Empirical validation of statistical parametric mapping for group imaging of fast neural activity using electrical impedance tomography.

Science.gov (United States)

Packham, B; Barnes, G; Dos Santos, G Sato; Aristovich, K; Gilad, O; Ghosh, A; Oh, T; Holder, D

2016-06-01

Electrical impedance tomography (EIT) allows for the reconstruction of internal conductivity from surface measurements. A change in conductivity occurs as ion channels open during neural activity, making EIT a potential tool for functional brain imaging. EIT images can have  >10 000 voxels, which means statistical analysis of such images presents a substantial multiple testing problem. One way to optimally correct for these issues and still maintain the flexibility of complicated experimental designs is to use random field theory. This parametric method estimates the distribution of peaks one would expect by chance in a smooth random field of a given size. Random field theory has been used in several other neuroimaging techniques but never validated for EIT images of fast neural activity, such validation can be achieved using non-parametric techniques. Both parametric and non-parametric techniques were used to analyze a set of 22 images collected from 8 rats. Significant group activations were detected using both techniques (corrected p  <  0.05). Both parametric and non-parametric analyses yielded similar results, although the latter was less conservative. These results demonstrate the first statistical analysis of such an image set and indicate that such an analysis is an approach for EIT images of neural activity.

Kinetic parametric estimation in animal PET molecular imaging based on artificial immune network

International Nuclear Information System (INIS)

Chen Yuting; Ding Hong; Lu Rui; Huang Hongbo; Liu Li

2011-01-01

Objective: To develop an accurate,reliable method without the need of initialization in animal PET modeling for estimation of the tracer kinetic parameters based on the artificial immune network. Methods: The hepatic and left ventricular time activity curves (TACs) were obtained by drawing ROIs of liver tissue and left ventricle on dynamic 18 F-FDG PET imaging of small mice. Meanwhile, the blood TAC was analyzed by sampling the tail vein blood at different time points after injection. The artificial immune network for parametric optimization of pharmacokinetics (PKAIN) was adapted to estimate the model parameters and the metabolic rate of glucose (K i ) was calculated. Results: TACs of liver,left ventricle and tail vein blood were obtained.Based on the artificial immune network, K i in 3 mice was estimated as 0.0024, 0.0417 and 0.0047, respectively. The average weighted residual sum of squares of the output model generated by PKAIN was less than 0.0745 with a maximum standard deviation of 0.0084, which indicated that the proposed PKAIN method can provide accurate and reliable parametric estimation. Conclusion: The PKAIN method could provide accurate and reliable tracer kinetic modeling in animal PET imaging without the need of initialization of model parameters. (authors)

Quantum network theory

International Nuclear Information System (INIS)

Yurke, B.; Denker, J.S.

1984-01-01

A general approach, within the framework of canonical quantization, is described for analyzing the quantum behavior of complicated electronic circuits. This approach is capable of dealing with electrical networks having nonlinear or dissipative elements. The techniques are used to analyze a degenerate parametric amplifier, a device capable of generating squeezed coherent state signals. A circuit capable of performing back-action-evading electrical measurements is also discussed. (author)

Electricity networks: how 'natural' is the monopoly?

International Nuclear Information System (INIS)

Kuenneke, Rolf W.

1999-01-01

This article deals with the changing economic characteristics of the electricity network. Traditionally, electricity networks are considered natural monopolies for various kinds of market failures coincide in this essential part of the electricity infrastructure. Technological induced complementarities between nodes and links are causing network externalities, economies of scale, a high degree of mono-functionality, collective good characteristics and an inherent tendency towards concentrated market structures. It is argued that recent technological trends imply a dramatic change of the network economics, leading to possibilities of inter- and intra-network competition, as well as inter fuel competition. The possible implications for the regulatory framework of this sector are addressed. (Author)

The Parametric Evaluation of Competitiveness of the Franchising Tourism Networks

Directory of Open Access Journals (Sweden)

Tkachuk Tetyana M.

2017-03-01

Full Text Available The article is aimed at studying and evaluating competitiveness of the franchising tourism networks by the proposed options with the possibility to define the characteristics of the relevant tourism franchise at the national market of services. The dynamic changes of positions of Ukraine and of the countries-leaders in the ranking of competitiveness of the travel and tourism sector have been analyzed. The actual parameters of an evaluation of competitiveness of the franchising networks, operating at the domestic market of tourism services, have been defined and substantiated. For the implementation of quantitative evaluation of specific parameters, a questionnaire survey along with point rating of 50 tourism franchisee enterprises was conducted. The franchising networks which are leaders at the national tourism market were analyzed and defined. Based on the results obtained by calculations, a parametric model for evaluation of competitiveness of franchising tourism networks has been proposed and the key characteristics of a tourism franchise have been determined. Further researches will focus on the formation of a structured system for increasing the efficiency of interaction between the tourism enterprises in the franchising system and on the basic principles to ensure their competitiveness.

Application of semi parametric modelling to times series forecasting: case of the electricity consumption

International Nuclear Information System (INIS)

Lefieux, V.

2007-10-01

Reseau de Transport d'Electricite (RTE), in charge of operating the French electric transportation grid, needs an accurate forecast of the power consumption in order to operate it correctly. The forecasts used everyday result from a model combining a nonlinear parametric regression and a SARIMA model. In order to obtain an adaptive forecasting model, nonparametric forecasting methods have already been tested without real success. In particular, it is known that a nonparametric predictor behaves badly with a great number of explanatory variables, what is commonly called the curse of dimensionality. Recently, semi parametric methods which improve the pure nonparametric approach have been proposed to estimate a regression function. Based on the concept of 'dimension reduction', one those methods (called MAVE : Moving Average -conditional- Variance Estimate) can apply to time series. We study empirically its effectiveness to predict the future values of an autoregressive time series. We then adapt this method, from a practical point of view, to forecast power consumption. We propose a partially linear semi parametric model, based on the MAVE method, which allows to take into account simultaneously the autoregressive aspect of the problem and the exogenous variables. The proposed estimation procedure is practically efficient. (author)

Parametric Resonance in Dynamical Systems

CERN Document Server

Nijmeijer, Henk

2012-01-01

Parametric Resonance in Dynamical Systems discusses the phenomenon of parametric resonance and its occurrence in mechanical systems,vehicles, motorcycles, aircraft and marine craft, and micro-electro-mechanical systems. The contributors provide an introduction to the root causes of this phenomenon and its mathematical equivalent, the Mathieu-Hill equation. Also included is a discussion of how parametric resonance occurs on ships and offshore systems and its frequency in mechanical and electrical systems. This book also: Presents the theory and principles behind parametric resonance Provides a unique collection of the different fields where parametric resonance appears including ships and offshore structures, automotive vehicles and mechanical systems Discusses ways to combat, cope with and prevent parametric resonance including passive design measures and active control methods Parametric Resonance in Dynamical Systems is ideal for researchers and mechanical engineers working in application fields such as MEM...

Parametric trends analysis of the critical heat flux based on artificial neural networks

International Nuclear Information System (INIS)

Moon, S.K.; Baek, W.P.; Chang, S.H.

1996-01-01

Parametric trends of the critical heat flux (CHF) are analyzed by applying artificial neural networks (ANNs) to a CHF data base for upward flow of water in uniformly heated vertical round tubes. The analyses are performed from three viewpoints, i.e., for fixed inlet conditions, for fixed exit conditions, and based on local conditions hypothesis. Katto's and Groeneveld et al. dimensionless parameters are used to train the ANNs with the experimental CHF data. The trained ANNs predict the CHF better than any other conventional correlations, showing RMS errors of 8.9%, 13.1% and 19.3% for fixed inlet conditions, for fixed exit conditions, and for local conditions hypothesis, respectively. The parametric trends of the CHF obtained from those trained ANNs show a general agreement with previous understanding. In addition, this study provides more comprehensive information and indicates interesting points for the effects of the tube diameter, the heated length, and the mass flux. It is expected that better understanding of the parametric trends is feasible with an extended data base. (orig.)

Impacts of climate change on electricity network business

International Nuclear Information System (INIS)

Martikainen, A.

2006-04-01

Climate has a significant impact on the electricity network business. The electricity network is under the weather pressure all the time and it is planned and constructed to withstand normal climatic stresses. The electricity network that has been planned and constructed now, is expected to be in operation next 40 years. If climatic stresses change in this period, it can cause significant impacts on electricity network business. If the impacts of climate change are figured out in advance, it is possible to mitigate negative points of climate change and exploit the positive points. In this paper the impact of climate change on electricity network business is presented. The results are based on RCAO climate model scenarios. The climate predictions were composed to the period 2016. 2045. The period 1960.1990 was used as a control period. The climate predictions were composed for precipitation, temperature, hoarfrost, thunder, ground frost and wind. The impacts of the change of the climate variables on electricity network business were estimated from technical and economical points of view. The estimation was based on the change predictions of the climate variables. It is expected that climate change will cause more damages than benefits on the electricity network business. The increase of the number of network faults will be the most significant and demanding disadvantage caused by climate change. If networks are not improved to be more resistant for faults, then thunder, heavy snow and wind cause more damages especially to overhead lines in medium voltage network. Increasing precipitation and decreasing amount of ground frost weaken the strength of soil. The construction work will be more difficult with the present vehicles because wet and unfrozen ground can not carry heavy vehicles. As a consequence of increasing temperature, the demand of heating energy will decrease and the demand of cooling energy will increase. This is significant for the electricity

Parametric optimization design for supercritical CO2 power cycle using genetic algorithm and artificial neural network

International Nuclear Information System (INIS)

Wang Jiangfeng; Sun Zhixin; Dai Yiping; Ma Shaolin

2010-01-01

Supercritical CO 2 power cycle shows a high potential to recover low-grade waste heat due to its better temperature glide matching between heat source and working fluid in the heat recovery vapor generator (HRVG). Parametric analysis and exergy analysis are conducted to examine the effects of thermodynamic parameters on the cycle performance and exergy destruction in each component. The thermodynamic parameters of the supercritical CO 2 power cycle is optimized with exergy efficiency as an objective function by means of genetic algorithm (GA) under the given waste heat condition. An artificial neural network (ANN) with the multi-layer feed-forward network type and back-propagation training is used to achieve parametric optimization design rapidly. It is shown that the key thermodynamic parameters, such as turbine inlet pressure, turbine inlet temperature and environment temperature have significant effects on the performance of the supercritical CO 2 power cycle and exergy destruction in each component. It is also shown that the optimum thermodynamic parameters of supercritical CO 2 power cycle can be predicted with good accuracy using artificial neural network under variable waste heat conditions.

Network of time-multiplexed optical parametric oscillators as a coherent Ising machine

Science.gov (United States)

Marandi, Alireza; Wang, Zhe; Takata, Kenta; Byer, Robert L.; Yamamoto, Yoshihisa

2014-12-01

Finding the ground states of the Ising Hamiltonian maps to various combinatorial optimization problems in biology, medicine, wireless communications, artificial intelligence and social network. So far, no efficient classical and quantum algorithm is known for these problems and intensive research is focused on creating physical systems—Ising machines—capable of finding the absolute or approximate ground states of the Ising Hamiltonian. Here, we report an Ising machine using a network of degenerate optical parametric oscillators (OPOs). Spins are represented with above-threshold binary phases of the OPOs and the Ising couplings are realized by mutual injections. The network is implemented in a single OPO ring cavity with multiple trains of femtosecond pulses and configurable mutual couplings, and operates at room temperature. We programmed a small non-deterministic polynomial time-hard problem on a 4-OPO Ising machine and in 1,000 runs no computational error was detected.

Combined natural gas and electricity network pricing

Energy Technology Data Exchange (ETDEWEB)

Morais, M.S.; Marangon Lima, J.W. [Universidade Federal de Itajuba, Rua Dr. Daniel de Carvalho, no. 296, Passa Quatro, Minas Gerais, CEP 37460-000 (Brazil)

2007-04-15

The introduction of competition to electricity generation and commercialization has been the main focus of many restructuring experiences around the world. The open access to the transmission network and a fair regulated tariff have been the keystones for the development of the electricity market. Parallel to the electricity industry, the natural gas business has great interaction with the electricity market in terms of fuel consumption and energy conversion. Given that the transmission and distribution monopolistic activities are very similar to the natural gas transportation through pipelines, economic regulation related to the natural gas network should be coherent with the transmission counterpart. This paper shows the application of the main wheeling charge methods, such as MW/gas-mile, invested related asset cost (IRAC) and Aumman-Shapley allocation, to both transmission and gas network. Stead-state equations are developed to adequate the various pricing methods. Some examples clarify the results, in terms of investments for thermal generation plants and end consumers, when combined pricing methods are used for transmission and gas networks. The paper also shows that the synergies between gas and electricity industry should be adequately considered, otherwise wrong economic signals are sent to the market players. (author)

Multidimensional Risk Management for Underground Electricity Networks

Directory of Open Access Journals (Sweden)

Garcez Thalles V.

2014-08-01

Full Text Available In the paper we consider an electricity provider company that makes decision on allocating resources on electric network maintenance. The investments decrease malfunction rate of network nodes. An accidental event (explosion, fire, etc. or a malfunctioning on underground system can have various consequences and in different perspectives, such as deaths and injuries of pedestrians, fires in nearby locations, disturbances in the flow of vehicular traffic, loss to the company image, operating and financial losses, etc. For this reason it is necessary to apply an approach of the risk management that considers the multidimensional view of the consequences. Furthermore an analysis of decision making should consider network dependencies between the nodes of the electricity distribution system. In the paper we propose the use of the simulation to assess the network effects (such as the increase of the probability of other accidental event and the occurrence of blackouts of the dependent nodes in the multidimensional risk assessment in electricity grid. The analyzed effects include node overloading due to malfunction of adjacent nodes and blackouts that take place where there is temporarily no path in the grid between the power plant and a node. The simulation results show that network effects have crucial role for decisions in the network maintenance – outcomes of decisions to repair a particular node in the network can have significant influence on performance of other nodes. However, those dependencies are non-linear. The effects of network connectivity (number of connections between nodes on its multidimensional performance assessment depend heavily on the overloading effect level. The simulation results do not depend on network type structure (random or small world – however simulation outcomes for random networks have shown higher variance compared to small-world networks.

Impacts of climate change on electricity network business

International Nuclear Information System (INIS)

Auvinen, O.; Martikainen, A.

2006-01-01

In this project the impact of climate change on electricity network business was study. The results are based on RCAO climate model scenarios. The climate predictions were composed to the period 2016- 2045. The period 1960-1990 was used as a control period. The climate predictions were composed for precipitation, temperature, hoarfrost, thunder, ground frost and wind. Impacts of the change of the climate variables on electricity network business were estimated from technical and economical points of view. It is expected that climate change will cause more damages than benefits on the electricity network business. The increase of the number of network faults will be the most significant and demanding disadvantage caused by climate change in distribution network. If networks are not improved to be more resistant for faults, then thunder, heavy snow and wind cause more damages especially to overhead lines in medium voltage network. Increasing precipitation and decreasing amount of ground frost weaken the strength of soil. The construction work will be more difficult with the present vehicles because wet and unfrozen ground can not carry heavy vehicles. As a consequence of increasing temperature, the demand of heating energy will decrease and the demand of cooling energy will increase. This is significant for the electricity consumption and the peak load of temperature-dependent electricity users. (orig.)

Australia's long-term electricity demand forecasting using deep neural networks

OpenAIRE

Hamedmoghadam, Homayoun; Joorabloo, Nima; Jalili, Mahdi

2018-01-01

Accurate prediction of long-term electricity demand has a significant role in demand side management and electricity network planning and operation. Demand over-estimation results in over-investment in network assets, driving up the electricity prices, while demand under-estimation may lead to under-investment resulting in unreliable and insecure electricity. In this manuscript, we apply deep neural networks to predict Australia's long-term electricity demand. A stacked autoencoder is used in...

Noticing climate change in electricity network design and construction

International Nuclear Information System (INIS)

Syri, S.; Martikeinen, A.; Lehtonen, M.

2007-01-01

The climate change is widely known to cause remarkable effects to electricity network systems on the whole. Some of the changes are good but the most of the changes cause disadvantages to electricity network. Consequence of climate change, blackouts can be long-standing which affect remarkable society and economic life. Most of electricity networks are coming to a renovation phase and the solutions, that are being made nowadays, affect still after decades. Taking account of climate change, now when networks are being developed and planned, it is possible to avoid possible large repair operation and increase reliability of distribution in the future. The aim of this project is to clarify how climate change should be noticed in planning and construction processes. According to the results of this project electricity network companies can be prepared for climate change by developing planning processes and network cost effectively. Also construction processes are being developed but emphasis is on planning process. The results and developed knowledge of VTT research project 'Impacts of climate change on electricity network business' are exploited in this project. In addition, impacts of climate change on cables and transformers are analyzed in collaboration with TKK in the project. (orig.)

Parametric laws to model urban pollutant dispersion with a street network approach

Science.gov (United States)

Soulhac, L.; Salizzoni, P.; Mejean, P.; Perkins, R. J.

2013-03-01

This study discusses the reliability of the street network approach for pollutant dispersion modelling in urban areas. This is essentially based on a box model, with parametric relations that explicitly model the main phenomena that contribute to the street canyon ventilation: the mass exchanges between the street and the atmosphere, the pollutant advection along the street axes and the pollutant transfer at street intersections. In the first part of the paper the focus is on the development of a model for the bulk transfer street/atmosphere, which represents the main ventilation mechanisms for wind direction that are almost perpendicular to the axis of the street. We then discuss the role of the advective transfer along the street axis on its ventilation, depending on the length of the street and the direction of the external wind. Finally we evaluate the performances of a box model integrating parametric exchange laws for these transfer phenomena. To that purpose we compare the prediction of the model to wind tunnel experiments of pollutant dispersion within a street canyon placed in an idealised urban district.

Piezoelectric energy harvesting with parametric uncertainty

International Nuclear Information System (INIS)

Ali, S F; Friswell, M I; Adhikari, S

2010-01-01

The design and analysis of energy harvesting devices is becoming increasing important in recent years. Most of the literature has focused on the deterministic analysis of these systems and the problem of uncertain parameters has received less attention. Energy harvesting devices exhibit parametric uncertainty due to errors in measurement, errors in modelling and variability in the parameters during manufacture. This paper investigates the effect of parametric uncertainty in the mechanical system on the harvested power, and derives approximate explicit formulae for the optimal electrical parameters that maximize the mean harvested power. The maximum of the mean harvested power decreases with increasing uncertainty, and the optimal frequency at which the maximum mean power occurs shifts. The effect of the parameter variance on the optimal electrical time constant and optimal coupling coefficient are reported. Monte Carlo based simulation results are used to further analyse the system under parametric uncertainty

EMMNet: Sensor Networking for Electricity Meter Monitoring

Directory of Open Access Journals (Sweden)

Zhi-Ting Lin

2010-06-01

Full Text Available Smart sensors are emerging as a promising technology for a large number of application domains. This paper presents a collection of requirements and guidelines that serve as a basis for a general smart sensor architecture to monitor electricity meters. It also presents an electricity meter monitoring network, named EMMNet, comprised of data collectors, data concentrators, hand-held devices, a centralized server, and clients. EMMNet provides long-distance communication capabilities, which make it suitable suitable for complex urban environments. In addition, the operational cost of EMMNet is low, compared with other existing remote meter monitoring systems based on GPRS. A new dynamic tree protocol based on the application requirements which can significantly improve the reliability of the network is also proposed. We are currently conducting tests on five networks and investigating network problems for further improvements. Evaluation results indicate that EMMNet enhances the efficiency and accuracy in the reading, recording, and calibration of electricity meters.

EMMNet: sensor networking for electricity meter monitoring.

Science.gov (United States)

Lin, Zhi-Ting; Zheng, Jie; Ji, Yu-Sheng; Zhao, Bao-Hua; Qu, Yu-Gui; Huang, Xu-Dong; Jiang, Xiu-Fang

2010-01-01

Smart sensors are emerging as a promising technology for a large number of application domains. This paper presents a collection of requirements and guidelines that serve as a basis for a general smart sensor architecture to monitor electricity meters. It also presents an electricity meter monitoring network, named EMMNet, comprised of data collectors, data concentrators, hand-held devices, a centralized server, and clients. EMMNet provides long-distance communication capabilities, which make it suitable suitable for complex urban environments. In addition, the operational cost of EMMNet is low, compared with other existing remote meter monitoring systems based on GPRS. A new dynamic tree protocol based on the application requirements which can significantly improve the reliability of the network is also proposed. We are currently conducting tests on five networks and investigating network problems for further improvements. Evaluation results indicate that EMMNet enhances the efficiency and accuracy in the reading, recording, and calibration of electricity meters.

Integration of electric drive vehicles in the Danish electricity network with high wind power penetration

DEFF Research Database (Denmark)

Chandrashekhara, Divya K; Østergaard, Jacob; Larsen, Esben

2010-01-01

/conventional) which are likely to fuel these cars. The study was carried out considering the Danish electricity network state around 2025, when the EDV penetration levels would be significant enough to have an impact on the power system. Some of the interesting findings of this study are - EDV have the potential......This paper presents the results of a study carried out to examine the feasibility of integrating electric drive vehicles (EDV) in the Danish electricity network which is characterised by high wind power penetration. One of the main aims of this study was to examine the effect of electric drive...... vehicles on the Danish electricity network, wind power penetration and electricity market. In particular the study examined the effect of electric drive vehicles on the generation capacity constraints, load curve, cross border transmission capacity and the type of generating sources (renewable...

STRATEGIC RESEARCH AGENDA FOR EUROPE’S ELECTRICITY NETWORKS OF THE FUTURE

DEFF Research Database (Denmark)

Bamberger, Yves; Baptista, João; Botting, Duncan

The first milestone towards the establishment of a common strategy for the development of Europe’s electricity networks was set in April 2006 when the paper ‘Vision and Strategy for Europe’s Electricity Networks of the Future’1 was published. In this Vision, future electricity markets and networks...

Incorporating network effects in a competitive electricity industry. An Australian perspective

International Nuclear Information System (INIS)

Outhred, H.; Kaye, J.

1996-01-01

The role of an electricity network in a competitive electricity industry is reviewed, the nation's experience with transmission pricing is discussed, and a 'Nodal Auction Model' for incorporating network effects in a competitive electricity industry is proposed. The model uses a computer-based auction procedure to address both the spatial issues associated with an electricity network and the temporal issues associated with operation scheduling. The objective is to provide a market framework that addresses both network effects and operation scheduling in a coordinated implementation of spot pricing theory. 12 refs

Network governance in electricity distribution: Public utility or commodity

International Nuclear Information System (INIS)

Kuenneke, Rolf; Fens, Theo

2005-01-01

This paper addresses the question whether the operation and management of electricity distribution networks in a liberalized market environment evolves into a market driven commodity business or might be perceived as a genuine public utility task. A framework is developed to classify and compare different institutional arrangements according to the public utility model and the commodity model. These models are exemplified for the case of the Dutch electricity sector. It appears that the institutional organization of electricity distribution networks is at the crossroads of two very different institutional development paths. They develop towards commercial business if the system characteristics of the electricity sector remain basically unchanged to the traditional situation. If however innovative technological developments allow for a decentralization and decomposition of the electricity system, distribution networks might be operated as public utilities while other energy services are exploited commercially. (Author)

Parametric trapping of electromagnetic waves in an inhomogeneous plasma

International Nuclear Information System (INIS)

Silin, V.P.; Starodub, A.N.

1977-01-01

Considered is parametric instability in an inhomogeneous plasma at which a pumping wave is transformed to an electromagnetic wave and aperiodically in-time-growing disturbances. It is shown that after achievement of some boundary pumping value by electric field intensity an absolute parametric instability evolution becomes possible. In-time growing plasma disturbances are localized near electric field extremums of a pumping wave. Such localization areas are small as compared to characteristic size of pumping inhomogeneity in a plasma. The secondary electromagnetic waves stay within the localization areas and, therefore, are not scattered by a plasma. As following from this it has been established, that due to parametric instability electromagnetic radiation trapping by a plasma occurs. Such a trapping is considerably connected with a spatial structure of a pumping field and it cannot arise within the field of a running wave in the theoretical model considered. However parametric trapping turns out to be possible even with very small reflection coefficients

Market tools: the immaterial part of the electricity transmission network

International Nuclear Information System (INIS)

Maillard, Dominique

2014-01-01

The author first evokes the activities of RTE (Reseau de transport d'electricite - the French power transmission network) to improve the performance of its technical and industrial equipment (notably equipment evolution, maintenance policies) with, for example, the installation of a fibre optic network for network control automation, the development of software for a better exploitation and steering of electricity fluxes, notably the electricity produced by wind and photovoltaic power. He more particularly addresses the role of RTE in the construction of the electricity market. He outlines the role of the European electricity market in the economic optimization, the new approaches and tools for a higher flexibility of the electric system, the expertise of RTE, and the perspective of always more smart grids

Will electrical cyber-physical interdependent networks undergo first-order transition under random attacks?

Science.gov (United States)

Ji, Xingpei; Wang, Bo; Liu, Dichen; Dong, Zhaoyang; Chen, Guo; Zhu, Zhenshan; Zhu, Xuedong; Wang, Xunting

2016-10-01

Whether the realistic electrical cyber-physical interdependent networks will undergo first-order transition under random failures still remains a question. To reflect the reality of Chinese electrical cyber-physical system, the "partial one-to-one correspondence" interdependent networks model is proposed and the connectivity vulnerabilities of three realistic electrical cyber-physical interdependent networks are analyzed. The simulation results show that due to the service demands of power system the topologies of power grid and its cyber network are highly inter-similar which can effectively avoid the first-order transition. By comparing the vulnerability curves between electrical cyber-physical interdependent networks and its single-layer network, we find that complex network theory is still useful in the vulnerability analysis of electrical cyber-physical interdependent networks.

Developing electricity distribution networks and their regulation to support sustainable energy

International Nuclear Information System (INIS)

Shaw, Rita; Attree, Mike; Jackson, Tim

2010-01-01

A more sustainable energy system will alter the current patterns of electricity demand and generation. This means technical, commercial and regulatory change for electricity network systems such as distribution networks. This paper traces the links in Great Britain between changes in energy policy since privatisation, changes in the objectives of the electricity regulator and changes in the objectives of the distribution networks and their owners, the distribution network operators (DNOs). The paper identifies tensions in regulatory policy and suggests reforms to the regulatory framework to support a lower-carbon future. DNOs are licensed regional infrastructure providers. In addition to their network services, the network companies can potentially deliver public policy objectives to facilitate heat infrastructure, energy-efficiency and distributed renewables. The paper identifies the potential benefits of a novel approach to facilitating renewable energy feed-in tariffs for electricity and heat, using DNOs.

Network Theory Integrated Life Cycle Assessment for an Electric Power System

Directory of Open Access Journals (Sweden)

Heetae Kim

2015-08-01

Full Text Available In this study, we allocate Greenhouse gas (GHG emissions of electricity transmission to the consumers. As an allocation basis, we introduce energy distance. Energy distance takes the transmission load on the electricity energy system into account in addition to the amount of electricity consumption. As a case study, we estimate regional GHG emissions of electricity transmission loss in Chile. Life cycle assessment (LCA is used to estimate the total GHG emissions of the Chilean electric power system. The regional GHG emission of transmission loss is calculated from the total GHG emissions. We construct the network model of Chilean electric power grid as an undirected network with 466 nodes and 543 edges holding the topology of the power grid based on the statistical record. We analyze the total annual GHG emissions of the Chilean electricity energy system as 23.07 Mt CO2-eq. and 1.61 Mt CO2-eq. for the transmission loss, respectively. The total energy distance for the electricity transmission accounts for 12,842.10 TWh km based on network analysis. We argue that when the GHG emission of electricity transmission loss is estimated, the electricity transmission load should be separately considered. We propose network theory as a useful complement to LCA analysis for the complex allocation. Energy distance is especially useful on a very large-scale electric power grid such as an intercontinental transmission network.

Distributed control of deregulated electrical power networks

NARCIS (Netherlands)

Hermans, R.M.

2012-01-01

A prerequisite for reliable operation of electrical power networks is that supply and demand are balanced at all time, as efficient ways for storing large amounts of electrical energy are scarce. Balancing is challenging, however, due to the power system's dimensions and complexity, the low

Estimating the cost of improving quality in electricity distribution: A parametric distance function approach

International Nuclear Information System (INIS)

Coelli, Tim J.; Gautier, Axel; Perelman, Sergio; Saplacan-Pop, Roxana

2013-01-01

The quality of electricity distribution is being more and more scrutinized by regulatory authorities, with explicit reward and penalty schemes based on quality targets having been introduced in many countries. It is then of prime importance to know the cost of improving the quality for a distribution system operator. In this paper, we focus on one dimension of quality, the continuity of supply, and we estimated the cost of preventing power outages. For that, we make use of the parametric distance function approach, assuming that outages enter in the firm production set as an input, an imperfect substitute for maintenance activities and capital investment. This allows us to identify the sources of technical inefficiency and the underlying trade-off faced by operators between quality and other inputs and costs. For this purpose, we use panel data on 92 electricity distribution units operated by ERDF (Electricité de France - Réseau Distribution) in the 2003–2005 financial years. Assuming a multi-output multi-input translog technology, we estimate that the cost of preventing one interruption is equal to 10.7€ for an average DSO. Furthermore, as one would expect, marginal quality improvements tend to be more expensive as quality itself improves. - Highlights: ► We estimate the implicit cost of outages for the main distribution company in France. ► For this purpose, we make use of a parametric distance function approach. ► Marginal quality improvements tend to be more expensive as quality itself improves. ► The cost of preventing one interruption varies from 1.8 € to 69.2 € (2005 prices). ► We estimate that, in average, it lays 33% above the regulated price of quality.

Neural network based photovoltaic electrical forecasting in south Algeria

International Nuclear Information System (INIS)

Hamid Oudjana, S.; Hellal, A.; Hadj Mahammed, I

2014-01-01

Photovoltaic electrical forecasting is significance for the optimal operation and power predication of grid-connected photovoltaic (PV) plants, and it is important task in renewable energy electrical system planning and operating. This paper explores the application of neural networks (NN) to study the design of photovoltaic electrical forecasting systems for one week ahead using weather databases include the global irradiance, and temperature of Ghardaia city (south of Algeria) for one year of 2013 using a data acquisition system. Simulations were run and the results are discussed showing that neural networks Technique is capable to decrease the photovoltaic electrical forecasting error. (author)

Computational Principle and Performance Evaluation of Coherent Ising Machine Based on Degenerate Optical Parametric Oscillator Network

Directory of Open Access Journals (Sweden)

Yoshitaka Haribara

2016-04-01

Full Text Available We present the operational principle of a coherent Ising machine (CIM based on a degenerate optical parametric oscillator (DOPO network. A quantum theory of CIM is formulated, and the computational ability of CIM is evaluated by numerical simulation based on c-number stochastic differential equations. We also discuss the advanced CIM with quantum measurement-feedback control and various problems which can be solved by CIM.

Developing electricity distribution networks and their regulation to support sustainable energy

Energy Technology Data Exchange (ETDEWEB)

Shaw, Rita; Attree, Mike [Electricity North West Ltd., 304 Bridgewater Place, Birchwood, Warrington, Cheshire WA3 6XG (United Kingdom); Jackson, Tim [RESOLVE, Centre for Environmental Strategy D3, University of Surrey, Guildford, Surrey GU2 7XH (United Kingdom)

2010-10-15

A more sustainable energy system will alter the current patterns of electricity demand and generation. This means technical, commercial and regulatory change for electricity network systems such as distribution networks. This paper traces the links in Great Britain between changes in energy policy since privatisation, changes in the objectives of the electricity regulator and changes in the objectives of the distribution networks and their owners, the distribution network operators (DNOs). The paper identifies tensions in regulatory policy and suggests reforms to the regulatory framework to support a lower-carbon future. DNOs are licensed regional infrastructure providers. In addition to their network services, the network companies can potentially deliver public policy objectives to facilitate heat infrastructure, energy-efficiency and distributed renewables. The paper identifies the potential benefits of a novel approach to facilitating renewable energy feed-in tariffs for electricity and heat, using DNOs. (author)

Introduction to neural networks with electric power applications

International Nuclear Information System (INIS)

Wildberger, A.M.; Hickok, K.A.

1990-01-01

This is an introduction to the general field of neural networks with emphasis on prospects for their application in the power industry. It is intended to provide enough background information for its audience to begin to follow technical developments in neural networks and to recognize those which might impact on electric power engineering. Beginning with a brief discussion of natural and artificial neurons, the characteristics of neural networks in general and how they learn, neural networks are compared with other modeling tools such as simulation and expert systems in order to provide guidance in selecting appropriate applications. In the power industry, possible applications include plant control, dispatching, and maintenance scheduling. In particular, neural networks are currently being investigated for enhancements to the Thermal Performance Advisor (TPA) which General Physics Corporation (GP) has developed to improve the efficiency of electric power generation

Modeling and prediction of Turkey's electricity consumption using Artificial Neural Networks

International Nuclear Information System (INIS)

Kavaklioglu, Kadir; Ozturk, Harun Kemal; Canyurt, Olcay Ersel; Ceylan, Halim

2009-01-01

Artificial Neural Networks are proposed to model and predict electricity consumption of Turkey. Multi layer perceptron with backpropagation training algorithm is used as the neural network topology. Tangent-sigmoid and pure-linear transfer functions are selected in the hidden and output layer processing elements, respectively. These input-output network models are a result of relationships that exist among electricity consumption and several other socioeconomic variables. Electricity consumption is modeled as a function of economic indicators such as population, gross national product, imports and exports. It is also modeled using export-import ratio and time input only. Performance comparison among different models is made based on absolute and percentage mean square error. Electricity consumption of Turkey is predicted until 2027 using data from 1975 to 2006 along with other economic indicators. The results show that electricity consumption can be modeled using Artificial Neural Networks, and the models can be used to predict future electricity consumption. (author)

Design of pressure-driven microfluidic networks using electric circuit analogy.

Science.gov (United States)

Oh, Kwang W; Lee, Kangsun; Ahn, Byungwook; Furlani, Edward P

2012-02-07

This article reviews the application of electric circuit methods for the analysis of pressure-driven microfluidic networks with an emphasis on concentration- and flow-dependent systems. The application of circuit methods to microfluidics is based on the analogous behaviour of hydraulic and electric circuits with correlations of pressure to voltage, volumetric flow rate to current, and hydraulic to electric resistance. Circuit analysis enables rapid predictions of pressure-driven laminar flow in microchannels and is very useful for designing complex microfluidic networks in advance of fabrication. This article provides a comprehensive overview of the physics of pressure-driven laminar flow, the formal analogy between electric and hydraulic circuits, applications of circuit theory to microfluidic network-based devices, recent development and applications of concentration- and flow-dependent microfluidic networks, and promising future applications. The lab-on-a-chip (LOC) and microfluidics community will gain insightful ideas and practical design strategies for developing unique microfluidic network-based devices to address a broad range of biological, chemical, pharmaceutical, and other scientific and technical challenges.

Current-driven parametric resonance in magnetic multilayers

International Nuclear Information System (INIS)

Wang, C; Seinige, H; Tsoi, M

2013-01-01

Current-induced parametric excitations were observed in point-contact spin-valve nanodevices. Point contacts were used to inject high densities of direct and microwave currents into spin valves, thus producing oscillating spin-transfer and Oersted-field torques on magnetic moments. The resulting magnetodynamics were observed electrically by measuring rectified voltage signals across the contact. In addition to the spin-torque-driven ferromagnetic resonance we observe doubled-frequency signals which correspond to the parametric excitation of magnetic moments. Numerical simulations suggest that while both spin-transfer torque and ac Oersted field contribute to the parametrically excited dynamics, the ac spin torque dominates, and dc spin torque can switch it on and off. The dc bias dependence of the parametric resonance signal enabled the mapping of instability regions characterizing the nonlinearity of the oscillation. (paper)

Modeling and optimization of an electric power distribution network ...

African Journals Online (AJOL)

Modeling and optimization of an electric power distribution network planning system using ... of the network was modelled with non-linear mathematical expressions. ... given feasible locations, re-conductoring of existing feeders in the network, ...

An extended parametrization of gas amplification in proportional wire chambers

International Nuclear Information System (INIS)

Beingessner, S.P.; Carnegie, R.K.; Hargrove, C.K.

1987-01-01

It is normally assumed that the gas amplification in proportional chambers is a function of Townsend's first ionization coefficient, α, and that α is a function of the anode surface electric field only. Experimental measurements are presented demonstrating the breakdown of the latter assumption for electric fields, X, greater than about 150 V/cm/Torr on the anode wire surface for a gas mixture of 80/20 argon/methane. For larger values of X, the parametrization of the proportional gas gain data requires an additional term related to the gradient of the electric field near the wire. This extended gain parametrization remains valid until the onset of nonproportional contributions such as positive ion space charge saturation effects. Furthermore, deviations of the data from this parametrization are used to measure the onset of these space charge effects. A simple scaling dependence of the gain data on the product of pressure and wire radius over the whole proportional range is also demonstrated. (orig.)

Squeezed light in an optical parametric oscillator network with coherent feedback quantum control.

Science.gov (United States)

Crisafulli, Orion; Tezak, Nikolas; Soh, Daniel B S; Armen, Michael A; Mabuchi, Hideo

2013-07-29

We present squeezing and anti-squeezing spectra of the output from a degenerate optical parametric oscillator (OPO) network arranged in different coherent quantum feedback configurations. One OPO serves as a quantum plant, the other as a quantum controller. The addition of coherent feedback enables shaping of the output squeezing spectrum of the plant, and is found to be capable of pushing the frequency of maximum squeezing away from the optical driving frequency and broadening the spectrum over a wider frequency band. The experimental results are in excellent agreement with the developed theory, and illustrate the use of coherent quantum feedback to engineer the quantum-optical properties of the plant OPO output.

Electric Vehicle Integration into Modern Power Networks

DEFF Research Database (Denmark)

software tools to assess the impacts resulting from the electric vehicles deployment on the steady state and dynamic operation of electricity grids, identifies strategies to mitigate them and the possibility to support simultaneously large-scale integration of renewable energy sources. New business models......Electric Vehicle Integration into Modern Power Networks provides coverage of the challenges and opportunities posed by the progressive integration of electric drive vehicles. Starting with a thorough overview of the current electric vehicle and battery state-of-the-art, this work describes dynamic...... and control management architectures, as well as the communication infrastructure required to integrate electric vehicles as active demand are presented. Finally, regulatory issues of integrating electric vehicles into modern power systems are addressed. Inspired by two courses held under the EES...

Electric Vehicle Integration into Modern Power Networks

DEFF Research Database (Denmark)

Electric Vehicle Integration into Modern Power Networks provides coverage of the challenges and opportunities posed by the progressive integration of electric drive vehicles. Starting with a thorough overview of the current electric vehicle and battery state-of-the-art, this work describes dynamic...... software tools to assess the impacts resulting from the electric vehicles deployment on the steady state and dynamic operation of electricity grids, identifies strategies to mitigate them and the possibility to support simultaneously large-scale integration of renewable energy sources. New business models...... and control management architectures, as well as the communication infrastructure required to integrate electric vehicles as active demand are presented. Finally, regulatory issues of integrating electric vehicles into modern power systems are addressed. Inspired by two courses held under the EES...

Electrical Properties of an m × n Hammock Network

Science.gov (United States)

Tan, Zhen; Tan, Zhi-Zhong; Zhou, Ling

2018-05-01

Electrical property is an important problem in the field of natural science and physics, which usually involves potential, current and resistance in the electric circuit. We investigate the electrical properties of an arbitrary hammock network, which has not been resolved before, and propose the exact potential formula of an arbitrary m × n hammock network by means of the Recursion-Transform method with current parameters (RT-I) pioneered by one of us [Z. Z. Tan, Phys. Rev. E 91 (2015) 052122], and the branch currents and equivalent resistance of the network are derived naturally. Our key technique is to setting up matrix equations and making matrix transformation, the potential formula derived is a meaningful discovery, which deduces many novel applications. The discovery of potential formula of the hammock network provides new theoretical tools and techniques for related scientific research. Supported by the Natural Science Foundation of Jiangsu Province under Grant No. BK20161278

Facing a Problem of Electrical Energy Quality in Ship Networks-measurements, Estimation, Control

Institute of Scientific and Technical Information of China (English)

Tomasz Tarasiuk; Janusz Mindykowski; Xiaoyan Xu

2003-01-01

In this paper, electrical energy quality and its indices in ship electric networks are introduced, especially the meaning of electrical energy quality terms in voltage and active and reactive power distribution indices. Then methods of measurement of marine electrical energy indices are introduced in details and a microprocessor measurement-diagnosis system with the function of measurement and control is designed. Afterwards, estimation and control of electrical power quality of marine electrical power networks are introduced. And finally, according to the existing method of measurement and control of electrical power quality in ship power networks, the improvement of relative method is proposed.

NOTICE OF ELECTRICAL CUT - TEST OF THE SECURED NETWORK

CERN Multimedia

Electrical Service ST/EL

2001-01-01

The electrical service ST/EL will test the switching sequence between the secured network and the diesel generators on January 8, 2002. The normal network, general services of the sites Meyrin, Prevessin, SPS, Zone Nord, LHC1 and LHC18 will be cut between 6:00am and 6:10am. The secured network will be resupplied by the diesel generators after approximately 1 minute. The UPS network will not be affected. To facilitate the restart of the electrical network and to minimize the impact of the tests on critical equipment, we would like to ask you to stop any equipment that might suffer major inconveniences during the tests (e.g. computers). For any further information, please do not hesitate to contact the Technical Control Room TCR (72201) or G. Cumer (160592).

A sequential Monte Carlo model of the combined GB gas and electricity network

International Nuclear Information System (INIS)

Chaudry, Modassar; Wu, Jianzhong; Jenkins, Nick

2013-01-01

A Monte Carlo model of the combined GB gas and electricity network was developed to determine the reliability of the energy infrastructure. The model integrates the gas and electricity network into a single sequential Monte Carlo simulation. The model minimises the combined costs of the gas and electricity network, these include gas supplies, gas storage operation and electricity generation. The Monte Carlo model calculates reliability indices such as loss of load probability and expected energy unserved for the combined gas and electricity network. The intention of this tool is to facilitate reliability analysis of integrated energy systems. Applications of this tool are demonstrated through a case study that quantifies the impact on the reliability of the GB gas and electricity network given uncertainties such as wind variability, gas supply availability and outages to energy infrastructure assets. Analysis is performed over a typical midwinter week on a hypothesised GB gas and electricity network in 2020 that meets European renewable energy targets. The efficacy of doubling GB gas storage capacity on the reliability of the energy system is assessed. The results highlight the value of greater gas storage facilities in enhancing the reliability of the GB energy system given various energy uncertainties. -- Highlights: •A Monte Carlo model of the combined GB gas and electricity network was developed. •Reliability indices are calculated for the combined GB gas and electricity system. •The efficacy of doubling GB gas storage capacity on reliability of the energy system is assessed. •Integrated reliability indices could be used to assess the impact of investment in energy assets

Human networks in the European electric power industry

International Nuclear Information System (INIS)

Barjot, Dominique; Kurgan-van Hentenryk, Ginette

2004-01-01

Behind electrical systems, we should not forget the human networks. The European case is interesting for that matter. There were major players involved, from the pioneers up to the conceivers of national and international systems. More particularly, the engineers should be considered for their technical as well as organizational performance. Attitudes must also be stressed: in Europe, electricity has constantly been developed with both nationalist and internationalist considerations, as shown by the passage from Unternehmergeschaeft to Bankgeschaeft after 1918. Neither should we forget the role played by institutions in the formation of networks: schools, holdings, cartels, and also those frontier zones formed by small countries like Belgium and Switzerland. The human networks, finally, left long term results such as: interconnection, inter-firm cooperation, technocracy, and the growing intervention of the State

The impact of high PV penetration levels on electrical distribution networks

Energy Technology Data Exchange (ETDEWEB)

Collinson, A; Beddoes, A; Thornycroft, J [Halcrow (United Kingdom); Strbac, G; Jenkins, N [UMIST, Manchester (United Kingdom); Verhoeven, B [KEMA (Netherlands)

2002-07-01

This report describes the results of a collaborative study by EA Technology, UMIST and Halcrow into the effects of large-scale connection of dispersed photovoltaic (PV) power systems on the national electricity supply network. The report is intended to help manufacturers and installers of PV systems and electricity companies to understand the issues associated with grid connection of PV power systems. The increased use of PV systems is expected to have a significant impact on the design, operation and management of electricity supply networks. The study examined three main areas: probability and risk analysis of islanding; PV and network voltage control (including analysis of voltage control in a commercial, domestic retrofit and domestic new build scenarios); and future low voltage network design and operational policies.

AutoCAD electrical 2013 for electrical control designers

CERN Document Server

Tickoo, Sham; CADCIM Technologies

2013-01-01

The AutoCAD Electrical 2013 for Electrical Control Designers textbook has been written to assist the engineering students and the practicing designers learn the application of various AutoCAD Electrical tools and options for creating electrical control designs. After reading this textbook, the users will be able to create professional electrical-control drawings easily and effectively. Moreover, the users will be able to automate various control engineering tasks such as building circuits, numbering wires, creating bills of materials, and many more. The textbook takes the users across a wide spectrum of electrical control drawings through progressive examples and numerous illustrations and exercises, thereby making it an ideal guide for both the novice and the advanced users. Salient Features of the Textbook Consists of 14 chapters that are organized in a pedagogical sequence covering various tools and features of AutoCAD Electrical such as schematic drawings, parametric and non-parametric PLC modules, Circu...

Virtual CO2 Emission Flows in the Global Electricity Trade Network.

Science.gov (United States)

Qu, Shen; Li, Yun; Liang, Sai; Yuan, Jiahai; Xu, Ming

2018-05-14

Quantifying greenhouse gas emissions due to electricity consumption is crucial for climate mitigation in the electric power sector. Current practices primarily use production-based emission factors to quantify emissions for electricity consumption, assuming production and consumption of electricity take place within the same region. The increasingly intensified cross-border electricity trade complicates the accounting for emissions of electricity consumption. This study employs a network approach to account for the flows in the whole electricity trade network to estimate CO 2 emissions of electricity consumption for 137 major countries/regions in 2014. Results show that in some countries, especially those in Europe and Southern Africa, the impacts of electricity trade on the estimation of emission factors and embodied emissions are significant. The changes made to emission factors by considering intergrid electricity trade can have significant implications for emission accounting and climate mitigation when multiplied by total electricity consumption of the corresponding countries/regions.

Information and management system for the secondary electricity distribution network

Energy Technology Data Exchange (ETDEWEB)

Knezevic, M. (Rudnik i Termoelectrana Gacko u Osnivanju (Yugoslavia))

1988-07-01

Emphasizes the importance of a reliable and continuous secondary electrical distribution network for surface coal mine productivity. Interruptions in equipment operation caused by mechanical and electrical failures should be eliminated without delay. Effective communication systems should lead to reliable management and high productivity in mines. It is suggested that mines be divided into four groups according to their sensitivity to supply interruptions, and provided with remotely controlled signalling devices linked to main and auxiliary dispatching stations equipped with micro-computers. Productivity may be increased by some 50-70% and supply costs decreased by some 35% if appropriate electrical distribution systems are used. A sketch of a secondary electrical supply network is attached. 11 refs.

