Estimation of productivity in Korean electric power plants:a semiparametric smooth coefficient model

This paper analyzes the impact of load factor, facility and generator types on the productivity of Korean electric power plants. In order to capture important differences in the effect of load policy on power output, we use a semiparametric smooth coefficient (SPSC) model that allows us to model heterogeneous performances across power plants and over time by allowing underlying technologies to be heterogeneous. The SPSC model accommodates both continuous and discrete covariates. Various specification tests are conducted to assess the performance of the SPSC model. Using a unique generator level panel dataset spanning the period 1995-2006, we find that the impact of load factor, generator and facility types on power generation varies substantially in terms of magnitude and significance across different plant characteristics. The results have strong implications for generation policy in Korea as outlined in this study.

Pulse width modulation (PWM) method for power components estimation in power meters

The scope of this paper is to present the Pulse Width Modulation (PWM) based method for Active Power (AP) and Reactive Power (RP) measurements as can be applied in Power Meters. Necessarily, the main aim of the material presented is a twofold, first to present a realization methodology of the proposed algorithm, and second to verify the algorithm’s robustness and validity. The method takes advantage of the fact that frequencies present in a power line are of a specific fundamental frequency range (a range centred on the 50 Hz or 60 Hz) and that in case of the presence of harmonics the frequencies of those dominating in the power line spectrum can be specified on the basis of the fundamental. In contrast to a number of existing methods a time delay or shifting of the input signal is not required by the method presented and the time delay by n/2 of the Current signal with respect to the Voltage signal required by many of the existing measurement techniques, does not apply in the case of the PWM method as well.

Optimal Resource Deployment in an Infostation-Based Network

This paper considers the problem of finding an optimal deployment of information resources on an InfoStation network in order to minimize the overhead and reduce the time needed to satisfy user requests for resources. The RG-Optimization problem and an approach for its solving are presented as well.

Coding together at scale:GitHub as a collaborative social network

GitHub is the most popular repository for open source code (Finley 2011). It has more than 3.5 million users, as the company declared in April 2013, and more than 10 million repositories, as of December 2013. It has a publicly accessible API and, since March 2012, it also publishes a stream of all the events occurring on public projects. Interactions among GitHub users are of a complex nature and take place in different forms. Developers create and fork repositories, push code, approve code pushed by others, bookmark their favorite projects and follow other developers to keep track of their activities. In this paper we present a characterization of GitHub, as both a social network and a collaborative platform. To the best of our knowledge, this is the first quantitative study about the interactions happening on GitHub. We analyze the logs from the service over 18 months (between March 11, 2012 and September 11, 2013), describing 183.54 million events and we obtain information about 2.19 million users and 5.68 million repositories, both growing linearly in time. We show that the distributions of the number of contributors per project, watchers per project and followers per user show a power-law-like shape. We analyze social ties and repository-mediated collaboration patterns, and we observe a remarkably low level of reciprocity of the social connections. We also measure the activity of each user in terms of authored events and we observe that very active users do not necessarily have a large number of followers. Finally, we provide a geographic characterization of the centers of activity and we investigate how distance influences collaboration.

Short-term wind power forecasting using Gaussian processes

Since wind has an intrinsically complex and stochastic nature, accurate wind power forecasts are necessary for the safety and economics of wind energy utilization. In this paper, we investigate a combination of numeric and probabilistic models: one-day-ahead wind power forecasts were made with Gaussian Processes (GPs) applied to the outputs of a Numerical Weather Prediction (NWP) model. Firstly the wind speed data from NWP was corrected by a GP. Then, as there is always a defined limit on power generated in a wind turbine due the turbine controlling strategy, a Censored GP was used to model the relationship between the corrected wind speed and power output. To validate the proposed approach, two real world datasets were used for model construction and testing. The simulation results were compared with the persistence method and Artificial Neural Networks (ANNs); the proposed model achieves about 11% improvement in forecasting accuracy (Mean Absolute Error) compared to the ANN model on one dataset, and nearly 5% improvement on another.

