WorldWideScience

Sample records for adaptive intelligent power

  1. Adaptive intelligent power systems: Active distribution networks

    International Nuclear Information System (INIS)

    McDonald, Jim

    2008-01-01

    Electricity networks are extensive and well established. They form a key part of the infrastructure that supports industrialised society. These networks are moving from a period of stability to a time of potentially major transition, driven by a need for old equipment to be replaced, by government policy commitments to cleaner and renewable sources of electricity generation, and by change in the power industry. This paper looks at moves towards active distribution networks. The novel transmission and distribution systems of the future will challenge today's system designs. They will cope with variable voltages and frequencies, and will offer more flexible, sustainable options. Intelligent power networks will need innovation in several key areas of information technology. Active control of flexible, large-scale electrical power systems is required. Protection and control systems will have to react to faults and unusual transient behaviour and ensure recovery after such events. Real-time network simulation and performance analysis will be needed to provide decision support for system operators, and the inputs to energy and distribution management systems. Advanced sensors and measurement will be used to achieve higher degrees of network automation and better system control, while pervasive communications will allow networks to be reconfigured by intelligent systems

  2. Design of Power Cable UAV Intelligent Patrol System Based on Adaptive Kalman Filter Fuzzy PID Control

    Directory of Open Access Journals (Sweden)

    Chen Siyu

    2017-01-01

    Full Text Available Patrol UAV has poor aerial posture stability and is largely affected by anthropic factors, which lead to some shortages such as low power cable tracking precision, captured image loss and inconvenient temperature measurement, etc. In order to solve these disadvantages, this article puts forward a power cable intelligent patrol system. The core innovation of the system is a 360° platform. This collects the position information of power cables by using far infrared sensors and carries out real-time all-direction adjustment of UAV lifting platform through the adaptive Kalman filter fuzzy PID control algorithm, so that the precise tracking of power cables is achieved. An intelligent patrol system is established to detect the faults more accurately, so that a high intelligence degree of power cable patrol system is realized.

  3. 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.

  4. Power System for Intelligent House

    Directory of Open Access Journals (Sweden)

    Michal Jahelka

    2010-01-01

    Full Text Available Power supply of intelligent houses or house phones is possible to do with standard transformer with voltage stabilizer or with intelligent power supply. Standard solution can has as a result of failure fuse blown or fire occurrence. Intelligent power supply switch off power and tests with little current whether short circuit is removed. After it resume system power supply. At the same time it cares of system backup with accumulator, informs control system about short circuit or failure net power supply, or can switch off all system power after command from control system.

  5. Using Emotional Intelligence in Personalized Adaptation

    NARCIS (Netherlands)

    Damjanovic, Violeta; Kravcik, Milos

    2007-01-01

    Damjanovic, V. & Kravcik, M. (2007). Using Emotional Intelligence in Personalized Adaptation. In V. Sugumaran (Ed.), Intelligent Information Technologies: Concepts, Methodologies, Tools, and Applications (pp. 1716-1742). IGI Publishing.

  6. Intelligent Speed Adaptation in Company Vehicles

    DEFF Research Database (Denmark)

    Agerholm, Niels; Tradisauskas, Nerius; Waagepetersen, Rasmus

    2008-01-01

    This paper describes an intelligent speed adaptation project for company vehicles. The intelligent speed adaptation function in the project is both information and incentive, which means that the intelligent speed adaptation equipment gives a warning as well as penalty points if the driver...... is speeding. Each month the driver with that monthpsilas fewest points wins an award. The paper presents results concerning speed attitude on the first three of a planned 12 months test period. In all 26 vehicles and 51 drivers from six companies participate in the project. The key result is that speeding...

  7. Self-Adaptive Systems for Machine Intelligence

    CERN Document Server

    He, Haibo

    2011-01-01

    This book will advance the understanding and application of self-adaptive intelligent systems; therefore it will potentially benefit the long-term goal of replicating certain levels of brain-like intelligence in complex and networked engineering systems. It will provide new approaches for adaptive systems within uncertain environments. This will provide an opportunity to evaluate the strengths and weaknesses of the current state-of-the-art of knowledge, give rise to new research directions, and educate future professionals in this domain. Self-adaptive intelligent systems have wide application

  8. Using Emotional Intelligence in Personalized Adaptation

    NARCIS (Netherlands)

    Damjanovic, Violeta; Kravcik, Milos

    2008-01-01

    Damjanovic, V. & Kravcik, M. (2007). Using Emotional Intelligence in Personalized Adaptation. In M. D. Lytras & A. Naeve (Eds.), Ubiquitous and Pervasive Knowledge and Learning Management (pp. 158-197). IGI Publishing.

  9. Adaptive Intelligent Ventilation Noise Control, Phase II

    Data.gov (United States)

    National Aeronautics and Space Administration — To address the NASA need for quiet on-orbit crew quarters (CQ), Physical Optics Corporation (POC) proposes to develop a new Adaptive Intelligent Ventilation Noise...

  10. Adaptive Intelligent Ventilation Noise Control, Phase I

    Data.gov (United States)

    National Aeronautics and Space Administration — To address NASA needs for quiet crew volumes in a space habitat, Physical Optics Corporation (POC) proposes to develop a new Adaptive Intelligent Ventilation Noise...

  11. Intelligent power supply controller

    International Nuclear Information System (INIS)

    Rumrill, R.S.; Reinagel, D.J.

    1991-01-01

    The authors have developed a new power supply controller which would combine 20-bit precision, simple interfacing, and versatile software control. It performs many tasks internal to the power supply and also communicates with an external host computer. Parameters can be entered and/or read over a serial link using one of the 82 command words. In addition, an optional remote control panel can be located up to thousands of feet away. This new controller will reduce the software development time normally spent by the user, while increasing the reliability of the system. The cost is less than buying the equivalent separate CAMAC system. Nonvolatile memory remembers all configuration data; one generic controller can thus be programmed to use anywhere from the smallest power supply to the largest. The controllers will be used at the Clinton P. Anderson Meson Facility at Los Alamos

  12. Next generation intelligent environments ambient adaptive systems

    CERN Document Server

    Nothdurft, Florian; Heinroth, Tobias; Minker, Wolfgang

    2016-01-01

    This book covers key topics in the field of intelligent ambient adaptive systems. It focuses on the results worked out within the framework of the ATRACO (Adaptive and TRusted Ambient eCOlogies) project. The theoretical background, the developed prototypes, and the evaluated results form a fertile ground useful for the broad intelligent environments scientific community as well as for industrial interest groups. The new edition provides: Chapter authors comment on their work on ATRACO with final remarks as viewed in retrospective Each chapter has been updated with follow-up work emerging from ATRACO An extensive introduction to state-of-the-art statistical dialog management for intelligent environments Approaches are introduced on how Trust is reflected during the dialog with the system.

  13. Map Matching for Intelligent Speed Adaptation

    DEFF Research Database (Denmark)

    Tradisauskas, Nerius; Juhl, Jens; Lahrmann, Harry

    2007-01-01

    The availability of Global Navigation Satellite Systems enables sophisticated vehicle guidance and advisory systems such as Intelligent Speed Adaptation (ISA) systems. In ISA systems, it is essential to be able to position vehicles within a road network. Because digital road networks as well as G...

  14. Intelligent power plant simulator for educational purposes

    International Nuclear Information System (INIS)

    Seifi, A.; Seifi, H.; Ansari, M. R.; Parsa Moghaddam, M.

    2001-01-01

    An Intelligent Tutoring System can be effectively employed for a power plant simulator so that the need for instructor in minimized. In this paper using the above concept as well as object oriented programming and SIMULINK Toolbox of MATLAB, an intelligent tutoring power plant simulator is proposed. Its successful application on a typical 11 MW power plant is demonstrated

  15. Adaptive Fuzzy-Lyapunov Controller Using Biologically Inspired Swarm Intelligence

    Directory of Open Access Journals (Sweden)

    Alejandro Carrasco Elizalde

    2008-01-01

    Full Text Available The collective behaviour of swarms produces smarter actions than those achieved by a single individual. Colonies of ants, flocks of birds and fish schools are examples of swarms interacting with their environment to achieve a common goal. This cooperative biological intelligence is the inspiration for an adaptive fuzzy controller developed in this paper. Swarm intelligence is used to adjust the parameters of the membership functions used in the adaptive fuzzy controller. The rules of the controller are designed using a computing-with-words approach called Fuzzy-Lyapunov synthesis to improve the stability and robustness of an adaptive fuzzy controller. Computing-with-words provides a powerful tool to manipulate numbers and symbols, like words in a natural language.

  16. Adaptation and hybridization in computational intelligence

    CERN Document Server

    Jr, Iztok

    2015-01-01

      This carefully edited book takes a walk through recent advances in adaptation and hybridization in the Computational Intelligence (CI) domain. It consists of ten chapters that are divided into three parts. The first part illustrates background information and provides some theoretical foundation tackling the CI domain, the second part deals with the adaptation in CI algorithms, while the third part focuses on the hybridization in CI. This book can serve as an ideal reference for researchers and students of computer science, electrical and civil engineering, economy, and natural sciences that are confronted with solving the optimization, modeling and simulation problems. It covers the recent advances in CI that encompass Nature-inspired algorithms, like Artificial Neural networks, Evolutionary Algorithms and Swarm Intelligence –based algorithms.  

  17. Artificial Intelligence and Spacecraft Power Systems

    Science.gov (United States)

    Dugel-Whitehead, Norma R.

    1997-01-01

    This talk will present the work which has been done at NASA Marshall Space Flight Center involving the use of Artificial Intelligence to control the power system in a spacecraft. The presentation will include a brief history of power system automation, and some basic definitions of the types of artificial intelligence which have been investigated at MSFC for power system automation. A video tape of one of our autonomous power systems using co-operating expert systems, and advanced hardware will be presented.

  18. Artificial intelligence in power system optimization

    CERN Document Server

    Ongsakul, Weerakorn

    2013-01-01

    With the considerable increase of AI applications, AI is being increasingly used to solve optimization problems in engineering. In the past two decades, the applications of artificial intelligence in power systems have attracted much research. This book covers the current level of applications of artificial intelligence to the optimization problems in power systems. This book serves as a textbook for graduate students in electric power system management and is also be useful for those who are interested in using artificial intelligence in power system optimization.