Integration between electric vehicle charging and micro-cogeneration system

International Nuclear Information System (INIS)

Angrisani, Giovanni; Canelli, Michele; Roselli, Carlo; Sasso, Maurizio

2015-01-01

Highlights: • The interaction between an MCHP system and EV charging is investigated. • A parametric analysis with respect to daily driving distance of the EV is performed. • Dynamic simulations are carried out considering two different climates. • Two EV charging strategies are analyzed to maximize the self-consumed electricity. • The impact of EVs on electric grid and economic feasibility of MCHP can be improved. - Abstract: In the near future the diffusion of plug-in electric vehicles (EVs) could play an important role in the reduction of emissions and oil dependency associated with the transport sector. However this technology could have a big impact on the electric network because EVs require a considerable amount of electricity. In order to meet the growing load due to the diffusion of EVs, the construction of new infrastructures will be required. The introduction of micro-cogeneration systems could represent a key factor in the reduction of the negative effects on the electric network related to EVs charging. The EVs are often driven during the day and recharged during the night; so the overnight charge of the EVs allows to reduce the amount of electricity exported to the grid. In this way the economic benefits associated with the introduction of micro-cogenerator system (Micro Combined Heat and Power, MCHP), that depend on the economic value of the “produced” electricity, can be improved. At the same time the impact of EVs charge on the electric network can be reduced when electricity is provided by MCHP. In this paper the interaction between an MCHP system, the EV charging and a typical semidetached house is investigated by means of dynamic simulations. The analysis is carried out in two different locations (Torino and Napoli) in order to evaluate the effects of climatic conditions on the system performance. A parametric analysis with respect to the daily driving distance of the EV is carried out in order to highlight the effect of this

Modelling biochemical networks with intrinsic time delays: a hybrid semi-parametric approach

Directory of Open Access Journals (Sweden)

Oliveira Rui

2010-09-01

Full Text Available Abstract Background This paper presents a method for modelling dynamical biochemical networks with intrinsic time delays. Since the fundamental mechanisms leading to such delays are many times unknown, non conventional modelling approaches become necessary. Herein, a hybrid semi-parametric identification methodology is proposed in which discrete time series are incorporated into fundamental material balance models. This integration results in hybrid delay differential equations which can be applied to identify unknown cellular dynamics. Results The proposed hybrid modelling methodology was evaluated using two case studies. The first of these deals with dynamic modelling of transcriptional factor A in mammalian cells. The protein transport from the cytosol to the nucleus introduced a delay that was accounted for by discrete time series formulation. The second case study focused on a simple network with distributed time delays that demonstrated that the discrete time delay formalism has broad applicability to both discrete and distributed delay problems. Conclusions Significantly better prediction qualities of the novel hybrid model were obtained when compared to dynamical structures without time delays, being the more distinctive the more significant the underlying system delay is. The identification of the system delays by studies of different discrete modelling delays was enabled by the proposed structure. Further, it was shown that the hybrid discrete delay methodology is not limited to discrete delay systems. The proposed method is a powerful tool to identify time delays in ill-defined biochemical networks.

Forecasting electricity infeed for distribution system networks : an analysis of the Dutch case

NARCIS (Netherlands)

Tanrisever, F.; Derinkuyu, K.; Heeren, M.

2013-01-01

Estimating and managing electricity distribution losses are the core business competencies of distribution system operators (DSOs). Since electricity demand is a major driver of network losses, it is essential for DSOs to have an accurate estimate of the electricity infeed in their network. In this

THE EVALUATION OF THE EFFECT OF REACTIVE POWER COMPENSATION IN ELECTRIC POWER LOSSES IN ELECTRIC NETWORK OF RAILWAY JUNCTION

OpenAIRE

O. I. Bondar; I. L. Bondar

2009-01-01

In this work the generalized mathematical model of an electrical network of the electrified railway junction is proposed. An estimation of influence of static var compensators installation on electric power losses in a network is executed on the basis of given model.

AC Electric Field Communication for Human-Area Networking

Science.gov (United States)

Kado, Yuichi; Shinagawa, Mitsuru

We have proposed a human-area networking technology that uses the surface of the human body as a data transmission path and uses an AC electric field signal below the resonant frequency of the human body. This technology aims to achieve a “touch and connect” intuitive form of communication by using the electric field signal that propagates along the surface of the human body, while suppressing both the electric field radiating from the human body and mutual interference. To suppress the radiation field, the frequency of the AC signal that excites the transmitter electrode must be lowered, and the sensitivity of the receiver must be raised while reducing transmission power to its minimally required level. We describe how we are developing AC electric field communication technologies to promote the further evolution of a human-area network in support of ubiquitous services, focusing on three main characteristics, enabling-transceiver technique, application-scenario modeling, and communications quality evaluation. Special attention is paid to the relationship between electro-magnetic compatibility evaluation and regulations for extremely low-power radio stations based on Japan's Radio Law.

Multi-Objective Scheduling of Electric Vehicles in Smart Distribution Network

Directory of Open Access Journals (Sweden)

Changhong Deng

2016-11-01

Full Text Available Due to the energy savings and environmental protection they provide, plug-in electric vehicles (PEVs are increasing in number quickly. Rapid development of PEVs brings new opportunities and challenges to the electricity distribution network’s dispatching. A high number of uncoordinated charging PEVs has significant negative impacts on the secure and economic operation of a distribution network. In this paper, a bi-level programming approach that coordinates PEVs’ charging with the network load and electricity price of the open market is presented. The major objective of the upper level model is to minimize the total network costs and the deviation of electric vehicle aggregators’ charging power and the equivalent power. The subsequent objective of the lower level model after the upper level decision is to minimize the dispatching deviation of the sum of PEVs’ charging power and their optimization charging power under the upper level model. An improved particle swarm optimization algorithm is used to solve the bi-level programming. Numerical studies using a modified IEEE 69-bus distribution test system including six electric vehicle aggregators verify the efficiency of the proposed model.

Electrical localization of weakly electric fish using neural networks

International Nuclear Information System (INIS)

Kiar, Greg; Mamatjan, Yasin; Adler, Andy; Jun, James; Maler, Len

2013-01-01

Weakly Electric Fish (WEF) emit an Electric Organ Discharge (EOD), which travels through the surrounding water and enables WEF to locate nearby objects or to communicate between individuals. Previous tracking of WEF has been conducted using infrared (IR) cameras and subsequent image processing. The limitation of visual tracking is its relatively low frame-rate and lack of reliability when visually obstructed. Thus, there is a need for reliable monitoring of WEF location and behaviour. The objective of this study is to provide an alternative and non-invasive means of tracking WEF in real-time using neural networks (NN). This study was carried out in three stages. First stage was to recreate voltage distributions by simulating the WEF using EIDORS and finite element method (FEM) modelling. Second stage was to validate the model using phantom data acquired from an Electrical Impedance Tomography (EIT) based system, including a phantom fish and tank. In the third stage, the measurement data was acquired using a restrained WEF within a tank. We trained the NN based on the voltage distributions for different locations of the WEF. With networks trained on the acquired data, we tracked new locations of the WEF and observed the movement patterns. The results showed a strong correlation between expected and calculated values of WEF position in one dimension, yielding a high spatial resolution within 1 cm and 10 times higher temporal resolution than IR cameras. Thus, the developed approach could be used as a practical method to non-invasively monitor the WEF in real-time.

Private electricity consumption on the rise -- the impact of networking

International Nuclear Information System (INIS)

Aebischer, B.; Huser, A.

2001-01-01

This article discusses the effect of the networking of the various devices to be found in the average home and the trend towards increased electricity consumption that will be brought about by 'intelligent' houses. Different scenarios for the increase in electricity consumption due to the increased use of multimedia systems - from the personal computer and mobile phones to hi-fi systems and the Internet are discussed. The contrasting tendencies noted in this area - such as, for example, the use of electricity to operate systems that are used to optimise and thus reduce electricity consumption in general are also discussed. Also, indirect energy-reduction effects in other areas - such as traffic reduction as a result of tele-working - are examined. Results of simulations and prognoses made concerning future trends for the electricity consumption of the various devices in homes are presented and recommendations are made on how to keep electricity consumption low when networking domestic apparatus

Development scheme for the public electricity transport network - 2006-2020

International Nuclear Information System (INIS)

2006-01-01

After having discussed the role of the development scheme and its mains requirements, presented its important components (energy needs, energy transport needs), and described its elaboration mode, this report gives an overview of the present status of the electricity transport network in France: 400.000 volts transport and interconnection networks, 225.000 volts and high voltage networks, development objectives, development context, transport network characteristics in 2006 (country gridding, development dynamics and consumption growth). Then, it presents a set of hypotheses about consumption, production and European exchanges. It identifies different types of constraints (customer connection, supply safety, electric and economic performance, robustness against extreme climate phenomena) and presents a method to assess these constraints (simulation of situations at risk, supply quality analysis, works expertise). The last part present the middle- and long-term constraints for the network

Supply curve bidding of electricity in constrained power networks

Energy Technology Data Exchange (ETDEWEB)

Al-Agtash, Salem Y. [Hijjawi Faculty of Engineering; Yarmouk University; Irbid 21163 (Jordan)

2010-07-15

This paper presents a Supply Curve Bidding (SCB) approach that complies with the notion of the Standard Market Design (SMD) in electricity markets. The approach considers the demand-side option and Locational Marginal Pricing (LMP) clearing. It iteratively alters Supply Function Equilibria (SFE) model solutions, then choosing the best bid based on market-clearing LMP and network conditions. It has been argued that SCB better benefits suppliers compared to fixed quantity-price bids. It provides more flexibility and better opportunity to achieving profitable outcomes over a range of demands. In addition, SCB fits two important criteria: simplifies evaluating electricity derivatives and captures smooth marginal cost characteristics that reflect actual production costs. The simultaneous inclusion of physical unit constraints and transmission security constraints will assure a feasible solution. An IEEE 24-bus system is used to illustrate perturbations of SCB in constrained power networks within the framework of SDM. By searching in the neighborhood of SFE model solutions, suppliers can obtain their best bid offers based on market-clearing LMP and network conditions. In this case, electricity producers can derive their best offering strategy both in the power exchange and the long-term contractual markets within a profitable, yet secure, electricity market. (author)

Supply curve bidding of electricity in constrained power networks

International Nuclear Information System (INIS)

Al-Agtash, Salem Y.

2010-01-01

This paper presents a Supply Curve Bidding (SCB) approach that complies with the notion of the Standard Market Design (SMD) in electricity markets. The approach considers the demand-side option and Locational Marginal Pricing (LMP) clearing. It iteratively alters Supply Function Equilibria (SFE) model solutions, then choosing the best bid based on market-clearing LMP and network conditions. It has been argued that SCB better benefits suppliers compared to fixed quantity-price bids. It provides more flexibility and better opportunity to achieving profitable outcomes over a range of demands. In addition, SCB fits two important criteria: simplifies evaluating electricity derivatives and captures smooth marginal cost characteristics that reflect actual production costs. The simultaneous inclusion of physical unit constraints and transmission security constraints will assure a feasible solution. An IEEE 24-bus system is used to illustrate perturbations of SCB in constrained power networks within the framework of SDM. By searching in the neighborhood of SFE model solutions, suppliers can obtain their best bid offers based on market-clearing LMP and network conditions. In this case, electricity producers can derive their best offering strategy both in the power exchange and the long-term contractual markets within a profitable, yet secure, electricity market. (author)

ON THE MANAGEMENT OF URBAN ELECTRIC NETWORKS IN THE CONDITIONS OF THE SMART GRID

Directory of Open Access Journals (Sweden)

M. А. Fursanov

2018-01-01

Full Text Available The issues of prospective operation of the city electric networks in the conditions of the MART GRID, which will be quite different as compared to the traditional understanding and approaches, are under consideration. This requires the selection and application of appropriate analytical criteria and approaches to assessment, analysis and control of the networks. With this regard the following criteria are recommended: in a particular case – the optimal (minimal technological electric power consumption (losses, while in general – economically reasonable (minimal cost value of electric power transmission. It should be also borne in mind that contemporary urban networks are actively saturated with distributed sources of small generation that have radically changed the structure of electrical networks; therefore, account for such sources is an absolutely necessary objective of management regimes of urban electric networks, both traditional and in associated with the SMART GRID. A case of the analysis and control of urban electric 10 kV networks with distributed small sources of generation has been developed and presented according to the theoretical criterion of minimum relative active power losses in the circuit as a control case. The conducted research makes it possible to determine the magnitude of the tolerance network mode from the point of the theoretical minimum. 

Pristine transfinite graphs and permissive electrical networks

CERN Document Server

Zemanian, Armen H

2001-01-01

A transfinite graph or electrical network of the first rank is obtained conceptually by connecting conventionally infinite graphs and networks together at their infinite extremities. This process can be repeated to obtain a hierarchy of transfiniteness whose ranks increase through the countable ordinals. This idea, which is of recent origin, has enriched the theories of graphs and networks with radically new constructs and research problems. The book provides a more accessible introduction to the subject that, though sacrificing some generality, captures the essential ideas of transfiniteness for graphs and networks. Thus, for example, some results concerning discrete potentials and random walks on transfinite networks can now be presented more concisely. Conversely, the simplifications enable the development of many new results that were previously unavailable. Topics and features: *A simplified exposition provides an introduction to transfiniteness for graphs and networks.*Various results for conventional g...

Outsourcing services in electricity distribution network industry; Ostopalveluiden kaeyttoe verkkoliiketoiminnassa

Energy Technology Data Exchange (ETDEWEB)

Aminoff, A.; Lappetelaeinen, I. (VTT Technical Research Centre of Finland, Espoo (Finland)); Partanen, J.; Viljainen, S.; Tahvanainen, K. (Lappeenranta Univ. of Technology (Finland)); Jaerventausta, P.; Trygg, P. (Tampere Univ. of Technology (Finland))

2009-02-15

This report examines purchased services in the electricity distribution industry. The report is specially directed to readers working in the industry or otherwise interested in it. This report is a result of a research study that was done in 2008 by VTT, Lappeenranta University of Technology and Tampere University of Technology. The authors are thankful for funders and companies that made this research possible and provided lot of information and knowledge. We appreciate the participants in the steering group as well as the companies and people who answered to questionnaires, gave interviews and took part in GDSSinnovation session. In the business of electricity distribution the usage of purchased services has been increasing during the past years and network companies have focused more on their core business processes. There are a couple of peaks in the number of new purchasing decisions in the middle of the 90s and in the beginning of 2000. The most popular purchased services are network construction and maintenance services. On the other hand, many network planning related activities are still done in-house by the network companies, and are considered their core business. There are some industry specific factors that affect to the decision on whether or not to buy the service outside the company and how to cooperate with the suppliers. For instance, many network companies are owned by municipalities and many service providers are owned by the network companies. The former issue may sometimes bring local politics into the decision-making of the network companies. The latter issue, in turn, has an impact on the relationship between the customer and the supplier, and the infra-organizational issues may sometimes complicate the service purchasing process. Electricity network companies also have natural monopoly positions in their operating areas. To prevent the abuse of monopoly positions, the network companies are subjected to economic regulation. This affects

Electrifying Europe. The power of Europe in the construction of electricity networks

International Nuclear Information System (INIS)

Lagendijk, V.C.

2008-01-01

This book sets out to uncover the origins of the idea of a European electricity network. It explores historically the roots of a transnational European system, showing how engineers came to think in terms of 'Europe' already in the 1920s, and how these ideas continued to influence network-building in later decades. This thinking not only corresponded to economic and technical attributes of the system. This thesis claims that a European system was also legitimised by ideological motives. Covering the period between 1918 and 2001 the book provides a detailed analysis of ideas on, and the building of, a European electricity system. A substantial contribution is made to the much-neglected history of international collaboration in Europe. Prevailing histories of electricity infrastructures the focus is on national developments. Also, the history is placed in the broader historical context of the twentieth century, paying ample attention to the influence of both hot and cold wars, and interwar developments. By combining the specific history of this international collaboration with a more general political and economic history of the twentieth century, the author explains why a European solution emerged. The thesis primarily focuses on Western European developments and explains how this network took its specific shape through the building of different regional powerpools among national systems. In addition, the thesis presents a contribution to the emerging field of transnational history by focusing on the work and activities of international organisations, without neglecting the power and influence of nation-states. The book starts by revealing how an international community of electricity entrepreneurs and electrical engineers had existed since the turn of the century. Yet at the same time, national legislations came to limit the extent of international network development and operation. Whereas the first objections to these limitations were general, they became

Intelligent Electric Power Systems with Active-Adaptive Electric Networks: Challenges for Simulation Tools

Directory of Open Access Journals (Sweden)

Ufa Ruslan A.

2015-01-01

Full Text Available The motivation of the presented research is based on the needs for development of new methods and tools for adequate simulation of intelligent electric power systems with active-adaptive electric networks (IES including Flexible Alternating Current Transmission System (FACTS devices. The key requirements for the simulation were formed. The presented analysis of simulation results of IES confirms the need to use a hybrid modelling approach.

Bosch automotive electrics and automotive electronics systems and components, networking and hybrid drive

CERN Document Server

2014-01-01

The significance of electrical and electronic systems has increased considerably in the last few years and this trend is set to continue. The characteristics feature of innovative systems is the fact that they can work together in a network. This requires powerful bus systems that the electronic control units can use to exchange information. Networking and the various bus systems used in motor vehicles are the prominent new topic in the 5th edition of the "Automotive Electric, Automotive Electronics" technical manual. The existing chapters have also been updated, so that this new edition brings the reader up to date on the subjects of electrical and electronic systems in the motor vehicle. Content Electrical and electronical systems – Basic principles of networking - Examples of networked vehicles – Bus systems – Architecture of electronic systems – Mechatronics – Elektronics – Electronic control Units – Software – Sensors – Actuators – Hybrid drives – Vehicle electrical system – Start...

Information report on electricity distribution network security and financing

International Nuclear Information System (INIS)

2011-01-01

This report first outlines the degradation of electricity quality, and identifies the lack of investment as the main reason of the network weakness. It notices that the French network is much extended, and that the medium and low voltage networks need to be secured, and outlines that some legal measures have already been implemented to correct these problems. In its second part, the report comments the network manager's point of view, and denies his critics of the conceding authorities. It also discusses the network manager's investments, and finally formulates six propositions for a better future of the distribution network

Regulatory Improvements for Effective Integration of Distributed Generation into Electricity Distribution Networks

International Nuclear Information System (INIS)

Scheepers, M.J.J.; Jansen, J.C.; De Joode, J.; Bauknecht, D.; Gomez, T.; Pudjianto, D.; Strbac, G.; Ropenus, S.

2007-11-01

The growth of distributed electricity supply of renewable energy sources (RES-E) and combined heat and power (CHP) - so called distributed generation (DG) - can cause technical problems for electricity distribution networks. These integration problems can be overcome by reinforcing the network. Many European Member States apply network regulation that does not account for the impact of DG growth on the network costs. Passing on network integration costs to the DG-operator who is responsible for these extra costs may result in discrimination between different DG plants and between DG and large power generation. Therefore, in many regulatory systems distribution system operators (DSOs) are not being compensated for the DG integration costs. The DG-GRID project analysed technical and economical barriers for integration of distributed generation into electricity distribution networks. The project looked into the impact of a high DG deployment on the electricity distribution system costs and the impact on the financial position of the DSO. Several ways for improving network regulation in order to compensate DSOs for the increasing DG penetration were identified and tested. The DG-GRID project looked also into stimulating network innovations through economic regulation. The project was co-financed by the European Commission and carried out by nine European universities and research institutes. This report summarises the project results and is based on a number of DG-GRID reports that describe the conducted analyses and their results

Load management in electrical networks. Objectives, methods, prospects

International Nuclear Information System (INIS)

Gabioud, D.

2008-01-01

This illustrated article takes up the problems related to the variation of the load in electricity networks. How to handle the peak load? Different solutions in the energy demand management are discussed. Method based on the price, method based on the reduction of the load by electric utilities. Information systems are presented which gives the consumer the needed data to participate in the local load management.

Evaluating North American Electric Grid Reliability Using the Barabasi-Albert Network Model

OpenAIRE

Chassin, David P.; Posse, Christian

2004-01-01

The reliability of electric transmission systems is examined using a scale-free model of network structure and failure propagation. The topologies of the North American eastern and western electric networks are analyzed to estimate their reliability based on the Barabasi-Albert network model. A commonly used power system reliability index is computed using a simple failure propagation model. The results are compared to the values of power system reliability indices previously obtained using s...

From electric networks to 'Smart grids'

International Nuclear Information System (INIS)

Hadjsaid, Nourredine; Sabonnadiere, Jean-Claude

2015-12-01

After decades of slow evolutions, and because of the emergence of renewable energies and of a multiplication of actors due to the liberalisation of energy markets, electric networks are entering a phase of large and complex development which will lead to a massive introduction of intelligence and to the building up of the 'smart grid' concept. The authors first identify the characteristics of the new energetic paradigm. The present operation of electric grids is based on four components: production by means of high power units installed in strategic locations, transport to consumption centres by means of a highly instrumented transport network which has highly centralised and hierarchical management, and consumers who are passive actors. They comment the implications of recent development for these three components. They describe how information and communication technologies (ICT) are used at the service of the grid, and how new technologies are integrated in different instruments (smart counter, actuators, fast cut devices, sensors, advanced supervision and control functions). Then they discuss the definition of a smart network or smart grid, the objectives it allows to be reached for energy transport as well as energy distribution. They discuss the desirable evolution of distribution networks and their technical objectives. Then, they give an overview of the various involved actors (consumers, network managers, electric equipment manufacturers, energy producers, and so on), evokes bodies and institutions involved in research on smart grids (notably in Grenoble within the INPG), give some examples of innovative concepts which are now being developed (intelligence distribution, virtual central station, grid monitoring, re-configurable grid, smart building). They also identify scientific and technological deadlocks, and outline the challenge of preparing the needed abilities for the development of smart grids

Integrated Multimedia Based Intelligent Group Decision Support System for Electrical Power Network

Directory of Open Access Journals (Sweden)

Ajay Kumar Saxena

2002-05-01

Full Text Available Electrical Power Network in recent time requires an intelligent, virtual environment based decision process for the coordination of all its individual elements and the interrelated tasks. Its ultimate goal is to achieve maximum productivity and efficiency through the efficient and effective application of generation, transmission, distribution, pricing and regulatory systems. However, the complexity of electrical power network and the presence of conflicting multiple goals and objectives postulated by various groups emphasized the need of an intelligent group decision support system approach in this field. In this paper, an Integrated Multimedia based Intelligent Group Decision Support System (IM1GDSS is presented, and its main components are analyzed and discussed. In particular attention is focused on the Data Base, Model Base, Central Black Board (CBB and Multicriteria Futuristic Decision Process (MFDP module. The model base interacts with Electrical Power Network Load Forecasting and Planning (EPNLFP Module; Resource Optimization, Modeling and Simulation (ROMAS Module; Electrical Power Network Control and Evaluation Process (EPNCAEP Module, and MFDP Module through CBB for strategic planning, management control, operational planning and transaction processing. The richness of multimedia channels adds a totally new dimension in a group decision making for Electrical Power Network. The proposed IMIGDSS is a user friendly, highly interactive group decision making system, based on efficient intelligent and multimedia communication support for group discussions, retrieval of content and multi criteria decision analysis.

Control strategies for power distribution networks with electric vehicles integration

DEFF Research Database (Denmark)

Hu, Junjie

of electrical energy. A smart grid can also be dened as an electricity network that can intelligently integrate the actions of all users connected to it - generators, consumers and those that do both - in order to eciently deliver sustainable, economic and secure electricity supplies. This thesis focuses...... of the ii market. To build a complete solution for integration of EVs into the distribution network, a price coordinated hierarchical scheduling system is proposed which can well characterize the involved actors in the smart grid. With this system, we demonstrate that it is possible to schedule the charging......Demand side resources, like electric vehicles (EVs), can become integral parts of a smart grids because instead of just consuming power they are capable of providing valuable services to power systems. EVs can be used to balance the intermittent renewable energy resources such as wind and solar...

Identifying options for regulating the coordination of network investments with investments in distributed electricity generation

International Nuclear Information System (INIS)

Nisten, E.

2010-02-01

The increase in the distributed generation of electricity, with wind turbines and solar panels, necessitates investments in the distribution network. The current tariff regulation in the Dutch electricity industry, with its ex post evaluation of the efficiency of investments and the frontier shift in the x-factor, delays these investments. In the unbundled electricity industry, the investments in the network need to be coordinated with those in the distributed generation of electricity to enable the DSOs to build enough network capacity. The current Dutch regulations do not provide for a sufficient information exchange between the generators and the system operators to coordinate the investments. This paper analyses these two effects of the Dutch regulation, and suggests improvements to the regulation of the network connection and transportation tariffs to allow for sufficient network capacity and coordination between the investments in the network and in the generation of electricity. These improvements include locally differentiated tariffs that increase with an increasing concentration of distributed generators.

Network investments and the integration of distributed generation: Regulatory recommendations for the Dutch electricity industry

International Nuclear Information System (INIS)

Niesten, Eva

2010-01-01

An increase in the distributed generation of electricity necessitates investments in the distribution network. The current tariff regulation in the Dutch electricity industry, with its ex post evaluation of the efficiency of investments, average benchmarking and a frontier shift in the x-factor, delays these investments. In the unbundled electricity industry, the investments in the network need to be coordinated with those in the distributed generation of electricity to enable the system operators to build enough network capacity. The current Dutch regulations do not provide for a sufficient information exchange between the generators and the system operators to coordinate the investments. This paper analyses these two effects of the Dutch regulations, and suggests improvements to the regulation of the network connection and transportation tariffs to allow for sufficient network capacity and coordination between the investments in the network and in the generation of electricity. These improvements include locally differentiated tariffs that increase with an increasing concentration of distributed generation.

Application of Artificial Neural Networks in the Heart Electrical Axis Position Conclusion Modeling

Science.gov (United States)

Bakanovskaya, L. N.

2016-08-01

The article touches upon building of a heart electrical axis position conclusion model using an artificial neural network. The input signals of the neural network are the values of deflections Q, R and S; and the output signal is the value of the heart electrical axis position. Training of the network is carried out by the error propagation method. The test results allow concluding that the created neural network makes a conclusion with a high degree of accuracy.

Visible technologies, invisible organisations: An empirical study of public beliefs about electricity supply networks

International Nuclear Information System (INIS)

Devine-Wright, Patrick; Devine-Wright, Hannah; Sherry-Brennan, Fionnguala

2010-01-01

Reducing carbon emissions in the energy system poses significant challenges to electricity transmission and distribution networks. Whilst these challenges are as much social as economic or technical, to date few research studies have investigated public beliefs about electricity supply networks. This research aimed to address this gap by means of a nationally representative study of UK adults (n=1041), probing beliefs about how electricity reaches the home, responsibility for electricity supply, associations with the words 'National Grid', as well as beliefs about the planning of new infrastructure. Findings suggest that electricity networks are represented predominantly in terms of technologies rather than organisations, specifically in terms of familiar, visible components such as cables or wires, rather than more systemic concepts such as networks. Transmission and distribution network operators were largely invisible to members of the public. In terms of planning new lines, most respondents assumed that government ministers were involved in decision-making, while local residents were widely perceived to have little influence; moreover, there was strong public support for placing new power lines underground, regardless of the cost. In conclusion, organisational invisibility, coupled with low expectations of participatory involvement, could provoke public opposition and delay siting new network infrastructure.

SYNCHRONIZATION OF NATIONAL GRID NETWORK WITH THE ELECTRICITY SHIPS NETWORK IN THE "SHORE TO SHIP" SYSTEM

Directory of Open Access Journals (Sweden)

Dariusz TARNAPOWICZ

2013-07-01

Full Text Available ‘Shore to ship’ system – ships’ power supply from the local electrical substations – is one of the effective ways to limit the negative impact of the ships lying in ports on the environment. Energy infrastructure of the port installation necessary to provide ships with power supply has to be designed so that different types of ships can use it. The important issue concerning ‘shore to ship’ system is the quality of power supply. This can be achieved via sustaining continuity of power supply while switching from the ships’ electrical network over to the national grid. In this article the author presents the way of synchronizing the national grid with the ships’ electrical network during ship’s lying in port. Such synchronization would allow for uninterruptible work of the ship’s electrical devices.

Short-term electricity prices forecasting in a competitive market: A neural network approach

International Nuclear Information System (INIS)

Catalao, J.P.S.; Mariano, S.J.P.S.; Mendes, V.M.F.; Ferreira, L.A.F.M.

2007-01-01

This paper proposes a neural network approach for forecasting short-term electricity prices. Almost until the end of last century, electricity supply was considered a public service and any price forecasting which was undertaken tended to be over the longer term, concerning future fuel prices and technical improvements. Nowadays, short-term forecasts have become increasingly important since the rise of the competitive electricity markets. In this new competitive framework, short-term price forecasting is required by producers and consumers to derive their bidding strategies to the electricity market. Accurate forecasting tools are essential for producers to maximize their profits, avowing profit losses over the misjudgement of future price movements, and for consumers to maximize their utilities. A three-layered feedforward neural network, trained by the Levenberg-Marquardt algorithm, is used for forecasting next-week electricity prices. We evaluate the accuracy of the price forecasting attained with the proposed neural network approach, reporting the results from the electricity markets of mainland Spain and California. (author)

An Electricity Price Forecasting Model by Hybrid Structured Deep Neural Networks

Directory of Open Access Journals (Sweden)

Ping-Huan Kuo

2018-04-01

Full Text Available Electricity price is a key influencer in the electricity market. Electricity market trades by each participant are based on electricity price. The electricity price adjusted with the change in supply and demand relationship can reflect the real value of electricity in the transaction process. However, for the power generating party, bidding strategy determines the level of profit, and the accurate prediction of electricity price could make it possible to determine a more accurate bidding price. This cannot only reduce transaction risk, but also seize opportunities in the electricity market. In order to effectively estimate electricity price, this paper proposes an electricity price forecasting system based on the combination of 2 deep neural networks, the Convolutional Neural Network (CNN and the Long Short Term Memory (LSTM. In order to compare the overall performance of each algorithm, the Mean Absolute Error (MAE and Root-Mean-Square error (RMSE evaluating measures were applied in the experiments of this paper. Experiment results show that compared with other traditional machine learning methods, the prediction performance of the estimating model proposed in this paper is proven to be the best. By combining the CNN and LSTM models, the feasibility and practicality of electricity price prediction is also confirmed in this paper.

On Parametric (and Non-Parametric Variation

Directory of Open Access Journals (Sweden)

Neil Smith

2009-11-01

Full Text Available This article raises the issue of the correct characterization of ‘Parametric Variation’ in syntax and phonology. After specifying their theoretical commitments, the authors outline the relevant parts of the Principles–and–Parameters framework, and draw a three-way distinction among Universal Principles, Parameters, and Accidents. The core of the contribution then consists of an attempt to provide identity criteria for parametric, as opposed to non-parametric, variation. Parametric choices must be antecedently known, and it is suggested that they must also satisfy seven individually necessary and jointly sufficient criteria. These are that they be cognitively represented, systematic, dependent on the input, deterministic, discrete, mutually exclusive, and irreversible.

Significance of application of the nine parametric coordinate transformation where local state network is not enough reliable

Directory of Open Access Journals (Sweden)

Ristić Kornelija T.

2016-01-01

Full Text Available The most commonly used method for establishing the mathematical basis of surveying and spatial data collection is the method of Global Navigation Satellite Positioning System (GNSS. However, these data relate to the World Geodetic Date WGS84 which is different from the State geodetic network,. As a part of realization the project of determining spatial local reference network Mrkonjić Grad the GNSS observations on 15 trigonometric points whose position is known to the State system of coordinates (x, y, h were made. For the purpose of coordinate transformation between the two system two different transformation models were anlyzed. Beside the most commonly used Helmert seven parameter transformation, afina nine parametric transformation was tested. Comparing the two transformations models, conclusion was made that showes some benefits of using affina nine parameter transformation models in Republic of Serpska.

A generative modeling approach to connectivity-Electrical conduction in vascular networks

DEFF Research Database (Denmark)

Hald, Bjørn Olav

2016-01-01

The physiology of biological structures is inherently dynamic and emerges from the interaction and assembly of large collections of small entities. The extent of coupled entities complicates modeling and increases computational load. Here, microvascular networks are used to present a novel...... to synchronize vessel tone across the vast distances within a network. We hypothesize that electrical conduction capacity is delimited by the size of vascular structures and connectivity of the network. Generation and simulation of series of dynamical models of electrical spread within vascular networks...... of different size and composition showed that (1) Conduction is enhanced in models harboring long and thin endothelial cells that couple preferentially along the longitudinal axis. (2) Conduction across a branch point depends on endothelial connectivity between branches. (3) Low connectivity sub...

New approach in electricity network regulation: an issue on effective integration of distributed generation in electricity supply systems

International Nuclear Information System (INIS)

Scheepers, Martin J.J.; Wals, Adrian F.

2003-11-01

Technological developments and EU targets for penetration of renewable energy sources (RES) and greenhouse gas (GHG) reduction are decentralising the electricity infrastructure and services. Although, the liberalisation and internationalisation of the European electricity market has resulted in efforts to harmonise transmission pricing and regulation, hardly any initiative exists to consider the opening up and regulation of distribution networks to ensure effective participation of RES and distributed generation (DG) in the internal market. The SUSTELNET project has been created in order to close this policy gap. Its main objective is to develop regulatory roadmaps for the transition to an electricity market and network structure that creates a level playing field between centralised and decentralised generation and that facilitates the integration of RES, within the framework of the liberalisation of the EU electricity market. By analysing the technical, socio-economic and institutional dynamics of the European electricity system and markets, the project identifies the underlying patterns that provide the boundary conditions and levers for policy development to reach long term RES and GHG targets (2020-2030 time frame). This paper presents results of this analytical phase of the SUSTELNET project. Furthermore, preliminary results of the current work in progress are presented. Principles and criteria for a regulatory framework for sustainable electricity systems are discussed, as well as the development of medium to long-term transition strategies/roadmaps for network regulation and market transformation to facilitate the integration of RES and decentralised electricity generating systems.

Parametric and Non-Parametric Vibration-Based Structural Identification Under Earthquake Excitation

Science.gov (United States)

Pentaris, Fragkiskos P.; Fouskitakis, George N.

2014-05-01

The problem of modal identification in civil structures is of crucial importance, and thus has been receiving increasing attention in recent years. Vibration-based methods are quite promising as they are capable of identifying the structure's global characteristics, they are relatively easy to implement and they tend to be time effective and less expensive than most alternatives [1]. This paper focuses on the off-line structural/modal identification of civil (concrete) structures subjected to low-level earthquake excitations, under which, they remain within their linear operating regime. Earthquakes and their details are recorded and provided by the seismological network of Crete [2], which 'monitors' the broad region of south Hellenic arc, an active seismic region which functions as a natural laboratory for earthquake engineering of this kind. A sufficient number of seismic events are analyzed in order to reveal the modal characteristics of the structures under study, that consist of the two concrete buildings of the School of Applied Sciences, Technological Education Institute of Crete, located in Chania, Crete, Hellas. Both buildings are equipped with high-sensitivity and accuracy seismographs - providing acceleration measurements - established at the basement (structure's foundation) presently considered as the ground's acceleration (excitation) and at all levels (ground floor, 1st floor, 2nd floor and terrace). Further details regarding the instrumentation setup and data acquisition may be found in [3]. The present study invokes stochastic, both non-parametric (frequency-based) and parametric methods for structural/modal identification (natural frequencies and/or damping ratios). Non-parametric methods include Welch-based spectrum and Frequency response Function (FrF) estimation, while parametric methods, include AutoRegressive (AR), AutoRegressive with eXogeneous input (ARX) and Autoregressive Moving-Average with eXogeneous input (ARMAX) models[4, 5

Processing of optical combs with fiber optic parametric amplifiers

Czech Academy of Sciences Publication Activity Database

Slavík, Radan; Kakande, J.; Richardson, D.J.; Petropoulos, P.

2012-01-01

Roč. 20, č. 9 (2012), s. 10059-10070 ISSN 1094-4087 Institutional support: RVO:67985882 Keywords : Fiber -optic parametric amplifier * Phase sensitive * Spectral coverage Subject RIV: JA - Electronics ; Optoelectronics, Electrical Engineering Impact factor: 3.546, year: 2012

History of electricity network control and distributed generation in the UK and Western Denmark

International Nuclear Information System (INIS)

Lehtonen, Markku; Nye, Sheridan

2009-01-01

Achieving the ambitious targets for renewable electricity generation in Europe will require harnessing a diverse range of energy sources, many of which are decentralised, small scale, and will be connected directly to the distribution networks. To control the two-way flows of electricity, the current passive network configurations will need to be replaced by active network management. This will require, in particular, innovations in intelligent IT-based network control. This paper draws on research on Large Technical Systems (LTS) and control systems in other sectors to analyse the evolution of electricity network control in western Denmark and the UK, since the Second World War. It concludes that lack of progress in network control has only recently-largely because of the combined needs to provide greater reliability and 'green' electricity within liberalised markets-emerged as a 'reverse salient' that will prevent the further development of the LTS of electricity supply industry towards desired direction. Breaking the inertia in the LTS and its control systems will require determined government action to promote learning and collaborative search for solutions. The UK might well draw lessons from the Danish pragmatism in fostering innovation through targeted support to collaborative R and D efforts towards sustainability objectives.

History of electricity network control and distributed generation in the UK and Western Denmark

Energy Technology Data Exchange (ETDEWEB)

Lehtonen, Markku [Sussex Energy Group, SPRU, University of Sussex, Freeman Centre, Falmer, Brighton, East Sussex BN1 9QE (United Kingdom); Nye, Sheridan [SPRU, University of Sussex, Freeman Centre, Falmer, Brighton, East Sussex BN1 9QE (United Kingdom)

2009-06-15

Achieving the ambitious targets for renewable electricity generation in Europe will require harnessing a diverse range of energy sources, many of which are decentralised, small scale, and will be connected directly to the distribution networks. To control the two-way flows of electricity, the current passive network configurations will need to be replaced by active network management. This will require, in particular, innovations in intelligent IT-based network control. This paper draws on research on Large Technical Systems (LTS) and control systems in other sectors to analyse the evolution of electricity network control in western Denmark and the UK, since the Second World War. It concludes that lack of progress in network control has only recently - largely because of the combined needs to provide greater reliability and 'green' electricity within liberalised markets - emerged as a 'reverse salient' that will prevent the further development of the LTS of electricity supply industry towards desired direction. Breaking the inertia in the LTS and its control systems will require determined government action to promote learning and collaborative search for solutions. The UK might well draw lessons from the Danish pragmatism in fostering innovation through targeted support to collaborative R and D efforts towards sustainability objectives. (author)

Gross domestic product estimation based on electricity utilization by artificial neural network

Science.gov (United States)

Stevanović, Mirjana; Vujičić, Slađana; Gajić, Aleksandar M.

2018-01-01

The main goal of the paper was to estimate gross domestic product (GDP) based on electricity estimation by artificial neural network (ANN). The electricity utilization was analyzed based on different sources like renewable, coal and nuclear sources. The ANN network was trained with two training algorithms namely extreme learning method and back-propagation algorithm in order to produce the best prediction results of the GDP. According to the results it can be concluded that the ANN model with extreme learning method could produce the acceptable prediction of the GDP based on the electricity utilization.

Parametric motion control of robotic arms: A biologically based approach using neural networks

Science.gov (United States)

Bock, O.; D'Eleuterio, G. M. T.; Lipitkas, J.; Grodski, J. J.

1993-01-01

A neural network based system is presented which is able to generate point-to-point movements of robotic manipulators. The foundation of this approach is the use of prototypical control torque signals which are defined by a set of parameters. The parameter set is used for scaling and shaping of these prototypical torque signals to effect a desired outcome of the system. This approach is based on neurophysiological findings that the central nervous system stores generalized cognitive representations of movements called synergies, schemas, or motor programs. It has been proposed that these motor programs may be stored as torque-time functions in central pattern generators which can be scaled with appropriate time and magnitude parameters. The central pattern generators use these parameters to generate stereotypical torque-time profiles, which are then sent to the joint actuators. Hence, only a small number of parameters need to be determined for each point-to-point movement instead of the entire torque-time trajectory. This same principle is implemented for controlling the joint torques of robotic manipulators where a neural network is used to identify the relationship between the task requirements and the torque parameters. Movements are specified by the initial robot position in joint coordinates and the desired final end-effector position in Cartesian coordinates. This information is provided to the neural network which calculates six torque parameters for a two-link system. The prototypical torque profiles (one per joint) are then scaled by those parameters. After appropriate training of the network, our parametric control design allowed the reproduction of a trained set of movements with relatively high accuracy, and the production of previously untrained movements with comparable accuracy. We conclude that our approach was successful in discriminating between trained movements and in generalizing to untrained movements.

Shortest loops are pacemakers in random networks of electrically coupled axons

Directory of Open Access Journals (Sweden)

Nikita eVladimirov

2012-04-01

Full Text Available High-frequency oscillations (HFOs are an important part of brain activity in health and disease. However, their origins remain obscure and controversial. One possible mechanism depends on the presence of sparsely distributed gap junctions that electrically couple the axons of principal cells. A plexus of electrically coupled axons is modeled as a random network with bidirectional connections between its nodes. Under certain conditions the network can demonstrate one of two types of oscillatory activity. Type I oscillations (100-200 Hz are predicted to be caused by spontaneously spiking axons in a network with strong (high-conductance gap junctions. Type II oscillations (200-300 Hz require no spontaneous spiking and relatively weak (low-conductance gap junctions, across which spike propagation failures occur. The type II oscillations are reentrant and self-sustained. Here we examine what determines the frequency of type II oscillations. Using simulations we show that the distribution of loop lengths is the key factor for determining frequency in type II network oscillations. We first analyze spike failure between two electrically coupled cells using a model of anatomically reconstructed CA1 pyramidal neuron. Then network oscillations are studied by a cellular automaton model with random network connectivity, in which we control loop statistics. We show that oscillation periods can be predicted from the network's loop statistics. The shortest loop, around which a spike can travel, is the most likely pacemaker candidate.The principle of one loop as a pacemaker is remarkable, because random networks contain a large number of loops juxtaposed and superimposed, and their number rapidly grows with network size. This principle allows us to predict the frequency of oscillations from network connectivity and visa versa. We finally propose that type I oscillations may correspond to ripples, while type II oscillations correspond to so-called fast ripples.

THE PROSPECTS OF DEVELOPMENT OF ELECTRIC POWER NETWORK IN GEORGIA

International Nuclear Information System (INIS)

Mshvidobadze, T.

2007-01-01

The possibility of application of one of the versions of development of the electric power network in Georgia is disscussed. The algorithm of grouping of the versions of power network development, which allows choosing the optimal network configuration under indefinite conditions, is offered. The experiments have demonstrated that the same optimal decision can be found by considerable reduction in the number of versions. (author)

Vision and Strategy for Europe’s Electricity Networks of the Future

DEFF Research Database (Denmark)

Bamberger, Yves; Baptista, João; Belmans, Ronnie

remotely fromdemand centres. The energy challenges that Europe is now facing are changing the electricity generationlandscape. The drive for lower-carbon generation technologies, combined with greatly improved efficiency on the demand side, will enable customers to become much more inter......-active with the networks. More customer-centric networks are the way ahead, but these fundamental changes will impact significantly on network design and control. In this context, the European Technology Platform (ETP) SmartGrids was set up in 2005 to create a jointvision for the European networks of 2020 and beyond....... The platform includes representatives fromindustry, transmission and distribution system operators, research bodies and regulators. It has identified clear objectives and proposes an ambitious strategy to make a reality of this vision for the benefits of Europe and its electricity customers....

Improving distribution efficiency of electrical network using geo-electrical options. A case study in a rural area of Assam (India)

Energy Technology Data Exchange (ETDEWEB)

Hazarika, S.; Hiloidhari, M.; Baruah, D.C. [Energy Conservation Laboratory, Department of Energy, Tezpur University, Tezpur, Assam (India)

2012-11-15

Reduction of electricity distribution loss is a major area of focus in India. This paper aims to investigate geo-electrical options to improve distribution efficiency of electrical network. Distribution efficiencies corresponding to several possible electrical network options are assessed using Geographical Information System (GIS) integrated electrical theory. An existing electrical distribution network of a rural area in Assam (India) is considered for the present investigation. Information related to characteristics of loads, features of conductors, and transformers of the existing network are used for this investigation. The line losses of the three existing transformers are estimated at about 36, 20, and 3 % of their respective connected loads. Longer distribution lines associated with higher loads are the causes of higher line losses. Using basic electrical theory and GIS tools, it is found that line losses can be reduced in the existing distribution system through management of distribution transformer and reconductoring. Two alternative locations for each of the three transformers are identified for optimal management of distribution transformers. Similarly, five different types of commercially available conductors are identified for possible reconductoring to reduce line loss. The economic viability of reconductoring of distribution lines are also assessed through an economic analysis. Net present values of total expenditure comprising purchase prices of conductor and cost attributed to line losses are estimated considering 30 years of useful life. The existing conductor has the worst economic merit, though it is the cheapest amongst all. A net saving of about USD 24,084 is possible through the best choice of distribution conductor for the village.

A capacitive ultrasonic transducer based on parametric resonance

Science.gov (United States)

Surappa, Sushruta; Satir, Sarp; Levent Degertekin, F.

2017-07-01

A capacitive ultrasonic transducer based on a parametric resonator structure is described and experimentally demonstrated. The transducer structure, which we call capacitive parametric ultrasonic transducer (CPUT), uses a parallel plate capacitor with a movable membrane as part of a degenerate parametric series RLC resonator circuit with a resonance frequency of fo. When the capacitor plate is driven with an incident harmonic ultrasonic wave at the pump frequency of 2fo with sufficient amplitude, the RLC circuit becomes unstable and ultrasonic energy can be efficiently converted to an electrical signal at fo frequency in the RLC circuit. An important characteristic of the CPUT is that unlike other electrostatic transducers, it does not require DC bias or permanent charging to be used as a receiver. We describe the operation of the CPUT using an analytical model and numerical simulations, which shows drive amplitude dependent operation regimes including parametric resonance when a certain threshold is exceeded. We verify these predictions by experiments with a micromachined membrane based capacitor structure in immersion where ultrasonic waves incident at 4.28 MHz parametrically drive a signal with significant amplitude in the 2.14 MHz RLC circuit. With its unique features, the CPUT can be particularly advantageous for applications such as wireless power transfer for biomedical implants and acoustic sensing.

Integrated Multimedia Based Intelligent Group Decision Support System for Electrical Power Network

OpenAIRE

Ajay Kumar Saxena; S. 0. Bhatnagar; P. K Saxena

2002-01-01

Electrical Power Network in recent time requires an intelligent, virtual environment based decision process for the coordination of all its individual elements and the interrelated tasks. Its ultimate goal is to achieve maximum productivity and efficiency through the efficient and effective application of generation, transmission, distribution, pricing and regulatory systems. However, the complexity of electrical power network and the presence of conflicting multiple goals and objectives p...

Software architecture for hybrid electrical/optical data center network

DEFF Research Database (Denmark)

Mehmeri, Victor; Vegas Olmos, Juan José; Tafur Monroy, Idelfonso

2016-01-01

This paper presents hardware and software architecture based on Software-Defined Networking (SDN) paradigm and OpenFlow/NETCONF protocols for enabling topology management of hybrid electrical/optical switching data center networks. In particular, a development on top of SDN open-source controller...... OpenDaylight is presented to control an optical switching matrix based on Micro-Electro-Mechanical System (MEMS) technology....

Electricity Networks: Infrastructure and Operations. Too complex for a resource?

Energy Technology Data Exchange (ETDEWEB)

Volk, Dennis

2013-07-01

Electricity security remains a priority of energy policy and continuous electrification will further enhance the importance in the years to come. Market liberalisation has brought substantial benefits to societies, including competition, innovation, more client-oriented services and the reduced needs for public expenditure. Further, the path of decarbonisation is a must but experiences with many new technologies and policies show their many implications on power systems. Electricity networks form the backbone of reliable and affordable power systems and also significantly support the inception of renewable generation. The importance of distribution and transmission networks has to be well understood by policy makers and regulators to maintain the sensitive balance within the policy triangle of reliability, affordability and sustainability as power systems rapidly change. Failures in choosing the right institutions and regulatory frameworks to operate and build networks will put the sensitive balance within the policy triangle at risk. ''Too complex for a resource?'' identifies the key challenges the electricity distribution and transmission networks face today and in the future. It further provides for best practice examples on institutional design choices and regulatory frameworks for sound network service provision but also highlights the importance of additional responses required. More market-based and dynamic frameworks for various system services, the growing need for active service participation of renewable generators and highly independent and transparent central operators seem to be at the heart of these responses. ''Too complex for a resource?'' finds that the answer to the challenges ahead is not always more infrastructure and that networks and the services they provide have to be regarded as equal part of the total power system. Thus, accurate and dynamic cost allocation can significantly support to transform

An Industrial Control System for the Supervision of the CERN Electrical Distribution Network

CERN Document Server

Poulsen, S

1999-01-01

CERN operates a large distribution network for the supply of electricity to the particle accelerators, experiments and the associated infrastructure. The distribution network operates on voltage levels from 400 V to 400 kV with a total yearly consumption of near to 1000 GWh. In the past, the laboratory has developed an in-house control system for this network, using the technologies applied to the accelerator control system. However, CERN is now working on a project to purchase, configure and install an industrial Electrical Network Supervisor (ENS). This is a state-of-the-art industrial control system completely developed and supported by an external contractor. The system - based on a scalable and distributed architecture - will allow the installation to be performed gradually, and will be tested while the existing system is fully operational. Ultimately, the complete electrical distribution network will be supervised with this new system, the maintenance and further development of which will be the complet...

