weight absorption tended to increase by 464 ± 557 g/d (P = .05), as did urine production by 765 ± 759 g/d (P =02). Intestinal energy absorption improved...

A least squares approach for efficient and reliable short-term versus long-term optimization