  19. Adaption of the power distribution system to a sustainable energy system - Smart meters and intelligent nets; Anpassning av elnaeten, till ett uthaalligt energisystem - Smarta maetare och intelligenta naet

    Energy Technology Data Exchange (ETDEWEB)

    Bollen, Math

    2010-11-15

    The conversion of the energy system towards sustainability is a major challenge for society. The conversion includes a large-scale introduction of renewable electricity and the electrification of transport. Adaptations of the grid are needed in order to cope with this development: - Facilitate an increased introduction of renewable electricity; - Enabling power reduction at peak load; - Improve incentives for energy efficiency; - Creating conditions for more active purchasers of electricity. Security of supply must be high, although the new production affects the electricity grid in a different way than today. Therefore, new technical solutions, a so-called smart grid, is necessary in order to, inter alia, prevent congestion and over voltages, but also to enhance the operational safety in general. There is new technology that can help adjust the grid in an efficient and flexible way. Intelligent networks, or smart grids, is the collection of new technology, function and regulatory framework in the electricity market, etc. that cost-effectively facilitate introduction and utilization of renewable electricity generation, leading to reduced energy consumption, contributes to power reduction in peak load and creates conditions for active electricity customers. Sweden is one of the countries that score high in terms of active electricity customers and feedback of consumption for electricity customers. There is a direct consequence of introduction of the metering reform and installation of the AMR, in which Sweden was one of the first countries in Europe. As for modern technology to increase transmission capacity of transmission networks such as HVDC and FACTS technology, Sweden is a world leader. This technology will play an important role in enabling large-scale use of renewable electricity generation on European level. The investigation has resulted in the following proposals: - A knowledge platform created to be collect and disseminate relevant knowledge of research

  20. Intelligent Optical Systems Using Adaptive Optics

    Science.gov (United States)

    Clark, Natalie

    2012-01-01

    Until recently, the phrase adaptive optics generally conjured images of large deformable mirrors being integrated into telescopes to compensate for atmospheric turbulence. However, the development of smaller, cheaper devices has sparked interest for other aerospace and commercial applications. Variable focal length lenses, liquid crystal spatial light modulators, tunable filters, phase compensators, polarization compensation, and deformable mirrors are becoming increasingly useful for other imaging applications including guidance navigation and control (GNC), coronagraphs, foveated imaging, situational awareness, autonomous rendezvous and docking, non-mechanical zoom, phase diversity, and enhanced multi-spectral imaging. The active components presented here allow flexibility in the optical design, increasing performance. In addition, the intelligent optical systems presented offer advantages in size and weight and radiation tolerance.

  1. Wind power systems. Applications of computational intelligence

    Energy Technology Data Exchange (ETDEWEB)

    Wang, Lingfeng [Toledo Univ., OH (United States). Dept. of Electrical Engineering and Computer Science; Singh, Chanan [Texas A and M Univ., College Station, TX (United States). Electrical and Computer Engineering Dept.; Kusiak, Andrew (eds.) [Iowa Univ., Iowa City, IA (United States). Mechanical and Industrial Engineering Dept.

    2010-07-01

    Renewable energy sources such as wind power have attracted much attention because they are environmentally friendly, do not produce carbon dioxide and other emissions, and can enhance a nation's energy security. For example, recently more significant amounts of wind power are being integrated into conventional power grids. Therefore, it is necessary to address various important and challenging issues related to wind power systems, which are significantly different from the traditional generation systems. This book is a resource for engineers, practitioners, and decision-makers interested in studying or using the power of computational intelligence based algorithms in handling various important problems in wind power systems at the levels of power generation, transmission, and distribution. Researchers have been developing biologically-inspired algorithms in a wide variety of complex large-scale engineering domains. Distinguished from the traditional analytical methods, the new methods usually accomplish the task through their computationally efficient mechanisms. Computational intelligence methods such as evolutionary computation, neural networks, and fuzzy systems have attracted much attention in electric power systems. Meanwhile, modern electric power systems are becoming more and more complex in order to meet the growing electricity market. In particular, the grid complexity is continuously enhanced by the integration of intermittent wind power as well as the current restructuring efforts in electricity industry. Quite often, the traditional analytical methods become less efficient or even unable to handle this increased complexity. As a result, it is natural to apply computational intelligence as a powerful tool to deal with various important and pressing problems in the current wind power systems. This book presents the state-of-the-art development in the field of computational intelligence applied to wind power systems by reviewing the most up

  2. Intelligent distributed control for nuclear power plants

    International Nuclear Information System (INIS)

    Klevans, E.H.

    1991-01-01

    In September of 1989 work began on the DOE University Program grant DE-FG07-89ER12889. The grant provides support for a three year project to develop and demonstrate Intelligent Distributed Control (IDC) for Nuclear Power Plants. The body of this First Annual Technical Progress report summarizes the first year tasks while the appendices provide detailed information presented at conference meetings. One major addendum report, authored by M.A. Schultz, describes the ultimate goals and projected structure of an automatic distributed control system for EBR-2. The remaining tasks of the project develop specific implementations of various components required to demonstrate the intelligent distributed control concept

  3. Intelligent operation system for nuclear power plants

    International Nuclear Information System (INIS)

    Morioka, Toshihiko; Fukumoto, Akira; Suto, Osamu; Naito, Norio.

    1987-01-01

    Nuclear power plants consist of many systems and are operated by skillful operators with plenty of knowledge and experience of nuclear plants. Recently, plant automation or computerized operator support systems have come to be utilized, but the synthetic judgment of plant operation and management remains as human roles. Toshiba is of the opinion that the activities (planning, operation and maintenance) should be integrated, and man-machine interface should be human-friendly. We have begun to develop the intelligent operation system aiming at reducing the operator's role within the fundamental judgment through the use of artificial intelligence. (author)

  4. Application of computational intelligence in emerging power systems

    African Journals Online (AJOL)

    ... in the electrical engineering applications. This paper highlights the application of computational intelligence methods in power system problems. Various types of CI methods, which are widely used in power system, are also discussed in the brief. Keywords: Power systems, computational intelligence, artificial intelligence.

  5. Artificial intelligence in nuclear power plants

    International Nuclear Information System (INIS)

    Haapanen, P.J.

    1990-01-01

    The IAEA Specialists' Meeting on Artificial Intelligence in Nuclear Power Plants was arranged in Helsink/Vantaa, Finland, on October 10-12, 1989, under auspices of the International Working Group of Nuclear Power Plant Control and Instrumentation of the International Atomic Energy Agency (IAEA/IWG NPPCI). Technical Research Centre of Finland together with Imatran Voima Oy and Teollisuuden Voima Oy answered for the practical arrangements of the meeting. 105 participants from 17 countries and 2 international organizations took part in the meeting and 58 papers were submitted for presentation. These papers gave a comprehensive picture of the recent status and further trends in applying the rapidly developing techniques of artificial intelligence and expert systems to improve the quality and safety in designing and using of nuclear power worldwide

  6. Artificial intelligence techniques in power systems

    Energy Technology Data Exchange (ETDEWEB)

    Laughton, M.A.

    1997-12-31

    Since the early to mid 1980s much of the effort in power systems analysis has turned away from the methodology of formal mathematical modelling which came from the fields of operations research, control theory and numerical analysis to the less rigorous techniques of artificial intelligence (AI). Today the main AI techniques found in power systems applications are those utilising the logic and knowledge representations of expert systems, fuzzy systems, artificial neural networks (ANN) and, more recently, evolutionary computing. These techniques will be outlined in this chapter and the power system applications indicated. (Author)

  7. Digital power - Electricity gets intelligent; Digitalstrom - Strom wird intelligent

    Energy Technology Data Exchange (ETDEWEB)

    Lieberherr, M.; Staub, R.

    2007-07-01

    This article takes a look at the setting up of the 'Viagialla' digital power alliance on the 7{sup th} of July 2007 at the Swiss Federal Institute of Technology in Zurich, Switzerland. The name 'Viagialla' is derived from the Italian for 'the yellow way'. The idea behind the project - to encourage the work of young students on machines and new developments - is discussed. The alliance encourages the use of energy forms that are available in great abundance such as solar energy and wind, thus preventing the so-called 'power-gap' and making the construction of new nuclear power stations unnecessary. The name 'digital power' refers to a new method of transmitting data over power lines on the basis of a new microchip controller. This chip can even be placed in small terminal blocks thus allowing electrical apparatus to communicate with switches and other devices. In this way, the apparatus can be remotely controlled. The developers of the system hope that their system will enable 'intelligent living' and intercommunication between normal domestic devices. External communication over the Internet is also foreseen.

  8. Intelligent distributed control for nuclear power plants

    International Nuclear Information System (INIS)

    Klevans, E.H.

    1993-01-01

    This project was initiated in September 1989 as a three year project to develop and demonstrate Intelligent Distributed Control (IDC) for Nuclear Power Plants. There were two primary goals of this research project. The first goal was to combine diagnostics and control to achieve a highly automated power plant as described by M.A. Schultz. The second goal was to apply this research to develop a prototype demonstration on an actual power plant system, the EBR-2 steam plant. Described in this Final (Third Annual) Technical Progress Report is the accomplishment of the project's final milestone, an in-plant intelligent control experiment conducted on April 1, 1993. The development of the experiment included: simulation validation, experiment formulation and final programming, procedure development and approval, and experimental results. Other third year developments summarized in this report are: (1) a theoretical foundation for Reconfigurable Hybrid Supervisory Control, (2) a steam plant diagnostic system, (3) control console design tools and (4) other advanced and intelligent control

  9. Low power adaptive synchronizer

    Energy Technology Data Exchange (ETDEWEB)

    Sadowski, Greg

    2018-02-20

    A circuit adapts to the occurrence of metastable states. The circuit inhibits passing of the metastable state to circuits that follow, by clock gating the output stage. In order to determine whether or not to gate the clock of the output stage, two detect circuits may be used. One circuit detects metastability and another circuit detects metastability resolved to a wrong logic level. The results from one or both detector circuits are used to gate the next clock cycle if needed, waiting for the metastable situation to be resolved.

  10. Intelligent Power Control of DC Microgrid

    DEFF Research Database (Denmark)

    Hajizadeh, Amin; N. Soltani, Mohsen; Norum, Lars

    2017-01-01

    In this paper, an intelligent power management strategy is proposed for hybrid DC microgrid, including wind turbine, fuel cell and battery energy storage. The considered wind turbine has a permanent magnet synchronous generator (PMSG). In the considered structure, wind turbine operates as the main...... condition and fuel cell will not generate excessive power. The proposed control scheme is based on the fuzzy algorithm. All simulations in variant operational modes are performed by MATLAB/Simulink and results show the effectiveness of the proposed control strategy....