Absolute parametric instability in a nonuniform plane plasma

Indian Academy of Sciences (India)

The paper reports an analysis of the effect of spatial plasma nonuniformity on absolute parametric instability (API) of electrostatic waves in magnetized plane waveguides subjected to an intense high-frequency (HF) electric field using the separation method. In this case the effect of strong static magnetic field is considered.

Analysis of reflectivity & predictability of electricity network tariff structures for household consumers

NARCIS (Netherlands)

Nijhuis, M.; Gibescu, M.; Cobben, J. F.G.

2017-01-01

Distribution network operators charge household consumers with a network tariff, so they can recover their network investment and operational costs. With the transition; towards a sustainable energy system, the household load is changing, through the introduction of photovoltaics and electric

Multiple synchronization transitions in scale-free neuronal networks with electrical and chemical hybrid synapses

International Nuclear Information System (INIS)

Liu, Chen; Wang, Jiang; Wang, Lin; Yu, Haitao; Deng, Bin; Wei, Xile; Tsang, Kaiming; Chan, Wailok

2014-01-01

Highlights: • Synchronization transitions in hybrid scale-free neuronal networks are investigated. • Multiple synchronization transitions can be induced by the time delay. • Effect of synchronization transitions depends on the ratio of the electrical and chemical synapses. • Coupling strength and the density of inter-neuronal links can enhance the synchronization. -- Abstract: The impacts of information transmission delay on the synchronization transitions in scale-free neuronal networks with electrical and chemical hybrid synapses are investigated. Numerical results show that multiple appearances of synchronization regions transitions can be induced by different information transmission delays. With the time delay increasing, the synchronization of neuronal activities can be enhanced or destroyed, irrespective of the probability of chemical synapses in the whole hybrid neuronal network. In particular, for larger probability of electrical synapses, the regions of synchronous activities appear broader with stronger synchronization ability of electrical synapses compared with chemical ones. Moreover, it can be found that increasing the coupling strength can promote synchronization monotonously, playing the similar role of the increasing the probability of the electrical synapses. Interestingly, the structures and parameters of the scale-free neuronal networks, especially the structural evolvement plays a more subtle role in the synchronization transitions. In the network formation process, it is found that every new vertex is attached to the more old vertices already present in the network, the more synchronous activities will be emerge

Absolute parametric instability in a nonuniform plane plasma ...

Indian Academy of Sciences (India)

Abstract. The paper reports an analysis of the effect of spatial plasma nonuniformity on absolute parametric instability (API) of electrostatic waves in magnetized plane waveguides subjected to an intense high-frequency (HF) electric field using the separation method. In this case the effect of strong static magnetic field is ...

Parametric studies and optimisation of pumped thermal electricity storage

International Nuclear Information System (INIS)

McTigue, Joshua D.; White, Alexander J.; Markides, Christos N.

2015-01-01

Highlights: • PTES is modelled by cycle analysis and a Schumann-style model of the thermal stores. • Optimised trade-off surfaces show a flat efficiency vs. energy density profile. • Overall roundtrip efficiencies of around 70% are not inconceivable. - Abstract: Several of the emerging technologies for electricity storage are based on some form of thermal energy storage (TES). Examples include liquid air energy storage, pumped heat energy storage and, at least in part, advanced adiabatic compressed air energy storage. Compared to other large-scale storage methods, TES benefits from relatively high energy densities, which should translate into a low cost per MW h of storage capacity and a small installation footprint. TES is also free from the geographic constraints that apply to hydro storage schemes. TES concepts for electricity storage rely on either a heat pump or refrigeration cycle during the charging phase to create a hot or a cold storage space (the thermal stores), or in some cases both. During discharge, the thermal stores are depleted by reversing the cycle such that it acts as a heat engine. The present paper is concerned with a form of TES that has both hot and cold packed-bed thermal stores, and for which the heat pump and heat engine are based on a reciprocating Joule cycle, with argon as the working fluid. A thermodynamic analysis is presented based on traditional cycle calculations coupled with a Schumann-style model of the packed beds. Particular attention is paid to the various loss-generating mechanisms and their effect on roundtrip efficiency and storage density. A parametric study is first presented that examines the sensitivity of results to assumed values of the various loss factors and demonstrates the rather complex influence of the numerous design variables. Results of an optimisation study are then given in the form of trade-off surfaces for roundtrip efficiency, energy density and power density. The optimised designs show a

A parametric study of AC electric field-induced toroidal vortex formation in laminar nonpremixed coflow flames

KAUST Repository

Xiong, Yuan

2017-05-02

This study presents an experimental work investigating the controlling parameters on the formation of an electrically-induced inner toroidal vortex (ITV) near a nozzle rim in small, laminar nonpremixed coflow flames, when an alternating current is applied to the nozzle. A systematic parametric study was conducted by varying the flow parameters of the fuel and coflowing-air velocities, and the nozzle diameter. The fuels tested were methane, ethylene, ethane, propane, n-butane, and i-butane, each representing different ion-generation characteristics and sooting tendencies. The results showed that the fluid dynamic effects on ITV formation were weak, causing only mild variation when altering flow velocities. However, increased fuel velocity resulted in increased polycyclic aromatic hydrocarbon (PAH) formation, which promoted ITV formation. When judging the ITV-formation tendency based on critical applied voltage and frequency, it was qualitatively well correlated with the PAH concentration and the relative location of PAHs to the nozzle rim. The sooting tendency of the fuels did not affect the results much. A change in the nozzle diameter highlighted the importance of the relative distance between the PAH zone and the nozzle rim, indicating the role of local electric-field intensity on ITV formation. Detailed onset conditions, characteristics of near-nozzle flow patterns, and PAH distributions are also discussed.

Impedance-Source Networks for Electric Power Conversion Part II

DEFF Research Database (Denmark)

Siwakoti, Yam P.; Peng, Fang Zheng; Blaabjerg, Frede

2015-01-01

Impedance-source networks cover the entire spectrum of electric power conversion applications (dc-dc, dc-ac, ac-dc, ac-ac) controlled and modulated by different modulation strategies to generate the desired dc or ac voltage and current at the output. A comprehensive review of various impedance......-source-network-based power converters has been covered in a previous paper and main topologies were discussed from an application point of view. Now Part II provides a comprehensive review of the most popular control and modulation strategies for impedance-source network-based power converters/inverters. These methods...

Monthly electric energy demand forecasting with neural networks and Fourier series

International Nuclear Information System (INIS)

Gonzalez-Romera, E.; Jaramillo-Moran, M.A.; Carmona-Fernandez, D.

2008-01-01

Medium-term electric energy demand forecasting is a useful tool for grid maintenance planning and market research of electric energy companies. Several methods, such as ARIMA, regression or artificial intelligence, have been usually used to carry out those predictions. Some approaches include weather or economic variables, which strongly influence electric energy demand. Economic variables usually influence the general series trend, while weather provides a periodic behavior because of its seasonal nature. This work investigates the periodic behavior of the Spanish monthly electric demand series, obtained by rejecting the trend from the consumption series. A novel hybrid approach is proposed: the periodic behavior is forecasted with a Fourier series while the trend is predicted with a neural network. Satisfactory results have been obtained, with a lower than 2% MAPE, which improve those reached when only neural networks or ARIMA were used for the same purpose. (author)

Architecture, design and protection of electrical distribution networks

Energy Technology Data Exchange (ETDEWEB)

Sorrel, J.P. [Schneider electric Industries SA (France)

2000-07-01

Architectures related to AII Electric Ship (AES) require high level of propulsion power. Merchant ships and obviously warships require a low vulnerability, a high reliability and availability, a simple maintainability as well as an ordinary ode of operation. These constraints converge to an optimum single line diagram. We will focus on the mode of operation of the network, its constraints, the facilities to use a ring distribution for the ship service distribution system, the earthing of HV network as well as future developments. (author)

Memristors in the electrical network of Aloe vera L.

Science.gov (United States)

Volkov, Alexander G; Reedus, Jada; Mitchell, Colee M; Tucket, Clayton; Forde-Tuckett, Victoria; Volkova, Maya I; Markin, Vladislav S; Chua, Leon

2014-01-01

A memristor is a resistor with memory, which is a non-linear passive two-terminal electrical element relating magnetic flux linkage and electrical charge. Here we found that memristors exist in vivo. The electrostimulation of the Aloe vera by bipolar sinusoidal or triangle periodic waves induce electrical responses with fingerprints of memristors. Uncouplers carbonylcyanide-3-chlorophenylhydrazone and carbonylcyanide-4-trifluoromethoxy-phenyl hydrazone decrease the amplitude of electrical responses at low and high frequencies of bipolar periodic sinusoidal or triangle electrostimulating waves. Memristive behavior of an electrical network in the Aloe vera is linked to the properties of voltage gated ion channels: the K+ channel blocker TEACl reduces the electric response to a conventional resistor. Our results demonstrate that a voltage gated K+ channel in the excitable tissue of plants has properties of a memristor. The discovery of memristors in plants creates a new direction in the modeling and understanding of electrical phenomena in plants. PMID:25763487

Incentive Regulation and Utility Benchmarking for Electricity Network Security

OpenAIRE

Zhang, Y.; Nepal, R.

2014-01-01

The incentive regulation of costs related to physical and cyber security in electricity networks is an important but relatively unexplored and ambiguous issue. These costs can be part of cost efficiency benchmarking or, alternatively, dealt with separately. This paper discusses the issues and proposes options for incorporating network security costs within incentive regulation in a benchmarking framework. The relevant concerns and limitations associated with the accounting and classification ...

A microbiology-based multi-parametric approach towards assessing biological stability in drinking water distribution networks

KAUST Repository

Lautenschlä ger, Karin; Hwang, Chiachi; Liu, Wentso; Boon, Nico; Kö ster, Oliver; Vrouwenvelder, Johannes S.; Egli, Thomas; Hammes, Frederik A.

2013-01-01

Biological stability of drinking water implies that the concentration of bacterial cells and composition of the microbial community should not change during distribution. In this study, we used a multi-parametric approach that encompasses different aspects of microbial water quality including microbial growth potential, microbial abundance, and microbial community composition, to monitor biological stability in drinking water of the non-chlorinated distribution system of Zürich. Drinking water was collected directly after treatment from the reservoir and in the network at several locations with varied average hydraulic retention times (6-52h) over a period of four months, with a single repetition two years later. Total cell concentrations (TCC) measured with flow cytometry remained remarkably stable at 9.5 (±0.6)×104cells/ml from water in the reservoir throughout most of the distribution network, and during the whole time period. Conventional microbial methods like heterotrophic plate counts, the concentration of adenosine tri-phosphate, total organic carbon and assimilable organic carbon remained also constant. Samples taken two years apart showed more than 80% similarity for the microbial communities analysed with denaturing gradient gel electrophoresis and 454 pyrosequencing. Only the two sampling locations with the longest water retention times were the exceptions and, sofar for unknown reasons, recorded a slight but significantly higher TCC (1.3(±0.1)×105cells/ml) compared to the other locations. This small change in microbial abundance detected by flow cytometry was also clearly observed in a shift in the microbial community profiles to a higher abundance of members from the Comamonadaceae (60% vs. 2% at other locations). Conventional microbial detection methods were not able to detect changes as observed with flow cytometric cell counts and microbial community analysis. Our findings demonstrate that the multi-parametric approach used provides a powerful

A microbiology-based multi-parametric approach towards assessing biological stability in drinking water distribution networks.

Science.gov (United States)

Lautenschlager, Karin; Hwang, Chiachi; Liu, Wen-Tso; Boon, Nico; Köster, Oliver; Vrouwenvelder, Hans; Egli, Thomas; Hammes, Frederik

2013-06-01

Biological stability of drinking water implies that the concentration of bacterial cells and composition of the microbial community should not change during distribution. In this study, we used a multi-parametric approach that encompasses different aspects of microbial water quality including microbial growth potential, microbial abundance, and microbial community composition, to monitor biological stability in drinking water of the non-chlorinated distribution system of Zürich. Drinking water was collected directly after treatment from the reservoir and in the network at several locations with varied average hydraulic retention times (6-52 h) over a period of four months, with a single repetition two years later. Total cell concentrations (TCC) measured with flow cytometry remained remarkably stable at 9.5 (± 0.6) × 10(4) cells/ml from water in the reservoir throughout most of the distribution network, and during the whole time period. Conventional microbial methods like heterotrophic plate counts, the concentration of adenosine tri-phosphate, total organic carbon and assimilable organic carbon remained also constant. Samples taken two years apart showed more than 80% similarity for the microbial communities analysed with denaturing gradient gel electrophoresis and 454 pyrosequencing. Only the two sampling locations with the longest water retention times were the exceptions and, so far for unknown reasons, recorded a slight but significantly higher TCC (1.3 (± 0.1) × 10(5) cells/ml) compared to the other locations. This small change in microbial abundance detected by flow cytometry was also clearly observed in a shift in the microbial community profiles to a higher abundance of members from the Comamonadaceae (60% vs. 2% at other locations). Conventional microbial detection methods were not able to detect changes as observed with flow cytometric cell counts and microbial community analysis. Our findings demonstrate that the multi-parametric approach used

A microbiology-based multi-parametric approach towards assessing biological stability in drinking water distribution networks

KAUST Repository

Lautenschläger, Karin

2013-06-01

Biological stability of drinking water implies that the concentration of bacterial cells and composition of the microbial community should not change during distribution. In this study, we used a multi-parametric approach that encompasses different aspects of microbial water quality including microbial growth potential, microbial abundance, and microbial community composition, to monitor biological stability in drinking water of the non-chlorinated distribution system of Zürich. Drinking water was collected directly after treatment from the reservoir and in the network at several locations with varied average hydraulic retention times (6-52h) over a period of four months, with a single repetition two years later. Total cell concentrations (TCC) measured with flow cytometry remained remarkably stable at 9.5 (±0.6)×104cells/ml from water in the reservoir throughout most of the distribution network, and during the whole time period. Conventional microbial methods like heterotrophic plate counts, the concentration of adenosine tri-phosphate, total organic carbon and assimilable organic carbon remained also constant. Samples taken two years apart showed more than 80% similarity for the microbial communities analysed with denaturing gradient gel electrophoresis and 454 pyrosequencing. Only the two sampling locations with the longest water retention times were the exceptions and, sofar for unknown reasons, recorded a slight but significantly higher TCC (1.3(±0.1)×105cells/ml) compared to the other locations. This small change in microbial abundance detected by flow cytometry was also clearly observed in a shift in the microbial community profiles to a higher abundance of members from the Comamonadaceae (60% vs. 2% at other locations). Conventional microbial detection methods were not able to detect changes as observed with flow cytometric cell counts and microbial community analysis. Our findings demonstrate that the multi-parametric approach used provides a powerful

A capacitive ultrasonic transducer based on parametric resonance.

Science.gov (United States)

Surappa, Sushruta; Satir, Sarp; Levent Degertekin, F

2017-07-24

A capacitive ultrasonic transducer based on a parametric resonator structure is described and experimentally demonstrated. The transducer structure, which we call capacitive parametric ultrasonic transducer (CPUT), uses a parallel plate capacitor with a movable membrane as part of a degenerate parametric series RLC resonator circuit with a resonance frequency of f o . When the capacitor plate is driven with an incident harmonic ultrasonic wave at the pump frequency of 2f o with sufficient amplitude, the RLC circuit becomes unstable and ultrasonic energy can be efficiently converted to an electrical signal at f o frequency in the RLC circuit. An important characteristic of the CPUT is that unlike other electrostatic transducers, it does not require DC bias or permanent charging to be used as a receiver. We describe the operation of the CPUT using an analytical model and numerical simulations, which shows drive amplitude dependent operation regimes including parametric resonance when a certain threshold is exceeded. We verify these predictions by experiments with a micromachined membrane based capacitor structure in immersion where ultrasonic waves incident at 4.28 MHz parametrically drive a signal with significant amplitude in the 2.14 MHz RLC circuit. With its unique features, the CPUT can be particularly advantageous for applications such as wireless power transfer for biomedical implants and acoustic sensing.

INTEGRAL INDEX OF OPERATION QUALITY FOR EVALUATION OF IMPACT OF DISTRIBUTIVE GENERATION SOURCES ON ELECTRIC NETWORK MODES

Directory of Open Access Journals (Sweden)

Petro D. Lezhniuk

2017-06-01

Full Text Available Method of operation quality evaluation of electric network, comprising renewable sources of energy (RSE is considered. Integral index that enables to evaluate the impact of RSE on energy losses and its quality as well as balance reliability in electric network is suggested. Mathematical model is constructed, taking into account the assumption that electric network with RSE may be in various operation modes, characterized by different technical economic indices. To determine the integral index of operation quality of electric network with RSE in all possible states tools of Markov processes theory and criterial method are used.

Classification rates: non‐parametric verses parametric models using ...

African Journals Online (AJOL)

This research sought to establish if non parametric modeling achieves a higher correct classification ratio than a parametric model. The local likelihood technique was used to model fit the data sets. The same sets of data were modeled using parametric logit and the abilities of the two models to correctly predict the binary ...

Reversible Control of Anisotropic Electrical Conductivity using Colloidal Microfluidic Networks

National Research Council Canada - National Science Library

Beskok, Ali; Bevan, Michael; Lagoudas, Dimitris; Ounaies, Zoubeida; Bahukudumbi, Pradipkumar; Everett, William

2007-01-01

This research addresses the tunable assembly of reversible colloidal structures within microfluidic networks to engineer multifunctional materials that exhibit a wide range of electrical properties...

Non-parametric Bayesian networks: Improving theory and reviewing applications

International Nuclear Information System (INIS)

Hanea, Anca; Morales Napoles, Oswaldo; Ababei, Dan

2015-01-01

Applications in various domains often lead to high dimensional dependence modelling. A Bayesian network (BN) is a probabilistic graphical model that provides an elegant way of expressing the joint distribution of a large number of interrelated variables. BNs have been successfully used to represent uncertain knowledge in a variety of fields. The majority of applications use discrete BNs, i.e. BNs whose nodes represent discrete variables. Integrating continuous variables in BNs is an area fraught with difficulty. Several methods that handle discrete-continuous BNs have been proposed in the literature. This paper concentrates only on one method called non-parametric BNs (NPBNs). NPBNs were introduced in 2004 and they have been or are currently being used in at least twelve professional applications. This paper provides a short introduction to NPBNs, a couple of theoretical advances, and an overview of applications. The aim of the paper is twofold: one is to present the latest improvements of the theory underlying NPBNs, and the other is to complement the existing overviews of BNs applications with the NPNBs applications. The latter opens the opportunity to discuss some difficulties that applications pose to the theoretical framework and in this way offers some NPBN modelling guidance to practitioners. - Highlights: • The paper gives an overview of the current NPBNs methodology. • We extend the NPBN methodology by relaxing the conditions of one of its fundamental theorems. • We propose improvements of the data mining algorithm for the NPBNs. • We review the professional applications of the NPBNs.

New Operation and Maintenance Contract for Electrical Network

CERN Document Server

Kowalik, G

2001-01-01

The Electrical Exploitation is one of the few remaining operation services at CERN which nearly entirely relies on the CERN staff. Last year CERN policy, in connection with the LHC project needs, have led to the formulation of the strategy of out-sourcing of the Electrical Exploitation activities, market survey and subsequent Invitation to Tender. The following paper presents the approach used in the preparation of the Invitation to Tender and in solving of the out-sourcing issues applied to the operation and maintenance of the CERN electrical network. In particular the problems of the results oriented contract, quality assurance and performance as well requirement of the constantly increasing productivity of the Contractors team are treated. The paper gives also the particularities of the application of the out-sourcing to the electrical operation service as will as techniques used for the estimation of the work load of the activities being outsourced.

APT cost scaling: Preliminary indications from a Parametric Costing Model (PCM)

International Nuclear Information System (INIS)

Krakowski, R.A.

1995-01-01

A Parametric Costing Model has been created and evaluate as a first step in quantitatively understanding important design options for the Accelerator Production of Tritium (APT) concept. This model couples key economic and technical elements of APT in a two-parameter search of beam energy and beam power that minimizes costs within a range of operating constraints. The costing and engineering depth of the Parametric Costing Model is minimal at the present open-quotes entry levelclose quotes, and is intended only to demonstrate a potential for a more-detailed, cost-based integrating design tool. After describing the present basis of the Parametric Costing Model and giving an example of a single parametric scaling run derived therefrom, the impacts of choices related to resistive versus superconducting accelerator structures and cost of electricity versus plant availability (open-quotes load curveclose quotes) are reported. Areas of further development and application are suggested

PARAMETRIC ANALYSIS OF A MINIATURIZED INVERTED II SHAPED ANTENNA FOR WIRELESS SENSOR NETWORK APPLICATIONS

Directory of Open Access Journals (Sweden)

M. Shanmugapriya

2015-06-01

Full Text Available A compact and simple design of a CPW-fed planar antenna for wireless sensor network antenna application with a better size reduction is presented. The proposed antenna consists of an inverted ? shaped metal patch on a printed circuit board fed by a 50-O coplanar waveguide (CPW. The parametric analysis of length and width are made. The designed antenna’s physical dimensions are 32 mm (length x 26 mm (width x 1.6 mm (height. The antenna structure has been modeled and fabricated and its performance has been evaluated using a method of moment based electromagnetic simulator, IE3D .The return loss of -22.5 dB and VSWR of 1.34 dB are noted. The radiation pattern of the antenna proves that it radiates in all direction. The antenna is fabricated and tested and the measured results go in good agreement with simulated one.

Fluid power network for centralized electricity generation in offshore wind farms

NARCIS (Netherlands)

Jarquin-Laguna, A.

2014-01-01

An innovative and completely different wind-energy conversion system is studied where a centralized electricity generation within a wind farm is proposed by means of a hydraulic network. This paper presents the dynamic interaction of two turbines when they are coupled to the same hydraulic network.

A network model for electrical transport in sea ice

International Nuclear Information System (INIS)

Zhu, J.; Golden, K.M.; Gully, A.; Sampson, C.

2010-01-01

Monitoring the thickness of sea ice is an important tool in assessing the impact of global warming on Earth's polar regions, and most methods of measuring ice thickness depend on detailed knowledge of its electrical properties. We develop a network model for the electrical conductivity of sea ice, which incorporates statistical measurements of the brine microstructure. The numerical simulations are in close agreement with direct measurements we made in Antarctica on the vertical conductivity of first year sea ice.

Mathematical models of electrical network systems theory and applications : an introduction

CERN Document Server

Kłos, Andrzej

2017-01-01

This book is for all those who are looking for a non-conventional mathematical model of electrical network systems. It presents a modern approach using linear algebra and derives various commonly unknown quantities and interrelations of network analysis. It also explores some applications of algebraic network model of and solves some examples of previously unsolved network problems in planning and operation of network systems. Complex mathematical aspects are illustrated and described in a way that is understandable for non-mathematicians. Discussing interesting concepts and practically useful methods of network analysis, it is a valuable resource for lecturers, students, engineers and research workers. .

MODELING OF SYMMETRIC THREE-PHASE ASYNCHRONOUS ELECTRIC MOTOR IN ASYMMETRIC CONNECTION TO NETWORK

Directory of Open Access Journals (Sweden)

V. I. Lukovnikov

2005-01-01

Full Text Available The paper shows how to solve the problem concerning reveal of changes in mathematical models and electric parameters of symmetric three-phase short-circuited asynchronous electric motors in case of their connection to single- or two-phase network in comparison with their connection to three-phase network. The uniform methodological approach permitting to generalize the known data and receive new results is offered in the paper.

Tensions on the electric network; Tensions sur le reseau

Energy Technology Data Exchange (ETDEWEB)

Garrigues, B.

2001-10-01

Facing the potential 12000 MW of wind power projects, it is necessary to solve quickly the management of queues for the connection to the french electric network. This paper presents the today situation and proposes solutions. (A.L.B.)

Parametric excitation of a SiN membrane via piezoelectricity

Directory of Open Access Journals (Sweden)

Shuhui Wu

2018-01-01

Full Text Available We develop a stoichiometric silicon nitride (SiN membrane-based electromechanical system, in which the spring constant of the mechanical resonator can be dynamically controlled via piezoelectric actuation. The degenerate parametric amplifier is studied in this configuration. We observe the splitting of mechanical mode in the response spectra of a phase-sensitive parametric amplifier. In addition, we demonstrate that the quality factor Q of the membrane oscillator can be significantly enhanced by more than two orders of magnitude due to the coherent amplification, reaching an effective Q factor of ∼3 × 108 at room temperature. The nonlinear effect on the parametric amplification is also investigated, as well as the thermomechanical noise squeezing. This system offers the possibility to integrate electrical, optical and mechanical degrees of freedom without compromising the exceptional material properties of SiN membranes, and can be a useful platform for studying cavity optoelectromechanics.

Parametric excitation of a SiN membrane via piezoelectricity

Science.gov (United States)

Wu, Shuhui; Sheng, Jiteng; Zhang, Xiaotian; Wu, Yuelong; Wu, Haibin

2018-01-01

We develop a stoichiometric silicon nitride (SiN) membrane-based electromechanical system, in which the spring constant of the mechanical resonator can be dynamically controlled via piezoelectric actuation. The degenerate parametric amplifier is studied in this configuration. We observe the splitting of mechanical mode in the response spectra of a phase-sensitive parametric amplifier. In addition, we demonstrate that the quality factor Q of the membrane oscillator can be significantly enhanced by more than two orders of magnitude due to the coherent amplification, reaching an effective Q factor of ˜3 × 108 at room temperature. The nonlinear effect on the parametric amplification is also investigated, as well as the thermomechanical noise squeezing. This system offers the possibility to integrate electrical, optical and mechanical degrees of freedom without compromising the exceptional material properties of SiN membranes, and can be a useful platform for studying cavity optoelectromechanics.

Does electricity (and heat) network regulation have anything to learn from fixed line telecoms regulation?

International Nuclear Information System (INIS)

Pollitt, Michael

2010-01-01

The purpose of this paper is to examine the lessons from the recent history of telecoms deregulation for electricity (and by implication heat) network regulation. We do this in the context of Ofgem's RPI-X rate at 20 review of energy regulation in the UK, which considers whether RPI-X-based price regulation is fit for purpose after over 20 years of operation in energy networks. We examine the deregulation of fixed line telecoms in the UK and the lessons which it seems to suggest. We then apply the lessons to electricity networks in the context of a possible increase in distributed generation directly connected to local distribution networks. We conclude that there is the possibility of more parallels over time and suggest several implications of this for the regulation of electricity and heat networks. (author)

Prediction of Industrial Electric Energy Consumption in Anhui Province Based on GA-BP Neural Network

Science.gov (United States)

Zhang, Jiajing; Yin, Guodong; Ni, Youcong; Chen, Jinlan

2018-01-01

In order to improve the prediction accuracy of industrial electrical energy consumption, a prediction model of industrial electrical energy consumption was proposed based on genetic algorithm and neural network. The model use genetic algorithm to optimize the weights and thresholds of BP neural network, and the model is used to predict the energy consumption of industrial power in Anhui Province, to improve the prediction accuracy of industrial electric energy consumption in Anhui province. By comparing experiment of GA-BP prediction model and BP neural network model, the GA-BP model is more accurate with smaller number of neurons in the hidden layer.

Simulation-based optimization parametric optimization techniques and reinforcement learning

CERN Document Server

Gosavi, Abhijit

2003-01-01

Simulation-Based Optimization: Parametric Optimization Techniques and Reinforcement Learning introduces the evolving area of simulation-based optimization. The book's objective is two-fold: (1) It examines the mathematical governing principles of simulation-based optimization, thereby providing the reader with the ability to model relevant real-life problems using these techniques. (2) It outlines the computational technology underlying these methods. Taken together these two aspects demonstrate that the mathematical and computational methods discussed in this book do work. Broadly speaking, the book has two parts: (1) parametric (static) optimization and (2) control (dynamic) optimization. Some of the book's special features are: *An accessible introduction to reinforcement learning and parametric-optimization techniques. *A step-by-step description of several algorithms of simulation-based optimization. *A clear and simple introduction to the methodology of neural networks. *A gentle introduction to converg...

Electric network interconnection of Mashreq Arab Countries

International Nuclear Information System (INIS)

El-Amin, I.M.; Al-Shehri, A.M.; Opoku, G.; Al-Baiyat, S.A.; Zedan, F.M.

1994-01-01

Power system interconnection is a well established practice for a variety of technical and economical reasons. Several interconnected networks exist worldwide for a number of factors. Some of these networks cross international boundaries. This presentation discusses the future developments of the power systems of Mashreq Arab Countries (MAC). MAC consists of Bahrain, Egypt, Iraq, Jordan, Kuwait, Lebanon, Oman, Qatar, Saudi Arabia, United Arab Emirates (UAE), and Yemen. Mac power systems are operated by government or semigovernment bodies. Many of these countries have national or regional electric grids but are generally isolated from each other. With the exception of Saudi Arabia power systems, which employ 60 Hz, all other MAC utilities use 50 Hz frequency. Each country is served by one utility, except Saudi Arabia, which is served by four major utilities and some smaller utilities serving remote towns and small load centers. The major utilities are the Saudi Consolidated electric Company in the Eastern Province (SCECO East), SCECO Center, SCECO West, and SCECO South. These are the ones considered in this study. The energy resources in MAC are varied. Countries such as Egypt, Iraq, and Syria have significant hydro resources.The gulf countries and Iraq have abundant fossil fuel, The variation in energy resources as well as the characteristics of the electric load make it essential to look into interconnections beyond the national boundaries. Most of the existing or planned interconnections involve few power systems. A study involving 12 countries and over 20 utilities with different characteristics represents a very large scale undertaking

Forecasting of electricity prices with neural networks

Energy Technology Data Exchange (ETDEWEB)

Gareta, Raquel [Centro de Investigacion de Recursos y Consumos Energeticos (CIRCE), Universidad de Zaragoza, Centro Politecnico Superior, Maria de Luna, 3, 50018 Zaragoza (Spain); Romeo, Luis M. [Centro de Investigacion de Recursos y Consumos Energeticos (CIRCE), Universidad de Zaragoza, Centro Politecnico Superior, Maria de Luna, 3, 50018 Zaragoza (Spain)]. E-mail: luismi@unizar.es; Gil, Antonia [Centro de Investigacion de Recursos y Consumos Energeticos (CIRCE), Universidad de Zaragoza, Centro Politecnico Superior, Maria de Luna, 3, 50018 Zaragoza (Spain)

2006-08-15

During recent years, the electricity energy market deregulation has led to a new free competition situation in Europe and other countries worldwide. Generators, distributors and qualified clients have some uncertainties about the future evolution of electricity markets. In consequence, feasibility studies of new generation plants, design of new systems and energy management optimization are frequently postponed. The ability of forecasting energy prices, for instance the electricity prices, would be highly appreciated in order to improve the profitability of utility investments. The development of new simulation techniques, such as Artificial Intelligence (AI), has provided a good tool to forecast time series. In this paper, it is demonstrated that the Neural Network (NN) approach can be used to forecast short term hourly electricity pool prices (for the next day and two or three days after). The NN architecture and design for prices forecasting are described in this paper. The results are tested with extensive data sets, and good agreement is found between actual data and NN results. This methodology could help to improve power plant generation capacity management and, certainly, more profitable operation in daily energy pools.

Forecasting of electricity prices with neural networks

International Nuclear Information System (INIS)

Gareta, Raquel; Romeo, Luis M.; Gil, Antonia

2006-01-01

During recent years, the electricity energy market deregulation has led to a new free competition situation in Europe and other countries worldwide. Generators, distributors and qualified clients have some uncertainties about the future evolution of electricity markets. In consequence, feasibility studies of new generation plants, design of new systems and energy management optimization are frequently postponed. The ability of forecasting energy prices, for instance the electricity prices, would be highly appreciated in order to improve the profitability of utility investments. The development of new simulation techniques, such as Artificial Intelligence (AI), has provided a good tool to forecast time series. In this paper, it is demonstrated that the Neural Network (NN) approach can be used to forecast short term hourly electricity pool prices (for the next day and two or three days after). The NN architecture and design for prices forecasting are described in this paper. The results are tested with extensive data sets, and good agreement is found between actual data and NN results. This methodology could help to improve power plant generation capacity management and, certainly, more profitable operation in daily energy pools

Increasing penetration of renewable and distributed electricity generation and the need for different network regulation

International Nuclear Information System (INIS)

Joode, J. de; Jansen, J.C.; Welle, A.J. van der; Scheepers, M.J.J.

2009-01-01

The amount of decentralised electricity generation (DG) connected to distribution networks increases across EU member states. This increasing penetration of DG units poses potential costs and benefits for distribution system operators (DSOs). These DSOs are regulated since the business of electricity distribution is considered to be a natural monopoly. This paper identifies the impact of increasing DG penetration on the DSO business under varying parameters (network characteristics, DG technologies, network management type) and argues that current distribution network regulation needs to be improved in order for DSOs to continue to facilitate the integration of DG in the network. Several possible adaptations are analysed.

Diagnosis and Reconfiguration using Bayesian Networks: An Electrical Power System Case Study

Science.gov (United States)

Knox, W. Bradley; Mengshoel, Ole

2009-01-01

Automated diagnosis and reconfiguration are important computational techniques that aim to minimize human intervention in autonomous systems. In this paper, we develop novel techniques and models in the context of diagnosis and reconfiguration reasoning using causal Bayesian networks (BNs). We take as starting point a successful diagnostic approach, using a static BN developed for a real-world electrical power system. We discuss in this paper the extension of this diagnostic approach along two dimensions, namely: (i) from a static BN to a dynamic BN; and (ii) from a diagnostic task to a reconfiguration task. More specifically, we discuss the auto-generation of a dynamic Bayesian network from a static Bayesian network. In addition, we discuss subtle, but important, differences between Bayesian networks when used for diagnosis versus reconfiguration. We discuss a novel reconfiguration agent, which models a system causally, including effects of actions through time, using a dynamic Bayesian network. Though the techniques we discuss are general, we demonstrate them in the context of electrical power systems (EPSs) for aircraft and spacecraft. EPSs are vital subsystems on-board aircraft and spacecraft, and many incidents and accidents of these vehicles have been attributed to EPS failures. We discuss a case study that provides initial but promising results for our approach in the setting of electrical power systems.

Markets in real electric networks require reactive prices

International Nuclear Information System (INIS)

Hogan, W.W.

1996-01-01

Extending earlier seminal work, the author finds that locational spot price differences in an electric network provide the natural measure of the appropriate internodal transport charge. However, the problem of loop flow requires different economic intuition for interpreting the implications of spot pricing. The Direct Current model, which is the usual approximation for estimating spot prices, ignores reactive power effects; this approximation is best when thermal constraints create network congestion. However, when voltage constraints are problematic, the DC Load model is insufficient; a full AC Model is required to determine both real and reactive spot prices. 16 figs., 3 tabs., 22 refs

The deregulation of network industries: is the electricity sector an exception?

International Nuclear Information System (INIS)

Coppens, F.; Vivet, D.

2006-01-01

In view of their special characteristics, network industries have for quite a long time been considered as (natural) monopolies. Network externalities and economies of scale in particular justified this (natural) monopoly thesis. Since the last decade of the past century, however, a trend towards deregulation of such industries has been observed worldwide. This trend started with the successful introduction of competition in the telecommunications sector. The success in that sector is often used as an argument for opening up other network industries to competition as well. The study analyses whether this reasoning can be applied to the electricity sector. At first glance, the sectors electricity and telecommunications seem very similar, as both are network industries having been characterised for a long time by economies of scale, but for which technological progress may have put an end to this scale effect. However, the study points out that there are important differences. In the telecommunications sector, technological progress on the supply side has been accompanied by a strong growth in demand. There is no such demand side effect in the electricity branch. Moreover, due to physical characteristics, the electricity sector seems to be more complicated. In order to introduce competition, the sector has to be split up into sub-sectors (production, transmission, distribution and supply). Only two segments, production and supply, are considered as open markets; transmission and distribution, on the other hand, remain monopolies. This splitting up, however, entails a new kind of costs, the so-called transaction costs. As such the gains from the liberalization in certain segments might (partly) offset increase in the transaction costs resulting from vertical disintegration. (authors)

Network reconfiguration for loss reduction in electrical distribution system using genetic algorithm

International Nuclear Information System (INIS)

Adail, A.S.A.A.

2012-01-01

Distribution system is a critical links between the utility and the nuclear installation. During feeding electricity to that installation there are power losses. The quality of the network depends on the reduction of these losses. Distribution system which feeds the nuclear installation must have a higher quality power. For example, in Inshas site, electrical power is supplied to it from two incoming feeders (one from new abu-zabal substation and the other from old abu-zabal substation). Each feeder is designed to carry the full load, while the operator preferred to connect with a new abu-zabal substation, which has a good power quality. Bad power quality affects directly the nuclear reactor and has a negative impact on the installed sensitive equipment's of the operation. The thesis is Studying the electrical losses in a distribution system (causes and effected factors), feeder reconfiguration methods, and applying of genetic algorithm in an electric distribution power system. In the end, this study proposes an optimization technique based on genetic algorithms for distribution network reconfiguration to reduce the network losses to minimum. The proposed method is applied to IEEE test network; that contain 3 feeders and 16 nodes. The technique is applied through two groups, distribution have general loads, and nuclear loads. In the groups the technique applied to seven cases at normal operation state, system fault condition as well as different loads conditions. Simulated results are drawn to show the accuracy of the technique.

Modeling generator power plant portfolios and pollution taxes in electric power supply chain networks: a transportation network equilibrium transformation

International Nuclear Information System (INIS)

Kai Wu; Nagurney, A.; University of Massachusetts, Amherst, MA; Zugang Liu; Stranlund, J.K.

2006-01-01

Global climate change and fuel security risks have encouraged international and regional adoption of pollution/carbon taxes. A major portion of such policy interventions is directed at the electric power industry with taxes applied according to the type of fuel used by the power generators in their power plants. This paper proposes an electric power supply chain network model that captures the behavior of power generators faced with a portfolio of power plant options and subject to pollution taxes. We demonstrate that this general model can be reformulated as a transportation network equilibrium model with elastic demands and qualitatively analyzed and solved as such. The connections between these two different modeling schemas is done through finite-dimensional variational inequality theory. The numerical examples illustrate how changes in the pollution/carbon taxes affect the equilibrium electric power supply chain network production outputs, the transactions between the various decision-makers the demand market prices, as well as the total amount of carbon emissions generated. (author)

Electric power plants and networks. Elektrische Kraftwerke

Energy Technology Data Exchange (ETDEWEB)

Happoldt, H [Brown, Boveri und Cie A.G., Mannheim (Germany, F.R.). Abt. Centralen; Oeding, D [Brown, Boveri und Cie A.G., Mannheim (Germany, F.R.). Zentralbereich Forschung und Entwicklung

1978-01-01

This book is itended for enginers working in the planning, construction and operation of plants to generate and distribute electric power; it is also a valuable aid for students of power engineering. This new edition places more emphasis on the presentation and calculation of three-phase current networks with the aid of symmetric components. The equations used for calculation are adapted to VDE regulations as far as possible.

The parametric modified limited penetrable visibility graph for constructing complex networks from time series

Science.gov (United States)

Li, Xiuming; Sun, Mei; Gao, Cuixia; Han, Dun; Wang, Minggang

2018-02-01

This paper presents the parametric modified limited penetrable visibility graph (PMLPVG) algorithm for constructing complex networks from time series. We modify the penetrable visibility criterion of limited penetrable visibility graph (LPVG) in order to improve the rationality of the original penetrable visibility and preserve the dynamic characteristics of the time series. The addition of view angle provides a new approach to characterize the dynamic structure of the time series that is invisible in the previous algorithm. The reliability of the PMLPVG algorithm is verified by applying it to three types of artificial data as well as the actual data of natural gas prices in different regions. The empirical results indicate that PMLPVG algorithm can distinguish the different time series from each other. Meanwhile, the analysis results of natural gas prices data using PMLPVG are consistent with the detrended fluctuation analysis (DFA). The results imply that the PMLPVG algorithm may be a reasonable and significant tool for identifying various time series in different fields.

Thermal and Arc Flash Analysis of Electric Motor Drives in Distribution Networks

OpenAIRE

Nikolovski, Srete; Mlakić, Dragan; Alibašić, Emir

2017-01-01

The paper presents thermal analysis and arc flash analysis taking care of protection relays coordination settings for electric motor drives connected to the electrical network. Power flow analysis is performed to check if there are any voltage and loading violation conditions in the system. Fault analysis is performed to check the short circuit values and compute arc flash energy dissipated at industrial busbars to eliminate damage to electrical equipment and electrical shocks and hazard to p...

Parametric packet-based audiovisual quality model for IPTV services

CERN Document Server

Garcia, Marie-Neige

2014-01-01

This volume presents a parametric packet-based audiovisual quality model for Internet Protocol TeleVision (IPTV) services. The model is composed of three quality modules for the respective audio, video and audiovisual components. The audio and video quality modules take as input a parametric description of the audiovisual processing path, and deliver an estimate of the audio and video quality. These outputs are sent to the audiovisual quality module which provides an estimate of the audiovisual quality. Estimates of perceived quality are typically used both in the network planning phase and as part of the quality monitoring. The same audio quality model is used for both these phases, while two variants of the video quality model have been developed for addressing the two application scenarios. The addressed packetization scheme is MPEG2 Transport Stream over Real-time Transport Protocol over Internet Protocol. In the case of quality monitoring, that is the case for which the network is already set-up, the aud...

A Novel Parametric Model For The Human Respiratory System

Directory of Open Access Journals (Sweden)

Clara Mihaela IONESCU

2003-12-01

Full Text Available The purpose of this work is to present some recent results in an ongoing research project between Ghent University and Chess Medical Technology Company Belgium. The overall aim of the project is to provide a fast method for identification of the human respiratory system in order to allow for an instantaneously diagnosis of the patient by the medical staff. A novel parametric model of the human respiratory system as well as the obtained experimental results is presented in this paper. A prototype apparatus developed by the company, based on the forced oscillation technique is used to record experimental data from 4 patients in this paper. Signal processing is based on spectral analysis and is followed by the parametric identification of a non-linear mechanistic model. The parametric model is equivalent to the structure of a simple electrical RLC-circuit, containing a non-linear capacitor. These parameters have a useful and easy-to-interpret physical meaning for the medical staff members.

Life cycle assessment of the Danish electricity distribution network

DEFF Research Database (Denmark)

Turconi, Roberto; Simonsen, Christian G.; Byriel, Inger P.

2014-01-01

Purpose This article provides life cycle inventory data for electricity distribution networks and a life cycle assessment (LCA) of the Danish transmission and distribution networks. The aim of the study was to evaluate the potential importance of environmental impacts associated with distribution...... complexity and material consumption. Infrastructure provided important contributions to metal depletion and freshwater eutrophication (copper and aluminum for manufacturing of the cables and associated recycling being the most important). Underground 50-kV lines had larger impacts than overhead lines, and 0...

Flow network QSAR for the prediction of physicochemical properties by mapping an electrical resistance network onto a chemical reaction poset.

Science.gov (United States)

Ivanciuc, Ovidiu; Ivanciuc, Teodora; Klein, Douglas J

2013-06-01

Usual quantitative structure-activity relationship (QSAR) models are computed from unstructured input data, by using a vector of molecular descriptors for each chemical in the dataset. Another alternative is to consider the structural relationships between the chemical structures, such as molecular similarity, presence of certain substructures, or chemical transformations between compounds. We defined a class of network-QSAR models based on molecular networks induced by a sequence of substitution reactions on a chemical structure that generates a partially ordered set (or poset) oriented graph that may be used to predict various molecular properties with quantitative superstructure-activity relationships (QSSAR). The network-QSAR interpolation models defined on poset graphs, namely average poset, cluster expansion, and spline poset, were tested with success for the prediction of several physicochemical properties for diverse chemicals. We introduce the flow network QSAR, a new poset regression model in which the dataset of chemicals, represented as a reaction poset, is transformed into an oriented network of electrical resistances in which the current flow results in a potential at each node. The molecular property considered in the QSSAR model is represented as the electrical potential, and the value of this potential at a particular node is determined by the electrical resistances assigned to each edge and by a system of batteries. Each node with a known value for the molecular property is attached to a battery that sets the potential on that node to the value of the respective molecular property, and no external battery is attached to nodes from the prediction set, representing chemicals for which the values of the molecular property are not known or are intended to be predicted. The flow network QSAR algorithm determines the values of the molecular property for the prediction set of molecules by applying Ohm's law and Kirchhoff's current law to the poset

Decompositions of injection patterns for nodal flow allocation in renewable electricity networks

Science.gov (United States)

Schäfer, Mirko; Tranberg, Bo; Hempel, Sabrina; Schramm, Stefan; Greiner, Martin

2017-08-01

The large-scale integration of fluctuating renewable power generation represents a challenge to the technical and economical design of a sustainable future electricity system. In this context, the increasing significance of long-range power transmission calls for innovative methods to understand the emerging complex flow patterns and to integrate price signals about the respective infrastructure needs into the energy market design. We introduce a decomposition method of injection patterns. Contrary to standard flow tracing approaches, it provides nodal allocations of link flows and costs in electricity networks by decomposing the network injection pattern into market-inspired elementary import/export building blocks. We apply the new approach to a simplified data-driven model of a European electricity grid with a high share of renewable wind and solar power generation.

Using adaptive network based fuzzy inference system to forecast regional electricity loads

International Nuclear Information System (INIS)

Ying, L.-C.; Pan, M.-C.

2008-01-01

Since accurate regional load forecasting is very important for improvement of the management performance of the electric industry, various regional load forecasting methods have been developed. The purpose of this study is to apply the adaptive network based fuzzy inference system (ANFIS) model to forecast the regional electricity loads in Taiwan and demonstrate the forecasting performance of this model. Based on the mean absolute percentage errors and statistical results, we can see that the ANFIS model has better forecasting performance than the regression model, artificial neural network (ANN) model, support vector machines with genetic algorithms (SVMG) model, recurrent support vector machines with genetic algorithms (RSVMG) model and hybrid ellipsoidal fuzzy systems for time series forecasting (HEFST) model. Thus, the ANFIS model is a promising alternative for forecasting regional electricity loads

Using adaptive network based fuzzy inference system to forecast regional electricity loads

Energy Technology Data Exchange (ETDEWEB)

Ying, Li-Chih [Department of Marketing Management, Central Taiwan University of Science and Technology, 11, Pu-tzu Lane, Peitun, Taichung City 406 (China); Pan, Mei-Chiu [Graduate Institute of Management Sciences, Nanhua University, 32, Chung Keng Li, Dalin, Chiayi 622 (China)

2008-02-15

Since accurate regional load forecasting is very important for improvement of the management performance of the electric industry, various regional load forecasting methods have been developed. The purpose of this study is to apply the adaptive network based fuzzy inference system (ANFIS) model to forecast the regional electricity loads in Taiwan and demonstrate the forecasting performance of this model. Based on the mean absolute percentage errors and statistical results, we can see that the ANFIS model has better forecasting performance than the regression model, artificial neural network (ANN) model, support vector machines with genetic algorithms (SVMG) model, recurrent support vector machines with genetic algorithms (RSVMG) model and hybrid ellipsoidal fuzzy systems for time series forecasting (HEFST) model. Thus, the ANFIS model is a promising alternative for forecasting regional electricity loads. (author)

Online fouling detection in electrical circulation heaters using neural networks

Energy Technology Data Exchange (ETDEWEB)

Lalot, S. [M.E.T.I.E.R., Longuenesse Cedex (France); Universite de Valenciennes (France). LME; Lecoeuche, S. [M.E.T.I.E.R., Longuenesse Cedex (France); Universite de Lille (France). Laboratoire 13D

2003-06-01

Here is presented a method that is able to detect fouling during the service of a circulation electrical heater. The neural based technique is divided in two major steps: identification and classification. Each step uses a neural network, the connection weights of the first one being the inputs of the second network. Each step is detailed and the main characteristics and abilities of the two neural networks are given. It is shown that the method is able to discriminate fouling from viscosity modification that would lead to the same type of effect on the total heat transfer coefficient. (author)

Parametric systems analysis for ICF hybrid reactors

International Nuclear Information System (INIS)

Berwald, D.H.; Maniscalco, J.A.; Chapin, D.L.