Functional astrocyte-neuron lactate shuttle in a human stem cell derived neuronal network

The development of stem cell-derived neuronal networks will promote experimental system development for drug screening, toxicological testing and disease modelling, providing that they mirror closely the functional competencies of their in vivo counterparts. The NT2 cell line is one of the best documented embryocarcinoma cell lines, and can be differentiated into neurons and astrocytes. Great focus has also been placed on defining the electrophysiological properties of these cells, and more recently we have investigated the functional properties of their associated astrocytes. We now show for the first time in a human stem cell derived co-culture model that these cultures are also metabolically competent and demonstrate a functional astrocyte neuron lactate shuttle (ANLS). The ANLS hypothesis proposes that during neuronal activity, glutamate released into the synaptic cleft is taken up by astrocytes and triggers glucose uptake which is converted into lactate and released via monocarboxylate transporters for neuronal use. Using mixed cultures of NT2 derived neurons and astrocytes we have shown that these cells modulate their glucose uptake in response to glutamate, an effect that was blocked by cytochalasin B and ouabain. Additionally we demonstrate that in response to increased neuronal activity and under hypoglycaemic conditions, co-cultures modulate glycogen turnover and increase lactate production. Similar results were also shown following treatment with glutamate, potassium, Isoproterenol and dbcAMP. Together these results demonstrate for the first time a functional ANLS in a human stem cell derived co-culture.

Power in distribution channels - Supplier assortment strategy for balancing power

This paper focuses on the move from buyer dominance toward interdependence between buyers and suppliers in a distribution channel. The paper introduces a case study collected through in-depth interviews and participative observations. It examines the relationships between a timber supplier and its customers in the builders' merchants sector. We stress the relevance of considering actions intended to change the power balance, rather than focusing only on trust. The power balance in a dyadic relationship is dynamic, and power positions need to be constantly re-evaluated. An important power resource is information asymmetry, manifested in the supplier's information about: products, regional and local demand, and the usage of the products. For practitioners, we highlight the possibility of exerting a non-coercive power resource, such as information asymmetry, in order to increase the relative power. Furthermore, being open about the power position between a buyer and a seller can foster a more efficient collaboration.

DC-link voltage control strategy for reducing capacitance and total harmonic distortion in single-phase grid-connected photovoltaic inverters

High-volume capacitance is required to buffer the power difference between the input and output ports in single-phase grid-connected photovoltaic inverters, which become an obstacle to high system efficiency and long device lifetime. Furthermore, total harmonic distortion becomes serious when the system runs into low power level. In this study, a comprehensive analysis is introduced for two-stage topology with the consideration of active power, DC-link (DCL) voltage, ripple and capacitance. This study proposed a comprehensive DCL voltage control strategy to minimise the DCL capacitance while maintaining a normal system operation. Furthermore, the proposed control strategy is flexible to be integrated with the pulse-skipping control that significantly improves the power quality at light power conditions. Since the proposed control strategy needs to vary DCL voltage, an active protection scheme is also introduced to prevent any voltage violation across the DCL. The proposed control strategy is evaluated by both simulation and experiments, whose results confirm the system effectiveness.

New integrated multilevel converter for switched reluctance motor drives in plug-in hybrid electric vehicles with flexible energy conversion

This paper presents an integrated multilevel converter of switched reluctance motors (SRMs) fed by a modular front-end circuit for plug-in hybrid electric vehicle (PHEV) applications. Several operating modes can be achieved by changing the on-off states of the switches in the front-end circuit. In generator driving mode, the battery bank is employed to elevate the phase voltage for fast excitation and demagnetization. In battery driving mode, the converter is reconfigured as a four-level converter, and the capacitor is used as an additional charge capacitor to produce multilevel voltage outputs, which enhances the torque capability. The operating modes of the proposed drive are explained and the phase current and voltage are analyzed in details. The battery charging is naturally achieved by the demagnetization current in motoring mode and by the regenerative current in braking mode. Moreover, the battery can be charged by the external AC source or generator through the proposed converter when the vehicle is in standstill condition. The SRM-based PHEV can operate at different speeds by coordinating the power flow between the generator and battery. Simulation in MATLAB/Simulink and experiments on a three-phase 12/8 SRM confirm the effectiveness of the proposed converter topology.