  11. Intelligent distributed control for nuclear power plants

    International Nuclear Information System (INIS)

    Klevans, E.H.

    1992-01-01

    This project was initiated in September 1989 as a three year project to develop and demonstrate Intelligent Distributed Control (IDC) for Nuclear Power Plants. The body of this Third Annual Technical Progress report summarizes the period from September 1991 to October 1992. There were two primary goals of this research project. The first goal was to combine diagnostics and control to achieve a highly automated power plant as described by M.A. Schultz. His philosophy, is to improve public perception of the safety of nuclear power plants by incorporating a high degree of automation where a greatly simplified operator control console minimizes the possibility of human error in power plant operations. To achieve this goal, a hierarchically distributed control system with automated responses to plant upset conditions was pursued in this research. The second goal was to apply this research to develop a prototype demonstration on an actual power plant system, the EBR-2 stem plant. Emphasized in this Third Annual Technical Progress Report is the continuing development of the in-plant intelligent control demonstration for the final project milestone and includes: simulation validation and the initial approach to experiment formulation

  12. Artificial intelligence analysis of paraspinal power spectra.

    Science.gov (United States)

    Oliver, C W; Atsma, W J

    1996-10-01

    OBJECTIVE: As an aid to discrimination of sufferers with back pain an artificial intelligence neural network was constructed to differentiate paraspinal power spectra. DESIGN: Clinical investigation using surface electromyography. METHOD: The surface electromyogram power spectra from 60 subjects, 33 non-back-pain sufferers and 27 chronic back pain sufferers were used to construct a back propagation neural network that was then tested. Subjects were placed on a test frame in 30 degrees of lumbar forward flexion. An isometric load of two-thirds maximum voluntary contraction was held constant for 30 s whilst surface electromyograms were recorded at the level of the L(4-5). Paraspinal power spectra were calculated and loaded into the input layer of a three-layer back propagation network. The neural network classified the spectra into normal or back pain type. RESULTS: The back propagation neural was shown to have satisfactory convergence with a specificity of 79% and a sensitivity of 80%. CONCLUSIONS: Artificial intelligence neural networks appear to be a useful method of differentiating paraspinal power spectra in back-pain sufferers.

  13. Adaptive Neural Network Algorithm for Power Control in Nuclear Power Plants

    International Nuclear Information System (INIS)

    Husam Fayiz, Al Masri

    2017-01-01

    The aim of this paper is to design, test and evaluate a prototype of an adaptive neural network algorithm for the power controlling system of a nuclear power plant. The task of power control in nuclear reactors is one of the fundamental tasks in this field. Therefore, researches are constantly conducted to ameliorate the power reactor control process. Currently, in the Department of Automation in the National Research Nuclear University (NRNU) MEPhI, numerous studies are utilizing various methodologies of artificial intelligence (expert systems, neural networks, fuzzy systems and genetic algorithms) to enhance the performance, safety, efficiency and reliability of nuclear power plants. In particular, a study of an adaptive artificial intelligent power regulator in the control systems of nuclear power reactors is being undertaken to enhance performance and to minimize the output error of the Automatic Power Controller (APC) on the grounds of a multifunctional computer analyzer (simulator) of the Water-Water Energetic Reactor known as Vodo-Vodyanoi Energetichesky Reaktor (VVER) in Russian. In this paper, a block diagram of an adaptive reactor power controller was built on the basis of an intelligent control algorithm. When implementing intelligent neural network principles, it is possible to improve the quality and dynamic of any control system in accordance with the principles of adaptive control. It is common knowledge that an adaptive control system permits adjusting the controller’s parameters according to the transitions in the characteristics of the control object or external disturbances. In this project, it is demonstrated that the propitious options for an automatic power controller in nuclear power plants is a control system constructed on intelligent neural network algorithms. (paper)

  14. Experimental development of power reactor intelligent control

    International Nuclear Information System (INIS)

    Edwards, R.M.; Garcia, H.E.; Lee, K.Y.

    1992-01-01

    The US nuclear utility industry initiated an ambitious program to modernize the control systems at a minimum of ten existing nuclear power plants by the year 2000. That program addresses urgent needs to replace obsolete instrumentation and analog controls with highly reliable state-of-the-art computer-based digital systems. Large increases in functionality that could theoretically be achieved in a distributed digital control system are not an initial priority in the industry program but could be logically considered in later phases. This paper discusses the initial development of an experimental sequence for developing, testing, and verifying intelligent fault-accommodating control for commercial nuclear power plant application. The sequence includes an ultra-safe university research reactor (TRIGA) and a passively safe experimental power plant (Experimental Breeder Reactor 2)

  15. Discussion on technical intelligence of nuclear power industry

    International Nuclear Information System (INIS)

    Chen Ming

    2010-01-01

    The very Paper introduces the contemporary challenges faced by the profession of technical intelligence on nuclear power, and expatiates the functions of technical intelligence such as sources of experience feedback, background information and supports for decision-making. Afterwards, the Paper explains characteristics of technical intelligence and its working methods, i.e., quantitative changes to reach qualitative changes, approve-negate-approve and oppositeness unity of comprehensiveness and limitation of technical intelligence. (authors)

  16. Intelligent Component Monitoring for Nuclear Power Plants

    International Nuclear Information System (INIS)

    Tsoukalas, Lefteri

    2010-01-01

    Reliability and economy are two major concerns for a nuclear power generation system. Next generation nuclear power reactors are being developed to be more reliable and economic. An effective and efficient surveillance system can generously contribute toward this goal. Recent progress in computer systems and computational tools has made it necessary and possible to upgrade current surveillance/monitoring strategy for better performance. For example, intelligent computing techniques can be applied to develop algorithm that help people better understand the information collected from sensors and thus reduce human error to a new low level. Incidents incurred from human error in nuclear industry are not rare and have been proven costly. The goal of this project is to develop and test an intelligent prognostics methodology for predicting aging effects impacting long-term performance of nuclear components and systems. The approach is particularly suitable for predicting the performance of nuclear reactor systems which have low failure probabilities (e.g., less than 10 -6 year -1 ). Such components and systems are often perceived as peripheral to the reactor and are left somewhat unattended. That is, even when inspected, if they are not perceived to be causing some immediate problem, they may not be paid due attention. Attention to such systems normally involves long term monitoring and possibly reasoning with multiple features and evidence, requirements that are not best suited for humans.

  17. Intelligent distributed control for nuclear power plants

    International Nuclear Information System (INIS)

    Klevans, E.H.; Edwards, R.M.; Ray, A.; Lee, K.Y.; Garcia, H.E.: Chavez, C.M.; Turso, J.A.; BenAbdennour, A.

    1991-01-01

    In September of 1989 work began on the DOE University Program grant DE-FG07-89ER12889. The grant provides support for a three year project to develop and demonstrate Intelligent Distributed Control (IDC) for Nuclear Power Plants. The body of this Second Annual Technical Progress report covers the period from September 1990 to September 1991. It summarizes the second year accomplishments while the appendices provide detailed information presented at conference meetings. These are two primary goals of this research. The first is to combine diagnostics and control to achieve a highly automated power plant as described by M.A. Schultz, a project consultant during the first year of the project. This philosophy, as presented in the first annual technical progress report, is to improve public perception of the safety of nuclear power plants by incorporating a high degree automation where greatly simplified operator control console minimizes the possibility of human error in power plant operations. A hierarchically distributed control system with automated responses to plant upset conditions is the focus of our research to achieve this goal. The second goal is to apply this research to develop a prototype demonstration on an actual power plant system, the EBR-II steam plant

  18. Intelligent power system data management systems (DBMS)

    Energy Technology Data Exchange (ETDEWEB)

    Middleton, A.; Macdonald, E. [GE Digital Energy, Markham, ON (Canada); Schreiner, Z. [Intelligent Process Solutions GmbH, Lindau (Germany); Bizjak, J. [Elektro Ljubljana d.d., Ljubljana (Slovenia)

    2010-07-01

    Network owners/operators from around the world have moved from electromechanical products to intelligent electronic devices (IEDs). Most networks have a multi-generation technology mix because protection assets have a normal application lifespan of between 10 and 40 years. Associated data capture and maintenance management regimes have therefore moved from paper based into digitized media, creating a significant increase in the volume of acquired data, such that there is now a mix of paper and digitized storage. Data is rarely consolidated or used for decision making in asset management processes once testing is completed, having a major impact on overall power system reliability. This paper presented the concept of intelligent operative maintenance management, now becoming more recognized in the industry. The concept was described as the management of operational data, resulting actions and responses, wherever and by whoever they are needed, without any additional overhead. The paper discussed new techniques of testing as well as planning and operative maintenance. The practical benefits of the new system were also presented, with particular reference to central management; simplification of routine protocols; secondary testing; and reduced cost of data handling. It was concluded that the main benefit from all of the techniques discussed in this paper is that experienced expert test engineers can focus more time upon making good, critical decisions to ensure that utilities maximize their customer service and safety regimes. 13 refs., 7 figs.

  19. Intelligent Navigation for a Solar Powered Unmanned Underwater Vehicle

    Directory of Open Access Journals (Sweden)

    Francisco García-Córdova

    2013-04-01

    Full Text Available In this paper, an intelligent navigation system for an unmanned underwater vehicle powered by renewable energy and designed for shadow water inspection in missions of a long duration is proposed. The system is composed of an underwater vehicle, which tows a surface vehicle. The surface vehicle is a small boat with photovoltaic panels, a methanol fuel cell and communication equipment, which provides energy and communication to the underwater vehicle. The underwater vehicle has sensors to monitor the underwater environment such as sidescan sonar and a video camera in a flexible configuration and sensors to measure the physical and chemical parameters of water quality on predefined paths for long distances. The underwater vehicle implements a biologically inspired neural architecture for autonomous intelligent navigation. Navigation is carried out by integrating a kinematic adaptive neuro-controller for trajectory tracking and an obstacle avoidance adaptive neuro- controller. The autonomous underwater vehicle is capable of operating during long periods of observation and monitoring. This autonomous vehicle is a good tool for observing large areas of sea, since it operates for long periods of time due to the contribution of renewable energy. It correlates all sensor data for time and geodetic position. This vehicle has been used for monitoring the Mar Menor lagoon.