1981-01-01

Parametric design and systems analysis for inertial confinement fusion-fission hybrids are presented. These results were generated as part of the Electric Power Research Institute (EPRI) sponsored Feasibility Assessment of Fusion-Fission Hybrids, using an Inertial Confinement Fusion (ICF) hybrid power plant design code developed in conjunction with the feasibility assessment. The SYMECON systems analysis code, developed by Westinghouse, was used to generate economic results for symbiotic electricity generation systems consisting of the hybrid and its client Light Water Reactors (LWRs). These results explore the entire fusion parameter space for uranium fast fission blanket hybrids, thorium fast fission blanket hybrids, and thorium suppressed fission blanket types are discussed, and system sensitivities to design uncertainties are explored

The study of human bodies' impedance networks in testing leakage currents of electrical equipments

Science.gov (United States)

Zhang, Zhaohui; Wang, Xiaofei

2006-11-01

In the testing of electrical equipments' leakage currents, impedance networks of human bodies are used to simulate the current's effect on human bodies, and they are key to the preciseness of the testing result. This paper analyses and calculates three human bodies' impedance networks of measuring electric burn current, perception or reaction current, let-go current in IEC60990, by using Matlab, compares the research result of current effect thresholds' change with sine wave's frequency published in IEC479-2, and amends parameters of measuring networks. It also analyses the change of perception or reaction current with waveform by Multisim.

Design and analysis of electrical energy storage demonstration projects on UK distribution networks

International Nuclear Information System (INIS)

Lyons, P.F.; Wade, N.S.; Jiang, T.; Taylor, P.C.; Hashiesh, F.; Michel, M.; Miller, D.

2015-01-01

Highlights: • Results of an EES system demonstration project carried out in the UK. • Approaches to the design of trials for EES and observation on their application. • A formalised methodology for analysis of smart grids trials. • Validated models of energy storage. • Capability of EES to connect larger quantities of heat pumps and PV is evaluated. - Abstract: The UK government’s CO 2 emissions targets will require electrification of much of the country’s infrastructure with low carbon technologies such as photovoltaic panels, electric vehicles and heat pumps. The large scale proliferation of these technologies will necessitate major changes to the planning and operation of distribution networks. Distribution network operators are trialling electrical energy storage (EES) across their networks to increase their understanding of the contribution that it can make to enable the expected paradigm shift in generation and consumption of electricity. In order to evaluate a range of applications for EES, including voltage control and power flow management, installations have taken place at various distribution network locations and voltage levels. This article reports on trial design approaches and their application to a UK trial of an EES system to ensure broad applicability of the results. Results from these trials of an EES system, low carbon technologies and trial distribution networks are used to develop validated power system models. These models are used to evaluate, using a formalised methodology, the impact that EES could have on the design and operation of future distribution networks

Infrastructure for Integration of Legacy Electrical Equipment into a Smart-Grid Using Wireless Sensor Networks.

Science.gov (United States)

de Araújo, Paulo Régis C; Filho, Raimir Holanda; Rodrigues, Joel J P C; Oliveira, João P C M; Braga, Stephanie A

2018-04-24

At present, the standardisation of electrical equipment communications is on the rise. In particular, manufacturers are releasing equipment for the smart grid endowed with communication protocols such as DNP3, IEC 61850, and MODBUS. However, there are legacy equipment operating in the electricity distribution network that cannot communicate using any of these protocols. Thus, we propose an infrastructure to allow the integration of legacy electrical equipment to smart grids by using wireless sensor networks (WSNs). In this infrastructure, each legacy electrical device is connected to a sensor node, and the sink node runs a middleware that enables the integration of this device into a smart grid based on suitable communication protocols. This middleware performs tasks such as the translation of messages between the power substation control centre (PSCC) and electrical equipment in the smart grid. Moreover, the infrastructure satisfies certain requirements for communication between the electrical equipment and the PSCC, such as enhanced security, short response time, and automatic configuration. The paper’s contributions include a solution that enables electrical companies to integrate their legacy equipment into smart-grid networks relying on any of the above mentioned communication protocols. This integration will reduce the costs related to the modernisation of power substations.

Infrastructure for Integration of Legacy Electrical Equipment into a Smart-Grid Using Wireless Sensor Networks

Directory of Open Access Journals (Sweden)

Paulo Régis C. de Araújo

2018-04-01

Full Text Available At present, the standardisation of electrical equipment communications is on the rise. In particular, manufacturers are releasing equipment for the smart grid endowed with communication protocols such as DNP3, IEC 61850, and MODBUS. However, there are legacy equipment operating in the electricity distribution network that cannot communicate using any of these protocols. Thus, we propose an infrastructure to allow the integration of legacy electrical equipment to smart grids by using wireless sensor networks (WSNs. In this infrastructure, each legacy electrical device is connected to a sensor node, and the sink node runs a middleware that enables the integration of this device into a smart grid based on suitable communication protocols. This middleware performs tasks such as the translation of messages between the power substation control centre (PSCC and electrical equipment in the smart grid. Moreover, the infrastructure satisfies certain requirements for communication between the electrical equipment and the PSCC, such as enhanced security, short response time, and automatic configuration. The paper’s contributions include a solution that enables electrical companies to integrate their legacy equipment into smart-grid networks relying on any of the above mentioned communication protocols. This integration will reduce the costs related to the modernisation of power substations.

Comparison between linear and non-parametric regression models for genome-enabled prediction in wheat.

Science.gov (United States)

Pérez-Rodríguez, Paulino; Gianola, Daniel; González-Camacho, Juan Manuel; Crossa, José; Manès, Yann; Dreisigacker, Susanne

2012-12-01

In genome-enabled prediction, parametric, semi-parametric, and non-parametric regression models have been used. This study assessed the predictive ability of linear and non-linear models using dense molecular markers. The linear models were linear on marker effects and included the Bayesian LASSO, Bayesian ridge regression, Bayes A, and Bayes B. The non-linear models (this refers to non-linearity on markers) were reproducing kernel Hilbert space (RKHS) regression, Bayesian regularized neural networks (BRNN), and radial basis function neural networks (RBFNN). These statistical models were compared using 306 elite wheat lines from CIMMYT genotyped with 1717 diversity array technology (DArT) markers and two traits, days to heading (DTH) and grain yield (GY), measured in each of 12 environments. It was found that the three non-linear models had better overall prediction accuracy than the linear regression specification. Results showed a consistent superiority of RKHS and RBFNN over the Bayesian LASSO, Bayesian ridge regression, Bayes A, and Bayes B models.

Using neural networks and extreme value distributions to model electricity pool prices: Evidence from the Australian National Electricity Market 1998–2013

International Nuclear Information System (INIS)

Dev, Priya; Martin, Michael A.

2014-01-01

Highlights: • Neural nets are unable to properly capture spiky price behavior found in the electricity market. • We modeled electricity price data from the Australian National Electricity Market over 15 years. • Neural nets need to be augmented with other modeling techniques to capture price spikes. • We fit a Generalized Pareto Distribution to price spikes using a peaks-over-thresholds approach. - Abstract: Competitors in the electricity supply industry desire accurate predictions of electricity spot prices to hedge against financial risks. Neural networks are commonly used for forecasting such prices, but certain features of spot price series, such as extreme price spikes, present critical challenges for such modeling. We investigate the predictive capacity of neural networks for electricity spot prices using Australian National Electricity Market data. Following neural net modeling of the data, we explore extreme price spikes through extreme value modeling, fitting a Generalized Pareto Distribution to price peaks over an estimated threshold. While neural nets capture the smoother aspects of spot price data, they are unable to capture local, volatile features that characterize electricity spot price data. Price spikes can be modeled successfully through extreme value modeling

Network cost in transmission and distribution of electric power

International Nuclear Information System (INIS)

Lindahl, A.; Naeslund, B.; Oettinger-Biberg, C.; Olander, H.; Wuolikainen, T.; Fritz, P.

1994-01-01

This report is divided in two parts, where part 1 treats the charges on the regional nets with special emphasis on the net owners tariffs on a deregulated market. Part 2 describes the development of the network costs in electric power distribution for the period 1991-1993. 11 figs, 33 tabs

A probabilistic approach to combining smart meter and electric vehicle charging data to investigate distribution network impacts

International Nuclear Information System (INIS)

Neaimeh, Myriam; Wardle, Robin; Jenkins, Andrew M.; Yi, Jialiang; Hill, Graeme; Lyons, Padraig F.; Hübner, Yvonne; Blythe, Phil T.; Taylor, Phil C.

2015-01-01

Highlights: • Working with unique datasets of EV charging and smart meter load demand. • Distribution networks are not a homogenous group with more capabilities to accommodate EVs than previously suggested. • Spatial and temporal diversity of EV charging demand alleviate the impacts on networks. • An extensive recharging infrastructure could enable connection of additional EVs on constrained distribution networks. • Electric utilities could increase the network capability to accommodate EVs by investing in recharging infrastructure. - Abstract: This work uses a probabilistic method to combine two unique datasets of real world electric vehicle charging profiles and residential smart meter load demand. The data was used to study the impact of the uptake of Electric Vehicles (EVs) on electricity distribution networks. Two real networks representing an urban and rural area, and a generic network representative of a heavily loaded UK distribution network were used. The findings show that distribution networks are not a homogeneous group with a variation of capabilities to accommodate EVs and there is a greater capability than previous studies have suggested. Consideration of the spatial and temporal diversity of EV charging demand has been demonstrated to reduce the estimated impacts on the distribution networks. It is suggested that distribution network operators could collaborate with new market players, such as charging infrastructure operators, to support the roll out of an extensive charging infrastructure in a way that makes the network more robust; create more opportunities for demand side management; and reduce planning uncertainties associated with the stochastic nature of EV charging demand.

The electrical network of maize root apex is gravity dependent.

Science.gov (United States)

Masi, Elisa; Ciszak, Marzena; Comparini, Diego; Monetti, Emanuela; Pandolfi, Camilla; Azzarello, Elisa; Mugnai, Sergio; Baluška, Frantisek; Mancuso, Stefano

2015-01-15

Investigations carried out on maize roots under microgravity and hypergravity revealed that gravity conditions have strong effects on the network of plant electrical activity. Both the duration of action potentials (APs) and their propagation velocities were significantly affected by gravity. Similarly to what was reported for animals, increased gravity forces speed-up APs and enhance synchronized electrical events also in plants. The root apex transition zone emerges as the most active, as well as the most sensitive, root region in this respect.

Parametric study of laser photovoltaic energy converters

Science.gov (United States)

Walker, G. H.; Heinbockel, J. H.

1987-01-01

Photovoltaic converters are of interest for converting laser power to electrical power in a space-based laser power system. This paper describes a model for photovoltaic laser converters and the application of this model to a neodymium laser silicon photovoltaic converter system. A parametric study which defines the sensitivity of the photovoltaic parameters is described. An optimized silicon photovoltaic converter has an efficiency greater than 50 percent for 1000 W/sq cm of neodymium laser radiation.

Machine learning-based dual-energy CT parametric mapping.

Science.gov (United States)

Su, Kuan-Hao; Kuo, Jung-Wen; Jordan, David W; Van Hedent, Steven; Klahr, Paul; Wei, Zhouping; Al Helo, Rose; Liang, Fan; Qian, Pengjiang; Pereira, Gisele C; Rassouli, Negin; Gilkeson, Robert C; Traughber, Bryan J; Cheng, Chee-Wai; Muzic, Raymond F

2018-05-22

The aim is to develop and evaluate machine learning methods for generating quantitative parametric maps of effective atomic number (Z_eff), relative electron density (ρ_e), mean excitation energy (I_x), and relative stopping power (RSP) from clinical dual-energy CT data. The maps could be used for material identification and radiation dose calculation. Machine learning methods of historical centroid (HC), random forest (RF), and artificial neural networks (ANN) were used to learn the relationship between dual-energy CT input data and ideal output parametric maps calculated for phantoms from the known compositions of 13 tissue substitutes. After training and model selection steps, the machine learning predictors were used to generate parametric maps from independent phantom and patient input data. Precision and accuracy were evaluated using the ideal maps. This process was repeated for a range of exposure doses, and performance was compared to that of the clinically-used dual-energy, physics-based method which served as the reference. The machine learning methods generated more accurate and precise parametric maps than those obtained using the reference method. Their performance advantage was particularly evident when using data from the lowest exposure, one-fifth of a typical clinical abdomen CT acquisition. The RF method achieved the greatest accuracy. In comparison, the ANN method was only 1% less accurate but had much better computational efficiency than RF, being able to produce parametric maps in 15 seconds. Machine learning methods outperformed the reference method in terms of accuracy and noise tolerance when generating parametric maps, encouraging further exploration of the techniques. Among the methods we evaluated, ANN is the most suitable for clinical use due to its combination of accuracy, excellent low-noise performance, and computational efficiency. . © 2018 Institute of Physics and Engineering in

Parametric structural modeling of insect wings

International Nuclear Information System (INIS)

Mengesha, T E; Vallance, R R; Barraja, M; Mittal, R

2009-01-01

Insects produce thrust and lift forces via coupled fluid-structure interactions that bend and twist their compliant wings during flapping cycles. Insight into this fluid-structure interaction is achieved with numerical modeling techniques such as coupled finite element analysis and computational fluid dynamics, but these methods require accurate and validated structural models of insect wings. Structural models of insect wings depend principally on the shape, dimensions and material properties of the veins and membrane cells. This paper describes a method for parametric modeling of wing geometry using digital images and demonstrates the use of the geometric models in constructing three-dimensional finite element (FE) models and simple reduced-order models. The FE models are more complete and accurate than previously reported models since they accurately represent the topology of the vein network, as well as the shape and dimensions of the veins and membrane cells. The methods are demonstrated by developing a parametric structural model of a cicada forewing.

Neural electrical activity and neural network growth.

Science.gov (United States)

Gafarov, F M

2018-05-01

The development of central and peripheral neural system depends in part on the emergence of the correct functional connectivity in its input and output pathways. Now it is generally accepted that molecular factors guide neurons to establish a primary scaffold that undergoes activity-dependent refinement for building a fully functional circuit. However, a number of experimental results obtained recently shows that the neuronal electrical activity plays an important role in the establishing of initial interneuronal connections. Nevertheless, these processes are rather difficult to study experimentally, due to the absence of theoretical description and quantitative parameters for estimation of the neuronal activity influence on growth in neural networks. In this work we propose a general framework for a theoretical description of the activity-dependent neural network growth. The theoretical description incorporates a closed-loop growth model in which the neural activity can affect neurite outgrowth, which in turn can affect neural activity. We carried out the detailed quantitative analysis of spatiotemporal activity patterns and studied the relationship between individual cells and the network as a whole to explore the relationship between developing connectivity and activity patterns. The model, developed in this work will allow us to develop new experimental techniques for studying and quantifying the influence of the neuronal activity on growth processes in neural networks and may lead to a novel techniques for constructing large-scale neural networks by self-organization. Copyright © 2018 Elsevier Ltd. All rights reserved.

RTE - Electricity transport network operator. Energy is our future: let's save it

International Nuclear Information System (INIS)

2014-01-01

Managing and developing the French electricity transport network is essential to provide quality electricity on a continuous basis to all consumers. Since it was founded in 2000, and since it was made into a public service company (2005), RTE has proven its ability to fulfil its public interest mission in complete security. In an open European electricity market, RTE is recognised for offering all of its customers fair access to its network, which is the first condition for healthy competition. Based on this and thanks to its investments and operating quality, RTE is constantly improving its performances to meet its customers', public authorities' and the Energy Regulation Committee's requirements. This public service action is focused on four strategic priorities: performance of industrial facilities; a human and managerial policy focused on skills and efficiency; sustainable development; professionalism and innovation. This brochure presents RTE's missions, company overview and European cooperation

Molecular dynamics in high electric fields

International Nuclear Information System (INIS)

Apostol, M.; Cune, L.C.

2016-01-01

Highlights: • New method for rotation molecular spectra in high electric fields. • Parametric resonances – new features in spectra. • New elementary excitations in polar solids from dipolar interaction (“dipolons”). • Discussion about a possible origin of the ferroelectricity from dipolar interactions. - Abstract: Molecular rotation spectra, generated by the coupling of the molecular electric-dipole moments to an external time-dependent electric field, are discussed in a few particular conditions which can be of some experimental interest. First, the spherical-pendulum molecular model is reviewed, with the aim of introducing an approximate method which consists in the separation of the azimuthal and zenithal motions. Second, rotation spectra are considered in the presence of a static electric field. Two particular cases are analyzed, corresponding to strong and weak fields. In both cases the classical motion of the dipoles consists of rotations and vibrations about equilibrium positions; this motion may exhibit parametric resonances. For strong fields a large macroscopic electric polarization may appear. This situation may be relevant for polar matter (like pyroelectrics, ferroelectrics), or for heavy impurities embedded in a polar solid. The dipolar interaction is analyzed in polar condensed matter, where it is shown that new polarization modes appear for a spontaneous macroscopic electric polarization (these modes are tentatively called “dipolons”); one of the polarization modes is related to parametric resonances. The extension of these considerations to magnetic dipoles is briefly discussed. The treatment is extended to strong electric fields which oscillate with a high frequency, as those provided by high-power lasers. It is shown that the effect of such fields on molecular dynamics is governed by a much weaker, effective, renormalized, static electric field.

Determinants of investment under incentive regulation: The case of the Norwegian electricity distribution networks

International Nuclear Information System (INIS)

Poudineh, Rahmatallah; Jamasb, Tooraj

2016-01-01

Investment in electricity networks, as regulated natural monopolies, is among the highest regulatory and energy policy priorities. The electricity sector regulators adopt different incentive mechanisms to ensure that the firms undertake sufficient investment to maintain and modernise the grid. Thus, an effective regulatory treatment of investment requires understanding the response of companies to the regulatory incentives. This study analyses the determinants of investment in electricity distribution networks using a panel dataset of 129 Norwegian companies observed from 2004 to 2010. A Bayesian Model Averaging approach is used to provide a robust statistical inference by taking into account the uncertainties around model selection and estimation. The results show that three factors drive nearly all network investments: investment rate in previous period, socio-economic costs of energy not supplied and finally useful life of assets. The results indicate that Norwegian companies have, to some degree, responded to the investment incentives provided by the regulatory framework. However, some of the incentives do not appear to be effective in driving the investments. - Highlights: • This paper investigates determinants of investment under incentive regulation. • We apply a Bayesian model averaging technique to deal with model uncertainty. • Dataset comprises 129 Norwegian electricity network companies from 2004 to 2010. • The results show that firms have generally responded to investment incentives. • However, some of the incentives do not appear to have been effective.

Modelling electric trains energy consumption using Neural Networks

Energy Technology Data Exchange (ETDEWEB)

Martinez Fernandez, P.; Garcia Roman, C.; Insa Franco, R.

2016-07-01

Nowadays there is an evident concern regarding the efficiency and sustainability of the transport sector due to both the threat of climate change and the current financial crisis. This concern explains the growth of railways over the last years as they present an inherent efficiency compared to other transport means. However, in order to further expand their role, it is necessary to optimise their energy consumption so as to increase their competitiveness. Improving railways energy efficiency requires both reliable data and modelling tools that will allow the study of different variables and alternatives. With this need in mind, this paper presents the development of consumption models based on neural networks that calculate the energy consumption of electric trains. These networks have been trained based on an extensive set of consumption data measured in line 1 of the Valencia Metro Network. Once trained, the neural networks provide a reliable estimation of the vehicles consumption along a specific route when fed with input data such as train speed, acceleration or track longitudinal slope. These networks represent a useful modelling tool that may allow a deeper study of railway lines in terms of energy expenditure with the objective of reducing the costs and environmental impact associated to railways. (Author)

Smart PV grid to reinforce the electrical network

Science.gov (United States)

AL-Hamad, Mohamed Y.; Qamber, Isa S.

2017-11-01

Photovoltaic (PV) became the new competitive energy resources of the planet and needs to be engaged in grid to break up the congestion in both Distribution and Transmission systems. The objective of this research is to reduce the load flow through the distribution and transmission equipment by 20%. This reduction will help in relief networks loaded equipment's in all networks. Many projects are starting to develop in the GCC countries and need to be organized to achieve maximum benefits from involving the Renewable Energy Sources (RES) in the network. The GCC countries have a good location for solar energy with high intensity of the solar radiation and clear sky along the year. The opportunities of the solar energy is to utilize and create a sustainable energy resource for this region. Moreover, the target of this research is to engage the PV technology in such a way to lower the over loaded equipment and increases the electricity demand at the consumer's side.

An efficient approach for electric load forecasting using distributed ART (adaptive resonance theory) and HS-ARTMAP (Hyper-spherical ARTMAP network) neural network

International Nuclear Information System (INIS)

Cai, Yuan; Wang, Jian-zhou; Tang, Yun; Yang, Yu-chen

2011-01-01

This paper presents a neural network based on adaptive resonance theory, named distributed ART (adaptive resonance theory) and HS-ARTMAP (Hyper-spherical ARTMAP network), applied to the electric load forecasting problem. The distributed ART combines the stable fast learning capabilities of winner-take-all ART systems with the noise tolerance and code compression capabilities of multi-layer perceptions. The HS-ARTMAP, a hybrid of an RBF (Radial Basis Function)-network-like module which uses hyper-sphere basis function substitute the Gaussian basis function and an ART-like module, performs incremental learning capabilities in function approximation problem. The HS-ARTMAP only receives the compressed distributed coding processed by distributed ART to deal with the proliferation problem which ARTMAP (adaptive resonance theory map) architecture often encounters and still performs well in electric load forecasting. To demonstrate the performance of the methodology, data from New South Wales and Victoria in Australia are illustrated. Results show that the developed method is much better than the traditional BP and single HS-ARTMAP neural network. -- Research highlights: → The processing of the presented network is based on compressed distributed data. It's an innovation among the adaptive resonance theory architecture. → The presented network decreases the proliferation the Fuzzy ARTMAP architectures usually encounter. → The network on-line forecasts electrical load accurately, stably. → Both one-period and multi-period load forecasting are executed using data of different cities.

Hybrid Electric Vehicle Experimental Model with CAN Network Real Time Control

Directory of Open Access Journals (Sweden)

RATOI, M.

2010-05-01

Full Text Available In this paper an experimental model with a distributed control system of a hybrid electrical vehicle is presented. A communication CAN network of high speed (1 Mbps assures a distributed control of the all components. The modeling and the control of different operating regimes are realized on an experimental test-bench of a hybrid electrical vehicle. The experimental results concerning the variations of the mains variables (currents, torques, speeds are presented.

Analysis of the electrical disturbances in CERN power distribution network with pattern mining methods

CERN Document Server

Abramenko, Oleksii

2017-01-01

The current research focuses on the perturbations within the electrical network of the LHC and its subsystems by analyzing measurements collected from oscilloscopes installed across different CERN sites, and alarms by electrical equipments. We analyze amplitude and duration of the glitches and, together with other relevant variables, correlate them with beam stopping events. The work also tries to identify assets affected by such perturbations using data mining and, in particular, frequent pattern mining methods. On the practical side we summarize results of our work by putting forward a prototype of a software tool enabling online monitoring of the alarms coming from the electrical network and facilitating glitch detection and analysis by a technical operator.

Business opportunities and dynamic competition through distributed generation in primary electricity distribution networks

International Nuclear Information System (INIS)

Raineri, R.; Rios, S.; Vasquez, R.

2005-01-01

In this paper, for a real electricity distribution network, an assessment of business opportunities to invest in distributed generation (DG) is performed through a simulation based on a full representation of three medium voltage (12 kV) feeders. The three feeders representation includes 1062 sections of conductors with 13 different sizes. The economic assessment focuses on both, the incentives of the incumbent distribution company and those of a new entrant. The technical and economic impact on losses, reliability and voltage regulation in the network area are verified. The DG solution analyzed determines a business opportunity for new investors where end users are also benefited. This work calls in the debate on the need to reformulate the current regulation model on electricity distribution, by defining clear rules to incorporate DG to the existing network, and to enable any agent to develop the proposed business. DG success depends on the location of adequate sites to strategically establish few DG units being a substitute to network expansion

An empirical examination of restructured electricity prices

International Nuclear Information System (INIS)

Knittel, C.R.; Roberts, M.R.

2005-01-01

We present an empirical analysis of restructured electricity prices. We study the distributional and temporal properties of the price process in a non-parametric framework, after which we parametrically model the price process using several common asset price specifications from the asset-pricing literature, as well as several less conventional models motivated by the peculiarities of electricity prices. The findings reveal several characteristics unique to electricity prices including several deterministic components of the price series at different frequencies. An 'inverse leverage effect' is also found, where positive shocks to the price series result in larger increases in volatility than negative shocks. We find that forecasting performance in dramatically improved when we incorporate features of electricity prices not commonly modelled in other asset prices. Our findings have implications for how empiricists model electricity prices, as well as how theorists specify models of energy pricing. (author)

CIRCUIT-DESIGN SOLUTIONS AND INFORMATION SUPPORT OF CITY ELECTRIC NETWORKS IN THE CONDITIONS OF THE SMART GRID

Directory of Open Access Journals (Sweden)

M. I. Fursanov

2017-01-01

Full Text Available The structure, circuit-design solutions and information support of the city electric networks in the conditions of the SMART GRID have been analyzed. It is demonstrated that the new conditions of functioning of electric power engineering, increasing demands for its technological state and reliability in most countries determined the transition to a restructuring of electrical networks to be based on the SMART GRID (intelligent power networks innovative new structure. The definitions of the SMART GRID, its various attributes and characteristics in most developed countries including Belarus are presented. It is revealed that the existing and future circuit and constructive solutions that can automate the process of managing modes of urban electric networks under the SMART GRID conditions are manifold. At present, the most common in distribution networks are the sources of distributed generation (combustion turbines, wind turbines, photovoltaic installations, mini-hydro, etc.. The patterns and problems of information traceability of a traditional urban networks of the unified energy system of Belarus have been analyzed, and it is demonstrated that in the conditions of the SMART GRID most of the problems of the control mode that are characteristic for traditional distribution networks 6–10 kV and 0.38 kV, lose their relevance. Therefore, the present article presents and features the main directions of development of automatic control modes of the SMART GRID.

Electricity network limitations on large-scale deployment of wind energy

Energy Technology Data Exchange (ETDEWEB)

Fairbairn, R.J.

1999-07-01

This report sought to identify limitation on large scale deployment of wind energy in the UK. A description of the existing electricity supply system in England, Scotland and Wales is given, and operational aspects of the integrated electricity networks, licence conditions, types of wind turbine generators, and the scope for deployment of wind energy in the UK are addressed. A review of technical limitations and technical criteria stipulated by the Distribution and Grid Codes, the effects of system losses, and commercial issues are examined. Potential solutions to technical limitations are proposed, and recommendations are outlined.

Index-aware model order reduction : LTI DAEs in electric networks

NARCIS (Netherlands)

Banagaaya, N.; Schilders, W.H.A.; Ali, G.; Tischendorf, C.

2014-01-01

Purpose Model order reduction (MOR) has been widely used in the electric networks but little has been done to reduce higher index differential algebraic equations (DAEs). The paper aims to discuss these issues. Design/methodology/approach Most methods first do an index reduction before reducing a

Bosch automotive electrics and automotive electronics. Systems and components, networking and hybrid drive. 5. ed.

Energy Technology Data Exchange (ETDEWEB)

NONE

2014-07-01

Complete reference guide to automotive electrics and electronics. The significance of electrical and electronic systems has increased considerably in the last few years and this trend is set to continue. The characteristics feature of innovative systems is the fact that they can work together in a network. This requires powerful bus systems that the electronic control units can use to exchange information. Networking and the various bus systems used in motor vehicles are the prominent new topic in the 5th edition of the ''Automotive Electric, Automotive Electronics'' technical manual. The existing chapters have also been updated, so that this new edition brings the reader up to date on the subjects of electrical and electronic systems in the motor vehicle.

Evaluating the electricity intensity of evolving water supply mixes: the case of California’s water network

Science.gov (United States)

Stokes-Draut, Jennifer; Taptich, Michael; Kavvada, Olga; Horvath, Arpad

2017-11-01

Climate change is making water supply less predictable, even unreliable, in parts of the world. Urban water providers, especially in already arid areas, will need to diversify their water resources by switching to alternative sources and negotiating trading agreements to create more resilient and interdependent networks. The increasing complexity of these networks will likely require more operational electricity. The ability to document, visualize, and analyze water-energy relationships will be critical to future water planning, especially as data needed to conduct the analyses become increasingly available. We have developed a network model and decision-support tool, WESTNet, to perform these tasks. Herein, WESTNet was used to analyze a model of California’s 2010 urban water network as well as the projected system for 2020 and 2030. Results for California’s ten hydrologic regions show that the average number of water sources per utility and total electricity consumption for supplying water will increase in spite of decreasing per-capita water consumption. Electricity intensity (kWh m-3) will increase in arid regions of the state due to shifts to alternative water sources such as indirect potable water reuse, desalination, and water transfers. In wetter, typically less populated, regions, reduced water demand for electricity-intensive supplies will decrease the electricity intensity of the water supply mix, though total electricity consumption will increase due to urban population growth. The results of this study provide a baseline for comparing current and potential innovations to California’s water system. The WESTNet tool can be applied to diverse water systems in any geographic region at a variety of scales to evaluate an array of network-dependent water-energy parameters.

The Use of Artificial Neural Networks for Forecasting the Electric Demand of Stand-Alone Consumers

Science.gov (United States)

Ivanin, O. A.; Direktor, L. B.

2018-05-01

The problem of short-term forecasting of electric power demand of stand-alone consumers (small inhabited localities) situated outside centralized power supply areas is considered. The basic approaches to modeling the electric power demand depending on the forecasting time frame and the problems set, as well as the specific features of such modeling, are described. The advantages and disadvantages of the methods used for the short-term forecast of the electric demand are indicated, and difficulties involved in the solution of the problem are outlined. The basic principles of arranging artificial neural networks are set forth; it is also shown that the proposed method is preferable when the input information necessary for prediction is lacking or incomplete. The selection of the parameters that should be included into the list of the input data for modeling the electric power demand of residential areas using artificial neural networks is validated. The structure of a neural network is proposed for solving the problem of modeling the electric power demand of residential areas. The specific features of generation of the training dataset are outlined. The results of test modeling of daily electric demand curves for some settlements of Kamchatka and Yakutia based on known actual electric demand curves are provided. The reliability of the test modeling has been validated. A high value of the deviation of the modeled curve from the reference curve obtained in one of the four reference calculations is explained. The input data and the predicted power demand curves for the rural settlement of Kuokuiskii Nasleg are provided. The power demand curves were modeled for four characteristic days of the year, and they can be used in the future for designing a power supply system for the settlement. To enhance the accuracy of the method, a series of measures based on specific features of a neural network's functioning are proposed.

Dynamics of global supply chain and electric power networks: Models, pricing analysis, and computations

Science.gov (United States)

Matsypura, Dmytro

In this dissertation, I develop a new theoretical framework for the modeling, pricing analysis, and computation of solutions to electric power supply chains with power generators, suppliers, transmission service providers, and the inclusion of consumer demands. In particular, I advocate the application of finite-dimensional variational inequality theory, projected dynamical systems theory, game theory, network theory, and other tools that have been recently proposed for the modeling and analysis of supply chain networks (cf. Nagurney (2006)) to electric power markets. This dissertation contributes to the extant literature on the modeling, analysis, and solution of supply chain networks, including global supply chains, in general, and electric power supply chains, in particular, in the following ways. It develops a theoretical framework for modeling, pricing analysis, and computation of electric power flows/transactions in electric power systems using the rationale for supply chain analysis. The models developed include both static and dynamic ones. The dissertation also adds a new dimension to the methodology of the theory of projected dynamical systems by proving that, irrespective of the speeds of adjustment, the equilibrium of the system remains the same. Finally, I include alternative fuel suppliers, along with their behavior into the supply chain modeling and analysis framework. This dissertation has strong practical implications. In an era in which technology and globalization, coupled with increasing risk and uncertainty, complicate electricity demand and supply within and between nations, the successful management of electric power systems and pricing become increasingly pressing topics with relevance not only for economic prosperity but also national security. This dissertation addresses such related topics by providing models, pricing tools, and algorithms for decentralized electric power supply chains. This dissertation is based heavily on the following

The need to strengthen the electricity market with a better network

International Nuclear Information System (INIS)

Morch, Stein

2002-01-01

Price regions in the Nordic electricity market has been common. The competition authorities, the electricity exchange and the other actors indicate the need for increased capacity of the network. A larger concentration of big, competing producers in the Nordic countries is not desirable. The current competition among bidders is satisfactory at a common price level. Under conditions of price regions it is essential that there is competition in the area, which has not always been the case

Absolute parametric instability of low-frequency waves in a 2D ...

Indian Academy of Sciences (India)

solved in two-dimensional (2D) nonuniform plane plasma. Equations which describe the spatial part of the electric potential are obtained. Also, the growth rates and conditions of the parametric instability for periodic and aperiodic cases are obtained. It is found that the spatial nonuniformity of the plasma exerts a stabilizing ...

Compressive stress-electrical conductivity characteristics of multiwall carbon nanotube networks

Czech Academy of Sciences Publication Activity Database

Slobodian, P.; Říha, Pavel; Lengálová, A.; Sáha, P.

2011-01-01

Roč. 46, č. 9 (2011), s. 3186-3190 ISSN 0022-2461 R&D Projects: GA AV ČR IAA200600803 Institutional research plan: CEZ:AV0Z20600510 Keywords : carbon nanotube network * compression * electrical conductivity * stress sensor Subject RIV: BK - Fluid Dynamics Impact factor: 2.015, year: 2011

Micro-grid platform based on NODE.JS architecture, implemented in electrical network instrumentation

Science.gov (United States)

Duque, M.; Cando, E.; Aguinaga, A.; Llulluna, F.; Jara, N.; Moreno, T.

2016-05-01

In this document, I propose a theory about the impact of systems based on microgrids in non-industrialized countries that have the goal to improve energy exploitation through alternatives methods of a clean and renewable energy generation and the creation of the app to manage the behavior of the micro-grids based on the NodeJS, Django and IOJS technologies. The micro-grids allow the optimal way to manage energy flow by electric injection directly in electric network small urban's cells in a low cost and available way. In difference from conventional systems, micro-grids can communicate between them to carry energy to places that have higher demand in accurate moments. This system does not require energy storage, so, costs are lower than conventional systems like fuel cells, solar panels or else; even though micro-grids are independent systems, they are not isolated. The impact that this analysis will generate, is the improvement of the electrical network without having greater control than an intelligent network (SMART-GRID); this leads to move to a 20% increase in energy use in a specified network; that suggest there are others sources of energy generation; but for today's needs, we need to standardize methods and remain in place to support all future technologies and the best option are the Smart Grids and Micro-Grids.

Parametric performance analysis of a concentrated photovoltaic co-generation system equipped with a thermal storage tank

International Nuclear Information System (INIS)

Imtiaz Hussain, M.; Lee, Gwi Hyun

2015-01-01

Highlights: • Both thermal and electrical powers varied by changing surface area of collector. • Thermal stratification and total system power were increased at critical flow rate. • Parametric analysis of the CPVC system offers to determine the desired outcome. • Thermal and electrical outputs varied by changing the focal length of Fresnel lens. - Abstract: This article presents a parametric study of a concentrated photovoltaic co-generation (CPVC) system with an attached thermal storage tank. The CPVC system utilized dual-axis tracker and multiple solar energy collector (SEC) modules and forced cooling system. Each SEC module comprised 16 triple-junction solar cells, copper tube absorbers, and 16 Fresnel lenses were aligned against each solar cell. This study investigated all possible parameters that can affect the CPVC system performance, including the collector area, solar irradiation, inlet temperature, and mass flow rate. The surface area of the collector and the thermal power were increased by increasing the number of SEC modules connected in series; however, the electrical power output decreased from the first to the fourth SEC module consecutively. At the measured optimal flow rate, mixing and thermal diffusion in the storage tank were decreased, and the total power generation from the CPVC system was increased. Variations in the thermal and electrical power outputs were also observed when the focal length of the Fresnel lens was changed. This parametric analysis enables the CPVC system to obtain the desired output by varying the combination of operational and geometrical parameters

Impact of Social Network and Business Model on Innovation Diffusion of Electric Vehicles in China

Directory of Open Access Journals (Sweden)

D. Y. Kong

2014-01-01

Full Text Available The diffusion of electric vehicles (EVs involves not only the technological development but also the construction of complex social networks. This paper uses the theory of network control to analyze the influence of network forms on EV diffusion in China, especially focusing on the building of EV business models (BMs and the resulting effects and control on the diffusion of EVs. The Bass model is adopted to forecast the diffusion process of EVs and genetic algorithm is used to estimate the parameters based on the diffusion data of Hybrid Electric Vehicle (HEV in the United States and Japan. Two different social network forms and BMs are selected, that is, battery leasing model and vehicle purchasing model, to analyze how different network forms may influence the innovation coefficient and imitation coefficient in the Bass model, which will in turn result in different diffusion results. Thereby, we can find the appropriate network forms and BMs for EVs which is suitable to the local market conditions.

Optical parametric amplification of arbitrarily polarized light in periodically poled LiNbO3.

Science.gov (United States)

Shao, Guang-hao; Song, Xiao-shi; Xu, Fei; Lu, Yan-qing

2012-08-13

Optical parametric amplification (OPA) of arbitrarily polarized light is proposed in a multi-section periodically poled Lithium Niobate (PPLN). External electric field is applied on selected sections to induce the polarization rotation of involved lights, thus the quasi-phase matched optical parametric processes exhibit polarization insensitivity under suitable voltage. In addition to the amplified signal wave, an idler wave with the same polarization is generated simultaneously. As an example, a ~10 times OPA showing polarization independency is simulated. Applications of this technology are also discussed.

Economic modeling and parametric studies for SOMBRERO - a laser-driven IFE power plant

International Nuclear Information System (INIS)

Meier, W.R.; Rosenberg, C.W. Jr. von

1992-01-01

Economic modeling and parametric studies for the SOMBRERO laser-driven inertial fusion energy (IFE) electric power plant have been conducted to determine the most attractive operating point. Cost scaling relationships have been developed and integrated into a cost-performance model of the plant. The figure-of-merit for determining the most attractive design point is the constant-dollar cost of electricity. Results are presented as a function of the driver energy. The sensitivity of the results to variations in the assumed net electric output and target performance is also examined

Economic modeling and parametric studies for OSIRIS - a HIB-driven IFE power plant

International Nuclear Information System (INIS)

Meier, W.R.; Bieri, R.L.

1992-01-01

Economic modeling and parametric studies for the Osiris HIB-driven inertial fusion energy (IFE) electric power plant have been conducted to determine the most attractive operating point. Cost scaling relationships have been developed and integrated into a cost-performance model of the plant. The figure-of-merit for determining the most attractive design point is the constant-dollar cost of electricity. Results are presented as a function of the driver energy. The sensitivity of the results to variations in the assumed net electric output and target performance is also examined

Electric-car simulation

Science.gov (United States)

Chapman, C. P.; Slusser, R. A.

1980-01-01

PARAMET, interactive simulation program for parametric studies of electric vehicles, guides user through simulation by menu and series of prompts for input parameters. Program considers aerodynamic drag, rolling resistance, linear and rotational acceleration, and road gradient as forces acting on vehicle.

Electricity price forecasting using Enhanced Probability Neural Network

International Nuclear Information System (INIS)

Lin, Whei-Min; Gow, Hong-Jey; Tsai, Ming-Tang

2010-01-01

This paper proposes a price forecasting system for electric market participants to reduce the risk of price volatility. Combining the Probability Neural Network (PNN) and Orthogonal Experimental Design (OED), an Enhanced Probability Neural Network (EPNN) is proposed in the solving process. In this paper, the Locational Marginal Price (LMP), system load and temperature of PJM system were collected and the data clusters were embedded in the Excel Database according to the year, season, workday, and weekend. With the OED to smooth parameters in the EPNN, the forecasting error can be improved during the training process to promote the accuracy and reliability where even the ''spikes'' can be tracked closely. Simulation results show the effectiveness of the proposed EPNN to provide quality information in a price volatile environment. (author)

Short-term facilitation may stabilize parametric working memory trace

Directory of Open Access Journals (Sweden)

Vladimir eItskov

2011-10-01

Full Text Available Networks with continuous set of attractors are considered to be a paradigmatic model for parametric working memory, but require fine-tuning of connections and are thus structurally unstable. Here we analyzed the network with ring attractor, where connections are not perfectly tuned and the activity state therefore drifts in the absence of the stabilizing stimulus. We derive an analytical expression for the drift dynamics and conclude that the network cannot function as working memory for a period of several seconds, a typical delay time in monkey memory experiments. We propose that short-term synaptic facilitation in recurrent connections significantly improves the robustness of the model by slowing down the drift of activity bump. Extending the calculation of the drift velocity to network with synaptic facilitation, we conclude that facilitation can slow down the drift by a large factor, rendering the network suitable as a model of working memory.

Non-Linear State Estimation Using Pre-Trained Neural Networks

DEFF Research Database (Denmark)

Bayramoglu, Enis; Andersen, Nils Axel; Ravn, Ole

2010-01-01

effecting the transformation. This function is approximated by a neural network using offline training. The training is based on monte carlo sampling. A way to obtain parametric distributions of flexible shape to be used easily with these networks is also presented. The method can also be used to improve...... other parametric methods around regions with strong non-linearities by including them inside the network....

Modeling and simulating the adaptive electrical properties of stochastic polymeric 3D networks

International Nuclear Information System (INIS)

Sigala, R; Smerieri, A; Camorani, P; Schüz, A; Erokhin, V

2013-01-01

Memristors are passive two-terminal circuit elements that combine resistance and memory. Although in theory memristors are a very promising approach to fabricate hardware with adaptive properties, there are only very few implementations able to show their basic properties. We recently developed stochastic polymeric matrices with a functionality that evidences the formation of self-assembled three-dimensional (3D) networks of memristors. We demonstrated that those networks show the typical hysteretic behavior observed in the ‘one input-one output’ memristive configuration. Interestingly, using different protocols to electrically stimulate the networks, we also observed that their adaptive properties are similar to those present in the nervous system. Here, we model and simulate the electrical properties of these self-assembled polymeric networks of memristors, the topology of which is defined stochastically. First, we show that the model recreates the hysteretic behavior observed in the real experiments. Second, we demonstrate that the networks modeled indeed have a 3D instead of a planar functionality. Finally, we show that the adaptive properties of the networks depend on their connectivity pattern. Our model was able to replicate fundamental qualitative behavior of the real organic 3D memristor networks; yet, through the simulations, we also explored other interesting properties, such as the relation between connectivity patterns and adaptive properties. Our model and simulations represent an interesting tool to understand the very complex behavior of self-assembled memristor networks, which can finally help to predict and formulate hypotheses for future experiments. (paper)

Future vision of advanced telecommunication networks for electric utilities; Denki jigyo ni okeru joho tsushin network no shorai vision

Energy Technology Data Exchange (ETDEWEB)

Tonaru, S.; Ono, K.; Sakai, S.; Kawai, Y.; Tsuboi, A. [Central Research Institute of Electric Power Industry, Tokyo (Japan); Manabe, S. [Shikoku Electric Power Co., Inc., Kagawa (Japan); Miki, Y. [Kansai Electric Power Co. Inc., Osaka (Japan)

1995-06-01

The vision of an advanced information system is proposed to cope with the future social demand and business environmental change in electric utilities. At the large turning point such as drastic reconsideration of Electricity Utilities Industry Law, further improvement of efficiency and cost reduction are requested as well as business innovation such as proposal of a new business policy. For that purpose utilization of information and its technology is indispensable, and use of multimedia and common information in organization are the future direction for improving information basis. Consequently, free information networks without any limitation due to person and media are necessary, and the following are important: high-speed, high-frequency band, digital, easily connectable and multimedia transmission lines, and cost reduction and high reliability of networks. Based on innovation of information networks and the clear principle on advanced information system, development of new applications by multimedia technologies, diffusion of communication terminals, and promotion of standardization are essential. 60 refs., 30 figs., 5 tabs.

Modelling renewable energy resource and the electricity network (East Midlands region)

Energy Technology Data Exchange (ETDEWEB)

Newton, P.A.; Ma, T.

2002-07-01

The UK Government's targets for renewable generation and combined heat and power (CHP) are expected to result in a significant growth in embedded generation. This report describes the results of a study of the capability of the electricity distribution network in the East Midlands to accept embedded generation. Detailed network studies were performed for two sample networks: one representing an urban network (Leicester) and one representing a rural network (Boston). The 132 kV networks of the grid groups covering these areas were also studied. This included an examination of the connection points from major 132 kV busbars at grid supply points down to 11 kV primary substations. Power system studies were performed to identify the constraints and capabilities of the existing network, These studies included load flow to examine voltage profile and overloading, fault level analysis and transient studies to examine generator and network stability following faults on the network and voltage step change due to generator tripping. Space network capacity for the region was identified and used to assess the ability to accommodate regional targets for renewables and CHP. The study also examined constraining factors and potential solutions, including four improvement scenarios.

An artificial neural network architecture for non-parametric visual odometry in wireless capsule endoscopy

Science.gov (United States)

Dimas, George; Iakovidis, Dimitris K.; Karargyris, Alexandros; Ciuti, Gastone; Koulaouzidis, Anastasios

2017-09-01

Wireless capsule endoscopy is a non-invasive screening procedure of the gastrointestinal (GI) tract performed with an ingestible capsule endoscope (CE) of the size of a large vitamin pill. Such endoscopes are equipped with a usually low-frame-rate color camera which enables the visualization of the GI lumen and the detection of pathologies. The localization of the commercially available CEs is performed in the 3D abdominal space using radio-frequency (RF) triangulation from external sensor arrays, in combination with transit time estimation. State-of-the-art approaches, such as magnetic localization, which have been experimentally proved more accurate than the RF approach, are still at an early stage. Recently, we have demonstrated that CE localization is feasible using solely visual cues and geometric models. However, such approaches depend on camera parameters, many of which are unknown. In this paper the authors propose a novel non-parametric visual odometry (VO) approach to CE localization based on a feed-forward neural network architecture. The effectiveness of this approach in comparison to state-of-the-art geometric VO approaches is validated using a robotic-assisted in vitro experimental setup.