Development and verification of control and protection strategies in hybrid AC/DC power systems for smart grid applications

Modern power networks incorporate communications and information technology infrastructure into the electrical power system to create a smart grid in terms of control and operation. The smart grid enables real-time communication and control between consumers and utility companies allowing suppliers to optimize energy usage based on price preference and system technical issues. The smart grid design aims to provide overall power system monitoring, create protection and control strategies to maintain system performance, stability and security. This dissertation contributed to the development of a unique and novel smart grid test-bed laboratory with integrated monitoring, protection and control systems. This test-bed was used as a platform to test the smart grid operational ideas developed here. The implementation of this system in the real-time software creates an environment for studying, implementing and verifying novel control and protection schemes developed in this dissertation. Phasor measurement techniques were developed using the available Data Acquisition (DAQ) devices in order to monitor all points in the power system in real time. This provides a practical view of system parameter changes, system abnormal conditions and its stability and security information system. These developments provide valuable measurements for technical power system operators in the energy control centers. Phasor Measurement technology is an excellent solution for improving system planning, operation and energy trading in addition to enabling advanced applications in Wide Area Monitoring, Protection and Control (WAMPAC). Moreover, a virtual protection system was developed and implemented in the smart grid laboratory with integrated functionality for wide area applications. Experiments and procedures were developed in the system in order to detect the system abnormal conditions and apply proper remedies to heal the system. A design for DC microgrid was developed to integrate it to the AC system with appropriate control capability. This system represents realistic hybrid AC/DC microgrids connectivity to the AC side to study the use of such architecture in system operation to help remedy system abnormal conditions. In addition, this dissertation explored the challenges and feasibility of the implementation of real-time system analysis features in order to monitor the system security and stability measures. These indices are measured experimentally during the operation of the developed hybrid AC/DC microgrids. Furthermore, a real-time optimal power flow system was implemented to optimally manage the power sharing between AC generators and DC side resources. A study relating to real-time energy management algorithm in hybrid microgrids was performed to evaluate the effects of using energy storage resources and their use in mitigating heavy load impacts on system stability and operational security.

Hybrid power system intelligent operation and protection involving distributed architectures and pulsed loads

Efficient and reliable techniques for power delivery and utilization are needed to account for the increased penetration of renewable energy sources in electric power systems. Such methods are also required for current and future demands of plug-in electric vehicles and high-power electronic loads. Distributed control and optimal power network architectures will lead to viable solutions to the energy management issue with high level of reliability and security. This dissertation is aimed at developing and verifying new techniques for distributed control by deploying DC microgrids, involving distributed renewable generation and energy storage, through the operating AC power system. To achieve the findings of this dissertation, an energy system architecture was developed involving AC and DC networks, both with distributed generations and demands. The various components of the DC microgrid were designed and built including DC-DC converters, voltage source inverters (VSI) and AC-DC rectifiers featuring novel designs developed by the candidate. New control techniques were developed and implemented to maximize the operating range of the power conditioning units used for integrating renewable energy into the DC bus. The control and operation of the DC microgrids in the hybrid AC/DC system involve intelligent energy management. Real-time energy management algorithms were developed and experimentally verified. These algorithms are based on intelligent decision-making elements along with an optimization process. This was aimed at enhancing the overall performance of the power system and mitigating the effect of heavy non-linear loads with variable intensity and duration. The developed algorithms were also used for managing the charging/discharging process of plug-in electric vehicle emulators. The protection of the proposed hybrid AC/DC power system was studied. Fault analysis and protection scheme and coordination, in addition to ideas on how to retrofit currently available protection concepts and devices for AC systems in a DC network, were presented. A study was also conducted on the effect of changing the distribution architecture and distributing the storage assets on the various zones of the network on the system's dynamic security and stability. A practical shipboard power system was studied as an example of a hybrid AC/DC power system involving pulsed loads. Generally, the proposed hybrid AC/DC power system, besides most of the ideas, controls and algorithms presented in this dissertation, were experimentally verified at the Smart Grid Testbed, Energy Systems Research Laboratory. All the developments in this dissertation were experimentally verified at the Smart Grid Testbed.

Energy-efficient self -organization of wireless acoustic sensor networks for ground target tracking