  20. Application of computational intelligence techniques for load shedding in power systems: A review

    International Nuclear Information System (INIS)

    Laghari, J.A.; Mokhlis, H.; Bakar, A.H.A.; Mohamad, Hasmaini

    2013-01-01

    Highlights: • The power system blackout history of last two decades is presented. • Conventional load shedding techniques, their types and limitations are presented. • Applications of intelligent techniques in load shedding are presented. • Intelligent techniques include ANN, fuzzy logic, ANFIS, genetic algorithm and PSO. • The discussion and comparison between these techniques are provided. - Abstract: Recent blackouts around the world question the reliability of conventional and adaptive load shedding techniques in avoiding such power outages. To address this issue, reliable techniques are required to provide fast and accurate load shedding to prevent collapse in the power system. Computational intelligence techniques, due to their robustness and flexibility in dealing with complex non-linear systems, could be an option in addressing this problem. Computational intelligence includes techniques like artificial neural networks, genetic algorithms, fuzzy logic control, adaptive neuro-fuzzy inference system, and particle swarm optimization. Research in these techniques is being undertaken in order to discover means for more efficient and reliable load shedding. This paper provides an overview of these techniques as applied to load shedding in a power system. This paper also compares the advantages of computational intelligence techniques over conventional load shedding techniques. Finally, this paper discusses the limitation of computational intelligence techniques, which restricts their usage in load shedding in real time

  1. Intelligent, Autonomous Electrical Power System Management and Distribution, Phase I

    Data.gov (United States)

    National Aeronautics and Space Administration — EPS-MAESTRO (EPS Management through intelligent, AdaptivE, autonomouS, faulT identification and diagnosis, Reconfiguration/replanning/rescheduling Optimization)...

  2. Intelligent Adaptation Process for Case Based Systems

    International Nuclear Information System (INIS)

    Nassar, A.M.; Mohamed, A.H.; Mohamed, A.H.

    2014-01-01

    Case Based Reasoning (CBR) Systems is one of the important decision making systems applied in many fields all over the world. The effectiveness of any CBR system based on the quality of the storage cases in the case library. Similar cases can be retrieved and adapted to produce the solution for the new problem. One of the main issues faced the CBR systems is the difficulties of achieving the useful cases. The proposed system introduces a new approach that uses the genetic algorithm (GA) technique to automate constructing the cases into the case library. Also, it can optimize the best one to be stored in the library for the future uses. However, the proposed system can avoid the problems of the uncertain and noisy cases. Besides, it can simply the retrieving and adaptation processes. So, it can improve the performance of the CBR system. The suggested system can be applied for many real-time problems. It has been applied for diagnosis the faults of the wireless network, diagnosis of the cancer diseases, diagnosis of the debugging of a software as cases of study. The proposed system has proved its performance in this field

  3. Intelligent agents for adaptive security market surveillance

    Science.gov (United States)

    Chen, Kun; Li, Xin; Xu, Baoxun; Yan, Jiaqi; Wang, Huaiqing

    2017-05-01

    Market surveillance systems have increasingly gained in usage for monitoring trading activities in stock markets to maintain market integrity. Existing systems primarily focus on the numerical analysis of market activity data and generally ignore textual information. To fulfil the requirements of information-based surveillance, a multi-agent-based architecture that uses agent intercommunication and incremental learning mechanisms is proposed to provide a flexible and adaptive inspection process. A prototype system is implemented using the techniques of text mining and rule-based reasoning, among others. Based on experiments in the scalping surveillance scenario, the system can identify target information evidence up to 87.50% of the time and automatically identify 70.59% of cases depending on the constraints on the available information sources. The results of this study indicate that the proposed information surveillance system is effective. This study thus contributes to the market surveillance literature and has significant practical implications.

  4. Distributed Problem Solving: Adaptive Networks with a Computer Intermediary Resource. Intelligent Executive Computer Communication

    Science.gov (United States)

    1991-06-01

    Proceedings of The National Conference on Artificial Intelligence , pages 181-184, The American Association for Aritificial Intelligence , Pittsburgh...Intermediary Resource: Intelligent Executive Computer Communication John Lyman and Carla J. Conaway University of California at Los Angeles for Contracting...Include Security Classification) Interim Report: Distributed Problem Solving: Adaptive Networks With a Computer Intermediary Resource: Intelligent

  5. Intelligent agents: adaptation of autonomous bimodal microsystems

    Science.gov (United States)

    Smith, Patrice; Terry, Theodore B.

    2014-03-01

    Autonomous bimodal microsystems exhibiting survivability behaviors and characteristics are able to adapt dynamically in any given environment. Equipped with a background blending exoskeleton it will have the capability to stealthily detect and observe a self-chosen viewing area while exercising some measurable form of selfpreservation by either flying or crawling away from a potential adversary. The robotic agent in this capacity activates a walk-fly algorithm, which uses a built in multi-sensor processing and navigation subsystem or algorithm for visual guidance and best walk-fly path trajectory to evade capture or annihilation. The research detailed in this paper describes the theoretical walk-fly algorithm, which broadens the scope of spatial and temporal learning, locomotion, and navigational performances based on optical flow signals necessary for flight dynamics and walking stabilities. By observing a fly's travel and avoidance behaviors; and, understanding the reverse bioengineering research efforts of others, we were able to conceptualize an algorithm, which works in conjunction with decisionmaking functions, sensory processing, and sensorimotor integration. Our findings suggest that this highly complex decentralized algorithm promotes inflight or terrain travel mobile stability which is highly suitable for nonaggressive micro platforms supporting search and rescue (SAR), and chemical and explosive detection (CED) purposes; a necessity in turbulent, non-violent structured or unstructured environments.

  6. Business Intelligence: Turning Knowledge into Power

    Science.gov (United States)

    Endsley, Krista

    2009-01-01

    Today, many school districts are turning to business intelligence tools to retrieve, organize, and share knowledge for faster analysis and more effective, guided decision making. Business intelligence (BI) tools are the technologies and applications that gather and report information to help an organization's leaders make better decisions. BI…

  7. Intelligent and Adaptive Educational-Learning Systems Achievements and Trends

    CERN Document Server

    2013-01-01

    The Smart Innovation, Systems and Technologies book series encompasses the topics of knowledge, intelligence, innovation and sustainability. The aim of the series is to make available a platform for the publication of books on all aspects of single and multi-disciplinary research on these themes in order to make the latest results available in a readily-accessible form.  This book is devoted to the “Intelligent and Adaptive Educational-Learning Systems”. It privileges works that highlight key achievements and outline trends to inspire future research.  After a rigorous revision process twenty manuscripts were accepted and organized into four parts as follows: ·     Modeling: The first part embraces five chapters oriented to: 1) shape the affective behavior; 2) depict the adaptive learning curriculum; 3) predict learning achievements; 4) mine learner models to outcome optimized and adaptive e-learning objects; 5) classify learning preferences of learners. ·     Content: The second part encompas...

  8. Intelligent adaptive systems an interaction-centered design perspective

    CERN Document Server

    Hou, Ming; Burns, Catherine

    2014-01-01

    A synthesis of recent research and developments on intelligent adaptive systems from the HF (human factors) and HCI (human-computer interaction) domains, this book provides integrated design guidance and recommendations for researchers and system developers. It addresses a recognized lack of integration between the HF and HCI research communities, which has led to inconsistencies between the research approaches adopted, and a lack of exploitation of research from one field by the other. The book establishes design guidance through the review of conceptual frameworks, analytical methodologies,

  9. Fundamentals of Adaptive Intelligent Tutoring Systems for Self-Regulated Learning

    Science.gov (United States)

    2015-03-01

    ARL-SR-0318 ● MAR 2015 US Army Research Laboratory Fundamentals of Adaptive Intelligent Tutoring Systems for Self-Regulated...Adaptive Intelligent Tutoring Systems for Self-Regulated Learning by Robert A Sottilare Human Research and Engineering Directorate, ARL...TITLE AND SUBTITLE Fundamentals of Adaptive Intelligent Tutoring Systems for Self-Regulated Learning 5a. CONTRACT NUMBER 5b. GRANT NUMBER 5c

  10. Use of artificial intelligence in nuclear power plants

    International Nuclear Information System (INIS)

    Uhrig, R.E.

    1990-01-01

    The application of artificial intelligence, in the form of expert systems and neural networks, to the control room activities in a nuclear power plant has the potential to reduce operator error and increase plant safety, reliability, and efficiency. Furthermore, there are a large number of non-operating activities (testing, routine maintenance, outage planning, equipment diagnostics, and fuel management) in which artificial intelligence can increase the efficiency and effectiveness of overall plant and corporate operations. This paper reviews the state-of-the-art of artificial intelligence techniques, specifically, expert systems and neural networks, to nuclear power plants. This paper has reviewed the state-of-the-art of artificial intelligence, specifically expert systems and neural networks that are applied to problems in nuclear power plants

  11. Adaptive Moving Object Tracking Integrating Neural Networks And Intelligent Processing

    Science.gov (United States)

    Lee, James S. J.; Nguyen, Dziem D.; Lin, C.

    1989-03-01

    A real-time adaptive scheme is introduced to detect and track moving objects under noisy, dynamic conditions including moving sensors. This approach integrates the adaptiveness and incremental learning characteristics of neural networks with intelligent reasoning and process control. Spatiotemporal filtering is used to detect and analyze motion, exploiting the speed and accuracy of multiresolution processing. A neural network algorithm constitutes the basic computational structure for classification. A recognition and learning controller guides the on-line training of the network, and invokes pattern recognition to determine processing parameters dynamically and to verify detection results. A tracking controller acts as the central control unit, so that tracking goals direct the over-all system. Performance is benchmarked against the Widrow-Hoff algorithm, for target detection scenarios presented in diverse FLIR image sequences. Efficient algorithm design ensures that this recognition and control scheme, implemented in software and commercially available image processing hardware, meets the real-time requirements of tracking applications.

  12. Research on intelligent power distribution system for spacecraft

    Science.gov (United States)

    Xia, Xiaodong; Wu, Jianju

    2017-10-01

    The power distribution system (PDS) mainly realizes the power distribution and management of the electrical load of the whole spacecraft, which is directly related to the success or failure of the mission, and hence is an important part of the spacecraft. In order to improve the reliability and intelligent degree of the PDS, and considering the function and composition of spacecraft power distribution system, this paper systematically expounds the design principle and method of the intelligent power distribution system based on SSPC, and provides the analysis and verification of the test data additionally.

  13. Advanced solutions in power systems HVDC, facts, and artificial intelligence

    CERN Document Server

    Liu, Chen-Ching; Edris, Abdel-Aty

    2016-01-01

    Provides insight on both classical means and new trends in the application of power electronic and artificial intelligence techniques in power system operation and control This book presents advanced solutions for power system controllability improvement, transmission capability enhancement and operation planning. The book is organized into three parts. The first part describes the CSC-HVDC and VSC-HVDC technologies, the second part presents the FACTS devices, and the third part refers to the artificial intelligence techniques. All technologies and tools approached in this book are essential for power system development to comply with the smart grid requirements.