An artificial neural network architecture for non-parametric visual odometry in wireless capsule endoscopy

International Nuclear Information System (INIS)

Dimas, George; Iakovidis, Dimitris K; Karargyris, Alexandros; Ciuti, Gastone; Koulaouzidis, Anastasios

2017-01-01

Wireless capsule endoscopy is a non-invasive screening procedure of the gastrointestinal (GI) tract performed with an ingestible capsule endoscope (CE) of the size of a large vitamin pill. Such endoscopes are equipped with a usually low-frame-rate color camera which enables the visualization of the GI lumen and the detection of pathologies. The localization of the commercially available CEs is performed in the 3D abdominal space using radio-frequency (RF) triangulation from external sensor arrays, in combination with transit time estimation. State-of-the-art approaches, such as magnetic localization, which have been experimentally proved more accurate than the RF approach, are still at an early stage. Recently, we have demonstrated that CE localization is feasible using solely visual cues and geometric models. However, such approaches depend on camera parameters, many of which are unknown. In this paper the authors propose a novel non-parametric visual odometry (VO) approach to CE localization based on a feed-forward neural network architecture. The effectiveness of this approach in comparison to state-of-the-art geometric VO approaches is validated using a robotic-assisted in vitro experimental setup. (paper)

Impact of Electric Vehicle Charging Station Load on Distribution Network

Directory of Open Access Journals (Sweden)

Sanchari Deb

2018-01-01

Full Text Available Recent concerns about environmental pollution and escalating energy consumption accompanied by the advancements in battery technology have initiated the electrification of the transportation sector. With the universal resurgence of Electric Vehicles (EVs the adverse impact of the EV charging loads on the operating parameters of the power system has been noticed. The detrimental impact of EV charging station loads on the electricity distribution network cannot be neglected. The high charging loads of the fast charging stations results in increased peak load demand, reduced reserve margins, voltage instability, and reliability problems. Further, the penalty paid by the utility for the degrading performance of the power system cannot be neglected. This work aims to investigate the impact of the EV charging station loads on the voltage stability, power losses, reliability indices, as well as economic losses of the distribution network. The entire analysis is performed on the IEEE 33 bus test system representing a standard radial distribution network for six different cases of EV charging station placement. It is observed that the system can withstand placement of fast charging stations at the strong buses up to a certain level, but the placement of fast charging stations at the weak buses of the system hampers the smooth operation of the power system. Further, a strategy for the placement of the EV charging stations on the distribution network is proposed based on a novel Voltage stability, Reliability, and Power loss (VRP index. The results obtained indicate the efficacy of the VRP index.

An Optimal Domestic Electric Vehicle Charging Strategy for Reducing Network Transmission Loss While Taking Seasonal Factors into Consideration

Directory of Open Access Journals (Sweden)

Yuancheng Zhao

2018-01-01

Full Text Available With the rapid growth of domestic electric vehicle charging loads, the peak-valley gap and power fluctuation rate of power systems increase sharply, which can lead to the increase of network losses and energy efficiency reduction. This paper tries to regulate network loads and reduce power system transmission loss by optimizing domestic electric vehicle charging loads. In this paper, a domestic electric vehicle charging loads model is first developed by analyzing the key factors that can affect users’ charging behavior. Subsequently, the Monte Carlo method is proposed to simulate the power consumption of a cluster of domestic electric vehicles. After that, an optimal electric vehicle charging strategy based on the 0-1 integer programming is presented to regulate network daily loads. Finally, by taking the IEEE33 distributed power system as an example, this paper tries to verify the efficacy of the proposed optimal charging strategy and the necessity for considering seasonal factors when scheduling electric vehicle charging loads. Simulation results show that the proposed 0-1 integer programming method does have good performance in reducing the network peak-valley gap, voltage fluctuation rate, and transmission loss. Moreover, it has some potential to further reduce power system transmission loss when seasonal factors are considered.

Spare part management of an electricity distribution network

Energy Technology Data Exchange (ETDEWEB)

Lauronen, J.

1998-07-01

Electricity distribution companies are required to improve their operational cost effectiveness. The storage systems of the companies have traditionally been based on the 'adequate' number of stores with plenty of different components. Therefore, they are potential objects for cost reduction. The effective operation of spare part management of an electricity distribution network requires that the spare components can be delivered at the fault site quickly in order to avoid excessive outage costs. In a fault situation the stores form a net structure. Currently the rural electricity distribution companies lack suitable methods for designing a spare part storage system. This thesis presents a suitable method for the designing problem. The models assume that faults of a distribution network are stochastic. Therefore, they are best suited for component types installed in large quantities. Improved methods for defining the outage, material and total costs for perpetual order quantity and periodic order-up-to-level storage control systems are described. The method for determining the control parameters of the stores is also presented and ways for finding the necessary initial parameter values are introduced. The developed method is tested in Haemeen Saehko Oy (HSOY). The results of the calculations are given. The key findings are: Small differences in the designing results can increase costs remarkably. For example, in HSOY too low stock levels can result in even eight folds higher outage costs than in the proper design. The best number of stores is not the same for all component types. For example, in HSOY the best number of stores is seven for the 50 kVA transformers and one for the 315 kVA transformers in a summer. If the stock levels are increased the protection against the demand variations is the better the shorter the duration of the review period and/or the replenishment lead time is. (orig.)

Spare part management of an electricity distribution network

Energy Technology Data Exchange (ETDEWEB)

Lauronen, J

1998-07-01

Electricity distribution companies are required to improve their operational cost effectiveness. The storage systems of the companies have traditionally been based on the 'adequate' number of stores with plenty of different components. Therefore, they are potential objects for cost reduction. The effective operation of spare part management of an electricity distribution network requires that the spare components can be delivered at the fault site quickly in order to avoid excessive outage costs. In a fault situation the stores form a net structure. Currently the rural electricity distribution companies lack suitable methods for designing a spare part storage system. This thesis presents a suitable method for the designing problem. The models assume that faults of a distribution network are stochastic. Therefore, they are best suited for component types installed in large quantities. Improved methods for defining the outage, material and total costs for perpetual order quantity and periodic order-up-to-level storage control systems are described. The method for determining the control parameters of the stores is also presented and ways for finding the necessary initial parameter values are introduced. The developed method is tested in Haemeen Saehko Oy (HSOY). The results of the calculations are given. The key findings are: Small differences in the designing results can increase costs remarkably. For example, in HSOY too low stock levels can result in even eight folds higher outage costs than in the proper design. The best number of stores is not the same for all component types. For example, in HSOY the best number of stores is seven for the 50 kVA transformers and one for the 315 kVA transformers in a summer. If the stock levels are increased the protection against the demand variations is the better the shorter the duration of the review period and/or the replenishment lead time is. (orig.)

Monte Carlo simulations of electrical percolation in multicomponent thin films with nanofillers

Science.gov (United States)

Ni, Xiaojuan; Hui, Chao; Su, Ninghai; Jiang, Wei; Liu, Feng

2018-02-01

We developed a 2D disk-stick percolation model to investigate the electrical percolation behavior of an insulating thin film reinforced with 1D and 2D conductive nanofillers via Monte Carlo simulation. Numerical predictions of the percolation threshold in single component thin films showed good agreement with the previous published work, validating our model for investigating the characteristics of the percolation phenomena. Parametric studies of size effect, i.e., length of 1D nanofiller and diameter of 2D nanofiller, were carried out to predict the electrical percolation threshold for hybrid systems. The relationships between the nanofillers in two hybrid systems was established, which showed differences from previous linear assumption. The effective electrical conductance was evaluated through Kirchhoff’s current law by transforming it into a resistor network. The equivalent resistance was obtained from the distribution of nodal voltages by solving a system of linear equations with a Gaussian elimination method. We examined the effects of stick length, relative concentration, and contact patterns of 1D/2D inclusions on electrical performance. One novel aspect of our study is its ability to investigate the effective conductance of nanocomposites as a function of relative concentrations, which shows there is a synergistic effect when nanofillers with different dimensionalities combine properly. Our work provides an important theoretical basis for designing the conductive networks and predicting the percolation properties of multicomponent nanocomposites.

PSO-RBF Neural Network PID Control Algorithm of Electric Gas Pressure Regulator

Directory of Open Access Journals (Sweden)

Yuanchang Zhong

2014-01-01

Full Text Available The current electric gas pressure regulator often adopts the conventional PID control algorithm to take drive control of the core part (micromotor of electric gas pressure regulator. In order to further improve tracking performance and to shorten response time, this paper presents an improved PID intelligent control algorithm which applies to the electric gas pressure regulator. The algorithm uses the improved RBF neural network based on PSO algorithm to make online adjustment on PID parameters. Theoretical analysis and simulation result show that the algorithm shortens the step response time and improves tracking performance.

Planning of optimal electricity and gas distribution networks; Planung von optimalen Strom- und Gasverteilungsnetzen

Energy Technology Data Exchange (ETDEWEB)

Berg, Andreas; Hinueber, Gerd; Moser, Albert [RWTH Aachen (DE). Inst. fuer Elektrische Anlagen und Energiewirtschaft (IAEW)

2009-12-15

Framework conditions for the planning of energy networks are changing under the influence of European energy policy, incentive regulation and the politically motivated promotion of new technologies such as electromobility or intelligent metering. The future use of information and communication technologies in energy networks will create new degrees of freedom. This will necessitate changes in the way in which gas and electricity networks have been planned in the past. Especially computer-assisted methods for objectifying planning decisions are moving into the focus of network operators as a valuable network development tool.

Systems for protection and automation of distribution electric networks 22 kv

International Nuclear Information System (INIS)

Horak, M.

2012-01-01

This article deals with the new concept of fault location in overhead and cable 22 kV distribution systems, which are operated by ZSE Distribucia, a.s.. In the past the localisation of faults was a demanding and lengthy procedure, because the electric protection indicated only the affected output feeder. The exact fault point was then localised by manipulation in the field and by test switching in the power line where the fault took place. The current development of electric facilities and sharp fall in prices give use the possibility to broadly apply the simple digital metering devices equipped with the electric protection function. Once these devices are positioned densely along the individual power lines of the network, it is possible to localise the failure position quite exactly and electricity supply can be quickly restored. (Authors)

A multi-criteria decision aid methodology to design electric vehicles public charging networks

Directory of Open Access Journals (Sweden)

João Raposo

2015-05-01

Full Text Available This article presents a new multi-criteria decision aid methodology, dynamic-PROMETHEE, here used to design electric vehicle charging networks. In applying this methodology to a Portuguese city, results suggest that it is effective in designing electric vehicle charging networks, generating time and policy based scenarios, considering offer and demand and the city’s urban structure. Dynamic-PROMETHE adds to the already known PROMETHEE’s characteristics other useful features, such as decision memory over time, versatility and adaptability. The case study, used here to present the dynamic-PROMETHEE, served as inspiration and base to create this new methodology. It can be used to model different problems and scenarios that may present similar requirement characteristics.

A multi-criteria decision aid methodology to design electric vehicles public charging networks

Science.gov (United States)

Raposo, João; Rodrigues, Ana; Silva, Carlos; Dentinho, Tomaz

2015-05-01

This article presents a new multi-criteria decision aid methodology, dynamic-PROMETHEE, here used to design electric vehicle charging networks. In applying this methodology to a Portuguese city, results suggest that it is effective in designing electric vehicle charging networks, generating time and policy based scenarios, considering offer and demand and the city's urban structure. Dynamic-PROMETHE adds to the already known PROMETHEE's characteristics other useful features, such as decision memory over time, versatility and adaptability. The case study, used here to present the dynamic-PROMETHEE, served as inspiration and base to create this new methodology. It can be used to model different problems and scenarios that may present similar requirement characteristics.

Optimal Control for Bufferbloat Queue Management Using Indirect Method with Parametric Optimization

Directory of Open Access Journals (Sweden)

Amr Radwan

2016-01-01

Full Text Available Because memory buffers become larger and cheaper, they have been put into network devices to reduce the number of loss packets and improve network performance. However, the consequences of large buffers are long queues at network bottlenecks and throughput saturation, which has been recently noticed in research community as bufferbloat phenomenon. To address such issues, in this article, we design a forward-backward optimal control queue algorithm based on an indirect approach with parametric optimization. The cost function which we want to minimize represents a trade-off between queue length and packet loss rate performance. Through the integration of an indirect approach with parametric optimization, our proposal has advantages of scalability and accuracy compared to direct approaches, while still maintaining good throughput and shorter queue length than several existing queue management algorithms. All numerical analysis, simulation in ns-2, and experiment results are provided to solidify the efficiency of our proposal. In detailed comparisons to other conventional algorithms, the proposed procedure can run much faster than direct collocation methods while maintaining a desired short queue (≈40 packets in simulation and 80 (ms in experiment test.

Electricity price forecast using Combinatorial Neural Network trained by a new stochastic search method

International Nuclear Information System (INIS)

Abedinia, O.; Amjady, N.; Shafie-khah, M.; Catalão, J.P.S.

2015-01-01

Highlights: • Presenting a Combinatorial Neural Network. • Suggesting a new stochastic search method. • Adapting the suggested method as a training mechanism. • Proposing a new forecast strategy. • Testing the proposed strategy on real-world electricity markets. - Abstract: Electricity price forecast is key information for successful operation of electricity market participants. However, the time series of electricity price has nonlinear, non-stationary and volatile behaviour and so its forecast method should have high learning capability to extract the complex input/output mapping function of electricity price. In this paper, a Combinatorial Neural Network (CNN) based forecasting engine is proposed to predict the future values of price data. The CNN-based forecasting engine is equipped with a new training mechanism for optimizing the weights of the CNN. This training mechanism is based on an efficient stochastic search method, which is a modified version of chemical reaction optimization algorithm, giving high learning ability to the CNN. The proposed price forecast strategy is tested on the real-world electricity markets of Pennsylvania–New Jersey–Maryland (PJM) and mainland Spain and its obtained results are extensively compared with the results obtained from several other forecast methods. These comparisons illustrate effectiveness of the proposed strategy.

Developing Large-Scale Bayesian Networks by Composition: Fault Diagnosis of Electrical Power Systems in Aircraft and Spacecraft

Science.gov (United States)

Mengshoel, Ole Jakob; Poll, Scott; Kurtoglu, Tolga

2009-01-01

In this paper, we investigate the use of Bayesian networks to construct large-scale diagnostic systems. In particular, we consider the development of large-scale Bayesian networks by composition. This compositional approach reflects how (often redundant) subsystems are architected to form systems such as electrical power systems. We develop high-level specifications, Bayesian networks, clique trees, and arithmetic circuits representing 24 different electrical power systems. The largest among these 24 Bayesian networks contains over 1,000 random variables. Another BN represents the real-world electrical power system ADAPT, which is representative of electrical power systems deployed in aerospace vehicles. In addition to demonstrating the scalability of the compositional approach, we briefly report on experimental results from the diagnostic competition DXC, where the ProADAPT team, using techniques discussed here, obtained the highest scores in both Tier 1 (among 9 international competitors) and Tier 2 (among 6 international competitors) of the industrial track. While we consider diagnosis of power systems specifically, we believe this work is relevant to other system health management problems, in particular in dependable systems such as aircraft and spacecraft. (See CASI ID 20100021910 for supplemental data disk.)

Preparing tomorrow's network today: RTE at the crossroads of the European electricity system. Cross-border electricity interconnections Key issues and figures - 2014 Edition

International Nuclear Information System (INIS)

2014-10-01

The interconnected electricity transmission network is a key element for ensuring security of supply, the creation of a single market and the integration of renewable energies. RTE and its European partners provide strengthened coordination by the use of interconnections to ensure solidarity between European countries. Interconnections also allow an electricity supplier to sell its energy to a customer located in another country in Europe. They contribute on a European scale to optimising the use of production means and in particular the integration of variable renewable energies. RTE, within the EnTSo-E (European Network of Transmission System Operators for Electricity), contributes to the publication of a common vision of the future of networks by 2030. The needs for new interconnection capacity are identified in the ten-year European network development plan (TYnDP) on the basis of a cost-benefit analysis. France is interconnected to all its neighbours via many cross-border links. However interconnection capacity with the various countries and its use differ widely. The usage profile of the interconnections is specific to each border and varies according to: - the characteristics of the production mix of each country, and in particular the level of production of renewable energies. - the level of consumption, which depends on the season, the type of day (working or non-working) the time of day, etc. - import and export capacity, which may be different depending on the internal constraints of the networks of each country

CFD Parametric Studies for Global Performance Improvement of Open Refrigerated Display Cabinets

Directory of Open Access Journals (Sweden)

Pedro Dinis Gaspar

2012-01-01

Full Text Available A detailed CFD modelling of an open refrigerated display cabinet has been formulated in a previous study. Some modifications are introduced in order to perform parametric studies dealing with low-cost geometrical and functional characteristics for improvement of the global performance and energy efficiency. The parametric studies are devoted to the analysis of the thermal response and behaviour inside the food conservation space influenced by (1 air flow rate through the evaporator heat exchanger; (2 air curtain behaviour; (3 hole dimensions and distribution of the back panel; (4 discharge and return grilles angles; and (5 flow deflectors inside the internal duct. The analysis of the numerical predictions from the parametric studies allows the development of an optimized model for the conception of an open refrigerated display cabinet with a more adequate configuration. The numerical predictions of the optimized model show lower product temperature and reduced electrical energy consumption, allowing the improvement of the food safety and the energy rationalization of the refrigeration equipment.

Forecasting electricity market pricing using artificial neural networks

International Nuclear Information System (INIS)

Pao, Hsiao-Tien

2007-01-01

Electricity price forecasting is extremely important for all market players, in particular for generating companies: in the short term, they must set up bids for the spot market; in the medium term, they have to define contract policies; and in the long term, they must define their expansion plans. For forecasting long-term electricity market pricing, in order to avoid excessive round-off and prediction errors, this paper proposes a new artificial neural network (ANN) with single output node structure by using direct forecasting approach. The potentials of ANNs are investigated by employing a rolling cross validation scheme. Out of sample performance evaluated with three criteria across five forecasting horizons shows that the proposed ANNs are a more robust multi-step ahead forecasting method than autoregressive error models. Moreover, ANN predictions are quite accurate even when the length of the forecast horizon is relatively short or long

Application of high-resolution domestic electricity load profiles in network modelling

DEFF Research Database (Denmark)

Marszal, Anna Joanna; Mendaza, Iker Diaz de Cerio; Heiselberg, Per Kvols

2016-01-01

the generated profiles are inputted in a low-voltage network model created in DIgSILENT PowerFactory. By means of employing 1 hour based demand and generation profiles in during dynamic studies, the representation of the local power system performance might sometimes not be as accurate as needed. In the test...... with modeling when 1-minute domestic electricity demand and generation profiles are used as inputs. The analysis is done with a case study of low-voltage network located in Northern Denmark. The analysis includes two parts. The first part focuses on modeling the domestic demands and on-site generation in 1......-minute resolution. The load profiles of the household appliances are created using a bottom-up model, which uses the 1-minute cycle power use characteristics of a single appliance as the main building block. The profiles of heavy electric appliances, such as heat pump, are not included in the above...

Massively multi-parametric immunoassays using ICPMS

International Nuclear Information System (INIS)

Tanner, S.D.; Ornatsky, O.; Bandura, D.R.; Baranov, V.I.

2009-01-01

The use of stable isotopes as tags in immunoassays, and their determination by ICPMS, is poised to have a huge impact on multi-parametric bioanalysis. A new technology, which we term 'mass cytometry', enables high throughput, highly multiplexed individual cell analysis. Preliminary results for T-cell immunophenotyping in peripheral blood mononuclear cells (PBMC), agonist influence on concomitant phosphorylation pathways, and sub-classification of acute myeloid leukemia patients' samples will be presented. The significance of individual cell analysis is demonstrated by the identification of populations of rogue cells in PBMC samples through the use of multidimensional neural network cluster analysis. (author)

A parametric visualization software for the assignment problem

Directory of Open Access Journals (Sweden)

Papamanthou Charalampos

2005-01-01

Full Text Available In this paper we present a parametric visualization software used to assist the teaching of the Network Primal Simplex Algorithm for the assignment problem (AP. The assignment problem is a special case of the balanced transportation problem. The main functions of the algorithm and design techniques are also presented. Through this process, we aim to underline the importance and necessity of using such educational methods in order to improve the teaching of Computer Algorithms.

Three Essays in Energy Economics and Industrial Organization, with Applications to Electricity and Distribution Networks

Science.gov (United States)

Dimitropoulos, Dimitrios

Electricity industries are experiencing upward cost pressures in many parts of the world. Chapter 1 of this thesis studies the production technology of electricity distributors. Although production and cost functions are mathematical duals, practitioners typically estimate only one or the other. This chapter proposes an approach for joint estimation of production and costs. Combining such quantity and price data has the effect of adding statistical information without introducing additional parameters into the model. We define a GMM estimator that produces internally consistent parameter estimates for both the production function and the cost function. We consider a multi-output framework, and show how to account for the presence of certain types of simultaneity and measurement error. The methodology is applied to data on 73 Ontario distributors for the period 2002-2012. As expected, the joint model results in a substantial improvement in the precision of parameter estimates. Chapter 2 focuses on productivity trends in electricity distribution. We apply two methodologies for estimating productivity growth . an index based approach, and an econometric cost based approach . to our data on the 73 Ontario distributors for the period 2002 to 2012. The resulting productivity growth estimates are approximately 1% per year, suggesting a reversal of the positive estimates that have generally been reported in previous periods. We implement flexible semi-parametric variants to assess the robustness of these conclusions and discuss the use of such statistical analyses for calibrating productivity and relative efficiencies within a price-cap framework. In chapter 3, I turn to the historically important problem of vertical contractual relations. While the existing literature has established that resale price maintenance is sufficient to coordinate the distribution network of a manufacturer, this chapter asks whether such vertical restraints are necessary. Specifically, I study

The Study on the Communication Network of Wide Area Measurement System in Electricity Grid

Science.gov (United States)

Xiaorong, Cheng; Ying, Wang; Yangdan, Ni

Wide area measurement system(WAMS) is a fundamental part of security defense in Smart Grid, and the communication system of WAMS is an important part of Electric power communication network. For a large regional network is concerned, the real-time data which is transferred in the communication network of WAMS will affect the safe operation of the power grid directly. Therefore, WAMS raised higher requirements for real-time, reliability and security to its communication network. In this paper, the architecture of WASM communication network was studied according to the seven layers model of the open systems interconnection(OSI), and the network architecture was researched from all levels. We explored the media of WAMS communication network, the network communication protocol and network technology. Finally, the delay of the network were analyzed.

IPv6-Based Smart Metering Network for Monitoring Building Electricity

Directory of Open Access Journals (Sweden)

Dong Xu

2013-01-01

Full Text Available A smart electricity monitoring system of building is presented using ZigBee and internet to establish the network. This system consists of three hardware layers: the host PC, the router, and the sensor nodes. A hierarchical ant colony algorithm is developed for data transmission among the wireless sensor nodes. The wireless communication protocol is also designed based on IPv6 protocol on IEEE 802.15.4 wireless network. All-IP approach and peer-to-peer mode are integrated to optimize the network building. Each node measures the power, current, and voltage and transmits them to the host PC through the router. The host software is designed for building test characteristics, having a tree hierarchy and a friendly interface for the user. The reliability and accuracy of this monitoring system are verified in the experiment and application.

Evaluation of parametric and nonparametric models to predict water flow; Avaliacao entre modelos parametricos e nao parametricos para previsao de vazoes afluentes

Energy Technology Data Exchange (ETDEWEB)

Marques, T.C.; Cruz Junior, G.; Vinhal, C. [Universidade Federal de Goias (UFG), Goiania, GO (Brazil). Escola de Engenharia Eletrica e de Computacao], Emails: thyago@eeec.ufg.br, gcruz@eeec.ufg.br, vinhal@eeec.ufg.br

2009-07-01

The goal of this paper is to present a methodology to carry out the seasonal stream flow forecasting using database of average monthly inflows of one Brazilian hydroelectric plant located at Grande, Tocantins, Paranaiba, Sao Francisco and Iguacu river's. The model is based on the Adaptive Network Based Fuzzy Inference System (ANFIS), the non-parametric model. The performance of this model was compared with a periodic autoregressive model, the parametric model. The results show that the forecasting errors of the non-parametric model considered are significantly lower than the parametric model. (author)

AutoCAD electrical 2016 for electrical control designers

CERN Document Server

Tickoo, Sham

2016-01-01

The AutoCAD Electrical 2016 for Electrical Control Designers textbook has been written to assist the engineering students and the practicing designers who are new to AutoCAD Electrical. Using this textbook, the readers can learn the application of basic tools required for creating professional electrical control drawings with the help of AutoCAD Electrical. Keeping in view the varied requirements of the users, this textbook covers a wide range of tools and features such as schematic drawings, Circuit Builder, panel drawings, parametric and nonparametric PLC modules, stand-alone PLC I/O points, ladder diagrams, point-to-point wiring diagrams, report generation, creation of symbols, and so on. This will help the readers to create electrical drawings easily and effectively. Special emphasis has been laid on the introduction of concepts, which have been explained using text and supported with graphical examples. The examples and tutorials used in this book ensure that the users can relate the information provided...

Towards future electricity networks - Final report

Energy Technology Data Exchange (ETDEWEB)

Papaemmanouil, A.

2008-07-01

This comprehensive final report for the Swiss Federal Office of Energy (SFOE) reviews work done on the development of new power transmission planning tools for restructured power networks. These are needed in order to face the challenges that arise due to economic, environmental and social issues. The integration of transmission, generation and energy policy planning in order to support a common strategy with respect to sustainable electricity networks is discussed. In the first phase of the project the main focus was placed on the definition of criteria and inputs that are most likely to affect sustainable transmission expansion plans. Models, concepts, and methods developed in order to study the impact of the internalisation of external costs in power production are examined. To consider external costs in the planning process, a concurrent software tool has been implemented that is capable of studying possible development scenarios. The report examines a concept that has been developed to identify congested transmission lines or corridors and evaluates the dependencies between the various market participants. The paper includes a set of three appendices that include a paper on the 28{sup th} USAEE North American conference, an abstract from Powertech 2009 and an SFOE report from July 2008.

Towards future electricity networks - Final report

International Nuclear Information System (INIS)

Papaemmanouil, A.

2008-01-01

This comprehensive final report for the Swiss Federal Office of Energy (SFOE) reviews work done on the development of new power transmission planning tools for restructured power networks. These are needed in order to face the challenges that arise due to economic, environmental and social issues. The integration of transmission, generation and energy policy planning in order to support a common strategy with respect to sustainable electricity networks is discussed. In the first phase of the project the main focus was placed on the definition of criteria and inputs that are most likely to affect sustainable transmission expansion plans. Models, concepts, and methods developed in order to study the impact of the internalisation of external costs in power production are examined. To consider external costs in the planning process, a concurrent software tool has been implemented that is capable of studying possible development scenarios. The report examines a concept that has been developed to identify congested transmission lines or corridors and evaluates the dependencies between the various market participants. The paper includes a set of three appendices that include a paper on the 28 th USAEE North American conference, an abstract from Powertech 2009 and an SFOE report from July 2008.

Price-based optimal control of power flow in electrical energy transmission networks

NARCIS (Netherlands)

Jokic, A.; Lazar, M.; Bosch, van den P.P.J.; Bemporad, A.; Bicchi, A.; Buttazzo, G.

2007-01-01

This article presents a novel control scheme for achieving optimal power balancing and congestion control in electrical energy transmission networks via nodal prices. We develop an explicit controller that guarantees economically optimal steady-state operation while respecting all line flow

A control technique for integration of DG units to the electrical networks

DEFF Research Database (Denmark)

Pouresmaeil, Edris; Miguel-Espinar, Carlos; Massot-Campos, Miquel

2013-01-01

This paper deals with a multiobjective control technique for integration of distributed generation (DG) resources to the electrical power network. The proposed strategy provides compensation for active, reactive, and harmonic load current components during connection of DG link to the grid...

Effects of extracellular potassium diffusion on electrically coupled neuron networks

Science.gov (United States)

Wu, Xing-Xing; Shuai, Jianwei

2015-02-01

Potassium accumulation and diffusion during neuronal epileptiform activity have been observed experimentally, and potassium lateral diffusion has been suggested to play an important role in nonsynaptic neuron networks. We adopt a hippocampal CA1 pyramidal neuron network in a zero-calcium condition to better understand the influence of extracellular potassium dynamics on the stimulus-induced activity. The potassium concentration in the interstitial space for each neuron is regulated by potassium currents, Na+-K+ pumps, glial buffering, and ion diffusion. In addition to potassium diffusion, nearby neurons are also coupled through gap junctions. Our results reveal that the latency of the first spike responding to stimulus monotonically decreases with increasing gap-junction conductance but is insensitive to potassium diffusive coupling. The duration of network oscillations shows a bell-like shape with increasing potassium diffusive coupling at weak gap-junction coupling. For modest electrical coupling, there is an optimal K+ diffusion strength, at which the flow of potassium ions among the network neurons appropriately modulates interstitial potassium concentrations in a degree that provides the most favorable environment for the generation and continuance of the action potential waves in the network.

Neural network control of a parallel hybrid-electric propulsion system for a small unmanned aerial vehicle

Science.gov (United States)

Harmon, Frederick G.

2005-11-01

Parallel hybrid-electric propulsion systems would be beneficial for small unmanned aerial vehicles (UAVs) used for military, homeland security, and disaster-monitoring missions. The benefits, due to the hybrid and electric-only modes, include increased time-on-station and greater range as compared to electric-powered UAVs and stealth modes not available with gasoline-powered UAVs. This dissertation contributes to the research fields of small unmanned aerial vehicles, hybrid-electric propulsion system control, and intelligent control. A conceptual design of a small UAV with a parallel hybrid-electric propulsion system is provided. The UAV is intended for intelligence, surveillance, and reconnaissance (ISR) missions. A conceptual design reveals the trade-offs that must be considered to take advantage of the hybrid-electric propulsion system. The resulting hybrid-electric propulsion system is a two-point design that includes an engine primarily sized for cruise speed and an electric motor and battery pack that are primarily sized for a slower endurance speed. The electric motor provides additional power for take-off, climbing, and acceleration and also serves as a generator during charge-sustaining operation or regeneration. The intelligent control of the hybrid-electric propulsion system is based on an instantaneous optimization algorithm that generates a hyper-plane from the nonlinear efficiency maps for the internal combustion engine, electric motor, and lithium-ion battery pack. The hyper-plane incorporates charge-depletion and charge-sustaining strategies. The optimization algorithm is flexible and allows the operator/user to assign relative importance between the use of gasoline, electricity, and recharging depending on the intended mission. A MATLAB/Simulink model was developed to test the control algorithms. The Cerebellar Model Arithmetic Computer (CMAC) associative memory neural network is applied to the control of the UAVs parallel hybrid-electric

Econometric model as a regulatory tool in electricity distribution - Case Network Performance Assessment Model

International Nuclear Information System (INIS)

Honkapuro, S.; Lassila, J.; Viljainen, S.; Tahvanainen, K.; Partanen, J.

2004-01-01

Electricity distribution companies operate in the state of natural monopolies since building of parallel networks is not cost-effective. Monopoly companies do not have pressure from the open markets to keep their prices and costs at reasonable level. The regulation of these companies is needed to prevent the misuse of the monopoly position. Regulation is usually focused either on the profit of company or on the price of electricity. In this document, the usability of an econometric model in the regulation of electricity distribution companies is evaluated. Regulation method which determines allowed income for each company with generic computation model can be seen as an econometric model. As the special case of an econometric model, the method called Network Performance Assessment Model, NPAM (Naetnyttomodellen in Swedish), is analysed. NPAM is developed by Swedish Energy Agency (STEM) for the regulation of electricity distribution companies. Both theoretical analysis and calculations of an example network area are presented in this document to find the major directing effects of the model. The parameters of NPAM, which are used in the calculations of this research report, were dated on 30th of March 2004. These parameters were most recent available at the time when analysis was done. However, since NPAM is under development, the parameters have been constantly changing. Therefore slightly changes in the results can occur if calculations were made with latest parameters. However, main conclusions are same and do not depend on exact parameters. (orig.)

Benefits analysis of Soft Open Points for electrical distribution network operation

International Nuclear Information System (INIS)

Cao, Wanyu; Wu, Jianzhong; Jenkins, Nick; Wang, Chengshan; Green, Timothy

2016-01-01

Highlights: • An analysis framework was developed to quantify the operational benefits. • The framework considers both network reconfiguration and SOP control. • Benefits were analyzed through both quantitative and sensitivity analysis. - Abstract: Soft Open Points (SOPs) are power electronic devices installed in place of normally-open points in electrical power distribution networks. They are able to provide active power flow control, reactive power compensation and voltage regulation under normal network operating conditions, as well as fast fault isolation and supply restoration under abnormal conditions. A steady state analysis framework was developed to quantify the operational benefits of a distribution network with SOPs under normal network operating conditions. A generic power injection model was developed and used to determine the optimal SOP operation using an improved Powell’s Direct Set method. Physical limits and power losses of the SOP device (based on back to back voltage-source converters) were considered in the model. Distribution network reconfiguration algorithms, with and without SOPs, were developed and used to identify the benefits of using SOPs. Test results on a 33-bus distribution network compared the benefits of using SOPs, traditional network reconfiguration and the combination of both. The results showed that using only one SOP achieved a similar improvement in network operation compared to the case of using network reconfiguration with all branches equipped with remotely controlled switches. A combination of SOP control and network reconfiguration provided the optimal network operation.

The impact of plug-in hybrid electric vehicles on distribution networks: A review and outlook

International Nuclear Information System (INIS)

Green, Robert C. II.; Wang, Lingfeng; Alam, Mansoor

2011-01-01

Plug-in hybrid electric vehicles (PHEVs) are the next big thing in the electric transportation market. While much work has been done to detail what economic costs and benefits PHEVs will have on consumers and producers alike, it seems that it is also important to understand what impact PHEVs will have on distribution networks nationwide. This paper finds that the impact of PHEVs on the distribution network can be determined using the following aspects of PHEVs: driving patterns, charging characteristics, charge timing, and vehicle penetration. The impacts that these aspects of PHEVs will have on distribution networks have been measured and calculated by multiple authors in different locations using many different tools that range from analytical techniques to simulations and beyond. While much work has already been completed in this area, there is still much to do. Areas left for improvement and future work will include adding more stochasticity into models as well as computing and analyzing reliability indices with respect to distribution networks. (author)

Assessing pupil and school performance by non-parametric and parametric techniques

NARCIS (Netherlands)

de Witte, K.; Thanassoulis, E.; Simpson, G.; Battisti, G.; Charlesworth-May, A.

2010-01-01

This paper discusses the use of the non-parametric free disposal hull (FDH) and the parametric multi-level model (MLM) as alternative methods for measuring pupil and school attainment where hierarchical structured data are available. Using robust FDH estimates, we show how to decompose the overall

Design of RFID Mesh Network for Electric Vehicle Smart Charging Infrastructure

Energy Technology Data Exchange (ETDEWEB)

Chung, Ching-Yen; Shepelev, Aleksey; Qiu, Charlie; Chu, Chi-Cheng; Gadh, Rajit

2013-09-04

With an increased number of Electric Vehicles (EVs) on the roads, charging infrastructure is gaining an ever-more important role in simultaneously meeting the needs of the local distribution grid and of EV users. This paper proposes a mesh network RFID system for user identification and charging authorization as part of a smart charging infrastructure providing charge monitoring and control. The Zigbee-based mesh network RFID provides a cost-efficient solution to identify and authorize vehicles for charging and would allow EV charging to be conducted effectively while observing grid constraints and meeting the needs of EV drivers

Classification of Company Performance using Weighted Probabilistic Neural Network

Science.gov (United States)

Yasin, Hasbi; Waridi Basyiruddin Arifin, Adi; Warsito, Budi

2018-05-01

Classification of company performance can be judged by looking at its financial status, whether good or bad state. Classification of company performance can be achieved by some approach, either parametric or non-parametric. Neural Network is one of non-parametric methods. One of Artificial Neural Network (ANN) models is Probabilistic Neural Network (PNN). PNN consists of four layers, i.e. input layer, pattern layer, addition layer, and output layer. The distance function used is the euclidean distance and each class share the same values as their weights. In this study used PNN that has been modified on the weighting process between the pattern layer and the addition layer by involving the calculation of the mahalanobis distance. This model is called the Weighted Probabilistic Neural Network (WPNN). The results show that the company's performance modeling with the WPNN model has a very high accuracy that reaches 100%.

Competition and network expansion in the electricity market: an analysis of producers' strategic behavior

International Nuclear Information System (INIS)

Fumagalli, Elena; Garrone, Paola; Internullo, Marco

2006-01-01

Expansion of the transmission capacity is ODe of the most efficient means of enhancing competition in electricity markets. The issue is extremely relevant far the Italian electricity market, where competition in generation has not Jet been achieved. In order to study the effects on competition of a network expansion project, a description of the influence of transmission constraints on the strategic behavior of generators is necessary. The problem was addressed in the literature far a limited number only of simplified models. This work presents an original methodology (MIXEL), based on non-cooperative game theory, far the study of a rather broad set of electricity market models. The case study illustrated in this article, shows that the effects on competition of an expansion of the network is not always positive (or as positive) as expected, given the cases illustrated in the literature. The effects on competition vary with the market structure, the ratio between demand and supply and, above all, the size of the transmission capacity expansion. For these reasons, policy provisions mandating or encouraging expansion of the transmission system with the objective of promoting competition, should take into careful consideration the underlying market structure; in a similar way, provision encouraging divestiture of generation capacity should take into account the effects of the network [it

Modelling Altitude Information in Two-Dimensional Traffic Networks for Electric Mobility Simulation

Directory of Open Access Journals (Sweden)

Diogo Santos

2016-06-01

Full Text Available Elevation data is important for electric vehicle simulation. However, traffic simulators are often two-dimensional and do not offer the capability of modelling urban networks taking elevation into account. Specifically, SUMO - Simulation of Urban Mobility, a popular microscopic traffic simulator, relies on networks previously modelled with elevation data as to provide this information during simulations. This work tackles the problem of adding elevation data to urban network models - particularly for the case of the Porto urban network, in Portugal. With this goal in mind, a comparison between different altitude information retrieval approaches is made and a simple tool to annotate network models with altitude data is proposed. The work starts by describing the methodological approach followed during research and development, then describing and analysing its main findings. This description includes an in-depth explanation of the proposed tool. Lastly, this work reviews some related work to the subject.

Towards Stabilizing Parametric Active Contours

DEFF Research Database (Denmark)

Liu, Jinchao; Fan, Zhun; Olsen, Søren Ingvor

2014-01-01

Numerical instability often occurs in evolving of parametric active contours. This is mainly due to the undesired change of parametrization during evolution. In this paper, we propose a new tangential diffusion term to compensate this undesired change. As a result, the parametrization will converge...

Competition and regulation in the European network industries. From general case to the case of electricity

International Nuclear Information System (INIS)

Jonquieres, F.

1995-01-01

The paper focuses on the institutional arrangements present situation in the European Electricity Supply Industry, which is characterized by its diversity. There is unquestionably, a trend to put pressure on the national electricity systems by the European Union organisms to accept the unbundling, Third Party Access to the network, deregulation etc. An opposing reaction appears, trying to underline the potential important drawbacks of such a trend. The conclusion of the author can be summarised as follows: Competition at the generation level? Yes[ Access to the network ? No[ (author)

Wide range operation of regenerative optical parametric wavelength converter using ASE-degraded 43-Gb/s RZ-DPSK signals.

Science.gov (United States)

Gao, Mingyi; Kurumida, Junya; Namiki, Shu

2011-11-07

For sustainable growth of the Internet, wavelength-tunable optical regeneration is the key to scaling up high energy-efficiency dynamic optical path networks while keeping the flexibility of the network. Wavelength-tunable optical parametric regenerator (T-OPR) based on the gain saturation effect of parametric amplification in a highly nonlinear fiber is promising for noise reduction in phase-shift keying signals. In this paper, we experimentally evaluated the T-OPR performance for ASE-degraded 43-Gb/s RZ-DPSK signals over a 20-nm input wavelength range between 1527 nm and 1547 nm. As a result, we achieved improved power penalty performance for the regenerated idler with a proper pump power range.

The value of electricity distribution networks

International Nuclear Information System (INIS)

De Paoli, L.

2000-01-01

This article presents the results of a study aimed at evaluating parts of the distribution network of ENEL, in charge of distributing and supplying electricity to its captive market, that could be sold as a separate entity. To determine the asset value of these hypothetical companies, the discounted cash flow method has been used applied to the 147 ENEL's distributing zones. The econometric analysis shows that the relevant variables are the quantity sold to non residential and non big industrial consumers and the length of medium voltage lines. According to the available data and to the methodology chosen, the per client value of the distribution zones of ENEL varies substantially. The maximum value is bout three times the mean value and the minimum value is largely negative. The article maintains that changes in regulation could greatly modify the asset value of distribution networks. The main regulatory risks are linked to the degree of market opening, the introduction of compensation mechanisms between different distributors and the allowed maximum revenue fixed by energy Authority for a given period of time. This point is developed in the appendix where it is shown that the price cap method is decided on the basis of a rate of return which is valid at the moment of the cap fixing but that could be no longer valid if the rate of inflation varies [it

Identification of lines of electric lines of three-phase distribution networks in the composition of ASMAE

Directory of Open Access Journals (Sweden)

Omorov Turatbek

2017-01-01

Full Text Available The problem of protection of a three-phase four-wire distribution network (DEN with a voltage of 0.4 kV from the interruption of electric power lines is considered. On the basis of the analysis of the values of complex resistances of interpersonal sections of the main line of the network, criteria are proposed that allow detecting critical situations associated with discontinuities in power transmission lines. Using these criteria makes it possible to localize the places of breaks of phase and neutral wires. Mathematical models and methods that are used to evaluate the complex resistances of interpersonal sections of a three-phase network are briefly considered. The obtained results are oriented for use in the automated system of electricity control and accounting (ASMAE.

Evaluation of Suitability of a Parametrically Controlled Louvers for Various Orientations throughout a Year Comparing to an Existing Case

Directory of Open Access Journals (Sweden)

Ahmad Eltaweel

2017-11-01

Full Text Available Nowadays, daylighting systems and shading devices are controlled automatically to achieve their optimum benefits. For more comprehensive accuracy, parametric control was recently used to manage complex parameters with more accuracy. Such a system was proposed and investigated in a previous research to provide steadier and more uniform daylight illuminance during the day and reduce more than 80% of the electricity consumption. This study is examining the daylighting performance by using the parametric system in different orientations and comparing with the conventional ones. Furthermore, the study will evaluate the suitability of the parametric system throughout the year during the working hours in a typical office room.

Variance in parametric images: direct estimation from parametric projections

International Nuclear Information System (INIS)

Maguire, R.P.; Leenders, K.L.; Spyrou, N.M.

2000-01-01

Recent work has shown that it is possible to apply linear kinetic models to dynamic projection data in PET in order to calculate parameter projections. These can subsequently be back-projected to form parametric images - maps of parameters of physiological interest. Critical to the application of these maps, to test for significant changes between normal and pathophysiology, is an assessment of the statistical uncertainty. In this context, parametric images also include simple integral images from, e.g., [O-15]-water used to calculate statistical parametric maps (SPMs). This paper revisits the concept of parameter projections and presents a more general formulation of the parameter projection derivation as well as a method to estimate parameter variance in projection space, showing which analysis methods (models) can be used. Using simulated pharmacokinetic image data we show that a method based on an analysis in projection space inherently calculates the mathematically rigorous pixel variance. This results in an estimation which is as accurate as either estimating variance in image space during model fitting, or estimation by comparison across sets of parametric images - as might be done between individuals in a group pharmacokinetic PET study. The method based on projections has, however, a higher computational efficiency, and is also shown to be more precise, as reflected in smooth variance distribution images when compared to the other methods. (author)

Identifying the Effective Factors in Making Trust in Online Social Networks on the perspective of Iranian experts Using Fuzzy ELECTRE

Directory of Open Access Journals (Sweden)

Elham Haghighi

2015-12-01

Full Text Available this paper attempts to rank the effective factors in making trust in social networks to provide the possibility of attracting and increasing users’ trust on these social networks for providers and designers of online social networks. Identifying the effective factors in making trust in social networks is a multi-criteria decision making problem and most of effective factors are ambiguous and uncertain, thereby this article uses Fuzzy ELECTRE to rank them. By implementing Fuzzy ELECTRE on gathered data, respectively «usability factor», «supporting up to date technology factor», «integrity» and «the rate of ethics factor» are on the top of effective factors in making trust in users. In general, «web features» and «technology features» have a higher degree of importance than «security features», «individual-social features» and «cultural features». Ranking of Fuzzy ELECTRE comparison ranking of Fuzzy TOPSIS and Fuzzy ELECTRE method becomes validate because Spearman correlation coefficients is 0/867. Result of sensitivity analysis on changing weight of criteria shows that Fuzzy ELECTRE isn’t affected by ambiguity and uncertainty in inputs.

PAT Design Strategy for Energy Recovery in Water Distribution Networks by Electrical Regulation

Directory of Open Access Journals (Sweden)

Helena M. Ramos

2013-01-01

Full Text Available In the management of water distribution networks, large energy savings can be yielded by exploiting the head drop due to the network pressure control strategy, i.e., for leak reductions. Hydropower in small streams is already exploited, but technical solutions combining efficiency and economic convenience are still required. In water distribution networks, an additional design problem comes out from the necessity of ensuring a required head drop under variable operating conditions, i.e., head and discharge variations. Both a hydraulic regulation (HR—via a series-parallel hydraulic circuit- and an electrical regulation (ER—via inverter- are feasible solutions. A design procedure for the selection of a production device in a series-parallel hydraulic circuit has been recently proposed. The procedure, named VOS (Variable Operating Strategy, is based on the overall plant efficiency criteria and is applied to a water distribution network where a PAT (pump as a turbine is used in order to produce energy. In the present paper the VOS design procedure has been extended to the electrical regulation and a comparison between HR and ER efficiency and flexibility within a water distribution network is shown: HR was found more flexible than ER and more efficient. Finally a preliminary economic study has been carried out in order to show the viability of both systems, and a shorter payback period of the electromechanical equipment was found for HR mode.

Econometric model as a regulatory tool in electricity distribution. Case network performance assessment model

International Nuclear Information System (INIS)

Honkapuro, S.; Lassila, J.; Viljainen, S.; Tahvanainen, K.; Partanen, J.

2004-01-01

Electricity distribution companies operate in the state of natural monopolies since building of parallel networks is not cost- effective. Monopoly companies do not have pressure from the open markets to keep their prices and costs at reasonable level. The regulation of these companies is needed to prevent the misuse of the monopoly position. Regulation is usually focused either on the profit of company or on the price of electricity. Regulation method which determines allowed income for each company with generic computation model can be seen as an econometric model. In this document, the usability of an econometric model in the regulation of electricity distribution companies is evaluated. As the special case of an econometric model, the method called Network Performance Assessment Model, NPAM (Naetnyttomodellen in Swedish), is analysed. NPAM is developed by Swedish Energy Agency (STEM) for the regulation of electricity distribution companies. Both theoretical analysis and calculations of an example network area are presented in this document to find the major directing effects of the model. The parameters of NPAM, which are used in the calculations of this research report, were dated on 30th of March 2004. These parameters were most recent ones available at the time when analysis was done. However, since NPAM have been under development, the parameters have been constantly changing. Therefore slight changes might occur in the numerical results of calculations if they were made with the latest set of parameters. However, main conclusions are same and do not depend on exact parameters

Households' willingness to pay for overhead-to-underground conversion of electricity distribution networks

Energy Technology Data Exchange (ETDEWEB)

McNair, Ben J., E-mail: Ben.McNair@anu.edu.a [Crawford School of Economics and Government, Australian National University, Crawford Building, Lennox Crossing, Canberra ACT 0200 (Australia); Bennett, Jeff [Crawford School of Economics and Government, Australian National University, Crawford Building, Lennox Crossing, Canberra ACT 0200 (Australia); Hensher, David A.; Rose, John M. [Institute of Transport and Logistics Studies, The Business School, University of Sydney, NSW 2006 (Australia)

2011-05-15

Underground low-voltage electricity networks have several advantages over overhead networks including reliability of supply, safety and improved visual amenity. The economic viability of replacing existing overhead networks with new underground networks depends on the value of these benefits to households, but no complete value estimates are available in the literature. This paper represents a contribution towards addressing this research gap. A stated choice survey is used to estimate willingness to pay for undergrounding in established residential areas in Canberra, Australia. Average willingness to pay is at least A$6838 per household and there is significant variation in preferences over the population. The results suggest that benefits would be highest in areas with higher household income and older residents where visual amenity, safety, tree trimming, or restrictions on the use of yard space are of concern. - Research highlights: {yields} A choice experiment is used to estimate values for undergrounding electricity wires. {yields} Average willingness to pay is at least A$6838 per household in Canberra, Australia. {yields} Preferences vary considerably over the population. {yields} Benefits would be highest in areas with higher income and older residents.

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

Directory of Open Access Journals (Sweden)

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.