With the developments in computing and communication technologies, wireless sensor networks have become popular in wide range of application areas such as health, military, environment and habitant monitoring. Moreover, wireless acoustic sensor networks have been widely used for target tracking applications due to their passive nature, reliability and low cost. Traditionally, acoustic sensor arrays built in linear, circular or other regular shapes are used for tracking acoustic sources. The maintaining of relative geometry of the acoustic sensors in the array is vital for accurate target tracking, which greatly reduces the flexibility of the sensor network. To overcome this limitation, we propose using only a single acoustic sensor at each sensor node. This design greatly improves the flexibility of the sensor network and makes it possible to deploy the sensor network in remote or hostile regions through air-drop or other stealth approaches. Acoustic arrays are capable of performing the target localization or generating the bearing estimations on their own. However, with only a single acoustic sensor, the sensor nodes will not be able to generate such measurements. Thus, self-organization of sensor nodes into virtual arrays to perform the target localization is essential. We developed an energy-efficient and distributed self-organization algorithm for target tracking using wireless acoustic sensor networks. The major error sources of the localization process were studied, and an energy-aware node selection criterion was developed to minimize the target localization errors. Using this node selection criterion, the self-organization algorithm selects a near-optimal localization sensor group to minimize the target tracking errors. In addition, a message passing protocol was developed to implement the self-organization algorithm in a distributed manner. In order to achieve extended sensor network lifetime, energy conservation was incorporated into the self-organization algorithm by incorporating a sleep-wakeup management mechanism with a novel cross layer adaptive wakeup probability adjustment scheme. The simulation results confirm that the developed self-organization algorithm provides satisfactory target tracking performance. Moreover, the energy saving analysis confirms the effectiveness of the cross layer power management scheme in achieving extended sensor network lifetime without degrading the target tracking performance.

Energy-Efficient Self-Organization of Wireless Acoustic Sensor Networks for Ground Target Tracking

With the developments in computing and communication technologies, wireless sensor networks have become popular in wide range of application areas such as health, military, environment and habitant monitoring. Moreover, wireless acoustic sensor networks have been widely used for target tracking applications due to their passive nature, reliability and low cost. Traditionally, acoustic sensor arrays built in linear, circular or other regular shapes are used for tracking acoustic sources. The maintaining of relative geometry of the acoustic sensors in the array is vital for accurate target tracking, which greatly reduces the flexibility of the sensor network. To overcome this limitation, we propose using only a single acoustic sensor at each sensor node. This design greatly improves the flexibility of the sensor network and makes it possible to deploy the sensor network in remote or hostile regions through air-drop or other stealth approaches. Acoustic arrays are capable of performing the target localization or generating the bearing estimations on their own. However, with only a single acoustic sensor, the sensor nodes will not be able to generate such measurements. Thus, self-organization of sensor nodes into virtual arrays to perform the target localization is essential. We developed an energy-efficient and distributed self-organization algorithm for target tracking using wireless acoustic sensor networks. The major error sources of the localization process were studied, and an energy-aware node selection criterion was developed to minimize the target localization errors. Using this node selection criterion, the self-organization algorithm selects a near-optimal localization sensor group to minimize the target tracking errors. In addition, a message passing protocol was developed to implement the self-organization algorithm in a distributed manner. In order to achieve extended sensor network lifetime, energy conservation was incorporated into the self-organization algorithm by incorporating a sleep-wakeup management mechanism with a novel cross layer adaptive wakeup probability adjustment scheme. The simulation results confirm that the developed self-organization algorithm provides satisfactory target tracking performance. Moreover, the energy saving analysis confirms the effectiveness of the cross layer power management scheme in achieving extended sensor network lifetime without degrading the target tracking performance.

Regulador eletromagnético de frequência aplicado no controle de velocidade de geradores eólicos

The constant necessity for new sources of renewable energy is increasingly promoting the increase of investments in this area. Among other sources, the wind power has been becoming prominent. It is important to promote the search for the improvement of the technologies involved in the topologies of the wind turbines, seeking for alternatives which enhance the gotten performance, despite the irregularity of the wind speed. This study presents a new system for speed control, in this case applied to the wind turbines - the Electromagnetic Frequency Regulator (EFR). One of the most used devices in some topologies is the mechanical gearboxes which, along with a short service life, often represent sources of noise and defects. The EFR does not need these transmission boxes, representing a technological advancement, using for that an adapted induction machine, in which the stator becomes mobile, supportive to the axis of the turbine. In the topology used in this study, the EFR also allows us to leave out the usage of the eletronic converters to establish the coupling between the generator and the electrical grid. It also the reason why it provides the possibility of obtaining the generation in alternating current, with constant voltage and frequency, where there is no electrical grid. Responsable for the mechanical speed control of the generator, the EFR can be useful in other transmission systems in which the mechanical speed control output is the objective. In addition, the EFR operates through the combination of two inputs, a mechanical and other electrical. It multiplies the possibilities of application because it is able to synergistic coupling between different arrays of energy, and, for such reasons, it enables the various sources of energy involved to be uncoupled from the network, being the synchronous generator responsible for the system connection with the electrical grid, simplifying the control strategies on the power injected in it. Experimental and simulation results are presented through this study, about a wind turbine, validating the proposal related to the efficience in the speed control of the system for different wind conditions.