  14. OPUS One: An Intelligent Adaptive Learning Environment Using Artificial Intelligence Support

    Science.gov (United States)

    Pedrazzoli, Attilio

    2010-06-01

    AI based Tutoring and Learning Path Adaptation are well known concepts in e-Learning scenarios today and increasingly applied in modern learning environments. In order to gain more flexibility and to enhance existing e-learning platforms, the OPUS One LMS Extension package will enable a generic Intelligent Tutored Adaptive Learning Environment, based on a holistic Multidimensional Instructional Design Model (PENTHA ID Model), allowing AI based tutoring and adaptation functionality to existing Web-based e-learning systems. Relying on "real time" adapted profiles, it allows content- / course authors to apply a dynamic course design, supporting tutored, collaborative sessions and activities, as suggested by modern pedagogy. The concept presented combines a personalized level of surveillance, learning activity- and learning path adaptation suggestions to ensure the students learning motivation and learning success. The OPUS One concept allows to implement an advanced tutoring approach combining "expert based" e-tutoring with the more "personal" human tutoring function. It supplies the "Human Tutor" with precise, extended course activity data and "adaptation" suggestions based on predefined subject matter rules. The concept architecture is modular allowing a personalized platform configuration.

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

    Science.gov (United States)

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

    2008-12-01

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

  16. The present status of artificial intelligence for nuclear power plants

    International Nuclear Information System (INIS)

    Suda, Kazunori; Yonekawa, Tuyoshi; Yoshikawa, Shinji; Hasegawa, Makoto

    1999-03-01

    JNC researches the development of distributed intelligence systems at autonomous plants and intelligent support system at nuclear power plant. This report describes the present status of artificial intelligence (AI) technologies for this research. The following are represented in this report: present research study for AI, Implementation of AI system and application of AI technologies in the field of industries, requirement for AI by industries, problems of social acceptance for AI. A development of AI systems has to be motivated both by current status of AI and requirement for AI. Furthermore a problem of social acceptance for AI technologies has to be solved for using AI systems in society. (author)

  17. Dynamic vulnerability assessment and intelligent control for sustainable power systems

    CERN Document Server

    Gonzalez-Longatt, Francisco

    2018-01-01

    Identifying, assessing, and mitigating electric power grid vulnerabilities is a growing focus in short-term operational planning of power systems. Through illustrated application, this important guide surveys state-of-the-art methodologies for the assessment and enhancement of power system security in short-term operational planning and real-time operation. The methodologies employ advanced methods from probabilistic theory, data mining, artificial intelligence, and optimization, to provide knowledge-based support for monitoring, control (preventive and corrective), and decision making tasks. Key features: Introduces behavioural recognition in wide-area monitoring and security constrained optimal power flow for intelligent control and protection and optimal grid management. Provides in-depth understanding of risk-based reliability and security assessment, dynamic vulnerability as essment methods, supported by the underpinning mathematics. Develops expertise in mitigation techniques using intelligent protect...

  18. Artificial Intelligence Techniques Applications for Power Disturbances Classification

    OpenAIRE

    K.Manimala; Dr.K.Selvi; R.Ahila

    2008-01-01

    Artificial Intelligence (AI) methods are increasingly being used for problem solving. This paper concerns using AI-type learning machines for power quality problem, which is a problem of general interest to power system to provide quality power to all appliances. Electrical power of good quality is essential for proper operation of electronic equipments such as computers and PLCs. Malfunction of such equipment may lead to loss of production or disruption of critical services resulting in huge...

  19. Intelligent engineering and technology for nuclear power plant operation

    International Nuclear Information System (INIS)

    Wang, P.P.; Gu, X.

    1996-01-01

    The Three-Mile-Island accident has drawn considerable attention by the engineering, scientific, management, financial, and political communities as well as society at large. This paper surveys possible causes of the accident studied by various groups. Research continues in this area with many projects aimed at specifically improving the performance and operation of a nuclear power plant using the contemporary technologies available. In addition to the known cause of the accident and suggest a strategy for coping with these problems in the future. With the increased use of intelligent methodologies called computational intelligence or soft-computing, a substantially larger collection of powerful tools are now available for our designers to use in order to tackle these sensitive and difficult issues. These intelligent methodologies consists of fuzzy logic, genetic algorithms, neural networks, artificial intelligence and expert systems, pattern recognition, machine intelligence, and fuzzy constraint networks. Using the Three-Mile-Island experience, this paper offers a set of specific recommendations for future designers to take advantage of the powerful tools of intelligent technologies that we are now able to master and encourages the adoption of a novel methodology called fuzzy constraint network

  20. Intelligence

    Science.gov (United States)

    Sternberg, Robert J.

    2012-01-01

    Intelligence is the ability to learn from experience and to adapt to, shape, and select environments. Intelligence as measured by (raw scores on) conventional standardized tests varies across the lifespan, and also across generations. Intelligence can be understood in part in terms of the biology of the brain—especially with regard to the functioning in the prefrontal cortex—and also correlates with brain size, at least within humans. Studies of the effects of genes and environment suggest that the heritability coefficient (ratio of genetic to phenotypic variation) is between .4 and .8, although heritability varies as a function of socioeconomic status and other factors. Racial differences in measured intelligence have been observed, but race is a socially constructed rather than biological variable, so such differences are difficult to interpret. PMID:22577301

  1. Intelligence.

    Science.gov (United States)

    Sternberg, Robert J

    2012-03-01

    Intelligence is the ability to learn from experience and to adapt to, shape, and select environments. Intelligence as measured by (raw scores on) conventional standardized tests varies across the lifespan, and also across generations. Intelligence can be understood in part in terms of the biology of the brain-especially with regard to the functioning in the prefrontal cortex-and also correlates with brain size, at least within humans. Studies of the effects of genes and environment suggest that the heritability coefficient (ratio of genetic to phenotypic variation) is between .4 and .8, although heritability varies as a function of socioeconomic status and other factors. Racial differences in measured intelligence have been observed, but race is a socially constructed rather than biological variable, so such differences are difficult to interpret.

  2. Enhanced situation awareness and decision making for an intelligent reconfigurable reactor power controller

    International Nuclear Information System (INIS)

    Kenney, S.J.; Edwards, R.M.

    1996-01-01

    A Learning Automata based intelligent reconfigurable controller has been adapted for use as a reactor power controller to achieve improved reactor temperature performance. The intelligent reconfigurable controller is capable of enforcing either a classical or an optimal reactor power controller based on control performance feedback. Four control performance evaluation measures: dynamically estimated average quadratic temperature error, power, rod reactivity and rod reactivity rate were developed to provide feedback to the control decision component of the intelligent reconfigurable controller. Fuzzy Logic and Neural Network controllers have been studied for inclusion in the bank of controllers that form the intermediate level of an enhanced intelligent reconfigurable reactor power controller (IRRPC). The increased number of alternatives available to the supervisory level of the IRRPC requires enhanced situation awareness. Additional performance measures have been designed and a method for synthesizing them into a single indication of the overall performance of the currently enforced reactor power controller has been conceptualized. Modification of the reward/penalty scheme implemented in the existing IRRPC to increase the quality of the supervisory level decision process has been studied. The logogen model of human memory (Morton, 1969) and individual controller design information could be used to allocate reward to the most appropriate controller. Methods for allocating supervisory level attention were also studied with the goal of maximizing learning rate

  3. Intelligent Power Management of hybrid Wind/ Fuel Cell/ Energy Storage Power Generation System

    OpenAIRE

    A. Hajizadeh; F. Hassanzadeh

    2013-01-01

    This paper presents an intelligent power management strategy for hybrid wind/ fuel cell/ energy storage power generation system. The dynamic models of wind turbine, fuel cell and energy storage have been used for simulation of hybrid power system. In order to design power flow control strategy, a fuzzy logic control has been implemented to manage the power between power sources. The optimal operation of the hybrid power system is a main goal of designing power management strategy. The hybrid ...

  4. Embedded intelligent adaptive PI controller for an electromechanical system.

    Science.gov (United States)

    El-Nagar, Ahmad M

    2016-09-01

    In this study, an intelligent adaptive controller approach using the interval type-2 fuzzy neural network (IT2FNN) is presented. The proposed controller consists of a lower level proportional - integral (PI) controller, which is the main controller and an upper level IT2FNN which tuning on-line the parameters of a PI controller. The proposed adaptive PI controller based on IT2FNN (API-IT2FNN) is implemented practically using the Arduino DUE kit for controlling the speed of a nonlinear DC motor-generator system. The parameters of the IT2FNN are tuned on-line using back-propagation algorithm. The Lyapunov theorem is used to derive the stability and convergence of the IT2FNN. The obtained experimental results, which are compared with other controllers, demonstrate that the proposed API-IT2FNN is able to improve the system response over a wide range of system uncertainties. Copyright © 2016 ISA. Published by Elsevier Ltd. All rights reserved.

  5. Beyond adaptive-critic creative learning for intelligent mobile robots

    Science.gov (United States)

    Liao, Xiaoqun; Cao, Ming; Hall, Ernest L.

    2001-10-01

    Intelligent industrial and mobile robots may be considered proven technology in structured environments. Teach programming and supervised learning methods permit solutions to a variety of applications. However, we believe that to extend the operation of these machines to more unstructured environments requires a new learning method. Both unsupervised learning and reinforcement learning are potential candidates for these new tasks. The adaptive critic method has been shown to provide useful approximations or even optimal control policies to non-linear systems. The purpose of this paper is to explore the use of new learning methods that goes beyond the adaptive critic method for unstructured environments. The adaptive critic is a form of reinforcement learning. A critic element provides only high level grading corrections to a cognition module that controls the action module. In the proposed system the critic's grades are modeled and forecasted, so that an anticipated set of sub-grades are available to the cognition model. The forecasting grades are interpolated and are available on the time scale needed by the action model. The success of the system is highly dependent on the accuracy of the forecasted grades and adaptability of the action module. Examples from the guidance of a mobile robot are provided to illustrate the method for simple line following and for the more complex navigation and control in an unstructured environment. The theory presented that is beyond the adaptive critic may be called creative theory. Creative theory is a form of learning that models the highest level of human learning - imagination. The application of the creative theory appears to not only be to mobile robots but also to many other forms of human endeavor such as educational learning and business forecasting. Reinforcement learning such as the adaptive critic may be applied to known problems to aid in the discovery of their solutions. The significance of creative theory is that it

  6. Artificial intelligence tool development and applications to nuclear power

    International Nuclear Information System (INIS)

    Naser, J.A.