Application of semi parametric modelling to times series forecasting: case of the electricity consumption; Modeles semi-parametriques appliques a la prevision des series temporelles. Cas de la consommation d'electricite

Energy Technology Data Exchange (ETDEWEB)

Lefieux, V

2007-10-15

Reseau de Transport d'Electricite (RTE), in charge of operating the French electric transportation grid, needs an accurate forecast of the power consumption in order to operate it correctly. The forecasts used everyday result from a model combining a nonlinear parametric regression and a SARIMA model. In order to obtain an adaptive forecasting model, nonparametric forecasting methods have already been tested without real success. In particular, it is known that a nonparametric predictor behaves badly with a great number of explanatory variables, what is commonly called the curse of dimensionality. Recently, semi parametric methods which improve the pure nonparametric approach have been proposed to estimate a regression function. Based on the concept of 'dimension reduction', one those methods (called MAVE : Moving Average -conditional- Variance Estimate) can apply to time series. We study empirically its effectiveness to predict the future values of an autoregressive time series. We then adapt this method, from a practical point of view, to forecast power consumption. We propose a partially linear semi parametric model, based on the MAVE method, which allows to take into account simultaneously the autoregressive aspect of the problem and the exogenous variables. The proposed estimation procedure is practically efficient. (author)

Social representations of electricity network technologies: exploring processes of anchoring and objectification through the use of visual research methods.

Science.gov (United States)

Devine-Wright, Hannah; Devine-Wright, Patrick

2009-06-01

The aim of this study was to explore everyday thinking about the UK electricity network, in light of government policy to increase the generation of electricity from renewable energy sources. Existing literature on public perceptions of electricity network technologies was broadened by adopting a more socially embedded conception of the construction of knowledge using the theory of social representations (SRT) to explore symbolic associations with network technologies. Drawing and association tasks were administered within nine discussion groups held in two places: a Scottish town where significant upgrades to the local transmission network were planned and an English city with no such plans. Our results illustrate the ways in which network technologies, such as high voltage (HV) pylons, are objectified in talk and drawings. These invoked positive as well as negative symbolic and affective associations, both at the level of specific pylons, and the 'National Grid' as a whole and are anchored in understanding of other networks such as mobile telecommunications. We conclude that visual methods are especially useful for exploring beliefs about technologies that are widespread, proximal to our everyday experience but nevertheless unfamiliar topics of everyday conversation.

Essays on electricity markets

Energy Technology Data Exchange (ETDEWEB)

Rud, Linda

2009-07-01

The report covers several topics of electricity markets: The first essay, 'Selected Topics on Early Electricity Market Design in Norway' studies market design issues in establishing the market-based Norwegian electricity market. Essays 2-4 focus on issues of network congestion: 'Capacity Charges: A Price Adjustment Process for Managing Congestion in Electricity Transmission Networks' presents the capacity charge approach for managing transmission constraints in electricity networks. 'Understanding the Stochastics of Nodal Prices: Price Processes in a Constrained Network' seeks a further understanding of stochastic nodal prices processes. 'Investment Evaluation in a Constrained Electricity Network with Stochastic Nodal Price Processes' studies how the interaction of the competitive market and the capacitated network affects the evaluation of investments under uncertainty, and points out potential pitfalls of evaluation. In the last essay, 'A Newsboy Model Perspective on the Power Market: The Case of a Wind Power Producer' we discuss aspects of optimal bidding for a wind power producer. (Author)

Essays on electricity markets

Energy Technology Data Exchange (ETDEWEB)

Rud, Linda

2009-07-01

The report covers several topics of electricity markets: The first essay, 'Selected Topics on Early Electricity Market Design in Norway' studies market design issues in establishing the market-based Norwegian electricity market. Essays 2-4 focus on issues of network congestion: 'Capacity Charges: A Price Adjustment Process for Managing Congestion in Electricity Transmission Networks' presents the capacity charge approach for managing transmission constraints in electricity networks. 'Understanding the Stochastics of Nodal Prices: Price Processes in a Constrained Network' seeks a further understanding of stochastic nodal prices processes. 'Investment Evaluation in a Constrained Electricity Network with Stochastic Nodal Price Processes' studies how the interaction of the competitive market and the capacitated network affects the evaluation of investments under uncertainty, and points out potential pitfalls of evaluation. In the last essay, 'A Newsboy Model Perspective on the Power Market: The Case of a Wind Power Producer' we discuss aspects of optimal bidding for a wind power producer. (Author)

Assessment of the voltage level and losses with photovoltaic and electric vehicle in low voltage network

NARCIS (Netherlands)

Ye, G.; Xiang, Y.; Cobben, J.F.G.

2014-01-01

Livelab from Alliander, a network operator, is a program which started to measure electrical and power quality data in the Dutch distribution network since 2013. A proper probability distribution can be used to model load distribution on feeders. This paper presents a methodology to generate the

Computer network for electric power control systems. Chubu denryoku (kabu) denryoku keito seigyoyo computer network

Energy Technology Data Exchange (ETDEWEB)

Tsuneizumi, T. (Chubu Electric Power Co. Inc., Nagoya (Japan)); Shimomura, S.; Miyamura, N. (Fuji Electric Co. Ltd., Tokyo (Japan))

1992-06-03

A computer network for electric power control system was developed that is applied with the open systems interconnection (OSI), an international standard for communications protocol. In structuring the OSI network, a direct session layer was accessed from the operation functions when high-speed small-capacity information is transmitted. File transfer, access and control having a function of collectively transferring large-capacity data were applied when low-speed large-capacity information is transmitted. A verification test for the realtime computer network (RCN) mounting regulation was conducted according to a verification model using a mini-computer, and a result that can satisfy practical performance was obtained. For application interface, kernel, health check and two-route transmission functions were provided as a connection control function, so were transmission verification function and late arrival abolishing function. In system mounting pattern, dualized communication server (CS) structure was adopted. A hardware structure may include a system to have the CS function contained in a host computer and a separate installation system. 5 figs., 6 tabs.

Modelling and Simulation of the SVC for Power System Flow Studies: Electrical Network in voltage drop

Directory of Open Access Journals (Sweden)

Narimen Aouzellag LAHAÇANI

2008-12-01

Full Text Available The goal of any Flexible AC Transmission Systems (FACTS devices study is to measure their impact on the state of the electrical networks into which they are introduced. Their principal function is to improve the static and dynamic properties of the electrical networks and that by increasing the margins of static and dynamic stability and to allow the power transit to the thermal limits of the lines.To study this impact, it is necessary to establish the state of the network (bus voltages and angles, powers injected and forwarded in the lines before and after the introduction of FACTS devices. This brings to calculate the powers transit by using an iterative method such as Newton-Raphson. Undertaking a calculation without the introduction of FACTS devices followed by a calculation with the modifications induced by the integration of FACTS devices into the network, makes it possible to compare the results obtained in both cases and thus assess the interest of the use of devices FACTS.

Combined effect of chemical and electrical synapses in Hindmarsh-Rose neural networks on synchronization and the rate of information.

Science.gov (United States)

Baptista, M S; Moukam Kakmeni, F M; Grebogi, C

2010-09-01

In this work we studied the combined action of chemical and electrical synapses in small networks of Hindmarsh-Rose (HR) neurons on the synchronous behavior and on the rate of information produced (per time unit) by the networks. We show that if the chemical synapse is excitatory, the larger the chemical synapse strength used the smaller the electrical synapse strength needed to achieve complete synchronization, and for moderate synaptic strengths one should expect to find desynchronous behavior. Otherwise, if the chemical synapse is inhibitory, the larger the chemical synapse strength used the larger the electrical synapse strength needed to achieve complete synchronization, and for moderate synaptic strengths one should expect to find synchronous behaviors. Finally, we show how to calculate semianalytically an upper bound for the rate of information produced per time unit (Kolmogorov-Sinai entropy) in larger networks. As an application, we show that this upper bound is linearly proportional to the number of neurons in a network whose neurons are highly connected.

Improvements in the computation of balances and localization of commercial losses of electric energy in 0.38-kV networks

International Nuclear Information System (INIS)

Vorotnitskii, V. Z.; Zaslonov, S. V.; Lysyuk, S. S.

2006-01-01

An example of four 0.38-kV overhead distribution lines fed from a 10/0.4-kV transformer substation of the Grodno Electrical Networks (Belarus') and supplying electricity to a cottage area is used for analyzing energy balances and commercial losses in the networks. It is shown that the reliability of such analysis can be ensured by the use of modern software and electronic energy meters recording a retrospective of half-hourly intervals of active and reactive electric energy

A modular neural network scheme applied to fault diagnosis in electric power systems.

Science.gov (United States)

Flores, Agustín; Quiles, Eduardo; García, Emilio; Morant, Francisco; Correcher, Antonio

2014-01-01

This work proposes a new method for fault diagnosis in electric power systems based on neural modules. With this method the diagnosis is performed by assigning a neural module for each type of component comprising the electric power system, whether it is a transmission line, bus or transformer. The neural modules for buses and transformers comprise two diagnostic levels which take into consideration the logic states of switches and relays, both internal and back-up, with the exception of the neural module for transmission lines which also has a third diagnostic level which takes into account the oscillograms of fault voltages and currents as well as the frequency spectrums of these oscillograms, in order to verify if the transmission line had in fact been subjected to a fault. One important advantage of the diagnostic system proposed is that its implementation does not require the use of a network configurator for the system; it does not depend on the size of the power network nor does it require retraining of the neural modules if the power network increases in size, making its application possible to only one component, a specific area, or the whole context of the power system.

Automated electric valve for electrokinetic separation in a networked microfluidic chip.

Science.gov (United States)

Cui, Huanchun; Huang, Zheng; Dutta, Prashanta; Ivory, Cornelius F

2007-02-15

This paper describes an automated electric valve system designed to reduce dispersion and sample loss into a side channel when an electrokinetically mobilized concentration zone passes a T-junction in a networked microfluidic chip. One way to reduce dispersion is to control current streamlines since charged species are driven along them in the absence of electroosmotic flow. Computer simulations demonstrate that dispersion and sample loss can be reduced by applying a constant additional electric field in the side channel to straighten current streamlines in linear electrokinetic flow (zone electrophoresis). This additional electric field was provided by a pair of platinum microelectrodes integrated into the chip in the vicinity of the T-junction. Both simulations and experiments of this electric valve with constant valve voltages were shown to provide unsatisfactory valve performance during nonlinear electrophoresis (isotachophoresis). On the basis of these results, however, an automated electric valve system was developed with improved valve performance. Experiments conducted with this system showed decreased dispersion and increased reproducibility as protein zones isotachophoretically passed the T-junction. Simulations of the automated electric valve offer further support that the desired shape of current streamlines was maintained at the T-junction during isotachophoresis. Valve performance was evaluated at different valve currents based on statistical variance due to dispersion. With the automated control system, two integrated microelectrodes provide an effective way to manipulate current streamlines, thus acting as an electric valve for charged species in electrokinetic separations.

Analysis of the network capacities and possible congestion of the electricity transmission networks within the accession countries

International Nuclear Information System (INIS)

Kristiansen, Tarjei; Hewicker, Cristian

2005-01-01

cross-border network constraints. Besides the technical parameters to describe production and main network characteristics, the main remaining input factors are costs/fuel prices and demand.The outputs of the PROSYM tool are generation quantities, costs, short-run marginal prices and flows. To calibrate the model and to check its accuracy, we have first performed simulations for the year 2003 (the reference year) where information on actual market prices and (physical) cross-border flows is available. Thereafter, we have run additional simulations for the years 2010 and 2020 to analyse the future development of generation, export and import patterns, and to assess the influence of new interconnector projects. Due to uncertainty about future development, we have additionally tested the sensitivity of our base case to changes in e.g. the rate of growth in generation capacity and demand, the future generation structure, or the development of fuel prices. With a view to the economic import and export potential, our investigations confirm the assumption that network constraints represent a major barrier to the free exchange of electricity within the IEM. Considering the frequency and severity of congestion, our calculations show major network constraints at the following borders: 1) From Central Eastern Europe (Poland, Czech Republic, Slovakia) to Germany, Austria and Hungary; 2) From Austria and Slovenia to Italy; 3) From Bulgaria and Serbia and Montenegro (respectively Macedonia) to Greece. Our results show, not unexpectedly, considerable differences in the net benefits of individual transmission capacity increases, due to differences in market value and/or investment costs. (Author)

STATCAT, Statistical Analysis of Parametric and Non-Parametric Data

International Nuclear Information System (INIS)

David, Hugh

1990-01-01

1 - Description of program or function: A suite of 26 programs designed to facilitate the appropriate statistical analysis and data handling of parametric and non-parametric data, using classical and modern univariate and multivariate methods. 2 - Method of solution: Data is read entry by entry, using a choice of input formats, and the resultant data bank is checked for out-of- range, rare, extreme or missing data. The completed STATCAT data bank can be treated by a variety of descriptive and inferential statistical methods, and modified, using other standard programs as required

Node localization algorithm of wireless sensor networks for large electrical equipment monitoring application

DEFF Research Database (Denmark)

Chen, Qinyin; Hu, Y.; Chen, Zhe

2016-01-01

Node localization technology is an important technology for the Wireless Sensor Networks (WSNs) applications. An improved 3D node localization algorithm is proposed in this paper, which is based on a Multi-dimensional Scaling (MDS) node localization algorithm for large electrical equipment monito...

A simulated-based neural network algorithm for forecasting electrical energy consumption in Iran

International Nuclear Information System (INIS)

Azadeh, A.; Ghaderi, S.F.; Sohrabkhani, S.

2008-01-01

This study presents an integrated algorithm for forecasting monthly electrical energy consumption based on artificial neural network (ANN), computer simulation and design of experiments using stochastic procedures. First, an ANN approach is illustrated based on supervised multi-layer perceptron (MLP) network for the electrical consumption forecasting. The chosen model, therefore, can be compared to that of estimated by time series model. Computer simulation is developed to generate random variables for monthly electricity consumption. This is achieved to foresee the effects of probabilistic distribution on monthly electricity consumption. The simulated-based ANN model is then developed. Therefore, there are four treatments to be considered in analysis of variance (ANOVA), which are actual data, time series, ANN and simulated-based ANN. Furthermore, ANOVA is used to test the null hypothesis of the above four alternatives being statistically equal. If the null hypothesis is accepted, then the lowest mean absolute percentage error (MAPE) value is used to select the best model, otherwise the Duncan method (DMRT) of paired comparison is used to select the optimum model which could be time series, ANN or simulated-based ANN. In case of ties the lowest MAPE value is considered as the benchmark. The integrated algorithm has several unique features. First, it is flexible and identifies the best model based on the results of ANOVA and MAPE, whereas previous studies consider the best fitted ANN model based on MAPE or relative error results. Second, the proposed algorithm may identify conventional time series as the best model for future electricity consumption forecasting because of its dynamic structure, whereas previous studies assume that ANN always provide the best solutions and estimation. To show the applicability and superiority of the proposed algorithm, the monthly electricity consumption in Iran from March 1994 to February 2005 (131 months) is used and applied to

Network access charges, vertical integration, and property rights structure - experiences from the German electricity markets

International Nuclear Information System (INIS)

Growitsch, C.; Wein, T.

2005-01-01

After the deregulation of the German electricity markets in 1998, the German government opted for a regulatory regime called negotiated third party access, which would be subject to ex-post control by the federal cartel office. Network access charges for new competitors are based on contractual arrangements between energy producers and industrial consumers. As the electricity networks are incontestable natural monopolies, the local and regional network operators are able to set (monopolistic) charges at their own discretion, restricted only by the possible interference of the federal cartel office (Bundeskartellamt). In this paper we analyze if there is evidence for varying charging behaviour depending on the supplier's economic independence (structure of property rights) or its level of vertical integration. For this purpose, we hypothesise that incorporated and vertically integrated suppliers set different charges than independent utility companies. Multivariate estimations show a relation between network access charges and the network operator's economic independence as well as level of vertical integration: on the low voltage level for an estimated annual consumption of 1700 kW/h, vertically integrated firms set-in accordance with our hypothesis-significantly lower access charges than vertically separated suppliers, whereas incorporated network operators charge significantly higher charges compared to independent suppliers. These results could not have been confirmed for other consumptions or voltage levels. (author)

Modeling Geoelectric Fields and Geomagnetically Induced Currents Around New Zealand to Explore GIC in the South Island's Electrical Transmission Network

Science.gov (United States)

Divett, T.; Ingham, M.; Beggan, C. D.; Richardson, G. S.; Rodger, C. J.; Thomson, A. W. P.; Dalzell, M.

2017-10-01

Transformers in New Zealand's South Island electrical transmission network have been impacted by geomagnetically induced currents (GIC) during geomagnetic storms. We explore the impact of GIC on this network by developing a thin-sheet conductance (TSC) model for the region, a geoelectric field model, and a GIC network model. (The TSC is composed of a thin-sheet conductance map with underlying layered resistivity structure.) Using modeling approaches that have been successfully used in the United Kingdom and Ireland, we applied a thin-sheet model to calculate the electric field as a function of magnetic field and ground conductance. We developed a TSC model based on magnetotelluric surveys, geology, and bathymetry, modified to account for offshore sediments. Using this representation, the thin sheet model gave good agreement with measured impedance vectors. Driven by a spatially uniform magnetic field variation, the thin-sheet model results in electric fields dominated by the ocean-land boundary with effects due to the deep ocean and steep terrain. There is a strong tendency for the electric field to align northwest-southeast, irrespective of the direction of the magnetic field. Applying this electric field to a GIC network model, we show that modeled GIC are dominated by northwest-southeast transmission lines rather than east-west lines usually assumed to dominate.

Parametric and non-parametric models for lifespan modeling of insulation systems in electrical machines

OpenAIRE

Salameh , Farah; Picot , Antoine; Chabert , Marie; Maussion , Pascal

2017-01-01

International audience; This paper describes an original statistical approach for the lifespan modeling of electric machine insulation materials. The presented models aim to study the effect of three main stress factors (voltage, frequency and temperature) and their interactions on the insulation lifespan. The proposed methodology is applied to two different insulation materials tested in partial discharge regime. Accelerated ageing tests are organized according to experimental optimization m...

Decision support for the definition of wind turbine systems adequacy to site specificities and weak electrical networks

International Nuclear Information System (INIS)

Arbaoui, A.

2006-10-01

A decision support system for the definition of wind turbine systems is developed by taking into account the wind and site characteristics, the wind turbine components and the electrical network properties close to the site. The approach is based on functional analysis, on the investigation of the functional fluxes and on the definition of a model suitable for supporting decision at the preliminary stages of wind turbine design. The complete set of solutions derived from the model is determined using a Constraint Satisfaction Problem solver. The intrinsic capability of the model to support decision is derived from the investigation of the model parsimony, precision, exactness and specialization. The model takes into account performance criteria resulting from knowledge of manufacturers, distributors and investors. These criteria are used to discriminate design alternatives. Design alternatives correspond to choices of site (wind, electric network) and wind turbine architectures (related to 7 design variables). Performance criteria are the cost of electric kWh, the amount of energy being produced and the discounted total cost of the project. Electric network connection to wind turbines is taken into account through slow variations of the voltage and Flickers phenomenon. First, the maximal rate of penetration of the wind turbine energy production is determined. Next, two design alternatives have been investigated to improve wind turbine system integration in electric distribution networks. These alternatives are a reactive power control system and an inertial energy storage system. Inertial storage systems seem to be more expensive than reactive power control systems for this type of application. The influence of site specificities on decision making process has been established through three different sites (a Mediterranean site and two sites located in northern Europe). Profits relative to the cost of kWh appear to be high for Mediterranean sites. Most of the

Policy and network regulation for the integration of distribution generation and renewables for electricity supply

International Nuclear Information System (INIS)

Ten Donkelaar, M.; Van Oostvoorn, F.

2005-08-01

This study has analysed the existing policy and regulation aimed at the integration of an increased share of Distributed Generation (DG) in electricity supply systems in the European Union. It illustrates the state of the art and progress in the development of support mechanisms and network regulation for large-scale integration of DG. Through a benchmark study a systematic comparison has been made of different DG support schemes and distribution network regulation in EU Member States to a predefined standard, the level playing field. This level playing field has been defined as the situation where energy markets, policy and regulation provide neutral incentives to central versus distributed generation, which results in an economically more efficient electricity supply to the consumer. In current regulation and policy a certain discrepancy can be noticed between the actual regulation and policy support systems in a number of countries, the medium to long term targets and the ideal situation described according to the level playing field objective. Policies towards DG and RES are now mainly aimed at removing short-term barriers, increasing the production share of DG/RES, but often ignoring the more complex barriers of integrating DG/RES that is created by the economic network regulation in current electricity markets

A neural network image reconstruction technique for electrical impedance tomography

International Nuclear Information System (INIS)

Adler, A.; Guardo, R.

1994-01-01

Reconstruction of Images in Electrical Impedance Tomography requires the solution of a nonlinear inverse problem on noisy data. This problem is typically ill-conditioned and requires either simplifying assumptions or regularization based on a priori knowledge. This paper presents a reconstruction algorithm using neural network techniques which calculates a linear approximation of the inverse problem directly from finite element simulations of the forward problem. This inverse is adapted to the geometry of the medium and the signal-to-noise ratio (SNR) used during network training. Results show good conductivity reconstruction where measurement SNR is similar to the training conditions. The advantages of this method are its conceptual simplicity and ease of implementation, and the ability to control the compromise between the noise performance and resolution of the image reconstruction

electric vehicle

Directory of Open Access Journals (Sweden)

W. R. Lee

1999-01-01

Full Text Available A major problem facing battery-powered electric vehicles is in their batteries: weight and charge capacity. Thus, a battery-powered electric vehicle only has a short driving range. To travel for a longer distance, the batteries are required to be recharged frequently. In this paper, we construct a model for a battery-powered electric vehicle, in which driving strategy is to be obtained such that the total travelling time between two locations is minimized. The problem is formulated as an optimization problem with switching times and speed as decision variables. This is an unconventional optimization problem. However, by using the control parametrization enhancing technique (CPET, it is shown that this unconventional optimization is equivalent to a conventional optimal parameter selection problem. Numerical examples are solved using the proposed method.

Undelivered electricity as an indicator of the effects of automation in the 10 kV network PD ED Belgrade

Directory of Open Access Journals (Sweden)

Vrcelj Nada

2013-01-01

Full Text Available The paper discusses the effects of automation in the 10 kV PD ED Belgrade valorized through undelivered electricity. In the paper it was observed the parts of the network for which it was possible to reconstruct the events of the past. Calculations undelivered electricity were carried out for the period prior to the implementation of recloser in remote control system and during the period of probation system. A significant reduction in the duration of the fault, and thus undelivered electricity in automated network, indicates an increase in the reliability level after the implementation in the system SCADA SN.

Power-law neuronal fluctuations in a recurrent network model of parametric working memory.

Science.gov (United States)

Miller, Paul; Wang, Xiao-Jing

2006-02-01

In a working memory system, persistent activity maintains information in the absence of external stimulation, therefore the time scale and structure of correlated neural fluctuations reflect the intrinsic microcircuit dynamics rather than direct responses to sensory inputs. Here we show that a parametric working memory model capable of graded persistent activity is characterized by arbitrarily long correlation times, with Fano factors and power spectra of neural activity described by the power laws of a random walk. Collective drifts of the mnemonic firing pattern induce long-term noise correlations between pairs of cells, with the sign (positive or negative) and amplitude proportional to the product of the gradients of their tuning curves. None of the power-law behavior was observed in a variant of the model endowed with discrete bistable neural groups, where noise fluctuations were unable to cause long-term changes in rate. Therefore such behavior can serve as a probe for a quasi-continuous attractor. We propose that the unusual correlated fluctuations have important implications for neural coding in parametric working memory circuits.

A SURVEY OF SMART ELECTRICAL BOARDS IN UBIQUITOUS SENSOR NETWORKS FOR GEOMATICS APPLICATIONS

Directory of Open Access Journals (Sweden)

S. M. R. Moosavi

2015-12-01

Full Text Available Nowadays more advanced sensor networks in various fields are developed. There are lots of online sensors spreading around the world. Sensor networks have been used in Geospatial Information Systems (GIS since sensor networks have expanded. Health monitoring, environmental monitoring, traffic monitoring, etc, are the examples of its applications in Geomatics. Sensor network is an infrastructure comprised of sensing (measuring, computing, and communication elements that gives an administrator the ability to instrument, observe, and react to events and phenomena in a specified environment. This paper describes about development boards which can be used in sensor networks and their applications in Geomatics and their role in wireless sensor networks and also a comparison between various types of boards. Boards that are discussed in this paper are Arduino, Raspberry Pi, Beagle board, Cubieboard. The Boards because of their great potential are also known as single board computers. This paper is organized in four phases: First, Reviewing on ubiquitous computing and sensor networks. Second, introducing of some electrical boards. Then, defining some criterions for comparison. Finally, comparing the Ubiquitous boards.

ELECTRIC MOTOR DIAGNOSTICS OF SWITCHES BASED ON THE NEURAL NETWORK DATA MODELING THE SPECTRAL DECOMPOSITION OF THE CURRENTS

Directory of Open Access Journals (Sweden)

O. M. Shvets

2009-07-01

Full Text Available The method of automated diagnostics of electric motors is offered. It uses a neural network revealing the electric motor faults on the basis of analysis of frequency spectrum of current flowing through the motor.

Electrical equivalent thermal network for direct contact membrane distillation modeling and analysis

KAUST Repository

Karam, Ayman M.

2016-09-19

Membrane distillation (MD) is an emerging water desalination technology that offers several advantages compared to conventional desalination methods. Although progress has been made to model the physics of the process, there are two common limitations of existing models. Firstly, many of the models are based on the steady-state analysis of the process and secondly, some of the models are based on partial differential equations, which when discretized introduce many states which are not accessible in practice. This paper presents the derivation of a novel dynamic model, based on the analogy between electrical and thermal systems, for direct contact membrane distillation (DCMD). An analogous electrical thermal network is constructed and its elements are parameterized such that the response of the network models the DCMD process. The proposed model captures the spatial and temporal responses of the temperature distribution along the flow direction and is able to accurately predict the distilled water flux output. To demonstrate the adequacy of the proposed model, validation with time varying and steady-state experimental data is presented. (C) 2016 Elsevier Ltd. All rights reserved.

Exploring the determinants of “best practice” benchmarking in electricity network regulation

International Nuclear Information System (INIS)

Brophy Haney, Aoife; Pollitt, Michael G.

2011-01-01

In this paper we use a best practice index constructed from the survey responses of regulators in 40 countries to explore the determinants of the methods used in electricity network regulation. Drawing from the incentive regulation and institutional economics literature, we construct an empirical model to investigate the impact of industry size, political and economic institutions on the degree of best practice regulation. Our results suggest that the existence and experience of an independent regulator is the most important institutional determinant of best practice regulation. In addition, small numbers of network companies act as a constraint on the use of advanced benchmarking methods. Finally, regional effects are also important. These findings lead us to question whether one “best practice” model is in fact applicable to countries with very different political and economic contexts. - Highlights: ► Political institutions are strong determinants of best practice electricity regulation. ► Behavior of neighboring regulators may shape regulatory outcomes. ► One “best practice” model may not be appropriate.

Assessing the Potential of Plug-in Electric Vehicles in Active Distribution Networks

Directory of Open Access Journals (Sweden)

Reza Ahmadi Kordkheili

2016-01-01

Full Text Available A multi-objective optimization algorithm is proposed in this paper to increase the penetration level of renewable energy sources (RESs in distribution networks by intelligent management of plug-in electric vehicle (PEV storage. The proposed algorithm is defined to manage the reverse power flow (PF from the distribution network to the upstream electrical system. Furthermore, a charging algorithm is proposed within the proposed optimization in order to assure PEV owner’s quality of service (QoS. The method uses genetic algorithm (GA to increase photovoltaic (PV penetration without jeopardizing PEV owners’ (QoS and grid operating limits, such as voltage level of the grid buses. The method is applied to a part of the Danish low voltage (LV grid to evaluate its effectiveness and capabilities. Different scenarios have been defined and tested using the proposed method. Simulation results demonstrate the capability of the algorithm in increasing solar power penetration in the grid up to 50%, depending on the PEV penetration level and the freedom of the system operator in managing the available PEV storage.

SERS investigations and electrical recording of neuronal networks with three-dimensional plasmonic nanoantennas (Conference Presentation)

Science.gov (United States)

De Angelis, Francesco

2017-06-01

SERS investigations and electrical recording of neuronal networks with three-dimensional plasmonic nanoantennas Michele Dipalo, Valeria Caprettini, Anbrea Barbaglia, Laura Lovato, Francesco De Angelis e-mail: francesco.deangelis@iit.it Istituto Italiano di Tecnologia, Via Morego 30, 16163, Genova Biological systems are analysed mainly by optical, chemical or electrical methods. Normally each of these techniques provides only partial information about the environment, while combined investigations could reveal new phenomena occurring in complex systems such as in-vitro neuronal networks. Aiming at the merging of optical and electrical investigations of biological samples, we introduced three-dimensional plasmonic nanoantennas on CMOS-based electrical sensors [1]. The overall device is then capable of enhanced Raman Analysis of cultured cells combined with electrical recording of neuronal activity. The Raman measurements show a much higher sensitivity when performed on the tip of the nanoantenna in respect to the flat substrate [2]; this effect is a combination of the high plasmonic field enhancement and of the tight adhesion of cells on the nanoantenna tip. Furthermore, when plasmonic opto-poration is exploited [3] the 3D nanoelectrodes are able to penetrate through the cell membrane thus accessing the intracellular environment. Our latest results (unpublished) show that the technique is completely non-invasive and solves many problems related to state-of-the-art intracellular recording approaches on large neuronal networks. This research received funding from ERC-IDEAS Program: "Neuro-Plasmonics" [Grant n. 616213]. References: [1] M. Dipalo, G. C. Messina, H. Amin, R. La Rocca, V. Shalabaeva, A. Simi, A. Maccione, P. Zilio, L. Berdondini, F. De Angelis, Nanoscale 2015, 7, 3703. [2] R. La Rocca, G. C. Messina, M. Dipalo, V. Shalabaeva, F. De Angelis, Small 2015, 11, 4632. [3] G. C. Messina et al., Spatially, Temporally, and Quantitatively Controlled Delivery of

Synthesis of CdS nanowire networks and their optical and electrical properties

International Nuclear Information System (INIS)

Ma, R M; Wei, X L; Dai, L; Huo, H B; Qin, G G

2007-01-01

High quality single-crystal CdS nanowire (NW) networks have been synthesized on Si(111) substrates via the chemical vapour deposition method. X-ray diffraction and selected area electron diffraction show that the NWs in the networks grow along the directions and their (0001) crystal planes are parallel to the Si(111) substrates. Room-temperature photoluminescence (PL) spectra of single CdS NWs in the networks are dominated by a near-band-edge emission and free from deep-level defect emissions. The PLs resulting from free-exciton and bound-exciton recombinations are detected at 77 K. The results of the electrical transport measurement on the CdS NW networks show that the current can flow through different NWs via the cross-junctions. The resistivity, electron concentration and electron mobility of single NWs in the networks are estimated by fitting the I-V curves measured on single NWs with the metal-semiconductor-metal model suggested by Zhang et al (2006 Appl. Phys. Lett. 88 073102; 2007 Adv. Funct. Mater. at press)

The European interconnection system between reality and utopia. Does the market organization fit into the electricity network?

International Nuclear Information System (INIS)

Stigler, H.

2016-01-01

On the basis of discussions about the contribution that research and innovations can make to the renewal of the electricity market, the synchronous grid of Continental Europe will be compared with the transmission network. The electricity market guidelines are put to critical consideration and the question is raised whether today's electricity market organization is sustainable in the long term. The paper concludes with regard to the usefulness of the organizational structure and the organization of the electricity markets. (rössner) [de

An enhanced radial basis function network for short-term electricity price forecasting

International Nuclear Information System (INIS)

Lin, Whei-Min; Gow, Hong-Jey; Tsai, Ming-Tang

2010-01-01

This paper proposed a price forecasting system for electric market participants to reduce the risk of price volatility. Combining the Radial Basis Function Network (RBFN) and Orthogonal Experimental Design (OED), an Enhanced Radial Basis Function Network (ERBFN) has been proposed for the solving process. The Locational Marginal Price (LMP), system load, transmission flow and temperature of the PJM system were collected and the data clusters were embedded in the Excel Database according to the year, season, workday and weekend. With the OED applied to learning rates in the ERBFN, the forecasting error can be reduced during the training process to improve both accuracy and reliability. This would mean that even the ''spikes'' could be tracked closely. The Back-propagation Neural Network (BPN), Probability Neural Network (PNN), other algorithms, and the proposed ERBFN were all developed and compared to check the performance. Simulation results demonstrated the effectiveness of the proposed ERBFN to provide quality information in a price volatile environment. (author)

Technical Topic 3.2.2.d Bayesian and Non-Parametric Statistics: Integration of Neural Networks with Bayesian Networks for Data Fusion and Predictive Modeling

Science.gov (United States)

2016-05-31

Distribution Unlimited UU UU UU UU 31-05-2016 15-Apr-2014 14-Jan-2015 Final Report: Technical Topic 3.2.2.d Bayesian and Non- parametric Statistics...of Papers published in non peer-reviewed journals: Final Report: Technical Topic 3.2.2.d Bayesian and Non- parametric Statistics: Integration of Neural...Transfer N/A Number of graduating undergraduates who achieved a 3.5 GPA to 4.0 (4.0 max scale ): Number of graduating undergraduates funded by a DoD funded

A case study to estimate costs using Neural Networks and regression based models

Directory of Open Access Journals (Sweden)

Nadia Bhuiyan

2012-07-01

Full Text Available Bombardier Aerospace’s high performance aircrafts and services set the utmost standard for the Aerospace industry. A case study in collaboration with Bombardier Aerospace is conducted in order to estimate the target cost of a landing gear. More precisely, the study uses both parametric model and neural network models to estimate the cost of main landing gears, a major aircraft commodity. A comparative analysis between the parametric based model and those upon neural networks model will be considered in order to determine the most accurate method to predict the cost of a main landing gear. Several trials are presented for the design and use of the neural network model. The analysis for the case under study shows the flexibility in the design of the neural network model. Furthermore, the performance of the neural network model is deemed superior to the parametric models for this case study.

Fluid power network for centralized electricity generation in offshore wind farms

International Nuclear Information System (INIS)

Jarquin-Laguna, A

2014-01-01

An innovative and completely different wind-energy conversion system is studied where a centralized electricity generation within a wind farm is proposed by means of a hydraulic network. This paper presents the dynamic interaction of two turbines when they are coupled to the same hydraulic network. Due to the stochastic nature of the wind and wake interaction effects between turbines, the operating parameters (i.e. pitch angle, rotor speed) of each turbine are different. Time domain simulations, including the main turbine dynamics and laminar transient flow in pipelines, are used to evaluate the efficiency and rotor speed stability of the hydraulic system. It is shown that a passive control of the rotor speed, as proposed in previous work for a single hydraulic turbine, has strong limitations in terms of performance for more than one turbine coupled to the same hydraulic network. It is concluded that in order to connect several turbines, a passive control strategy of the rotor speed is not sufficient and a hydraulic network with constant pressure is suggested. However, a constant pressure network requires the addition of active control at the hydraulic motors and spear valves, increasing the complexity of the initial concept. Further work needs to be done to incorporate an active control strategy and evaluate the feasibility of the constant pressure hydraulic network

Operating principle of Soft Open Points for electrical distribution network operation

International Nuclear Information System (INIS)

Cao, Wanyu; Wu, Jianzhong; Jenkins, Nick; Wang, Chengshan; Green, Timothy

2016-01-01

Highlights: • Two control modes were developed for a B2B VSCs based SOP. • The SOP operating principle was investigated under various network conditions. • The performance of the SOP using two control modes was analyzed. - Abstract: Soft Open Points (SOPs) are power electronic devices installed in place of normally-open points in electrical power distribution networks. They are able to provide active power flow control, reactive power compensation and voltage regulation under normal network operating conditions, as well as fast fault isolation and supply restoration under abnormal conditions. Two control modes were developed for the operation of an SOP, using back-to-back voltage-source converters (VSCs). A power flow control mode with current control provides independent control of real and reactive power. A supply restoration mode with a voltage controller enables power supply to isolated loads due to network faults. The operating principle of the back-to-back VSCs based SOP was investigated under both normal and abnormal network operating conditions. Studies on a two-feeder medium-voltage distribution network showed the performance of the SOP under different network-operating conditions: normal, during a fault and post-fault supply restoration. During the change of network operating conditions, a mode switch method based on the phase locked loop controller was used to achieve the transitions between the two control modes. Hard transitions by a direct mode switching were noticed unfavourable, but seamless transitions were obtained by deploying a soft cold load pickup and voltage synchronization process.

The photovoltaic generators and the electric network; Los generadores fotovoltaicos y la red electrica

Energy Technology Data Exchange (ETDEWEB)

Arteaga Novoa, Oscar E.; Agredano Diaz, Jaime; Huacuz Villamar, Jorge M. [Instituto de Investigaciones Electricas, Cuernavaca (Mexico)

1997-12-31

The photovoltaic generators are analyzed as an option for the electricity supply. An analysis is made of the option that these systems be utilized in sites where it is difficult to extend the power lines an in sites where the electric service already exists, such as residences, commercial buildings, network support power stations, central power stations, all this in order that the photovoltaic systems interact with the electric network for the generation of part of the energy consumed in these sites. In order that the photovoltaic systems can be interconnected with the electric network it is required: energy quality, protection and safety of the systems and persons and normativity for the interconnection. Some of the national programs of countries like Japan, United States of America and some organs of the Commission of the European Community are described. In conclusion, it is expected that the costs of this technology decrease so these systems can be widely utilized [Espanol] Se analizan los generadores fotovoltaicos como una alternativa para el suministro electrico. Se analiza la opcion de que estos sistemas se utilicen en lugares en donde es dificil extender la red electrica y en sitios en donde el servicio electrico ya existe, tales como: residencias, edificios comerciales, estaciones de apoyo a la red, estaciones centrales, esto con la finalidad de que el sistema fotovoltaico interactue con la red electrica a fin de generar parte de la energia que se consume en estos sitios. Para que los sistemas fotovoltaicos puedan estar interconectados con la red electrica se requiere: calidad de la energia, proteccion y seguridad de los sistemas y personas, y normatividad para la interconexion. Se describen algunos programas nacionales de paises como Japon, Estados Unidos y algunos organismos de la Comision de Comunidades Europeas. En conclusion, se espera que los costos de esta tecnologia disminuyan para que estos sistemas puedan ser ampliamante utilizados

The photovoltaic generators and the electric network; Los generadores fotovoltaicos y la red electrica

Energy Technology Data Exchange (ETDEWEB)

Arteaga Novoa, Oscar E; Agredano Diaz, Jaime; Huacuz Villamar, Jorge M [Instituto de Investigaciones Electricas, Cuernavaca (Mexico)

1998-12-31

The photovoltaic generators are analyzed as an option for the electricity supply. An analysis is made of the option that these systems be utilized in sites where it is difficult to extend the power lines an in sites where the electric service already exists, such as residences, commercial buildings, network support power stations, central power stations, all this in order that the photovoltaic systems interact with the electric network for the generation of part of the energy consumed in these sites. In order that the photovoltaic systems can be interconnected with the electric network it is required: energy quality, protection and safety of the systems and persons and normativity for the interconnection. Some of the national programs of countries like Japan, United States of America and some organs of the Commission of the European Community are described. In conclusion, it is expected that the costs of this technology decrease so these systems can be widely utilized [Espanol] Se analizan los generadores fotovoltaicos como una alternativa para el suministro electrico. Se analiza la opcion de que estos sistemas se utilicen en lugares en donde es dificil extender la red electrica y en sitios en donde el servicio electrico ya existe, tales como: residencias, edificios comerciales, estaciones de apoyo a la red, estaciones centrales, esto con la finalidad de que el sistema fotovoltaico interactue con la red electrica a fin de generar parte de la energia que se consume en estos sitios. Para que los sistemas fotovoltaicos puedan estar interconectados con la red electrica se requiere: calidad de la energia, proteccion y seguridad de los sistemas y personas, y normatividad para la interconexion. Se describen algunos programas nacionales de paises como Japon, Estados Unidos y algunos organismos de la Comision de Comunidades Europeas. En conclusion, se espera que los costos de esta tecnologia disminuyan para que estos sistemas puedan ser ampliamante utilizados

Emerging subspecialties in neurology: deep brain stimulation and electrical neuro-network modulation.

Science.gov (United States)

Hassan, Anhar; Okun, Michael S

2013-01-29

Deep brain stimulation (DBS) is a surgical therapy that involves the delivery of an electrical current to one or more brain targets. This technology has been rapidly expanding to address movement, neuropsychiatric, and other disorders. The evolution of DBS has created a niche for neurologists, both in the operating room and in the clinic. Since DBS is not always deep, not always brain, and not always simply stimulation, a more accurate term for this field may be electrical neuro-network modulation (ENM). Fellowships will likely in future years evolve their scope to include other technologies, and other nervous system regions beyond typical DBS therapy.

Motivations of parametric studies

International Nuclear Information System (INIS)

Birac, C.

1988-01-01

The paper concerns the motivations of parametric studies in connection with the Programme for the Inspection of Steel Components PISC II. The objective of the PISC II exercise is to evaluate the effectiveness of current and advanced NDT techniques for inspection of reactor pressure vessel components. The parametric studies were initiated to determine the influence of some parameters on defect detection and dimensioning, and to increase the technical bases of the Round Robin Tests. A description is given of the content of the parametric studies including:- the effect of the defects' characteristics, the effect of equipment characteristics, the effect of cladding, and possible use of electromagnetic techniques. (U.K.)

Fault detection and classification in electrical power transmission system using artificial neural network.

Science.gov (United States)

Jamil, Majid; Sharma, Sanjeev Kumar; Singh, Rajveer

2015-01-01

This paper focuses on the detection and classification of the faults on electrical power transmission line using artificial neural networks. The three phase currents and voltages of one end are taken as inputs in the proposed scheme. The feed forward neural network along with back propagation algorithm has been employed for detection and classification of the fault for analysis of each of the three phases involved in the process. A detailed analysis with varying number of hidden layers has been performed to validate the choice of the neural network. The simulation results concluded that the present method based on the neural network is efficient in detecting and classifying the faults on transmission lines with satisfactory performances. The different faults are simulated with different parameters to check the versatility of the method. The proposed method can be extended to the Distribution network of the Power System. The various simulations and analysis of signals is done in the MATLAB(®) environment.

A Modular Neural Network Scheme Applied to Fault Diagnosis in Electric Power Systems

Directory of Open Access Journals (Sweden)

Agustín Flores

2014-01-01

Full Text Available This work proposes a new method for fault diagnosis in electric power systems based on neural modules. With this method the diagnosis is performed by assigning a neural module for each type of component comprising the electric power system, whether it is a transmission line, bus or transformer. The neural modules for buses and transformers comprise two diagnostic levels which take into consideration the logic states of switches and relays, both internal and back-up, with the exception of the neural module for transmission lines which also has a third diagnostic level which takes into account the oscillograms of fault voltages and currents as well as the frequency spectrums of these oscillograms, in order to verify if the transmission line had in fact been subjected to a fault. One important advantage of the diagnostic system proposed is that its implementation does not require the use of a network configurator for the system; it does not depend on the size of the power network nor does it require retraining of the neural modules if the power network increases in size, making its application possible to only one component, a specific area, or the whole context of the power system.

Quality of electric service in utility distribution networks under electromagnetic compatibility principles. [ENEL

Energy Technology Data Exchange (ETDEWEB)

Chizzolini, P.; Lagostena, L.; Mirra, C.; Sani, G. (ENEL, Rome Milan (Italy))

1989-03-01

The development of electromagnetic compatibility criteria, being worked out in international standardization activities, requires the establishment of the characteristics of public utility distribution networks as a reference ambient. This is necessary for gauging the immunity levels towards users and for defining the disturbance emission limits. Therefore, it is a new way to look at the quality of electric service. Consequently, it is necessary to check and specify, in an homogeneous manner, the phenomena that affect electric service. Use must be made of experimental tests and of the collection and elaboration of operation data. In addition to testing techniques, this paper describes the checking procedures for the quality of electric service as they are implemented in the information system developed by ENEL (Italian Electricity Board) for distribution activities. The first reference data obtained from the national and international fields about voltage shape and supply continuity are also indicated.

Using ELECTRE TRI to support maintenance of water distribution networks

Directory of Open Access Journals (Sweden)

Flavio Trojan

2012-08-01

Full Text Available Problems encountered in the context of the maintenance management of water supply are evidenced by the lack of decision support models which gives a manager overview of the system. This paper, therefore, develops a model that uses, in its framework, the multicriteria outranking method ELECTRE TRI. The objective is to sort the areas of water flow measurement of a water distribution network, by priority of maintenance, with data collected from an automated system of abnormalities detection. This sorting is designed to support maintenance decisions in terms of the measure more appropriate to be applied per region. To illustrate the proposed model, an application was performed in a city with 100 thousand water connections. With this model it becomes possible to improve the allocation of maintenance measures for regions and mainly to improve the operation of the distribution network.

Accelerated reliability testing of highly aligned single-walled carbon nanotube networks subjected to DC electrical stressing.

Science.gov (United States)

Strus, Mark C; Chiaramonti, Ann N; Kim, Young Lae; Jung, Yung Joon; Keller, Robert R

2011-07-01

We investigate the electrical reliability of nanoscale lines of highly aligned, networked, metallic/semiconducting single-walled carbon nanotubes (SWCNTs) fabricated through a template-based fluidic assembly process. We find that these SWCNT networks can withstand DC current densities larger than 10 MA cm(-2) for several hours and, in some cases, several days. We develop test methods that show that the degradation rate, failure predictability and total device lifetime can be linked to the initial resistance. Scanning electron and transmission electron microscopy suggest that fabrication variability plays a critical role in the rate of degradation, and we offer an empirical method of quickly determining the long-term performance of a network. We find that well-fabricated lines subject to constant electrical stress show a linear accumulation of damage reminiscent of electromigration in metallic interconnects, and we explore the underlying physical mechanisms that could cause such behavior.

FEATURES OF SELECTION OF CAPACITOR BANKS IN ELECTRIC NETWORKS WITH INTERHARMONIC SOURCES

Directory of Open Access Journals (Sweden)

Yu. L. Sayenko

2017-10-01

Full Text Available Purpose. Development of a methodology for selecting capacitor bank parameters designed to compensate for reactive power, if there are sources of interharmonics in the electrical network. Development of a methodology for selecting the parameters of capacitor banks that are part of resonant filters of higher harmonics and interharmonics. Methodology. For the research, we used the decomposition of the non-sinusoidal voltage (current curve into the sum of the harmonic components with frequencies as multiple of the fundamental frequency - higher harmonics, and not multiple fundamental frequencies - interharmonics. Results. Expressions are obtained for checking the absence of inadmissible overloads of capacitor banks by voltage and current in the presence of voltage (current in the curve, along with higher harmonics, of the discrete spectrum of interharmonics. When selecting capacitor banks, both for reactive power compensation and for filter-compensating devices, the necessity of constructing the frequency characteristics of the input and mutual resistances of the electrical network for analyzing possible resonant phenomena is confirmed. Originality. The expediency of simplified calculation of the voltage variation at the terminals of the banks of the capacitors of the higher harmonics filters and interharmonics due to the presence of the reactor in the filters is substantiated. Practical value. The use of the proposed approaches will make it possible to resolve a number of issues related to the choice of parameters of capacitor banks in networks with nonlinear loads, including: ensuring reliable operation of capacitor banks when their parameters deviate from their nominal values, as well as deviations in the parameters of the supply network and sources of harmonic distortion; ensuring the absence of resonant phenomena at frequencies of both higher harmonics and interharmonics.

A Parametric k-Means Algorithm

Science.gov (United States)

Tarpey, Thaddeus

2007-01-01

Summary The k points that optimally represent a distribution (usually in terms of a squared error loss) are called the k principal points. This paper presents a computationally intensive method that automatically determines the principal points of a parametric distribution. Cluster means from the k-means algorithm are nonparametric estimators of principal points. A parametric k-means approach is introduced for estimating principal points by running the k-means algorithm on a very large simulated data set from a distribution whose parameters are estimated using maximum likelihood. Theoretical and simulation results are presented comparing the parametric k-means algorithm to the usual k-means algorithm and an example on determining sizes of gas masks is used to illustrate the parametric k-means algorithm. PMID:17917692

Application of Network-Constrained Transactive Control to Electric Vehicle Charging for Secure Grid Operation

DEFF Research Database (Denmark)

Hu, Junjie; Yang, Guangya; Bindner, Henrik W.