Investigating the encoding of visual stimuli by forming neural circuits in the cat primary visual cortex

Contexte La connectomique, ou la cartographie des connexions neuronales, est un champ de recherche des neurosciences évoluant rapidement, promettant des avancées majeures en ce qui concerne la compréhension du fonctionnement cérébral. La formation de circuits neuronaux en réponse à des stimuli environnementaux est une propriété émergente du cerveau. Cependant, la connaissance que nous avons de la nature précise de ces réseaux est encore limitée. Au niveau du cortex visuel, qui est l’aire cérébrale la plus étudiée, la manière dont les informations se transmettent de neurone en neurone est une question qui reste encore inexplorée. Cela nous invite à étudier l’émergence des microcircuits en réponse aux stimuli visuels. Autrement dit, comment l’interaction entre un stimulus et une assemblée cellulaire est-elle mise en place et modulée? Méthodes En réponse à la présentation de grilles sinusoïdales en mouvement, des ensembles neuronaux ont été enregistrés dans la couche II/III (aire 17) du cortex visuel primaire de chats anesthésiés, à l’aide de multi-électrodes en tungstène. Des corrélations croisées ont été effectuées entre l’activité de chacun des neurones enregistrés simultanément pour mettre en évidence les liens fonctionnels de quasi-synchronie (fenêtre de ± 5 ms sur les corrélogrammes croisés corrigés). Ces liens fonctionnels dévoilés indiquent des connexions synaptiques putatives entre les neurones. Par la suite, les histogrammes peri-stimulus (PSTH) des neurones ont été comparés afin de mettre en évidence la collaboration synergique temporelle dans les réseaux fonctionnels révélés. Enfin, des spectrogrammes dépendants du taux de décharges entre neurones ou stimulus-dépendants ont été calculés pour observer les oscillations gamma dans les microcircuits émergents. Un indice de corrélation (Rsc) a également été calculé pour les neurones connectés et non connectés. Résultats Les neurones liés fonctionnellement ont une activité accrue durant une période de 50 ms contrairement aux neurones fonctionnellement non connectés. Cela suggère que les connexions entre neurones mènent à une synergie de leur inter-excitabilité. En outre, l’analyse du spectrogramme dépendant du taux de décharge entre neurones révèle que les neurones connectés ont une plus forte activité gamma que les neurones non connectés durant une fenêtre d’opportunité de 50ms. L’activité gamma de basse-fréquence (20-40 Hz) a été associée aux neurones à décharge régulière (RS) et l’activité de haute fréquence (60-80 Hz) aux neurones à décharge rapide (FS). Aussi, les neurones fonctionnellement connectés ont systématiquement un Rsc plus élevé que les neurones non connectés. Finalement, l’analyse des corrélogrammes croisés révèle que dans une assemblée neuronale, le réseau fonctionnel change selon l’orientation de la grille. Nous démontrons ainsi que l’intensité des relations fonctionnelles dépend de l’orientation de la grille sinusoïdale. Cette relation nous a amené à proposer l’hypothèse suivante : outre la sélectivité des neurones aux caractères spécifiques du stimulus, il y a aussi une sélectivité du connectome. En bref, les réseaux fonctionnels «signature » sont activés dans une assemblée qui est strictement associée à l’orientation présentée et plus généralement aux propriétés des stimuli. Conclusion Cette étude souligne le fait que l’assemblée cellulaire, plutôt que le neurone, est l'unité fonctionnelle fondamentale du cerveau. Cela dilue l'importance du travail isolé de chaque neurone, c’est à dire le paradigme classique du taux de décharge qui a été traditionnellement utilisé pour étudier l'encodage des stimuli. Cette étude contribue aussi à faire avancer le débat sur les oscillations gamma, en ce qu'elles surviennent systématiquement entre neurones connectés dans les assemblées, en conséquence d’un ajout de cohérence. Bien que la taille des assemblées enregistrées soit relativement faible, cette étude suggère néanmoins une intrigante spécificité fonctionnelle entre neurones interagissant dans une assemblée en réponse à une stimulation visuelle. Cette étude peut être considérée comme une prémisse à la modélisation informatique à grande échelle de connectomes fonctionnels.