    1987-01-01

    Two parallel efforts are being performed at the Electric Power Research Institute (EPRI) to help the electric utility industry take advantage of the expert system technology. The first effort is the development of expert system building tools, which are tailored to electric utility industry applications. The second effort is the development of expert system applications. These two efforts complement each other. The application development tests the tools and identifies additional tool capabilities that are required. The tool development helps define the applications that can be successfully developed. Artificial intelligence, as demonstrated by the developments described is being established as a credible technological tool for the electric utility industry. The challenge to transferring artificial intelligence technology and an understanding of its potential to the electric utility industry is to gain an understanding of the problems that reduce power plant performance and identify which can be successfully addressed using artificial intelligence

  7. Professional adaptability of nuclear power plant operators

    International Nuclear Information System (INIS)

    He Xuhong; Huang Xiangrui

    2006-01-01

    The paper concerns in the results of analysis for nuclear power plant (NPP) operator job and analysis for human errors related NPP accidents. Based on the principle of ergonomics a full psychological selection system of the professional adaptability of NPP operators including cognitive ability, personality and psychological health was established. The application way and importance of the professional adaptability research are discussed. (authors)

  8. Artificial Intelligence Application in Power Generation Industry: Initial considerations

    Science.gov (United States)

    Ismail, Rahmat Izaizi B.; Ismail Alnaimi, Firas B.; AL-Qrimli, Haidar F.

    2016-03-01

    With increased competitiveness in power generation industries, more resources are directed in optimizing plant operation, including fault detection and diagnosis. One of the most powerful tools in faults detection and diagnosis is artificial intelligence (AI). Faults should be detected early so correct mitigation measures can be taken, whilst false alarms should be eschewed to avoid unnecessary interruption and downtime. For the last few decades there has been major interest towards intelligent condition monitoring system (ICMS) application in power plant especially with AI development particularly in artificial neural network (ANN). ANN is based on quite simple principles, but takes advantage of their mathematical nature, non-linear iteration to demonstrate powerful problem solving ability. With massive possibility and room for improvement in AI, the inspiration for researching them are apparent, and literally, hundreds of papers have been published, discussing the findings of hybrid AI for condition monitoring purposes. In this paper, the studies of ANN and genetic algorithm (GA) application will be presented.

  9. Power semiconductor device adaptive cooling assembly

    NARCIS (Netherlands)

    2011-01-01

    The invention relates to a power semiconductor device (100) cooling assembly for cooling a power semiconductor device (100), wherein the assembly comprises an actively cooled heat sink (102) and a controller (208; 300), wherein the controller (208; 300) is adapted for adjusting the cooling

  10. Intelligent Techniques for Power Systems Vulnerability Assessment

    OpenAIRE

    Mohamed A. El-Sharkawi

    2002-01-01

    With power grids considered national security matters, the reliable operation of the system is of top priority to utilities.  This concern is amplified by the utility’s deregulation, which increases the system’s openness while simultaneously decreasing the applied degree of control.  Vulnerability Assessment (VA) deals with the power system’s ability to continue to provide service in case of an unforeseen catastrophic contingency.  Such contingencies may include unauthorized tripping, breaks ...

  11. Reconfigurable, Intelligently-Adaptive, Communication System, an SDR Platform

    Science.gov (United States)

    Roche, Rigoberto J.; Shalkhauser, Mary Jo; Hickey, Joseph P.; Briones, Janette C.

    2016-01-01

    The Space Telecommunications Radio System (STRS) provides a common, consistent framework to abstract the application software from the radio platform hardware. STRS aims to reduce the cost and risk of using complex, configurable and reprogrammable radio systems across NASA missions. The NASA Glenn Research Center (GRC) team made a software defined radio (SDR) platform STRS compliant by adding an STRS operating environment and a field programmable gate array (FPGA) wrapper, capable of implementing each of the platforms interfaces, as well as a test waveform to exercise those interfaces. This effort serves to provide a framework toward waveform development onto an STRS compliant platform to support future space communication systems for advanced exploration missions. The use of validated STRS compliant applications provides tested code with extensive documentation to potentially reduce risk, cost and e ort in development of space-deployable SDRs. This paper discusses the advantages of STRS, the integration of STRS onto a Reconfigurable, Intelligently-Adaptive, Communication System (RIACS) SDR platform, and the test waveform and wrapper development e orts. The paper emphasizes the infusion of the STRS Architecture onto the RIACS platform for potential use in next generation flight system SDRs for advanced exploration missions.

  12. Adaptive neuro-fuzzy and expert systems for power quality analysis and prediction of abnormal operation

    Science.gov (United States)

    Ibrahim, Wael Refaat Anis

    The present research involves the development of several fuzzy expert systems for power quality analysis and diagnosis. Intelligent systems for the prediction of abnormal system operation were also developed. The performance of all intelligent modules developed was either enhanced or completely produced through adaptive fuzzy learning techniques. Neuro-fuzzy learning is the main adaptive technique utilized. The work presents a novel approach to the interpretation of power quality from the perspective of the continuous operation of a single system. The research includes an extensive literature review pertaining to the applications of intelligent systems to power quality analysis. Basic definitions and signature events related to power quality are introduced. In addition, detailed discussions of various artificial intelligence paradigms as well as wavelet theory are included. A fuzzy-based intelligent system capable of identifying normal from abnormal operation for a given system was developed. Adaptive neuro-fuzzy learning was applied to enhance its performance. A group of fuzzy expert systems that could perform full operational diagnosis were also developed successfully. The developed systems were applied to the operational diagnosis of 3-phase induction motors and rectifier bridges. A novel approach for learning power quality waveforms and trends was developed. The technique, which is adaptive neuro fuzzy-based, learned, compressed, and stored the waveform data. The new technique was successfully tested using a wide variety of power quality signature waveforms, and using real site data. The trend-learning technique was incorporated into a fuzzy expert system that was designed to predict abnormal operation of a monitored system. The intelligent system learns and stores, in compressed format, trends leading to abnormal operation. The system then compares incoming data to the retained trends continuously. If the incoming data matches any of the learned trends, an

  13. Colloquium paper: adaptive specializations, social exchange, and the evolution of human intelligence.

    Science.gov (United States)

    Cosmides, Leda; Barrett, H Clark; Tooby, John

    2010-05-11

    Blank-slate theories of human intelligence propose that reasoning is carried out by general-purpose operations applied uniformly across contents. An evolutionary approach implies a radically different model of human intelligence. The task demands of different adaptive problems select for functionally specialized problem-solving strategies, unleashing massive increases in problem-solving power for ancestrally recurrent adaptive problems. Because exchange can evolve only if cooperators can detect cheaters, we hypothesized that the human mind would be equipped with a neurocognitive system specialized for reasoning about social exchange. Whereas humans perform poorly when asked to detect violations of most conditional rules, we predicted and found a dramatic spike in performance when the rule specifies an exchange and violations correspond to cheating. According to critics, people's uncanny accuracy at detecting violations of social exchange rules does not reflect a cheater detection mechanism, but extends instead to all rules regulating when actions are permitted (deontic conditionals). Here we report experimental tests that falsify these theories by demonstrating that deontic rules as a class do not elicit the search for violations. We show that the cheater detection system functions with pinpoint accuracy, searching for violations of social exchange rules only when these are likely to reveal the presence of someone who intends to cheat. It does not search for violations of social exchange rules when these are accidental, when they do not benefit the violator, or when the situation would make cheating difficult.

  14. Functional requirements for an intelligent RPC. [remote power controller for spaceborne electrical distribution system

    Science.gov (United States)

    Aucoin, B. M.; Heller, R. P.

    1990-01-01

    An intelligent remote power controller (RPC) based on microcomputer technology can implement advanced functions for the accurate and secure detection of all types of faults on a spaceborne electrical distribution system. The intelligent RPC will implement conventional protection functions such as overcurrent, under-voltage, and ground fault protection. Advanced functions for the detection of soft faults, which cannot presently be detected, can also be implemented. Adaptive overcurrent protection changes overcurrent settings based on connected load. Incipient and high-impedance fault detection provides early detection of arcing conditions to prevent fires, and to clear and reconfigure circuits before soft faults progress to a hard-fault condition. Power electronics techniques can be used to implement fault current limiting to prevent voltage dips during hard faults. It is concluded that these techniques will enhance the overall safety and reliability of the distribution system.

  15. Towards more efficient e-learning, intelligence and adapted teaching material

    Directory of Open Access Journals (Sweden)

    Damir Kalpić

    2010-12-01

    Full Text Available This article presents results of a research project in which we attempted to determine the relationship between efficient E-learning and teaching materials adapted based on students’ structure of intelligence. The project was conducted on approximately 500 students, 23 classes, nine elementary schools, with ten teachers of history, informatics and several licensed psychologists. E-teaching material was prepared for the subject of History for eight-grade students of elementary school. Students were tested for the structure of intelligence, and based on their most prominent component, they were divided into groups, using teaching materials adapted to their most prominent intelligence component. The results have shown that use of the adapted teaching materials achieved 6-12% better results than E-materials not adapted to students’ structure of intelligence.

  16. Adaptive Distributed Intelligent Control Architecture for Future Propulsion Systems (Preprint)

    National Research Council Canada - National Science Library

    Behbahani, Alireza R

    2007-01-01

    .... Distributed control is potentially an enabling technology for advanced intelligent propulsion system concepts and is one of the few control approaches that is able to provide improved component...

  17. Hybrid intelligent monironing systems for thermal power plant trips

    Science.gov (United States)

    Barsoum, Nader; Ismail, Firas Basim

    2012-11-01

    Steam boiler is one of the main equipment in thermal power plants. If the steam boiler trips it may lead to entire shutdown of the plant, which is economically burdensome. Early boiler trips monitoring is crucial to maintain normal and safe operational conditions. In the present work two artificial intelligent monitoring systems specialized in boiler trips have been proposed and coded within the MATLAB environment. The training and validation of the two systems has been performed using real operational data captured from the plant control system of selected power plant. An integrated plant data preparation framework for seven boiler trips with related operational variables has been proposed for IMSs data analysis. The first IMS represents the use of pure Artificial Neural Network system for boiler trip detection. All seven boiler trips under consideration have been detected by IMSs before or at the same time of the plant control system. The second IMS represents the use of Genetic Algorithms and Artificial Neural Networks as a hybrid intelligent system. A slightly lower root mean square error was observed in the second system which reveals that the hybrid intelligent system performed better than the pure neural network system. Also, the optimal selection of the most influencing variables performed successfully by the hybrid intelligent system.