2016-01-01

including power transformer congestion and voltage violations. In this method, a price coordinator is introduced to facilitate the interaction between the distribution system operator (DSO) and aggregators in the smart grid. Electric vehicles are used to illustrate the proposed network...

Multi-objective optimization control of plug-in electric vehicles in low voltage distribution networks

DEFF Research Database (Denmark)

García-Villalobos, J.; Zamora, I.; Knezovic, Katarina

2016-01-01

The massive introduction of plug-in electric vehicles (PEVs) into low voltage (LV) distribution networks will lead to several problems, such as: increase of energy losses, decrease of distribution transformer lifetime, lines and transformer overload issues, voltage drops and unbalances...

A Complex Network Approach for the Estimation of the Energy Demand of Electric Mobility.

Science.gov (United States)

Mureddu, Mario; Facchini, Angelo; Scala, Antonio; Caldarelli, Guido; Damiano, Alfonso

2018-01-10

We study how renewable energy impacts regional infrastructures considering the full deployment of electric mobility at that scale. We use the Sardinia Island in Italy as a paradigmatic case study of a semi-closed system both by energy and mobility point of view. Human mobility patterns are estimated by means of census data listing the mobility dynamics of about 700,000 vehicles, the energy demand is estimated by modeling the charging behavior of electric vehicle owners. Here we show that current renewable energy production of Sardinia is able to sustain the commuter mobility even in the theoretical case of a full switch from internal combustion vehicles to electric ones. Centrality measures from network theory on the reconstructed network of commuter trips allows to identify the most important areas (hubs) involved in regional mobility. The analysis of the expected energy flows reveals long-range effects on infrastructures outside metropolitan areas and points out that the most relevant unbalances are caused by spatial segregation between production and consumption areas. Finally, results suggest the adoption of planning actions supporting the installation of renewable energy plants in areas mostly involved by the commuting mobility, avoiding spatial segregation between consumption and generation areas.

Absolute parametric instability of low frequency waves in a 2-D nonuniform anisotropic warm plasma

International Nuclear Information System (INIS)

Zaki, N.G.

2004-01-01

Using the separation method, the problem of absolute parametric instability (API) of electrostatic waves in magnetized pumped warm plasma is investigated. In this case the effect of static strong magnetic field is considered. The problem of strong magnetic field is solved in 2-D nonuniform plane plasma. The equations which describe the spatial part of the electric potential are obtained. Also the growth rates and conditions of the parametric instability for periodic cases are obtained. It is found that the spatial nonuniformity of the plasma exerts a stabilizing effect on the API. It is shown that the growth rates of periodic and aperiodic API in warm plasma are reduced in comparison with a cold plasma case

Prospective study related to the evolution of energy distribution networks. Needs of evolution of technical and organisational models of energy distribution networks with respect to energy transition scenarios in the Provence-Alpes-Cote d'Azur region. Part 1 - Hypotheses and perspectives, Part 2 - Needs of network evolution. Study related to the impact of the electric vehicle and of photovoltaic production on electric distribution networks - Case study for Provence-Alpes-Cote d'Azur

International Nuclear Information System (INIS)

Dauphin, Francois; Fontaine, Frederick

2013-02-01

The first part of this document aims at presenting perspectives of emergence of new energy production, consumption and storage sources, and their impacts on energy (electricity, gas, heat) distribution and transport networks. It is based on two scenarios: the regional climate-air-energy scheme, and the regional Negawatt scenario. The objective was to select a limited number of aspects: solutions enabling an optimal injection of biogas produced in the concerned region, development of photovoltaic energy and electric vehicles and their impact on the balance of medium-voltage and low-voltage networks, and smart grid technologies and their possible impact on the optimisation of electric network management. The second part reports the detailed study of these issues. It more particularly addresses technical impacts of different sectors on electric and gas networks in Provence-Alpes-Cote d'Azur, technical, economic and organisational assets of smart grid technologies, investments policies and implementation planning, and resulting evolutions for energy markets. Related documents published by ERDF and GrDF are provided

Electric restructuring and consumer choice: lessons from other network industries

International Nuclear Information System (INIS)

Crandall, R. W.

1999-01-01

The advantages of the U.S. model of private markets with limited regulation as the best alternative for delivering goods and services to consumers are discussed by citing examples from deregulated industries such as transportation, primary energy and financial markets. In all these cases deregulation has been extraordinarily successful. Experiences from these industries are examined in an effort to extract lessons that might be useful in predicting the likely evolution of competition in the electricity and telecommunications industries. A warning is sounded that deregulating these industries without opening access to the infrastructure (which is owned by carriers) could create major problems of natural-monopoly exploitation by the incumbents that would negate any productive and allocative efficiency gains conferred by deregulation. One obvious choice for liberalizing a network industry with natural-monopoly infrastructure is simply to separate the infrastructure from the delivery of the service as was done with railroads in the United Kingdom. A similar, but less far-reaching example might be the solution devised for natural gas pipelines in the U.S. where pipeline owners opened their infrastructure to competitors, albeit at regulated rates. In the electricity industry, separating power generation from transmission and distribution appears to be fairly simple, provided access to transmission and distribution network is granted. In the telecommunication industry where there is no generation, the natural monopoly may be in the local distribution of traffic to subscribers, hence separation of local distribution from national or regional distribution is the normal way to open up the market to new service providers. Experiences in the U. S., the U. K., Canada and New Zealand in electricity and telecommunications industry deregulation are examined and various pitfalls in current approaches are pointed out. It is the author's contention that announcing a date for the end

The Local Structure of Globalization. The Network Dynamics of Foreign Direct Investments in the International Electricity Industry

Science.gov (United States)

Koskinen, Johan; Lomi, Alessandro

2013-05-01

We study the evolution of the network of foreign direct investment (FDI) in the international electricity industry during the period 1994-2003. We assume that the ties in the network of investment relations between countries are created and deleted in continuous time, according to a conditional Gibbs distribution. This assumption allows us to take simultaneously into account the aggregate predictions of the well-established gravity model of international trade as well as local dependencies between network ties connecting the countries in our sample. According to the modified version of the gravity model that we specify, the probability of observing an investment tie between two countries depends on the mass of the economies involved, their physical distance, and the tendency of the network to self-organize into local configurations of network ties. While the limiting distribution of the data generating process is an exponential random graph model, we do not assume the system to be in equilibrium. We find evidence of the effects of the standard gravity model of international trade on evolution of the global FDI network. However, we also provide evidence of significant dyadic and extra-dyadic dependencies between investment ties that are typically ignored in available research. We show that local dependencies between national electricity industries are sufficient for explaining global properties of the network of foreign direct investments. We also show, however, that network dependencies vary significantly over time giving rise to a time-heterogeneous localized process of network evolution.

Evaluating the market splitting determinants: evidence from the Iberian spot electricity prices

International Nuclear Information System (INIS)

Figueiredo, Nuno Carvalho; Silva, Patrícia Pereira da; Cerqueira, Pedro A.

2015-01-01

This paper aims to assess the main determinants on the market splitting behaviour of the Iberian electricity spot markets. Iberia stands as an ideal case-study, where the high level deployment of wind power is observed, together with the implementation of the market splitting arrangement between the Portuguese and the Spanish spot electricity markets. Logit and non-parametric models are used to express the probability response for market splitting of day-ahead spot electricity prices as a function of the explanatory variables representing the main technologies in the generation mix: wind, hydro, thermal and nuclear power, together with the available transfer capacity and electricity demand. Logit models give preliminary indications about market splitting behaviour, and then, notwithstanding the demanding computational challenge, a non-parametric model is applied in order to overcome the limitations of the former models. Results show an increase of market splitting probability with higher wind power generation or, more generally, with higher availability of low marginal cost electricity such as nuclear power generation. The European interconnection capacity target of 10% of the peak demand of the smallest interconnected market might be insufficient to maintain electricity market integration. Therefore, pro-active coordination policies, governing both interconnections and renewables deployment, should be further developed. -- Highlights: •Assess determinants on market splitting behaviour of Iberian electricity markets. •Logit and non-parametric models to express market splitting probability response. •Explanatory variables: wind, hydro, thermal and nuclear power; ATC and demand. •Results: increase of market splitting probability with higher availability of low marginal cost electricity. •Coordination policies governing both interconnections and renewables deployment

The design of electric vehicle intelligent charger

Science.gov (United States)

Xu, Yangyang; Wang, Ying

2018-05-01

As the situation of the lack of energy and environment pollution deteriorates rapidly, electric vehicle, a new type of traffic tool, is being researched worldwide. As the core components of electric vehicle, the battery and charger's performance play an important roles in the quality of electric vehicle. So the design of the Electric Vehicle Intelligent Charger based on language-C is designed in this paper. The hardware system is used to produce the input signals of Electric Vehicle Intelligent Charger. The software system adopts the language-C software as development environment. The design can accomplish the test of the parametric such as voltage-current and temperature.

Planar Parametrization in Isogeometric Analysis

DEFF Research Database (Denmark)

Gravesen, Jens; Evgrafov, Anton; Nguyen, Dang-Manh

2012-01-01

Before isogeometric analysis can be applied to solving a partial differential equation posed over some physical domain, one needs to construct a valid parametrization of the geometry. The accuracy of the analysis is affected by the quality of the parametrization. The challenge of computing...... and maintaining a valid geometry parametrization is particularly relevant in applications of isogemetric analysis to shape optimization, where the geometry varies from one optimization iteration to another. We propose a general framework for handling the geometry parametrization in isogeometric analysis and shape...... are suitable for our framework. The non-linear methods we consider are based on solving a constrained optimization problem numerically, and are divided into two classes, geometry-oriented methods and analysis-oriented methods. Their performance is illustrated through a few numerical examples....

Optimized green operation of LTE networks in the presence of multiple electricity providers

KAUST Repository

Ghazzai, Hakim; Yaacoub, Elias E.; Alouini, Mohamed-Slim; Abu-Dayya, Adnan A.

2012-01-01

Energy efficiency aspects in cellular networks can significantly contribute to the reduction of greenhouse gas emissions and help to save the environment. The base station (BS) sleeping strategy has become a well-known technique to achieve energy savings by switching off redundant BSs mainly for lightly loaded networks. Besides, introducing renewable energies as alternative power sources becomes a real challenge to network operators. In this paper, we propose a method that reduces the energy consumption of BSs by not only shutting down underutilized BSs but also by optimizing the amounts of energy procured from different retailers (Renewable energy and electricity retailers). We formulate an optimization problem that leads to the maximization of the profit of a Long-Term Evolution (LTE) cellular operator, and at the same time to the minimization of CO2 emissions in green wireless cellular networks without affecting the desired Quality of Service. © 2012 IEEE.

Optimized green operation of LTE networks in the presence of multiple electricity providers

KAUST Repository

Ghazzai, Hakim

2012-12-01

Energy efficiency aspects in cellular networks can significantly contribute to the reduction of greenhouse gas emissions and help to save the environment. The base station (BS) sleeping strategy has become a well-known technique to achieve energy savings by switching off redundant BSs mainly for lightly loaded networks. Besides, introducing renewable energies as alternative power sources becomes a real challenge to network operators. In this paper, we propose a method that reduces the energy consumption of BSs by not only shutting down underutilized BSs but also by optimizing the amounts of energy procured from different retailers (Renewable energy and electricity retailers). We formulate an optimization problem that leads to the maximization of the profit of a Long-Term Evolution (LTE) cellular operator, and at the same time to the minimization of CO2 emissions in green wireless cellular networks without affecting the desired Quality of Service. © 2012 IEEE.

Electric dipole ordering in alkali-cyanides: NaCN and KCN

International Nuclear Information System (INIS)

Koiller, B.; Davidovich, M.A.; Carmo, L.C.S. do; Luety, F.

1983-01-01

A simple model for the low temperature electrically ordered state of NaCN and KCN is presented. The model takes into account electric dipole dressing effects which include cationic displacements determined experimentally. The ground state structure and the calculated values for the local electric fields are in fair agreement with experimental results. A parametrization for the elastic potencial confirms the plausibility of these model. (Author) [pt

Database management for an electrical distribution network of intermediate complexity CERN

CERN Document Server

De Ruschi, Daniele; Burdet, Georges

2010-01-01

This thesis is submitted as the final work for the degree of Master of Science in Engineering of Information that has been taken by the writer at at University of Bergamo, Italy. The report is based on the work conducted by the writer from September 2009 throughout June 2010 on a project assignment given by the department of Engineering Electrical Control at CERN Genève The work performed is a contribution to the GESMAR system of CERN. GESMAR is a CERN made complex platform for support and management of electric network. In this work is developed an information system for an ETL process. The report presents the design, implementation and evaluation made, prototypes of applications which take advantages of new information inserted in GESMAR are also presented.

Developing a Parametric Urban Design Tool

DEFF Research Database (Denmark)

Steinø, Nicolai; Obeling, Esben

2014-01-01

Parametric urban design is a potentially powerful tool for collaborative urban design processes. Rather than making one- off designs which need to be redesigned from the ground up in case of changes, parametric design tools make it possible keep the design open while at the same time allowing...... for a level of detailing which is high enough to facilitate an understan- ding of the generic qualities of proposed designs. Starting from a brief overview of parametric design, this paper presents initial findings from the development of a parametric urban design tool with regard to developing a structural...... logic which is flexible and expandable. It then moves on to outline and discuss further development work. Finally, it offers a brief reflection on the potentials and shortcomings of the software – CityEngine – which is used for developing the parametric urban design tool....

Forecasting Electricity Demand in Thailand with an Artificial Neural Network Approach

Directory of Open Access Journals (Sweden)

Karin Kandananond

2011-08-01

Full Text Available Demand planning for electricity consumption is a key success factor for the development of any countries. However, this can only be achieved if the demand is forecasted accurately. In this research, different forecasting methods—autoregressive integrated moving average (ARIMA, artificial neural network (ANN and multiple linear regression (MLR—were utilized to formulate prediction models of the electricity demand in Thailand. The objective was to compare the performance of these three approaches and the empirical data used in this study was the historical data regarding the electricity demand (population, gross domestic product: GDP, stock index, revenue from exporting industrial products and electricity consumption in Thailand from 1986 to 2010. The results showed that the ANN model reduced the mean absolute percentage error (MAPE to 0.996%, while those of ARIMA and MLR were 2.80981 and 3.2604527%, respectively. Based on these error measures, the results indicated that the ANN approach outperformed the ARIMA and MLR methods in this scenario. However, the paired test indicated that there was no significant difference among these methods at α = 0.05. According to the principle of parsimony, the ARIMA and MLR models might be preferable to the ANN one because of their simple structure and competitive performance

The safety and reliability of the electricity transportation network, and the opening of markets

International Nuclear Information System (INIS)

Merlin, A.

2003-01-01

Following a decade in which the electricity sector was concerned by the opening of markets the world over, the year 2003 highlighted the challenges of secure supply and of the safety of electrical systems. Major incidents are nothing new throughout history, and occurred well before the trend towards opening the markets dot underway. However, it is necessary to verify that the rules for the organisation, clarification of responsibilities and regulation make it possible to control the growing complexity of interconnected systems related to opening the market up to competition. Faced with such situations, changes are necessary in Europe. Firstly, it is important to have the second European directive on the internal electricity market introduced everywhere, this directive providing common rules to be met by all key players to ensure greater safety within the electricity system, and strengthening the role of the electricity transport network manager, who is separate from the other players in the market. It is also necessary to draft a third directive, focusing on both security of supply and the operational safety of the European electricity system. (authors)

Ionospheric modification and parametric instabilities

International Nuclear Information System (INIS)

Fejer, J.A.

1979-01-01

Thresholds and linear growth rates for stimulated Brillouin and Raman scattering and for the parametric decay instability are derived by using arguments of energy transfer. For this purpose an expression for the ponderomotive force is derived. Conditions under which the partial pressure force due to differential dissipation exceeds the ponderomotive force are also discussed. Stimulated Brillouin and Raman scattering are weakly excited by existing incoherent backscatter radars. The parametric decay instability is strongly excited in ionospheric heating experiments. Saturation theories of the parametric decay instability are therefore described. After a brief discussion of the purely growing instability the effect of using several pumps is discussed as well as the effects of inhomogenicity. Turning to detailed theories of ionospheric heating, artificial spread F is discussed in terms of a purely growing instability where the nonlinearity is due to dissipation. Field-aligned short-scale striations are explained in terms of dissipation of the parametrically excited Langmuir waves (plasma oscillations): they might be further amplified by an explosive instability (except the magnetic equator). Broadband absorption is probably responsible for the 'overshoot' effect: the initially observed level of parametrically excited Langmuir waves is much higher than the steady state level

Detection of Parametric Roll on Ships

DEFF Research Database (Denmark)

Galeazzi, Roberto; Blanke, Mogens; Poulsen, Niels Kjølstad

2012-01-01

phenomenon could make the navigator change ship’s speed and heading, and these remedial actions could make the vessel escape the bifurcation. This chapter proposes non-parametric methods to detect the onset of parametric roll resonance. Theoretical conditions for parametric resonance are re...... on experimental data from towing tank tests and data from a container ship passing an Atlantic storm....

Impact and Cost Evaluation of Electric Vehicle Integration on Medium Voltage Distribution Networks

DEFF Research Database (Denmark)

Wu, Qiuwei; Cheng, Lin; Pineau, Ulysse

2013-01-01

This paper presents the analysis of the impact of electric vehicle (EV) integration on medium voltage (MV) distribution networks and the cost evaluation of replacing the overloaded grid components. A number of EV charging scenarios have been studied. A 10 kV grid from the Bornholm Island...... in the city area has been used to carry out case studies. The case study results show that the secondary transformers are the bottleneck of the MV distribution networks and the increase of EV penetration leads to the overloading of secondary transformers. The cost of the transformer replacement has been...

Drive Control Scheme of Electric Power Assisted Wheelchair Based on Neural Network Learning of Human Wheelchair Operation Characteristics

Science.gov (United States)

Tanohata, Naoki; Seki, Hirokazu

This paper describes a novel drive control scheme of electric power assisted wheelchairs based on neural network learning of human wheelchair operation characteristics. “Electric power assisted wheelchair” which enhances the drive force of the operator by employing electric motors is expected to be widely used as a mobility support system for elderly and disabled people. However, some handicapped people with paralysis of the muscles of one side of the body cannot maneuver the wheelchair as desired because of the difference in the right and left input force. Therefore, this study proposes a neural network learning system of such human wheelchair operation characteristics and a drive control scheme with variable distribution and assistance ratios. Some driving experiments will be performed to confirm the effectiveness of the proposed control system.

SAInt – A novel quasi-dynamic model for assessing security of supply in coupled gas and electricity transmission networks

NARCIS (Netherlands)

Pambour, Kwabena Addo; Cakir Erdener, Burcin; Bolado-Lavin, Ricardo; Dijkema, Gerhard P.J.

2017-01-01

The integration of renewable energy sources into existing electric power systems is connected with an increased interdependence between natural gas and electricity transmission networks. To analyse this interdependence and its impact on security of supply, we developed a novel quasi-dynamic

Electrical network limitations on large-scale deployment of offshore wind energy

Energy Technology Data Exchange (ETDEWEB)

Power, P.B.

2001-07-01

In this report we have summarised the electrical network limitations to the connection of offshore wind energy schemes in the United Kingdom. The offshore wind resource in the United Kingdom could enable energy production in excess of 230 TWh to be realised. The wind resource of the UK coast should enable 4 GW of wind generation (13.4 GWh assuming 30% load factor) to be developed, providing appropriate technical and commercial arrangements can be made. (author)

Nonparametric Tree-Based Predictive Modeling of Storm Outages on an Electric Distribution Network.

Science.gov (United States)

He, Jichao; Wanik, David W; Hartman, Brian M; Anagnostou, Emmanouil N; Astitha, Marina; Frediani, Maria E B

2017-03-01

This article compares two nonparametric tree-based models, quantile regression forests (QRF) and Bayesian additive regression trees (BART), for predicting storm outages on an electric distribution network in Connecticut, USA. We evaluated point estimates and prediction intervals of outage predictions for both models using high-resolution weather, infrastructure, and land use data for 89 storm events (including hurricanes, blizzards, and thunderstorms). We found that spatially BART predicted more accurate point estimates than QRF. However, QRF produced better prediction intervals for high spatial resolutions (2-km grid cells and towns), while BART predictions aggregated to coarser resolutions (divisions and service territory) more effectively. We also found that the predictive accuracy was dependent on the season (e.g., tree-leaf condition, storm characteristics), and that the predictions were most accurate for winter storms. Given the merits of each individual model, we suggest that BART and QRF be implemented together to show the complete picture of a storm's potential impact on the electric distribution network, which would allow for a utility to make better decisions about allocating prestorm resources. © 2016 Society for Risk Analysis.

Hyperbolic and semi-parametric models in finance

Science.gov (United States)

Bingham, N. H.; Kiesel, Rüdiger

2001-02-01

The benchmark Black-Scholes-Merton model of mathematical finance is parametric, based on the normal/Gaussian distribution. Its principal parametric competitor, the hyperbolic model of Barndorff-Nielsen, Eberlein and others, is briefly discussed. Our main theme is the use of semi-parametric models, incorporating the mean vector and covariance matrix as in the Markowitz approach, plus a non-parametric part, a scalar function incorporating features such as tail-decay. Implementation is also briefly discussed.

Co-simulation with DIgSILENT PowerFactory and Matlab: Optimal integration of plug-in electric vehicles in distribution networks

DEFF Research Database (Denmark)

García-Villalobos, J.; Zamora, I.; Marinelli, Mattia

2017-01-01

Smart grid concept is gaining more and more importance in electric power systems. In near term, electric grids will be more intelligent, interconnected and decentralised. Dealing with a significant number of distributed resources in a smart way, frequently requires the use of optimal control tech...... mean square (RMS) simulations on DIgSILENT PowerFactory. As an example, the implementation of a smart charging control for plug-in electric vehicles in electric distribution networks is explained....

Parametric Sensitivity Analysis of Oscillatory Delay Systems with an Application to Gene Regulation.

Science.gov (United States)

Ingalls, Brian; Mincheva, Maya; Roussel, Marc R

2017-07-01

A parametric sensitivity analysis for periodic solutions of delay-differential equations is developed. Because phase shifts cause the sensitivity coefficients of a periodic orbit to diverge, we focus on sensitivities of the extrema, from which amplitude sensitivities are computed, and of the period. Delay-differential equations are often used to model gene expression networks. In these models, the parametric sensitivities of a particular genotype define the local geometry of the evolutionary landscape. Thus, sensitivities can be used to investigate directions of gradual evolutionary change. An oscillatory protein synthesis model whose properties are modulated by RNA interference is used as an example. This model consists of a set of coupled delay-differential equations involving three delays. Sensitivity analyses are carried out at several operating points. Comments on the evolutionary implications of the results are offered.

Adaptive complementary fuzzy self-recurrent wavelet neural network controller for the electric load simulator system

Directory of Open Access Journals (Sweden)

Wang Chao

2016-03-01

Full Text Available Due to the complexities existing in the electric load simulator, this article develops a high-performance nonlinear adaptive controller to improve the torque tracking performance of the electric load simulator, which mainly consists of an adaptive fuzzy self-recurrent wavelet neural network controller with variable structure (VSFSWC and a complementary controller. The VSFSWC is clearly and easily used for real-time systems and greatly improves the convergence rate and control precision. The complementary controller is designed to eliminate the effect of the approximation error between the proposed neural network controller and the ideal feedback controller without chattering phenomena. Moreover, adaptive learning laws are derived to guarantee the system stability in the sense of the Lyapunov theory. Finally, the hardware-in-the-loop simulations are carried out to verify the feasibility and effectiveness of the proposed algorithms in different working styles.

Design principles of electrical synaptic plasticity.

Science.gov (United States)

O'Brien, John

2017-09-08

Essentially all animals with nervous systems utilize electrical synapses as a core element of communication. Electrical synapses, formed by gap junctions between neurons, provide rapid, bidirectional communication that accomplishes tasks distinct from and complementary to chemical synapses. These include coordination of neuron activity, suppression of voltage noise, establishment of electrical pathways that define circuits, and modulation of high order network behavior. In keeping with the omnipresent demand to alter neural network function in order to respond to environmental cues and perform tasks, electrical synapses exhibit extensive plasticity. In some networks, this plasticity can have dramatic effects that completely remodel circuits or remove the influence of certain cell types from networks. Electrical synaptic plasticity occurs on three distinct time scales, ranging from milliseconds to days, with different mechanisms accounting for each. This essay highlights principles that dictate the properties of electrical coupling within networks and the plasticity of the electrical synapses, drawing examples extensively from retinal networks. Copyright © 2017 The Author. Published by Elsevier B.V. All rights reserved.

Probabilistic Harmonic Calculation in Distribution Networks with Electric Vehicle Charging Stations

Directory of Open Access Journals (Sweden)

Jianxue Wang

2014-01-01

Full Text Available Integrating EV charging station into power grid will bring impacts on power system, among which the most significant one is the harmonic pollution on distribution networks. Due to the uncertainty of the EV charging process, the harmonic currents brought by EV charging stations have a random nature. This paper proposed a mathematical simulation method for studying the working status of charging stations, which considers influencing factors including random leaving factor, electricity price, and waiting time. Based on the proposed simulation method, the probability distribution of the harmonic currents of EV charging stations is obtained and used in the calculation of the probability harmonic power flow. Then the impacts of EVs and EV charging stations on distribution networks can be analyzed. In the case study, the proposed simulation and analysis method is implemented on the IEEE-34 distribution network. The influences of EV arrival rates, the penetration rate, and the accessing location of EV charging station are also investigated. Results show that this research has good potential in guiding the planning and construction of charging station.

The neural network approach to parton fitting

International Nuclear Information System (INIS)

Rojo, Joan; Latorre, Jose I.; Del Debbio, Luigi; Forte, Stefano; Piccione, Andrea

2005-01-01

We introduce the neural network approach to global fits of parton distribution functions. First we review previous work on unbiased parametrizations of deep-inelastic structure functions with faithful estimation of their uncertainties, and then we summarize the current status of neural network parton distribution fits

Day-ahead price forecasting of electricity markets by a new feature selection algorithm and cascaded neural network technique

International Nuclear Information System (INIS)

Amjady, Nima; Keynia, Farshid

2009-01-01

With the introduction of restructuring into the electric power industry, the price of electricity has become the focus of all activities in the power market. Electricity price forecast is key information for electricity market managers and participants. However, electricity price is a complex signal due to its non-linear, non-stationary, and time variant behavior. In spite of performed research in this area, more accurate and robust price forecast methods are still required. In this paper, a new forecast strategy is proposed for day-ahead price forecasting of electricity markets. Our forecast strategy is composed of a new two stage feature selection technique and cascaded neural networks. The proposed feature selection technique comprises modified Relief algorithm for the first stage and correlation analysis for the second stage. The modified Relief algorithm selects candidate inputs with maximum relevancy with the target variable. Then among the selected candidates, the correlation analysis eliminates redundant inputs. Selected features by the two stage feature selection technique are used for the forecast engine, which is composed of 24 consecutive forecasters. Each of these 24 forecasters is a neural network allocated to predict the price of 1 h of the next day. The whole proposed forecast strategy is examined on the Spanish and Australia's National Electricity Markets Management Company (NEMMCO) and compared with some of the most recent price forecast methods.

Technique applied in electrical power distribution for Satellite Launch Vehicle

Directory of Open Access Journals (Sweden)

João Maurício Rosário

2010-09-01

Full Text Available The Satellite Launch Vehicle electrical network, which is currently being developed in Brazil, is sub-divided for analysis in the following parts: Service Electrical Network, Controlling Electrical Network, Safety Electrical Network and Telemetry Electrical Network. During the pre-launching and launching phases, these electrical networks are associated electrically and mechanically to the structure of the vehicle. In order to succeed in the integration of these electrical networks it is necessary to employ techniques of electrical power distribution, which are proper to Launch Vehicle systems. This work presents the most important techniques to be considered in the characterization of the electrical power supply applied to Launch Vehicle systems. Such techniques are primarily designed to allow the electrical networks, when submitted to the single-phase fault to ground, to be able of keeping the power supply to the loads.

Simple heterogeneity parametrization for sea surface temperature and chlorophyll

Science.gov (United States)

Skákala, Jozef; Smyth, Timothy J.

2016-06-01

Using satellite maps this paper offers a complex analysis of chlorophyll & SST heterogeneity in the shelf seas around the southwest of the UK. The heterogeneity scaling follows a simple power law and is consequently parametrized by two parameters. It is shown that in most cases these two parameters vary only relatively little with time. The paper offers a detailed comparison of field heterogeneity between different regions. How much heterogeneity is in each region preserved in the annual median data is also determined. The paper explicitly demonstrates how one can use these results to calculate representative measurement area for in situ networks.

Polarized DIS Structure Functions from Neural Networks

International Nuclear Information System (INIS)

Del Debbio, L.; Guffanti, A.; Piccione, A.

2007-01-01

We present a parametrization of polarized Deep-Inelastic-Scattering (DIS) structure functions based on Neural Networks. The parametrization provides a bias-free determination of the probability measure in the space of structure functions, which retains information on experimental errors and correlations. As an example we discuss the application of this method to the study of the structure function g 1 p (x,Q 2 )

Trimaran Resistance Artificial Neural Network

Science.gov (United States)

2011-01-01

11th International Conference on Fast Sea Transportation FAST 2011, Honolulu, Hawaii, USA, September 2011 Trimaran Resistance Artificial Neural Network Richard...Trimaran Resistance Artificial Neural Network 5a. CONTRACT NUMBER 5b. GRANT NUMBER 5c. PROGRAM ELEMENT NUMBER 6. AUTHOR(S) 5d. PROJECT NUMBER 5e... Artificial Neural Network and is restricted to the center and side-hull configurations tested. The value in the parametric model is that it is able to

Electric Arc Furnace Modeling with Artificial Neural Networks and Arc Length with Variable Voltage Gradient

Directory of Open Access Journals (Sweden)

Raul Garcia-Segura

2017-09-01

Full Text Available Electric arc furnaces (EAFs contribute to almost one third of the global steel production. Arc furnaces use a large amount of electrical energy to process scrap or reduced iron and are relevant to study because small improvements in their efficiency account for significant energy savings. Optimal controllers need to be designed and proposed to enhance both process performance and energy consumption. Due to the random and chaotic nature of the electric arcs, neural networks and other soft computing techniques have been used for modeling EAFs. This study proposes a methodology for modeling EAFs that considers the time varying arc length as a relevant input parameter to the arc furnace model. Based on actual voltages and current measurements taken from an arc furnace, it was possible to estimate an arc length suitable for modeling the arc furnace using neural networks. The obtained results show that the model reproduces not only the stable arc conditions but also the unstable arc conditions, which are difficult to identify in a real heat process. The presented model can be applied for the development and testing of control systems to improve furnace energy efficiency and productivity.

Relative localization in wireless sensor networks for measurement of electric fields under HVDC transmission lines.

Science.gov (United States)

Cui, Yong; Wang, Qiusheng; Yuan, Haiwen; Song, Xiao; Hu, Xuemin; Zhao, Luxing

2015-02-04

In the wireless sensor networks (WSNs) for electric field measurement system under the High-Voltage Direct Current (HVDC) transmission lines, it is necessary to obtain the electric field distribution with multiple sensors. The location information of each sensor is essential to the correct analysis of measurement results. Compared with the existing approach which gathers the location information by manually labelling sensors during deployment, the automatic localization can reduce the workload and improve the measurement efficiency. A novel and practical range-free localization algorithm for the localization of one-dimensional linear topology wireless networks in the electric field measurement system is presented. The algorithm utilizes unknown nodes' neighbor lists based on the Received Signal Strength Indicator (RSSI) values to determine the relative locations of nodes. The algorithm is able to handle the exceptional situation of the output permutation which can effectively improve the accuracy of localization. The performance of this algorithm under real circumstances has been evaluated through several experiments with different numbers of nodes and different node deployments in the China State Grid HVDC test base. Results show that the proposed algorithm achieves an accuracy of over 96% under different conditions.

Relative Localization in Wireless Sensor Networks for Measurement of Electric Fields under HVDC Transmission Lines

Directory of Open Access Journals (Sweden)

Yong Cui

2015-02-01

Full Text Available In the wireless sensor networks (WSNs for electric field measurement system under the High-Voltage Direct Current (HVDC transmission lines, it is necessary to obtain the electric field distribution with multiple sensors. The location information of each sensor is essential to the correct analysis of measurement results. Compared with the existing approach which gathers the location information by manually labelling sensors during deployment, the automatic localization can reduce the workload and improve the measurement efficiency. A novel and practical range-free localization algorithm for the localization of one-dimensional linear topology wireless networks in the electric field measurement system is presented. The algorithm utilizes unknown nodes’ neighbor lists based on the Received Signal Strength Indicator (RSSI values to determine the relative locations of nodes. The algorithm is able to handle the exceptional situation of the output permutation which can effectively improve the accuracy of localization. The performance of this algorithm under real circumstances has been evaluated through several experiments with different numbers of nodes and different node deployments in the China State Grid HVDC test base. Results show that the proposed algorithm achieves an accuracy of over 96% under different conditions.

Joint Modelling of Structural and Functional Brain Networks

DEFF Research Database (Denmark)

Andersen, Kasper Winther; Herlau, Tue; Mørup, Morten

-parametric Bayesian network model which allows for joint modelling and integration of multiple networks. We demonstrate the model’s ability to detect vertices that share structure across networks jointly in functional MRI (fMRI) and diffusion MRI (dMRI) data. Using two fMRI and dMRI scans per subject, we establish...

All-thin-film PZT/FeGa Multiferroic Cantilevers and Their Applications in Switching Devices and Parametric Amplification

Science.gov (United States)

Wang, Yi; Onuta, Tiberiu-Dan; Long, Chris; Lofland, Samuel; Takeuchi, Ichiro

2014-03-01

We are investigating the characteristics of microfabricated PZT/FeGa multiferroic cantilevers. The cantilevers can be driven by AC or DC magnetic and electric field, and the device response can be read off as a piezo-induced voltage. We can use the multiple input parameters to operate the devices in a variety of manners for different applications. They include electromagnetic energy harvesting, pulse triggered nonlinear memory devices, and parametrically amplified ME sensors. Due to the competition of anisotropy and Zeeman energies, the mechanical resonant frequency of the cantilevers was found to follow a hysteresis behavior with DC bias magnetic field applied in the cantilever easy axis. We can also control and tune the occurrence of nonlinear bifurcation in the frequency spectrum. The resulting hysteresis in the frequency spectrum can be used to make switching devices, where the input can be DC electric and magnetic fields, as well as pulses of AC fields. We have also demonstrated parametric pumping of the response from an AC magnetic field using frequency-doubled AC electric field. The enhanced equivalent ME coefficient is as high as 10 million V/(cm*Oe), when the pumping voltage is very close to a threshold voltage. The quality factor also increases from 2000 to 80000 with pumping.

On the parallelization of a three-parametric log-logistic estimation algorithm

OpenAIRE

Asenjo-Plaza, Rafael; Rodríguez, Andrés; Navarro, Ángeles; Fernández-Madrigal, Juan Antonio; Cruz-Martin, Ana Maria

2014-01-01

Networked telerobots transmit data from its sensors to the remote controller. To provide guarantees on the time requirements of these systems it is mandatory to keep the transmission time delays below a given threshold, and to that end we should predict them. In this paper we tackle the parallelization of a procedure that models these stochastic time delays. More precisely, we focus on fitting the time delay signal using a three-parametrical log-logistic distribution. Since, the robot and the...

Parametric nanomechanical amplification at very high frequency.

Science.gov (United States)

Karabalin, R B; Feng, X L; Roukes, M L

2009-09-01

Parametric resonance and amplification are important in both fundamental physics and technological applications. Here we report very high frequency (VHF) parametric resonators and mechanical-domain amplifiers based on nanoelectromechanical systems (NEMS). Compound mechanical nanostructures patterned by multilayer, top-down nanofabrication are read out by a novel scheme that parametrically modulates longitudinal stress in doubly clamped beam NEMS resonators. Parametric pumping and signal amplification are demonstrated for VHF resonators up to approximately 130 MHz and provide useful enhancement of both resonance signal amplitude and quality factor. We find that Joule heating and reduced thermal conductance in these nanostructures ultimately impose an upper limit to device performance. We develop a theoretical model to account for both the parametric response and nonequilibrium thermal transport in these composite nanostructures. The results closely conform to our experimental observations, elucidate the frequency and threshold-voltage scaling in parametric VHF NEMS resonators and sensors, and establish the ultimate sensitivity limits of this approach.

Parametric and non-parametric approach for sensory RATA (Rate-All-That-Apply) method of ledre profile attributes

Science.gov (United States)

Hastuti, S.; Harijono; Murtini, E. S.; Fibrianto, K.

2018-03-01

This current study is aimed to investigate the use of parametric and non-parametric approach for sensory RATA (Rate-All-That-Apply) method. Ledre as Bojonegoro unique local food product was used as point of interest, in which 319 panelists were involved in the study. The result showed that ledre is characterized as easy-crushed texture, sticky in mouth, stingy sensation and easy to swallow. It has also strong banana flavour with brown in colour. Compared to eggroll and semprong, ledre has more variances in terms of taste as well the roll length. As RATA questionnaire is designed to collect categorical data, non-parametric approach is the common statistical procedure. However, similar results were also obtained as parametric approach, regardless the fact of non-normal distributed data. Thus, it suggests that parametric approach can be applicable for consumer study with large number of respondents, even though it may not satisfy the assumption of ANOVA (Analysis of Variances).

Experimental Sentinel-2 LAI estimation using parametric, non-parametric and physical retrieval methods - A comparison

NARCIS (Netherlands)

Verrelst, Jochem; Rivera, Juan Pablo; Veroustraete, Frank; Muñoz-Marí, Jordi; Clevers, J.G.P.W.; Camps-Valls, Gustau; Moreno, José

2015-01-01

Given the forthcoming availability of Sentinel-2 (S2) images, this paper provides a systematic comparison of retrieval accuracy and processing speed of a multitude of parametric, non-parametric and physically-based retrieval methods using simulated S2 data. An experimental field dataset (SPARC),

Unified triminimal parametrizations of quark and lepton mixing matrices

International Nuclear Information System (INIS)

He Xiaogang; Li Shiwen; Ma Boqiang

2009-01-01

We present a detailed study on triminimal parametrizations of quark and lepton mixing matrices with different basis matrices. We start with a general discussion on the triminimal expansion of the mixing matrix and on possible unified quark and lepton parametrization using quark-lepton complementarity. We then consider several interesting basis matrices and compare the triminimal parametrizations with the Wolfenstein-like parametrizations. The usual Wolfenstein parametrization for quark mixing is a triminimal expansion around the unit matrix as the basis. The corresponding quark-lepton complementarity lepton mixing matrix is a triminimal expansion around the bimaximal basis. Current neutrino oscillation data show that the lepton mixing matrix is very well represented by the tribimaximal mixing. It is natural to take it as an expanding basis. The corresponding zeroth order basis for quark mixing in this case makes the triminimal expansion converge much faster than the usual Wolfenstein parametrization. The triminimal expansion based on tribimaximal mixing can be converted to the Wolfenstein-like parametrizations discussed in the literature. We thus have a unified description between different kinds of parametrizations for quark and lepton sectors: the standard parametrizations, the Wolfenstein-like parametrizations, and the triminimal parametrizations.

An innovation diffusion model of a local electricity network that is influenced by internal and external factors

Science.gov (United States)

Hattam, Laura; Greetham, Danica Vukadinović

2018-01-01

Haynes et al. (1977) derived a nonlinear differential equation to determine the spread of innovations within a social network across space and time. This model depends upon the imitators and the innovators within the social system, where the imitators respond to internal influences, whilst the innovators react to external factors. Here, this differential equation is applied to simulate the uptake of a low-carbon technology (LCT) within a real local electricity network that is situated in the UK. This network comprises of many households that are assigned to certain feeders. Firstly, travelling wave solutions of Haynes' model are used to predict adoption times as a function of the imitation and innovation influences. Then, the grid that represents the electricity network is created so that the finite element method (FEM) can be implemented. Next, innovation diffusion is modelled with Haynes' equation and the FEM, where varying magnitudes of the internal and external pressures are imposed. Consequently, the impact of these model parameters is investigated. Moreover, LCT adoption trajectories at fixed feeder locations are calculated, which give a macroscopic understanding of the uptake behaviour at specific network sites. Lastly, the adoption of LCTs at a household level is examined, where microscopic and macroscopic approaches are combined.

On the kinetic theory of parametric resonance in relativistic plasma

International Nuclear Information System (INIS)

El-Ashry, M.Y.

1982-08-01

The instability of relativistic hot plasma located in high-frequency external electric field is studied. The dispersion relation, in the case when the plasma electrons have relativistic oscillatory motion, is obtained. It is shown that if the electron Deby's radius is less than the wave length of plasma oscillation and far from the resonance on the overtones of the external field frequency, the oscillation build-up is possible. It is also shown that taking into account the relativistic motion of electrons leads to a considerable decrease in the frequency at which the parametric resonance takes place. (author)

Electrical responses and spontaneous activity of human iPS-derived neuronal networks characterized for three-month culture with 4096-electrode arrays

Directory of Open Access Journals (Sweden)

Hayder eAmin

2016-03-01

Full Text Available The recent availability of human induced pluripotent stem cells (hiPSCs holds great promise as a novel source of human-derived neurons for cell and tissue therapies as well as for in vitro drug screenings that might replace the use of animal models. However, there is still a considerable lack of knowledge on the functional properties of hiPSC-derived neuronal networks, thus limiting their application. Here, upon optimization of cell culture protocols, we demonstrate that both spontaneous and evoked electrical spiking activities of these networks can be characterized on-chip by taking advantage of the resolution provided by CMOS multielectrode arrays (CMOS-MEAs. These devices feature a large and closely-spaced array of 4096 simultaneously recording electrodes and multi-site on-chip electrical stimulation. Our results show that networks of human-derived neurons can respond to electrical stimulation with a physiological repertoire of spike waveforms after three months of cell culture, a period of time during which the network undergoes the expression of developing patterns of spontaneous spiking activity. To achieve this, we have investigated the impact on the network formation and on the emerging network-wide functional properties induced by different biochemical substrates, i.e. poly-dl-ornithine (PDLO, poly-l-ornithine (PLO, and polyethylenimine (PEI, that were used as adhesion promoters for the cell culture. Interestingly, we found that neuronal networks grown on PDLO coated substrates show significantly higher spontaneous firing activity, reliable responses to low-frequency electrical stimuli, and an appropriate level of PSD-95 that may denote a physiological neuronal maturation profile and synapse stabilization. However, our results also suggest that even three-month culture might not be sufficient for human-derived neuronal network maturation. Taken together, our results highlight the tight relationship existing between substrate coatings

Pyramidal resistor networks for electrical impedance tomography with partial boundary measurements

International Nuclear Information System (INIS)

Borcea, L; Mamonov, A V; Druskin, V; Vasquez, F Guevara

2010-01-01

We introduce an inversion algorithm for electrical impedance tomography (EIT) with partial boundary measurements in two dimensions. It gives stable and fast reconstructions using sparse parameterizations of the unknown conductivity on optimal grids that are computed as part of the inversion. We follow the approach in Borcea et al (2008 Inverse Problems 24 035013) and Vasquez (2006 PhD thesis Rice University, Houston, TX, USA) that connects inverse discrete problems for resistor networks to continuum EIT problems, using optimal grids. The algorithm in Borcea et al (2008 Inverse Problems 24 035013) and Vasquez (2006 PhD Thesis Rice University, Houston, TX, USA) is based on circular resistor networks, and solves the EIT problem with full boundary measurements. It is extended in Borcea et al (2010 Inverse Problems 26 045010) to EIT with partial boundary measurements, using extremal quasi-conformal mappings that transform the problem to one with full boundary measurements. Here we introduce a different class of optimal grids, based on resistor networks with pyramidal topology, that is better suited for the partial measurements setup. We prove the unique solvability of the discrete inverse problem for these networks and develop an algorithm for finding them from the measurements of the Dirichlet to Neumann map. Then, we show how to use the networks to define the optimal grids and to approximate the unknown conductivity. We assess the performance of our approach with numerical simulations and compare the results with those in Borcea et al (2010)

Three perspectives on the evolving electric vehicles innovation network of Finland

Energy Technology Data Exchange (ETDEWEB)

Rasanen, R.-S.; Temmes, A.; Lovio, R.

2013-06-01

This report compiles the electric vehicle related work done in 2012 in the project: Future innovation and technology policy for sustainable system-level transitions: the case of transport (FIP-Trans). The project focuses on researching alternative and complementary socio-technical pathways and related policy options for sustainable transition in the Finnish transport sector. The project is financed by Tekes - the Finnish Funding Agency for Technology and Innovation. Analysis is continued in 2013. In this paper we study the evolving electric vehicle innovation network of Finland. The analysis is built on combining the theoretical aspects of Strategic Niche Management and Technology Innovation Systems. Based on the literature we develop a framework for analyzing the development of innovation networks. The framework contains four steps. The first step is the identification and analysis of the main actors and their activities. The second step is the identification and analysis of the main events affecting the development of the industry. This step is based on the use of event structure analysis. The third step consists of the analysis of development of the architecture of the system while the fourth step deals with the description and analysis of the niche and innovation system development processes in a combined manner. The data consists of interviews, policy and consultation papers, newspaper articles, press releases and other enterprise publications and of private databases containing financial information of the enterprises. Based on the theoretical framework, the four separate, but complementing qualitative analyses were made. The electric vehicle niche has evolved through the interaction of private and public sector actors. The involvement of public sector affected strongly on the evolution of the system arenas and was an important event for the resource mobilization of the industry. As with other Finnish industries, the importance of the international dimension

Incident Duration Modeling Using Flexible Parametric Hazard-Based Models

Directory of Open Access Journals (Sweden)

Ruimin Li

2014-01-01

Full Text Available Assessing and prioritizing the duration time and effects of traffic incidents on major roads present significant challenges for road network managers. This study examines the effect of numerous factors associated with various types of incidents on their duration and proposes an incident duration prediction model. Several parametric accelerated failure time hazard-based models were examined, including Weibull, log-logistic, log-normal, and generalized gamma, as well as all models with gamma heterogeneity and flexible parametric hazard-based models with freedom ranging from one to ten, by analyzing a traffic incident dataset obtained from the Incident Reporting and Dispatching System in Beijing in 2008. Results show that different factors significantly affect different incident time phases, whose best distributions were diverse. Given the best hazard-based models of each incident time phase, the prediction result can be reasonable for most incidents. The results of this study can aid traffic incident management agencies not only in implementing strategies that would reduce incident duration, and thus reduce congestion, secondary incidents, and the associated human and economic losses, but also in effectively predicting incident duration time.

Performance assessment of electric power generations using an adaptive neural network algorithm

International Nuclear Information System (INIS)

Azadeh, A.; Ghaderi, S.F.; Anvari, M.; Saberi, M.