  18. An intelligent tutoring system for a power plant simulator

    Energy Technology Data Exchange (ETDEWEB)

    Seifi, H.; Seifi, A.R. [Tarbiat Modarres University, Tehran (Iran). Faculty of Engineering, Dept. of Electrical Engineers

    2002-07-28

    An intelligent tutoring system (ITS) is proposed for a power plant simulator. With a well designed ITS, the need for an instructor is minimized and the operator may readily and efficiently take, in real-time, the control of simulator with appropriate messages he(she) gets from the tutoring system. Using SIMULINK and based on object oriented programming (OOP) and C programming language, a fossil-fuelled power plant simulator with an ITS is proposed. Promising results are demonstrated for a typical power plant.

  19. New intelligent magnet power supplies for LAMPF

    International Nuclear Information System (INIS)

    Cohen, S.; Sturrock, J.

    1991-01-01

    New magnet power supplies are scheduled to be installed in the proton linac at the Clinton P. Anderson Meson Physics Facility (LAMPF). The control and interface design of these power supplies represents a departure from all others onsite. A high-level ASCII control protocol has been designed. The supplies have sophisticated microprocessor control onboard and communicate with the accelerator control system via RS-422 (serial communications). The low-level software used by the accelerator control system is currently being rewritten to accommodate these new devices. They will communicate with the control system through a terminal server port connected to the site-wide ethernet backbone. This means that each supply will, for all intents and purposes, be a network object. Details of the design strategies for the analog and digital control for these supplies as well as the control protocol interface will be presented. 5 refs., 5 figs., 1 tab

  20. Intelligent Techniques for Power Systems Vulnerability Assessment

    Directory of Open Access Journals (Sweden)

    Mohamed A. El-Sharkawi

    2002-06-01

    Full Text Available With power grids considered national security matters, the reliable operation of the system is of top priority to utilities.  This concern is amplified by the utility’s deregulation, which increases the system’s openness while simultaneously decreasing the applied degree of control.  Vulnerability Assessment (VA deals with the power system’s ability to continue to provide service in case of an unforeseen catastrophic contingency.  Such contingencies may include unauthorized tripping, breaks in communication links, sabotage or intrusion by external agents, human errors, natural calamities and faults.  These contingencies could lead to a disruption of service to part or all of the system.  The service disruption is known as outage or blackout.  The paper outlines an approach by which feature extraction and boundary tracking can be implemented to achieve on line vulnerability assessment.

  1. Using FML and fuzzy technology in adaptive ambient intelligent environments

    NARCIS (Netherlands)

    Acampora, G.; Loia, V.

    2005-01-01

    Ambient Intelligence (AmI, shortly) gathers best re-sults from three key technologies, Ubiquitous Computing, Ubiq-uitous Communication, and Intelligent User Friendly Inter-faces. The functional and spatial distribution of tasks is a natu-ral thrust to employ multi-agent paradigm to design and

  2. Connections between political intelligence and power maintenance in Niccolo Machiavelli

    Directory of Open Access Journals (Sweden)

    Fábio Régio Bento

    2015-07-01

    Full Text Available The Prince, written in 1513 and published in 1531, four years after Niccolo Machiavelli's death (1469-1527, continues to be permanently reproposed, after more than five centuries of its inception, throughout a wide range of translations, not always coherent with the 1513 manuscript. In fact, as noted by Marques (2006, p. 41, Prince's Machiavelli is still presented as a “teacher of evil”. On the contrary to what the common sense affirms, however, the Florentine secretary was not Machiavellian. In this paper, through a direct study of The Prince in the Italian manuscript of 1513 (Machiavelli, 1988, and with the aid of translation from Maria Lucia Cumo (Maquiavel 1996, we shall analyze the connections in The Prince between political intelligence and virtuous maintenance of power, by claiming that The Prince is not an amoral  neither immoral book, but of political morality of the intelligent maintenance of power according to what Machiavelli understands as political virtues.

  3. Fluid intelligence and psychosocial outcome: from logical problem solving to social adaptation.

    Science.gov (United States)

    Huepe, David; Roca, María; Salas, Natalia; Canales-Johnson, Andrés; Rivera-Rei, Álvaro A; Zamorano, Leandro; Concepción, Aimée; Manes, Facundo; Ibañez, Agustín

    2011-01-01

    While fluid intelligence has proved to be central to executive functioning, logical reasoning and other frontal functions, the role of this ability in psychosocial adaptation has not been well characterized. A random-probabilistic sample of 2370 secondary school students completed measures of fluid intelligence (Raven's Progressive Matrices, RPM) and several measures of psychological adaptation: bullying (Delaware Bullying Questionnaire), domestic abuse of adolescents (Conflict Tactic Scale), drug intake (ONUDD), self-esteem (Rosenberg's Self Esteem Scale) and the Perceived Mental Health Scale (Spanish adaptation). Lower fluid intelligence scores were associated with physical violence, both in the role of victim and victimizer. Drug intake, especially cannabis, cocaine and inhalants and lower self-esteem were also associated with lower fluid intelligence. Finally, scores on the perceived mental health assessment were better when fluid intelligence scores were higher. Our results show evidence of a strong association between psychosocial adaptation and fluid intelligence, suggesting that the latter is not only central to executive functioning but also forms part of a more general capacity for adaptation to social contexts.

  4. Fluid Intelligence and Psychosocial Outcome: From Logical Problem Solving to Social Adaptation

    Science.gov (United States)

    Huepe, David; Roca, María; Salas, Natalia; Canales-Johnson, Andrés; Rivera-Rei, Álvaro A.; Zamorano, Leandro; Concepción, Aimée; Manes, Facundo; Ibañez, Agustín

    2011-01-01

    Background While fluid intelligence has proved to be central to executive functioning, logical reasoning and other frontal functions, the role of this ability in psychosocial adaptation has not been well characterized. Methodology/Principal Findings A random-probabilistic sample of 2370 secondary school students completed measures of fluid intelligence (Raven's Progressive Matrices, RPM) and several measures of psychological adaptation: bullying (Delaware Bullying Questionnaire), domestic abuse of adolescents (Conflict Tactic Scale), drug intake (ONUDD), self-esteem (Rosenberg's Self Esteem Scale) and the Perceived Mental Health Scale (Spanish adaptation). Lower fluid intelligence scores were associated with physical violence, both in the role of victim and victimizer. Drug intake, especially cannabis, cocaine and inhalants and lower self-esteem were also associated with lower fluid intelligence. Finally, scores on the perceived mental health assessment were better when fluid intelligence scores were higher. Conclusions/Significance Our results show evidence of a strong association between psychosocial adaptation and fluid intelligence, suggesting that the latter is not only central to executive functioning but also forms part of a more general capacity for adaptation to social contexts. PMID:21957464

  5. Fluid intelligence and psychosocial outcome: from logical problem solving to social adaptation.

    Directory of Open Access Journals (Sweden)

    David Huepe

    Full Text Available While fluid intelligence has proved to be central to executive functioning, logical reasoning and other frontal functions, the role of this ability in psychosocial adaptation has not been well characterized.A random-probabilistic sample of 2370 secondary school students completed measures of fluid intelligence (Raven's Progressive Matrices, RPM and several measures of psychological adaptation: bullying (Delaware Bullying Questionnaire, domestic abuse of adolescents (Conflict Tactic Scale, drug intake (ONUDD, self-esteem (Rosenberg's Self Esteem Scale and the Perceived Mental Health Scale (Spanish adaptation. Lower fluid intelligence scores were associated with physical violence, both in the role of victim and victimizer. Drug intake, especially cannabis, cocaine and inhalants and lower self-esteem were also associated with lower fluid intelligence. Finally, scores on the perceived mental health assessment were better when fluid intelligence scores were higher.Our results show evidence of a strong association between psychosocial adaptation and fluid intelligence, suggesting that the latter is not only central to executive functioning but also forms part of a more general capacity for adaptation to social contexts.

  6. Advanced and intelligent control in power electronics and drives

    CERN Document Server

    Blaabjerg, Frede; Rodríguez, José

    2014-01-01

    Power electronics and variable frequency drives are continuously developing multidisciplinary fields in electrical engineering, and it is practically not possible to write a book covering the entire area by one individual specialist. Especially by taking account the recent fast development in the neighboring fields like control theory, computational intelligence and signal processing, which all strongly influence new solutions in control of power electronics and drives. Therefore, this book is written by individual key specialist working on the area of modern advanced control methods which penetrates current implementation of power converters and drives. Although some of the presented methods are still not adopted by industry, they create new solutions with high further research and application potential. The material of the book is presented in the following three parts: Part I: Advanced Power Electronic Control in Renewable Energy Sources (Chapters 1-4), Part II: Predictive Control of Power Converters and D...

  7. Low Power Multi-Hop Networking Analysis in Intelligent Environments.

    Science.gov (United States)

    Etxaniz, Josu; Aranguren, Gerardo

    2017-05-19

    Intelligent systems are driven by the latest technological advances in many different areas such as sensing, embedded systems, wireless communications or context recognition. This paper focuses on some of those areas. Concretely, the paper deals with wireless communications issues in embedded systems. More precisely, the paper combines the multi-hop networking with Bluetooth technology and a quality of service (QoS) metric, the latency. Bluetooth is a radio license-free worldwide communication standard that makes low power multi-hop wireless networking available. It establishes piconets (point-to-point and point-to-multipoint links) and scatternets (multi-hop networks). As a result, many Bluetooth nodes can be interconnected to set up ambient intelligent networks. Then, this paper presents the results of the investigation on multi-hop latency with park and sniff Bluetooth low power modes conducted over the hardware test bench previously implemented. In addition, the empirical models to estimate the latency of multi-hop communications over Bluetooth Asynchronous Connectionless Links (ACL) in park and sniff mode are given. The designers of devices and networks for intelligent systems will benefit from the estimation of the latency in Bluetooth multi-hop communications that the models provide.