2007-01-01

Efficiency frontier analysis has been an important approach of evaluating firms' performance in private and public sectors. There have been many efficiency frontier analysis methods reported in the literature. However, the assumptions made for each of these methods are restrictive. Each of these methodologies has its strength as well as major limitations. This study proposes a non-parametric efficiency frontier analysis method based on the adaptive neural network technique for measuring efficiency as a complementary tool for the common techniques of the efficiency studies in the previous studies. The proposed computational method is able to find a stochastic frontier based on a set of input-output observational data and do not require explicit assumptions about the function structure of the stochastic frontier. In this algorithm, for calculating the efficiency scores, a similar approach to econometric methods has been used. Moreover, the effect of the return to scale of decision-making units (DMUs) on its efficiency is included and the unit used for the correction is selected by notice of its scale (under constant return to scale assumption). An example using real data is presented for illustrative purposes. In the application to the power generation sector of Iran, we find that the neural network provide more robust results and identifies more efficient units than the conventional methods since better performance patterns are explored. Moreover, principle component analysis (PCA) is used to verify the findings of the proposed algorithm

Hybrid Forecasting Approach Based on GRNN Neural Network and SVR Machine for Electricity Demand Forecasting

Directory of Open Access Journals (Sweden)

Weide Li

2017-01-01

Full Text Available Accurate electric power demand forecasting plays a key role in electricity markets and power systems. The electric power demand is usually a non-linear problem due to various unknown reasons, which make it difficult to get accurate prediction by traditional methods. The purpose of this paper is to propose a novel hybrid forecasting method for managing and scheduling the electricity power. EEMD-SCGRNN-PSVR, the proposed new method, combines ensemble empirical mode decomposition (EEMD, seasonal adjustment (S, cross validation (C, general regression neural network (GRNN and support vector regression machine optimized by the particle swarm optimization algorithm (PSVR. The main idea of EEMD-SCGRNN-PSVR is respectively to forecast waveform and trend component that hidden in demand series to substitute directly forecasting original electric demand. EEMD-SCGRNN-PSVR is used to predict the one week ahead half-hour’s electricity demand in two data sets (New South Wales (NSW and Victorian State (VIC in Australia. Experimental results show that the new hybrid model outperforms the other three models in terms of forecasting accuracy and model robustness.

Assessing feasibility of IT-enabled networked value consellations: A case study in the electricity sector

NARCIS (Netherlands)

Derzsi, Z.; Gordijn, J.; Kok, J.K.; Akkermans, J.M.; Tan, Y.H.; Krogstie, J.; Opdahl, A.L.; Sindre, G.

2007-01-01

Innovative networked value constellations, such as Cisco or Dell, are often enabled by Information Technology (IT). The same holds for the Distributed Electricity Balancing Service (DBS), which we present in this case study. To explore feasibility of such constellations while designing them, we need

Explicit/multi-parametric model predictive control (MPC) of linear discrete-time systems by dynamic and multi-parametric programming

KAUST Repository

Kouramas, K.I.

2011-08-01

This work presents a new algorithm for solving the explicit/multi- parametric model predictive control (or mp-MPC) problem for linear, time-invariant discrete-time systems, based on dynamic programming and multi-parametric programming techniques. The algorithm features two key steps: (i) a dynamic programming step, in which the mp-MPC problem is decomposed into a set of smaller subproblems in which only the current control, state variables, and constraints are considered, and (ii) a multi-parametric programming step, in which each subproblem is solved as a convex multi-parametric programming problem, to derive the control variables as an explicit function of the states. The key feature of the proposed method is that it overcomes potential limitations of previous methods for solving multi-parametric programming problems with dynamic programming, such as the need for global optimization for each subproblem of the dynamic programming step. © 2011 Elsevier Ltd. All rights reserved.

Parametric Jominy profiles predictor based on neural networks

Directory of Open Access Journals (Sweden)

Valentini, R.

2005-12-01

Full Text Available The paper presents a method for the prediction of the Jominy hardness profiles of steels for microalloyed Boron steel which is based on neural networks. The Jominy profile has been parameterized and the parameters, which are a sort of "compact representation" of the profile itself, are linked to the steel chemical composition through a neural network. Numerical results are presented and discussed.

El trabajo presenta un método de estimación de perfiles de dureza Jominy para aceros microaleados al boro basado en redes neuronales. Los parámetros de perfil Jominy, que constituyen una especie de "representación compacta" del perfil mismo, son determinados y puestos en relación con la composición química del acero mediante una red neuronal. Los resultados numéricos son expuestos y discutidos.

Optimizing Electric Vehicle Coordination Over a Heterogeneous Mesh Network in a Scaled-Down Smart Grid Testbed

DEFF Research Database (Denmark)

Bhattarai, Bishnu Prasad; Lévesque, Martin; Maier, Martin

2015-01-01

High penetration of renewable energy sources and electric vehicles (EVs) create power imbalance and congestion in the existing power network, and hence causes significant problems in the control and operation. Despite investing huge efforts from the electric utilities, governments, and researchers......, smart grid (SG) is still at the developmental stage to address those issues. In this regard, a smart grid testbed (SGT) is desirable to develop, analyze, and demonstrate various novel SG solutions, namely demand response, real-time pricing, and congestion management. In this paper, a novel SGT...... is developed in a laboratory by scaling a 250 kVA, 0.4 kV real low-voltage distribution feeder down to 1 kVA, 0.22 kV. Information and communication technology is integrated in the scaled-down network to establish real-time monitoring and control. The novelty of the developed testbed is demonstrated...

Thermodynamic model and parametric analysis of a tubular SOFC module

Science.gov (United States)

Campanari, Stefano

Solid oxide fuel cells (SOFCs) have been considered in the last years as one of the most promising technologies for very high-efficiency electric energy generation from natural gas, both with simple fuel cell plants and with integrated gas turbine-fuel cell systems. Among the SOFC technologies, tubular SOFC stacks with internal reforming have emerged as one of the most mature technology, with a serious potential for a future commercialization. In this paper, a thermodynamic model of a tubular SOFC stack, with natural gas feeding, internal reforming of hydrocarbons and internal air preheating is proposed. In the first section of the paper, the model is discussed in detail, analyzing its calculating equations and tracing its logical steps; the model is then calibrated on the available data for a recently demonstrated tubular SOFC prototype plant. In the second section of the paper, it is carried out a detailed parametric analysis of the stack working conditions, as a function of the main operating parameters. The discussion of the results of the thermodynamic and parametric analysis yields interesting considerations about partial load SOFC operation and load regulation, and about system design and integration with gas turbine cycles.

Non-electrical uses of thermal energy generated in the production of fissile fuel in fusion--fission reactors: a comparative economic parametric analysis for a hybrid with or without synthetic fuel production

International Nuclear Information System (INIS)

Tai, A.S.; Krakowski, R.A.

1979-01-01

A parametric analysis has been carried out for testing the sensitivity of the synfuel production cost in relation to crucial economic and technologic quantities (investment costs of hybrid and synfuel plant, energy multiplication of the fission blanket, recirculating power fraction of the fusion driver, etc.). In addition, a minimum synfuel selling price has been evaluated, from which the fission--fusion--synfuel complex brings about a higher economic benefit than does the fusion--fission hybrid entirely devoted to fissile-fuel and electricity generation. Assuming an electricity cost of 2.7 cents/kWh, an annual investment cost per power unit of 4.2 to 6 $/GJ (132 to 189 k$/MWty) for the fission--fusion complex and 1.5 to 3 $/GJ (47 to 95 k$/MWty) for the synfuel plant, the synfuel production net cost (i.e., revenue = cost) varies between 6.5 and 8.6 $/GJ. These costs can compete with those obtained by other processes (natural gas reforming, resid partial oxidation, coal gasification, nuclear fission, solar electrolysis, etc.). This study points out a potential use of the fusion--fission hybrid other than fissile-fuel and electricity generation

Building and interconnecting hydrogen networks: Insights from the electricity and gas experience in Europe

International Nuclear Information System (INIS)

Bento, Nuno

2008-01-01

This paper aims to investigate the transition to a new energy system based on hydrogen in the European liberalized framework. After analyzing the literature on the hydrogen infrastructure needs in Europe, we estimate the size and scope of the transition challenge. We take the theoretical framework of network economics to analyze early hydrogen infrastructure needs. Therefore, several concepts are applied to hydrogen economics such as demand club effects, scale economies on large infrastructures, scope economies, and positive socio-economical externalities. Based on the examples of the electricity and natural gas industry formation in Europe, we argue for public intervention in order to create conditions to reach more rapidly the critical size of the network and to prompt network externalities, allowing for the market diffusion of and, thus, an effective transition to the new energy system

A Neural Parametric Singing Synthesizer Modeling Timbre and Expression from Natural Songs

Directory of Open Access Journals (Sweden)

Merlijn Blaauw

2017-12-01

Full Text Available We recently presented a new model for singing synthesis based on a modified version of the WaveNet architecture. Instead of modeling raw waveform, we model features produced by a parametric vocoder that separates the influence of pitch and timbre. This allows conveniently modifying pitch to match any target melody, facilitates training on more modest dataset sizes, and significantly reduces training and generation times. Nonetheless, compared to modeling waveform directly, ways of effectively handling higher-dimensional outputs, multiple feature streams and regularization become more important with our approach. In this work, we extend our proposed system to include additional components for predicting F0 and phonetic timings from a musical score with lyrics. These expression-related features are learned together with timbrical features from a single set of natural songs. We compare our method to existing statistical parametric, concatenative, and neural network-based approaches using quantitative metrics as well as listening tests.

Identifying groups of critical edges in a realistic electrical network by multi-objective genetic algorithms

International Nuclear Information System (INIS)

Zio, E.; Golea, L.R.; Rocco S, C.M.

2012-01-01

In this paper, an analysis of the vulnerability of the Italian high-voltage (380 kV) electrical transmission network (HVIET) is carried out for the identification of the groups of links (or edges, or arcs) most critical considering the network structure and flow. Betweenness centrality and network connection efficiency variations are considered as measures of the importance of the network links. The search of the most critical ones is carried out within a multi-objective optimization problem aimed at the maximization of the importance of the groups and minimization of their dimension. The problem is solved using a genetic algorithm. The analysis is based only on information on the topology of the network and leads to the identification of the most important single component, couples of components, triplets and so forth. The comparison of the results obtained with those reported by previous analyses indicates that the proposed approach provides useful complementary information.

Theoretical and algorithmic advances in multi-parametric programming and control

KAUST Repository

Pistikopoulos, Efstratios N.; Dominguez, Luis; Panos, Christos; Kouramas, Konstantinos; Chinchuluun, Altannar

2012-01-01

This paper presents an overview of recent theoretical and algorithmic advances, and applications in the areas of multi-parametric programming and explicit/multi-parametric model predictive control (mp-MPC). In multi-parametric programming, advances include areas such as nonlinear multi-parametric programming (mp-NLP), bi-level programming, dynamic programming and global optimization for multi-parametric mixed-integer linear programming problems (mp-MILPs). In multi-parametric/explicit MPC (mp-MPC), advances include areas such as robust multi-parametric control, multi-parametric nonlinear MPC (mp-NMPC) and model reduction in mp-MPC. A comprehensive framework for multi-parametric programming and control is also presented. Recent applications include a hydrogen storage device, a fuel cell power generation system, an unmanned autonomous vehicle (UAV) and a hybrid pressure swing adsorption (PSA) system. © 2012 Springer-Verlag.

Theoretical and algorithmic advances in multi-parametric programming and control

KAUST Repository

Pistikopoulos, Efstratios N.

2012-04-21

This paper presents an overview of recent theoretical and algorithmic advances, and applications in the areas of multi-parametric programming and explicit/multi-parametric model predictive control (mp-MPC). In multi-parametric programming, advances include areas such as nonlinear multi-parametric programming (mp-NLP), bi-level programming, dynamic programming and global optimization for multi-parametric mixed-integer linear programming problems (mp-MILPs). In multi-parametric/explicit MPC (mp-MPC), advances include areas such as robust multi-parametric control, multi-parametric nonlinear MPC (mp-NMPC) and model reduction in mp-MPC. A comprehensive framework for multi-parametric programming and control is also presented. Recent applications include a hydrogen storage device, a fuel cell power generation system, an unmanned autonomous vehicle (UAV) and a hybrid pressure swing adsorption (PSA) system. © 2012 Springer-Verlag.

Computing and the electrical transport properties of coupled quantum networks

Science.gov (United States)

Cain, Casey Andrew

In this dissertation a number of investigations were conducted on ballistic quantum networks in the mesoscopic range. In this regime, the wave nature of electron transport under the influence of transverse magnetic fields leads to interesting applications for digital logic and computing circuits. The work specifically looks at characterizing a few main areas that would be of interest to experimentalists who are working in nanostructure devices, and is organized as a series of papers. The first paper analyzes scaling relations and normal mode charge distributions for such circuits in both isolated and open (terminals attached) form. The second paper compares the flux-qubit nature of quantum networks to the well-established spintronics theory. The results found exactly contradict the conventional school of thought for what is required for quantum computation. The third paper investigates the requirements and limitations of extending the Thevenin theorem in classic electric circuits to ballistic quantum transport. The fourth paper outlines the optimal functionally complete set of quantum circuits that can completely satisfy all sixteen Boolean logic operations for two variables.

Integration of Electric Vehicles into the Power Distribution Network with a Modified Capacity Allocation Mechanism

DEFF Research Database (Denmark)

Hu, Junjie; Morais, Hugo; Sousa, Tiago

2017-01-01

-VPPs, considering the case of EVs charging and discharging. The three mechanisms include: (1) a market-based approach; (2) a pro-rata approach; and (3) a newly-proposed constrained market-based approach. A case study considering a 37-bus distribution network and high penetration of electric vehicles is presented...

Self-sustained firing activities of the cortical network with plastic rules in weak AC electrical fields

International Nuclear Information System (INIS)

Qin Ying-Mei; Wang Jiang; Men Cong; Zhao Jia; Wei Xi-Le; Deng Bin

2012-01-01

Both external and endogenous electrical fields widely exist in the environment of cortical neurons. The effects of a weak alternating current (AC) field on a neural network model with synaptic plasticity are studied. It is found that self-sustained rhythmic firing patterns, which are closely correlated with the cognitive functions, are significantly modified due to the self-organizing of the network in the weak AC field. The activities of the neural networks are affected by the synaptic connection strength, the external stimuli, and so on. In the presence of learning rules, the synaptic connections can be modulated by the external stimuli, which will further enhance the sensitivity of the network to the external signal. The properties of the external AC stimuli can serve as control parameters in modulating the evolution of the neural network. (interdisciplinary physics and related areas of science and technology)

Optimal interval for major maintenance actions in electricity distribution networks

Energy Technology Data Exchange (ETDEWEB)

Louit, Darko; Pascual, Rodrigo [Centro de Mineria, Pontificia Universidad Catolica de Chile, Av. Vicuna MacKenna, 4860 Santiago (Chile); Banjevic, Dragan [Centre for Maintenance Optimization and Reliability Engineering, University of Toronto, 5 King' s College Rd., Toronto, Ontario (Canada)

2009-09-15

Many systems require the periodic undertaking of major (preventive) maintenance actions (MMAs) such as overhauls in mechanical equipment, reconditioning of train lines, resurfacing of roads, etc. In the long term, these actions contribute to achieving a lower rate of occurrence of failures, though in many cases they increase the intensity of the failure process shortly after performed, resulting in a non-monotonic trend for failure intensity. Also, in the special case of distributed assets such as communications and energy networks, pipelines, etc., it is likely that the maintenance action takes place sequentially over an extended period of time, implying that different sections of the network underwent the MMAs at different periods. This forces the development of a model based on a relative time scale (i.e. time since last major maintenance event) and the combination of data from different sections of a grid, under a normalization scheme. Additionally, extended maintenance times and sequential execution of the MMAs make it difficult to identify failures occurring before and after the preventive maintenance action. This results in the loss of important information for the characterization of the failure process. A simple model is introduced to determine the optimal MMA interval considering such restrictions. Furthermore, a case study illustrates the optimal tree trimming interval around an electricity distribution network. (author)

Analysis of the reactive power consumption and the harmonics in the network by the non-linear electrical loads

Energy Technology Data Exchange (ETDEWEB)

Cogo, Joao Roberto [Escola Federal de Engenharia de Itajuba, MG (Brazil)

1994-12-31

The non linear electrical loads can give rise to a number of disturbances in electrical power networks. Among them, the high consumption of relative power is to be noted and so is the several harmonic components which may be injected in the industry system and very often in the utility system. So, by using appropriate technical considerations, as well as measurements in typical special electrical loads, such negative effects are analyzed and ways of minimizing them are suggested. (author) 3 refs., 11 figs., 6 tabs.

Co-Design Based Lateral Motion Control of All-Wheel-Independent-Drive Electric Vehicles with Network Congestion

Directory of Open Access Journals (Sweden)

Wanke Cao

2017-10-01

Full Text Available All-wheel-independent-drive electric vehicles (AWID-EVs have considerable advantages in terms of energy optimization, drivability and driving safety due to the remarkable actuation flexibility of electric motors. However, in their current implementations, various real-time data in the vehicle control system are exchanged via a controller area network (CAN, which causes network congestion and network-induced delays. These problems could lead to systemic instability and make the system integration difficult. The goal of this paper is to provide a design methodology that can cope with all these challenges for the lateral motion control of AWID-EVs. Firstly, a continuous-time model of an AWID-EV is derived. Then an expression for determining upper and lower bounds on the delays caused by CAN is presented and with which a discrete-time model of the closed-loop CAN system is derived. An expression on the bandwidth utilization is introduced as well. Thirdly, a co-design based scheme combining a period-dependent linear quadratic regulator (LQR and a dynamic period scheduler is designed for the resulting model and the stability criterion is also derived. The results of simulations and hard-in-loop (HIL experiments show that the proposed methodology can effectively guarantee the stability of the vehicle lateral motion control while obviously declining the network congestion.

Electric power balance sheet 2013

International Nuclear Information System (INIS)

2014-01-01

The mission of RTE, the French electricity Transportation grid, a public service assignment, is to balance the electricity supply and demand in real time. This report presents RTE's technical results for the year 2013: stabilisation of the electricity consumption in France, high level of hydropower generation, fast evolution of the European power network, electricity markets in a transition situation, adaptation of RTE's network to the evolutions of the energy system

Fiber optical parametric amplifiers in optical communication systems

Science.gov (United States)

Marhic (†), Michel E; Andrekson, Peter A; Petropoulos, Periklis; Radic, Stojan; Peucheret, Christophe; Jazayerifar, Mahmoud

2015-01-01

The prospects for using fiber optical parametric amplifiers (OPAs) in optical communication systems are reviewed. Phase-insensitive amplifiers (PIAs) and phase-sensitive amplifiers (PSAs) are considered. Low-penalty amplification at/or near 1 Tb/s has been achieved, for both wavelength- and time-division multiplexed formats. High-quality mid-span spectral inversion has been demonstrated at 0.64 Tb/s, avoiding electronic dispersion compensation. All-optical amplitude regeneration of amplitude-modulated signals has been performed, while PSAs have been used to demonstrate phase regeneration of phase-modulated signals. A PSA with 1.1-dB noise figure has been demonstrated, and preliminary wavelength-division multiplexing experiments have been performed with PSAs. 512 Gb/s have been transmitted over 6,000 km by periodic phase conjugation. Simulations indicate that PIAs could reach data rate x reach products in excess of 14,000 Tb/s × km in realistic wavelength-division multiplexed long-haul networks. Technical challenges remaining to be addressed in order for fiber OPAs to become useful for long-haul communication networks are discussed. PMID:25866588

PARAMETRIC DRAWINGS VS. AUTOLISP

OpenAIRE

PRUNĂ Liviu; SLONOVSCHI Andrei

2015-01-01

In this paper the authors make a critical analysis of the advantages offered by the parametric drawing use by comparison with the AutoLISP computer programs used when it comes about the parametric design. Studying and analysing these two work models the authors have got to some ideas and conclusions which should be considered in the moment in that someone must to decide if it is the case to elaborate a software, using the AutoLISP language, or to establish the base rules that must be followed...

Methods for calculation of undelivered electricity in medium voltage network that is not integrated into the remote control system

Directory of Open Access Journals (Sweden)

Vrcelj Nada

2013-01-01

Full Text Available The method is based on data obtained from the so-called. hand-held measuring current at 10 kV voltage level and from reports of outages at reclosers that are installed in a part of network that is observed. At first, is calculates the electrical load of the main distribution power lines, and then simulates the corresponding power flow and calculates the undelivered electricity. The method was applied to parts of the network PD ED Belgrade that are not in the remote control system and is developed for the purpose of considering the effects of automation in the 10 kV PD ED Belgrade.

Development of network-based multichannel neuromuscular electrical stimulation system for stroke rehabilitation.

Science.gov (United States)

Qu, Hongen; Xie, Yongji; Liu, Xiaoxuan; He, Xin; Hao, Manzhao; Bao, Yong; Xie, Qing; Lan, Ning

2016-01-01

Neuromuscular electrical stimulation (NMES) is a promising assistive technology for stroke rehabilitation. Here we present the design and development of a multimuscle stimulation system as an emerging therapy for people with paretic stroke. A network-based multichannel NMES system was integrated based on dual bus architecture of communication and an H-bridge current regulator with a power booster. The structure of the system was a body area network embedded with multiple stimulators and a communication protocol of controlled area network to transmit muscle stimulation parameter information to individual stimulators. A graphical user interface was designed to allow clinicians to specify temporal patterns and muscle stimulation parameters. We completed and tested a prototype of the hardware and communication software modules of the multichannel NMES system. The prototype system was first verified in nondisabled subjects for safety, and then tested in subjects with stroke for feasibility with assisting multijoint movements. Results showed that synergistic stimulation of multiple muscles in subjects with stroke improved performance of multijoint movements with more natural velocity profiles at elbow and shoulder and reduced acromion excursion due to compensatory trunk rotation. The network-based NMES system may provide an innovative solution that allows more physiological activation of multiple muscles in multijoint task training for patients with stroke.

Using of alternative sources of the electric power on telecommunication network of Uzbekistan

International Nuclear Information System (INIS)

Abdullaev, D.A.; Isaev, R.I.; Makhkamdzhanov, V.M.; Mansurov, M.S.

1997-01-01

The article presents the talk on the using of alternative sources of the electric power on telecommunication network of Uzbekistan given at the International Workshop on applied solar energy held in Tashkent (Uzbekistan) in June 1997. As an alternative source the combined solar-wind power plant on the basis of solar cells battery and wind-generator is proposed. The efficiency of proposed system is considered. (A.A.D.)

On-road magnetic emissions prediction of electric cars in terms of driving dynamics using neural networks

NARCIS (Netherlands)

Wefky, Ahmed M.; Espinosa, Felipe; Leferink, Frank Bernardus Johannes; Gardel, Alfredo; Vogt-Ardatjew, R.A.

2013-01-01

This paper presents a novel artificial neural network (ANN) model estimating vehicle-level radiated magnetic emissions of an electric car as a function of the corresponding driving pattern. Real world electromagnetic interference (EMI) experiments have been realized in a semi-anechoic chamber using

Analysis of Voltage Support by Electric Vehicles and Photovoltaic in a Real Danish Low Voltage Network

DEFF Research Database (Denmark)

Knezovic, Katarina; Marinelli, Mattia; Juul Møller, René

2014-01-01

of incorporating electric vehicles (EVs) in a low voltage distribution network with high penetration of photovoltaic installations (PVs), and focuses on analysing potential voltage support functions from EVs and PVs. In addition, the paper evaluates the benefits that reactive power control may provide...

Assessing the market power due to the network constraints in competitive electricity markets

International Nuclear Information System (INIS)

Bompard, E.; Ma, Y.C.; Napoli, R.; Jiang, C.W.

2006-01-01

The physical and operational constraints of the network pose very specific problems to market power analysis in the oligopolistic electricity markets. This paper presents a direct analytical approach to find the market equilibrium based on a supply function game model. The model is exploited to undertake a sensitivity analysis of the producer surplus with reference to the line flow limits under a DC power flow model for network representation. Two different kinds of indices, that can capture the market power arising under network constraints, are proposed. The first set of indices is the location privilege (LP), that measure the effect of the generators positioning in the grid on their surplus under perfect competition. The second set is for the network market power (NMP) indices that take into account the strategic behaviors of the producers that may take advantage of the congestion of the transmission lines. The indices allow for a ranking of the lines in terms of the market power they can induce and, in this respect, they may help the market regulator to focus on the network weakness in terms of the possible market outcomes under the market power behaviors from the supply side. The application of the proposed indices is illustrated with reference to the IEEE 30-bus test system. (author)

Overview of electrical energy in January 2009

International Nuclear Information System (INIS)

2009-01-01

The purpose of this report is to provide information on the results of operation of the French public transmission network and power system during the past month. Information comes from different sources: electricity generators, ERDF, METEOFRANCE, RTE. The information provided concerns: - the internal electricity consumption (perimeter France), Results at end of past month and trend over last 12 months; - the balance of physical electrical energy flows in France on the RTE network: net injections into the RTE network; net deliveries at the terminals of the RTE network; - consumption and physical exchanges (noteworthy data); - the electricity market: contractual electricity exchanges with foreign countries (exports, imports, trend); balancing mechanism - balance responsible entities; notification of new installations for transmission network development. This document presents the above information for January 2009. (J.S.)

Overview of electrical energy in April 2009

International Nuclear Information System (INIS)

2009-01-01

The purpose of this report is to provide information on the results of operation of the French public transmission network and power system during the past month. Information comes from different sources: electricity generators, ERDF, METEOFRANCE, RTE. The information provided concerns: - the internal electricity consumption (perimeter France), Results at end of past month and trend over last 12 months; - the balance of physical electrical energy flows in France on the RTE network: net injections into the RTE network; net deliveries at the terminals of the RTE network; - consumption and physical exchanges (noteworthy data); - the electricity market: contractual electricity exchanges with foreign countries (exports, imports, trend); balancing mechanism - balance responsible entities; notification of new installations for transmission network development. This document presents the above information for April 2009. (J.S.)

Overview of electrical energy in May 2009

International Nuclear Information System (INIS)

2009-01-01

The purpose of this report is to provide information on the results of operation of the French public transmission network and power system during the past month. Information comes from different sources: electricity generators, ERDF, METEOFRANCE, RTE. The information provided concerns: - the internal electricity consumption (perimeter France), Results at end of past month and trend over last 12 months; - the balance of physical electrical energy flows in France on the RTE network: net injections into the RTE network; net deliveries at the terminals of the RTE network; - consumption and physical exchanges (noteworthy data); - the electricity market: contractual electricity exchanges with foreign countries (exports, imports, trend); balancing mechanism - balance responsible entities; notification of new installations for transmission network development. This document presents the above information for May 2009. (J.S.)

Overview of electrical energy in March 2009

International Nuclear Information System (INIS)

2009-01-01

The purpose of this report is to provide information on the results of operation of the French public transmission network and power system during the past month. Information comes from different sources: electricity generators, ERDF, METEOFRANCE, RTE. The information provided concerns: - the internal electricity consumption (perimeter France), Results at end of past month and trend over last 12 months; - the balance of physical electrical energy flows in France on the RTE network: net injections into the RTE network; net deliveries at the terminals of the RTE network; - consumption and physical exchanges (noteworthy data); - the electricity market: contractual electricity exchanges with foreign countries (exports, imports, trend); balancing mechanism - balance responsible entities; notification of new installations for transmission network development. This document presents the above information for March 2009. (J.S.)

Managing the output of intermittent sources of electricity: Managers of distribution networks at the center of smart grids

International Nuclear Information System (INIS)

Gallean, Gilles

2013-01-01

A literal revolution is under way in electricity grids owing to: the rapid decentralized production of electricity, the emergence of an active management of demand, the announcement of new means of storage, and the development of new uses, such as electric vehicles. These changes will gradually happen, differently depending on the country and region; but they will combine to form a system that, to be managed, will call for more intelligence, robots and electronics. At the junction between the production and consumption of electricity, distribution network managers must oversee the new system's technical complexity, limit rising costs and guarantee the quality of the services expected by clients

Estimating technical efficiency in the hospital sector with panel data: a comparison of parametric and non-parametric techniques.

Science.gov (United States)

Siciliani, Luigi

2006-01-01

Policy makers are increasingly interested in developing performance indicators that measure hospital efficiency. These indicators may give the purchasers of health services an additional regulatory tool to contain health expenditure. Using panel data, this study compares different parametric (econometric) and non-parametric (linear programming) techniques for the measurement of a hospital's technical efficiency. This comparison was made using a sample of 17 Italian hospitals in the years 1996-9. Highest correlations are found in the efficiency scores between the non-parametric data envelopment analysis under the constant returns to scale assumption (DEA-CRS) and several parametric models. Correlation reduces markedly when using more flexible non-parametric specifications such as data envelopment analysis under the variable returns to scale assumption (DEA-VRS) and the free disposal hull (FDH) model. Correlation also generally reduces when moving from one output to two-output specifications. This analysis suggests that there is scope for developing performance indicators at hospital level using panel data, but it is important that extensive sensitivity analysis is carried out if purchasers wish to make use of these indicators in practice.

Assessing the Potential of Plug-in Electric Vehicles in Active Distribution Networks

DEFF Research Database (Denmark)

Kordheili, Reza Ahmadi; Pourmousavi, Seyyed Ali; Savaghebi, Mehdi

2016-01-01

A multi-objective optimization algorithm is proposed in this paper to increase the penetration level of renewable energy sources (RESs) in distribution networks by intelligent management of plug-in electric vehicle (PEV) storage. The proposed algorithm is defined to manage the reverse power flow ...... demonstrate the capability of the algorithm in increasing solar power penetration in the grid up to 50%, depending on the PEV penetration level and the freedom of the system operator in managing the available PEV storage....

Artificial Neural Network Maximum Power Point Tracker for Solar Electric Vehicle

Institute of Scientific and Technical Information of China (English)

Theodore Amissah OCRAN; CAO Junyi; CAO Binggang; SUN Xinghua

2005-01-01

This paper proposes an artificial neural network maximum power point tracker (MPPT) for solar electric vehicles. The MPPT is based on a highly efficient boost converter with insulated gate bipolar transistor (IGBT) power switch. The reference voltage for MPPT is obtained by artificial neural network (ANN) with gradient descent momentum algorithm. The tracking algorithm changes the duty-cycle of the converter so that the PV-module voltage equals the voltage corresponding to the MPPT at any given insolation, temperature, and load conditions. For fast response, the system is implemented using digital signal processor (DSP). The overall system stability is improved by including a proportional-integral-derivative (PID) controller, which is also used to match the reference and battery voltage levels. The controller, based on the information supplied by the ANN, generates the boost converter duty-cycle. The energy obtained is used to charge the lithium ion battery stack for the solar vehicle. The experimental and simulation results show that the proposed scheme is highly efficient.

Study of transmitting electric power utility communications in IP network. Transmission of existing electric power utility communications in best effort type IP network under delay constraint; Denryokuyo tsushin kaisen no IP mo eno shuyo kento. Chien jikan seiyakuka ni okeru best effort gata IP mo eno kison denryokuyo tsushin kaisen no shuyo

Energy Technology Data Exchange (ETDEWEB)

Miyake, H.

2000-07-01

Since IP network does best effort behavior fundamentally, it always generates delay time and delay variation. For this reason, IP network has been unsuitable to transmit real time data such as a voice. However, in recent years, the technologies which transmit real time data in IP network, e.g. VoIP, have spread. If it is possible to transmit the existing electric power utility communications in IP network using these technologies, total network cost can be reduced by the reduction of required bandwidth and the simplification of communication network systems. In this report, it is examined quantitatively whether end-end delay time of the existing electric power utility communications, e.g. on-line, telephone, carrier relay, CDT (cyclic digital transmission equipment), video conference, ITV(industrial television), is within their permission delay time when they are transmitted in the best effort type IP network. (author)

Nonlinear parametric phenomena in plasma during radio frequency heating in the ion cyclotron frequency range

International Nuclear Information System (INIS)

Stepanov, K.N.

1996-01-01

Parametric phenomena in plasma which occur due to varying electric fields with the ion cyclotron frequency are reviewed. Beam-like lower hybrid instability emerges in strong pumping fields provided that the transverse relative velocity of particles is larger than the ion thermal speed (υ Ti ). The resulting turbulence and the following numerous manifestations observed experimentally are addressed. The turbulence may prove important for experiments aimed at plasma production or radio frequency (RF) cleaning of metallic surfaces of vacuum chambers in stellarators, tokamaks and helicon devices. In contrast, for a weak field (U Ti ) the kinetic parametric instabilities of ion cyclotron oscillations arise due to electrons. The issues of the turbulence, mathematical modelling, its role in turbulent heating observed on the torsatron Uragan-3M, decay instabilities associated with ion cyclotron oscillations and the triggering of ion quasimodes are considered. (author)

Methods for Probabilistic Fault Diagnosis: An Electrical Power System Case Study

Science.gov (United States)

Ricks, Brian W.; Mengshoel, Ole J.

2009-01-01

Health management systems that more accurately and quickly diagnose faults that may occur in different technical systems on-board a vehicle will play a key role in the success of future NASA missions. We discuss in this paper the diagnosis of abrupt continuous (or parametric) faults within the context of probabilistic graphical models, more specifically Bayesian networks that are compiled to arithmetic circuits. This paper extends our previous research, within the same probabilistic setting, on diagnosis of abrupt discrete faults. Our approach and diagnostic algorithm ProDiagnose are domain-independent; however we use an electrical power system testbed called ADAPT as a case study. In one set of ADAPT experiments, performed as part of the 2009 Diagnostic Challenge, our system turned out to have the best performance among all competitors. In a second set of experiments, we show how we have recently further significantly improved the performance of the probabilistic model of ADAPT. While these experiments are obtained for an electrical power system testbed, we believe they can easily be transitioned to real-world systems, thus promising to increase the success of future NASA missions.

Absolute decay parametric instability of high-temperature plasma

International Nuclear Information System (INIS)

Zozulya, A.A.; Silin, V.P.; Tikhonchuk, V.T.

1986-01-01

A new absolute decay parametric instability having wide spatial localization region is shown to be possible near critical plasma density. Its excitation is conditioned by distributed feedback of counter-running Langmuir waves occurring during parametric decay of incident and reflected pumping wave components. In a hot plasma with the temperature of the order of kiloelectronvolt its threshold is lower than that of a known convective decay parametric instability. Minimum absolute instability threshold is shown to be realized under conditions of spatial parametric resonance of higher orders

Comparison and Evaluation of the Performance of Various Types of Neural Networks for Planning Issues Related to Optimal Management of Charging and Discharging Electric Cars in Intelligent Power Grids

Directory of Open Access Journals (Sweden)

Arash Moradzaeh

2018-01-01

Full Text Available The use of electric vehicles in addition to reducing environmental concerns can play a significant role in reducing the peak and filling the characteristic valleys of the daily network load. In other words, in the context of smart grids, it is possible to improve the battery of electric vehicles by scheduling charging and discharging processes. In this research, the issue of controlling the charge and discharge of electric vehicles was evaluated using a variety of neural models, until the by examining the effect of the growth rate of the penetration level of electric vehicles of the hybrid type that can be connected to the distribution network, the results of the charge management and discharge model of the proposed response are examined. The results indicate that due to increased penetration of these cars is increased the amount of responses to charge and discharge management. In this research, a variety of neural network methods, a neural network method using Multilayer Perceptron Training (MLP, b neural network method using Jordan Education (RNN, c neural network method using training (RBF Was evaluated based on parameters such as reduction of training error, reduction of network testing error, duration of run and number of replications for each one. The final results indicate that electric vehicles can be used as scattered power plants, and can be useful for regulating the frequency and regulation of network voltages and the supply of peak traffic. This also reduces peak charges and incidental costs, which ultimately helps to further network stability. Finally, the charge and discharge management response reflects the fact that intelligent network-based models have the ability to manage the charge and discharge of electric vehicles, and among the models the amount of error reduction training and testing is very favourable for both RNN, MLP.

Reliability Indicators of Urban Electric Network Schemes for Supply of Second and Third Category Consumers

Directory of Open Access Journals (Sweden)

M. A. Korotkevich

2012-01-01

Full Text Available The paper considers two schemes of the urban distributive electric network for supply of the second and third category consumers for whom indicators of reliability have been determined.As for a network scheme of the 2nd category it has been determined that while installing low-oil and vacuum switches at a distributive point the most remote transformer substation has the highest non-availability  factor which is higher of the corresponding non-availability  factor of the nearest transformer substation by 1,21–1,23 fold  accordingly.As for a network scheme of the 3rd category consumers it has been obtained the data that reliability of consumers receiving supply from bus-bars of transformer substations with 0,38 kW voltage changes  significantly (by 1,2–1,9-fold while changing a breakpoint of the network with 10 kW voltage.

Nonscaling parametrization of hadronic spectra and dual parton model

International Nuclear Information System (INIS)

Gaponenko, O.N.

2001-01-01

Using the popular Wdowczyk-Wolfendale parametrization (WW-parametrization) as an example one studies restrictions imposed by a dual parton model for different nonscaling parametrizations of the pulsed hadron spectra in soft hadron-hadron and hadron-nuclear interactions. One derived a new parametrization free from basic drawback of the WW-formulae. In the central range the determined parametrization show agreement with the Wdowczyk-Wolfendale formula, but in contrast to the last-named one it does not result in contradiction with the experiment due to fast reduction of inelastic factor reduction with energy increase [ru

Parametric Methods for Order Tracking Analysis

DEFF Research Database (Denmark)

Nielsen, Jesper Kjær; Jensen, Tobias Lindstrøm

2017-01-01

Order tracking analysis is often used to find the critical speeds at which structural resonances are excited by a rotating machine. Typically, order tracking analysis is performed via non-parametric methods. In this report, however, we demonstrate some of the advantages of using a parametric method...

Explicit/multi-parametric model predictive control (MPC) of linear discrete-time systems by dynamic and multi-parametric programming

KAUST Repository

Kouramas, K.I.; Faí sca, N.P.; Panos, C.; Pistikopoulos, E.N.

2011-01-01

This work presents a new algorithm for solving the explicit/multi- parametric model predictive control (or mp-MPC) problem for linear, time-invariant discrete-time systems, based on dynamic programming and multi-parametric programming techniques

Macromechanical Parametric Amplification

DEFF Research Database (Denmark)

Neumeyer, Stefan

between the two peaks can be altered. The first experimental bistable amplified steady-state responses are also reported. The derived analytical models and experimental setups can readily be extended to investigate other factors. Some of the results are also applicable to the more general field of systems...... for energy harvesting. Using analytical, numerical, and experimental methods, the thesis focuses on superthreshold pumping (above the systems parametric instability threshold), nonlinear effects, frequency response backbones, and frequency detuning effects for parametric amplifiers. Part one of the thesis...... covers superthreshold pumping and nonlinear effects. Superthresh-old pumping produces some useful characteristics. For instance, strong superthreshold pumping yields a high gain even though nonlinear effects tend to reduce it. In addition, a narrower excitation phase range is realized for which...

Comparative Study of Parametric and Non-parametric Approaches in Fault Detection and Isolation

DEFF Research Database (Denmark)

Katebi, S.D.; Blanke, M.; Katebi, M.R.

This report describes a comparative study between two approaches to fault detection and isolation in dynamic systems. The first approach uses a parametric model of the system. The main components of such techniques are residual and signature generation for processing and analyzing. The second...... approach is non-parametric in the sense that the signature analysis is only dependent on the frequency or time domain information extracted directly from the input-output signals. Based on these approaches, two different fault monitoring schemes are developed where the feature extraction and fault decision...

Tremor Detection Using Parametric and Non-Parametric Spectral Estimation Methods: A Comparison with Clinical Assessment

Science.gov (United States)

Martinez Manzanera, Octavio; Elting, Jan Willem; van der Hoeven, Johannes H.; Maurits, Natasha M.

2016-01-01

In the clinic, tremor is diagnosed during a time-limited process in which patients are observed and the characteristics of tremor are visually assessed. For some tremor disorders, a more detailed analysis of these characteristics is needed. Accelerometry and electromyography can be used to obtain a better insight into tremor. Typically, routine clinical assessment of accelerometry and electromyography data involves visual inspection by clinicians and occasionally computational analysis to obtain objective characteristics of tremor. However, for some tremor disorders these characteristics may be different during daily activity. This variability in presentation between the clinic and daily life makes a differential diagnosis more difficult. A long-term recording of tremor by accelerometry and/or electromyography in the home environment could help to give a better insight into the tremor disorder. However, an evaluation of such recordings using routine clinical standards would take too much time. We evaluated a range of techniques that automatically detect tremor segments in accelerometer data, as accelerometer data is more easily obtained in the home environment than electromyography data. Time can be saved if clinicians only have to evaluate the tremor characteristics of segments that have been automatically detected in longer daily activity recordings. We tested four non-parametric methods and five parametric methods on clinical accelerometer data from 14 patients with different tremor disorders. The consensus between two clinicians regarding the presence or absence of tremor on 3943 segments of accelerometer data was employed as reference. The nine methods were tested against this reference to identify their optimal parameters. Non-parametric methods generally performed better than parametric methods on our dataset when optimal parameters were used. However, one parametric method, employing the high frequency content of the tremor bandwidth under consideration

Vibration, buckling and smart control of microtubules using piezoelectric nanoshells under electric voltage in thermal environment

Energy Technology Data Exchange (ETDEWEB)

Farajpour, A., E-mail: ariobarzan.oderj@gmail.com; Rastgoo, A.; Mohammadi, M.

2017-03-15

Piezoelectric nanomaterials such as zinc oxide (ZnO) are of low toxicity and have many biomedical applications including optical imaging, drug delivery, biosensing and harvesting biomechanical energy using hybrid nanogenerators. In this paper, the vibration, buckling and smart control of microtubules (MTs) embedded in an elastic medium in thermal environment using a piezoelectric nanoshell (PNS) are investigated. The MT and PNS are considered to be coupled by a filament network. The PNS is subjected to thermal loads and an external electric voltage which operates to control the mechanical behavior of the MT. Using the nonlocal continuum mechanics, the governing differential equations are derived. An exact solution is presented for simply supported boundary conditions. The differential quadrature method is also used to solve the governing equations for other boundary conditions. A detailed parametric study is conducted to investigate the effects of the elastic constants of surrounding medium and internal filament matrix, scale coefficient, electric voltage, the radius-to-thickness ratio of PNSs and temperature change on the smart control of MTs. It is found that the applied electric voltage can be used as an effective controlling parameter for the vibration and buckling of MTs.

Distributed control in the electricity infrastructure

International Nuclear Information System (INIS)

Kok, J.K.; Warmer, C.; Kamphuis, I.G.; Mellstrand, P.; Gustavsson, R.

2006-01-01

Different driving forces push the electricity production towards decentralization. As a result, the current electricity infrastructure is expected to evolve into a network of networks, in which all system parts communicate with each other and influence each other. Multiagent systems and electronic markets form an appropriate technology needed for control and coordination tasks in the future electricity network. We present the PowerMatcher, a market-based control concept for supply demand matching (SDM) in electricity networks. In a simulation study we show the ability of this approach to raise the simultaneousness of electricity production and consumption within (local) control clusters. This control concept can be applied in different business cases like reduction of imbalance costs in commercial portfolios or virtual power plant operation of distributed generators. Two PowerMatcher-based field test configurations are described, one currently in operation, one currently under construction

Filamentation and networking of electric currents in dense Z-pinch plasmas

International Nuclear Information System (INIS)

Kukushkin, A.B.; Rantsev-Kartinov, V.A.

2001-01-01

The results of high-resolution processing using the multilevel dynamical contrasting method of earlier experiments on linear Z-pinches are presented which illustrate formation of a dynamical percolating network woven by long-living filaments of electric current. A qualitative approach is outlined which treats long-living filaments as a classical plasma formation governed by the long-range quantum bonds provided, at the microscopical level, by nanotubes of elements of optimal valence. The self-similarity of structuring in laboratory and cosmic plasmas is shown, and examples are found of nanotube-like and/or fullerene-like structures of cosmic length scales. (author)

Filamentation and networking of electric currents in dense Z-pinch plasmas

International Nuclear Information System (INIS)

Kukushkin, A.B.; Rantsev-Kartinov, V.A.

1999-01-01

The results of high-resolution processing using the multilevel dynamical contrasting method of earlier experiments on linear Z-pinches are presented which illustrate formation of a dynamical percolating network woven by long-living filaments of electric current. A qualitative approach is outlined which treats long-living filaments as a classical plasma formation governed by the long-range quantum bonds provided, at the micro-scopical level, by nanotubes of elements of optimal valence. The self-similarity of structuring in laboratory and cosmic plasmas is shown, and examples are found of nanotube-like and/or fullerene-like structures of cosmic length scales. (author)

Zero- vs. one-dimensional, parametric vs. non-parametric, and confidence interval vs. hypothesis testing procedures in one-dimensional biomechanical trajectory analysis.

Science.gov (United States)

Pataky, Todd C; Vanrenterghem, Jos; Robinson, Mark A

2015-05-01

Biomechanical processes are often manifested as one-dimensional (1D) trajectories. It has been shown that 1D confidence intervals (CIs) are biased when based on 0D statistical procedures, and the non-parametric 1D bootstrap CI has emerged in the Biomechanics literature as a viable solution. The primary purpose of this paper was to clarify that, for 1D biomechanics datasets, the distinction between 0D and 1D methods is much more important than the distinction between parametric and non-parametric procedures. A secondary purpose was to demonstrate that a parametric equivalent to the 1D bootstrap exists in the form of a random field theory (RFT) correction for multiple comparisons. To emphasize these points we analyzed six datasets consisting of force and kinematic trajectories in one-sample, paired, two-sample and regression designs. Results showed, first, that the 1D bootstrap and other 1D non-parametric CIs were qualitatively identical to RFT CIs, and all were very different from 0D CIs. Second, 1D parametric and 1D non-parametric hypothesis testing results were qualitatively identical for all six datasets. Last, we highlight the limitations of 1D CIs by demonstrating that they are complex, design-dependent, and thus non-generalizable. These results suggest that (i) analyses of 1D data based on 0D models of randomness are generally biased unless one explicitly identifies 0D variables before the experiment, and (ii) parametric and non-parametric 1D hypothesis testing provide an unambiguous framework for analysis when one׳s hypothesis explicitly or implicitly pertains to whole 1D trajectories. Copyright © 2015 Elsevier Ltd. All rights reserved.

A model-based eco-routing strategy for electric vehicles in large urban networks

OpenAIRE

De Nunzio , Giovanni; Thibault , Laurent; Sciarretta , Antonio

2016-01-01

International audience; A novel eco-routing navigation strategy and energy consumption modeling approach for electric vehicles are presented in this work. Speed fluctuations and road network infrastructure have a large impact on vehicular energy consumption. Neglecting these effects may lead to large errors in eco-routing navigation, which could trivially select the route with the lowest average speed. We propose an energy consumption model that considers both accelerations and impact of the ...

Stellar parametrization from Gaia RVS spectra

Science.gov (United States)

Recio-Blanco, A.; de Laverny, P.; Allende Prieto, C.; Fustes, D.; Manteiga, M.; Arcay, B.; Bijaoui, A.; Dafonte, C.; Ordenovic, C.; Ordoñez Blanco, D.

2016-01-01

Context. Among the myriad of data collected by the ESA Gaia satellite, about 150 million spectra will be delivered by the Radial Velocity Spectrometer (RVS) for stars as faint as GRVS~ 16. A specific stellar parametrization will be performed on most of these RVS spectra, I.e. those with enough high signal-to-noise ratio (S/N), which should correspond to single stars that have a magnitude in the RVS band brighter than ~14.5. Some individual chemical abundances will also be estimated for the brightest targets. Aims: We describe the different parametrization codes that have been specifically developed or adapted for RVS spectra within the GSP-Spec working group of the analysis consortium. The tested codes are based on optimisation (FERRE and GAUGUIN), projection (MATISSE), or pattern-recognition methods (Artificial Neural Networks). We present and discuss each of their expected performances in the recovered stellar atmospheric parameters (effective temperature, surface gravity, overall metallicity) for B- to K-type stars. The performances for determining of [α/Fe] ratios are also presented for cool stars. Methods: Each code has been homogeneously tested with a large grid of RVS simulated synthetic spectra of BAFGK-spectral types (dwarfs and giants), with metallicities varying from 10-2.5 to 10+ 0.5 the solar metallicity, and taking variations of ±0.4 dex in the composition of the α-elements into consideration. The tests were performed for S/N ranging from ten to 350. Results: For all the stellar types we considered, stars brighter than GRVS~ 12.5 are very efficiently parametrized by the GSP-Spec pipeline, including reliable estimations of [α/Fe]. Typical internal errors for FGK metal-rich and metal-intermediate stars are around 40 K in Teff, 0.10 dex in log(g), 0.04 dex in [M/H], and 0.03 dex in [α/Fe] at GRVS = 10.3. They degrade to 155 K in Teff, 0.15 dex in log(g), 0.10 dex in [M/H], and 0.1 dex in [α/Fe] at GRVS~ 12. Similar accuracies in Teff and [M/H] are

Optimized design of micromachined electric field mills to maximize electrostatic field sensitivity