  8. Examining the Role of Emotional Intelligence between Organizational Learning and Adaptive Performance in Indian Manufacturing Industries

    Science.gov (United States)

    Pradhan, Rabindra Kumar; Jena, Lalatendu Kesari; Singh, Sanjay Kumar

    2017-01-01

    Purpose: The purpose of this study is to examine the relationship between organisational learning and adaptive performance. Furthermore, the study investigates the moderating role of emotional intelligence in the perspective of organisational learning for addressing adaptive performance of executives employed in manufacturing organisations.…

  9. Intelligent Adaptation and Personalization Techniques in Computer-Supported Collaborative Learning

    CERN Document Server

    Demetriadis, Stavros; Xhafa, Fatos

    2012-01-01

    Adaptation and personalization have been extensively studied in CSCL research community aiming to design intelligent systems that adaptively support eLearning processes and collaboration. Yet, with the fast development in Internet technologies, especially with the emergence of new data technologies and the mobile technologies, new opportunities and perspectives are opened for advanced adaptive and personalized systems. Adaptation and personalization are posing new research and development challenges to nowadays CSCL systems. In particular, adaptation should be focused in a multi-dimensional way (cognitive, technological, context-aware and personal). Moreover, it should address the particularities of both individual learners and group collaboration. As a consequence, the aim of this book is twofold. On the one hand, it discusses the latest advances and findings in the area of intelligent adaptive and personalized learning systems. On the other hand it analyzes the new implementation perspectives for intelligen...

  10. Artificial intelligence in nuclear power plants. Vol. 2

    International Nuclear Information System (INIS)

    Haapanen, P.J.

    1990-01-01

    The IAEA Specialists' Meeting on Artificial Intelligence in Nuclear Power Plants was arranged in Helsinki/Vantaa, Finland, on October 10-12, 1989, under auspices of the International Working Group of Nuclear Power Plant Control and Instrumentation of the International Atomic Energy Agency (IAEA/IWG NPPCI). Technical Research Centre of Finland together with Imatran Voima Oy and Teollisuuden Voima Oy answered for the practical arrangements of the meeting. 105 participants from 17 countries and 2 international organizations took part in the meeting and 58 papers were submitted for presentation. These papers gave a comprehensive picture of the recent status and further trends in applying the rapidly developing techniques of and safety in designing and using of nuclear power worldwide

  11. Intelligent decision aids for abnormal events in nuclear power plants

    International Nuclear Information System (INIS)

    Kafka, P.; Polke, H.

    1988-01-01

    German nuclear power plants are characterized by a high degree of automation, not only for normal operation but also for abnormal events. Therefore the role of the operating personnel is mainly a supervisory function. Nevertheless, for a spectrum of unexpected events the operating personnel have to react with manual recovery actions. In order to minimize human error in such recovery actions, different kinds of intelligent decision aid support the operators today. In this paper such aids are discussed and one of them is described in more detail. (author)

  12. The Need for Intelligent Control of Space Power Systems

    Science.gov (United States)

    May, Ryan David; Soeder, James F.; Beach, Raymond F.; McNelis, Nancy B.

    2013-01-01

    As manned spacecraft venture farther from Earth, the need for reliable, autonomous control of vehicle subsystems becomes critical. This is particularly true for the electrical power system which is critical to every other system. Autonomy can not be achieved by simple scripting techniques due to the communication latency times and the difficulty associated with failures (or combinations of failures) that need to be handled in as graceful a manner as possible to ensure system availability. Therefore an intelligent control system must be developed that can respond to disturbances and failures in a robust manner and ensure that critical system loads are served and all system constraints are respected.

  13. Heuristic decision model for intelligent nuclear power systems design

    International Nuclear Information System (INIS)

    Nassersharif, B.; Portal, M.G.; Gaeta, M.J.

    1989-01-01

    The objective of this project was to investigate intelligent nuclear power systems design. A theoretical model of the design process has been developed. A fundamental process in this model is the heuristic decision making for design (i.e., selection of methods, components, materials, etc.). Rule-based expert systems do not provide the completeness that is necessary to generate good design. A new method, based on the fuzzy set theory, has been developed and is presented here. A feedwater system knowledge base (KB) was developed for a prototype software experiment to benchmark the theory

  14. Intelligent robots for nuclear power plant inspection and surveillance

    International Nuclear Information System (INIS)

    Miyazawa, Tatsuo; Suzuki, Kazumi; Fujie, Hideo; Fujii, Masaaki; Asai, Takashi; Sugimoto, Hiroshi.

    1986-01-01

    Recently, the research and development of robotizing the patrol and works in nuclear power plants have been actively carried out since the TMI-2 accident in March, 1979. In this paper, among these robots, six examples of the movable robots, of which the working and movement were intellectualized by using information processing techniques and others, are reported, and their intellectualization is concretely discussed. In Japan, the development of the supporting system for nuclear power generation was carried out for five years from fiscal year 1980 as the project subsidized by the Ministry of International Trade and Industry, and during this period, the inspection robots for LWR plants were developed. The development of the robots for ultimate working as the large scale project of the Agency of Industrial Science and Technology aiming at further heightening the function is in progress as the eight-year project from fiscal year 1983. Monorail type automatic surveillance robots, system maintenance robots 'AMOOTY', variable crawler type intelligent movable robots, hybrid running type intelligent movable robots, monorail running type small checkup robots, and floor running type checkup and light work robots are reported. Sense information processing control and a robot language processor for expanding the function of autonomous control are outlined. (Kako, I.)

  15. Development of Android Based Powered Intelligent Wheelchair for Quadriplegic Persons

    Science.gov (United States)

    Gupta, Ashutosh; Ghosh, Tathagata; Kumar, Pradeep; Bhawna, Shruthi. S.

    2017-08-01

    Several surveys give us the view that both children and adults benefit substantially from access towards independent mobility. With the inventions of technology, no individuals are satisfied with traditional manual operated machines. To accommodate population, researchers are using technology, originally developed for mobile robots to create ‘intelligent wheelchairs’. It’s a major challenge for quadriplegic persons as they really find it difficult to manipulate powered wheelchair during the activities of their daily living. As the Smartphone era has evolved with innovative android based applications, engineers are improving and trying to make such machines simple and cheap to the next level. In this paper, we present a development of android based powered intelligent wheelchair to assist the quadriplegic person by making them self sufficient in controlling the wheelchair. The wheels of the chair can be controlled by the voice or gesture movement or by touching the screen of the android app by the challenged persons. The system uses the Bluetooth communication to interface the microcontroller and the inbuilt sensors in the android Smartphone. According to the commands received from android phone, the kinematics of the wheels are controlled.

  16. Climate adaptation in power supply - status; Klimatilpasning i kraftforsyningen - statusrapport

    Energy Technology Data Exchange (ETDEWEB)

    Steen, Roger

    2009-12-15

    A survey of the now-status in the power supply when it comes to understanding possible climatic effects of power supply, the need for climate adaptation and motivation to adapt to climate change. (AG)

  17. Beginning Power BI with Excel 2013 self-service business intelligence using Power Pivot, Power View, Power Query, and Power Map

    CERN Document Server

    Clark, Dan

    2014-01-01

    Understanding your company's data has never been easier than with Microsoft's new Power BI package for Excel 2013. Consisting of four powerful tools-Power Pivot, Power View, Power Query and Power Maps-Power BI makes self-service business intelligence a reality for a wide range of users, bridging the traditional gap between Excel users, business analysts and IT experts and making it easier for everyone to work together to build the data models that can give you game-changing insights into your business. Beginning Power BI with Excel 2013 guides you step by step through the process of analyzin

  18. The adaption study of emotional intelligence inventory in sport

    Directory of Open Access Journals (Sweden)

    İlhan Adiloğulları

    2015-12-01

    Full Text Available Aim: The purpose of this study was to test the validity and reliability of the Turkish version of Emotional Intelligence Inventory in Sport (EIIS. Material and Methods: The emotional intelligence inventory in sport which have consists of nineteen items and five subscales, 157 female (age=20,10±1,95 and 247 male (age=21,25±2,18 in total 404 (age=20,80±2,17 participants completed. Respondents of the EIIS indicate the extent to which they agree with each statement on a five-point Likert scale, ranging from 1 (strongly disagree to 5 (strongly agree. Factor structures of the scale were tested by confirmatory factor analysis in AMOS programme. Results: The resulting factor is appropriate for the 19-item inventory value but is below the desired value of the item-total correlation values b4 and paragraphs are seen as loaded with low load factors. However, there was only one item with low factor loadings that was excluded from the inventory. It was obtained acceptable fit index values of inventory that confirming factor structures of Turkish version. Internal consistency coefficients of EIIS were found ranging from 0,69 (Appraisal of others emotions, 0,85 (Appraisal of own emotions, 0,67 (Emotional regulation 0,85 (Use of emotions and 0,61 (Social skills. Conclusion: Turkish version of the Emotional intelligence inventory in Sport is can be used for Turkish athletes.

  19. Adaptation of the Wechsler Intelligence Scale for Children-IV (WISC-IV) for Vietnam.

    Science.gov (United States)

    Dang, Hoang-Minh; Weiss, Bahr; Pollack, Amie; Nguyen, Minh Cao

    2012-12-01

    Intelligence testing is used for many purposes including identification of children for proper educational placement (e.g., children with learning disabilities, or intellectually gifted students), and to guide education by identifying cognitive strengths and weaknesses so that teachers can adapt their instructional style to students' specific learning styles. Most of the research involving intelligence tests has been conducted in highly developed Western countries, yet the need for intelligence testing is as or even more important in developing countries. The present study, conducted through the Vietnam National University Clinical Psychology CRISP Center , focused on the cultural adaptation of the WISC-IV intelligence test for Vietnam. We report on (a) the adaptation process including the translation, cultural analysis and modifications involved in adaptation, (b) present results of two pilot studies, and (c) describe collection of the standardization sample and results of analyses with the standardization sample, with the goal of sharing our experience with other researchers who may be involved in or interested in adapting or developing IQ tests for non-Western, non-English speaking cultures.

  20. Adaptive electrothermal protection of power converters

    Directory of Open Access Journals (Sweden)

    Baraniuk G. A.

    2017-06-01

    Full Text Available Thermal management for power converters during normal operation and transient modes when electrical components are warmed up is an actual problem. This can be particularly important for converters with intermittent duty operation, e.g. power supplies for resistance welding. According to some research, nearly 60% of failures are temperature-induced, and for every 10°C temperature rise in operating environment the failure rate nearly doubles. In this paper, thermal motion of state equations eigenvalue is analysed. It is shown, that in semiconductor converters with an output smoothing filter it is appropriate to use thermal protection devices based on thermal normalisation of the converter filter and, while for cases when short circuits are possible it is appropriate to use a soft start system with thermal adaptation for soft start time factor. Based on these results, two systems of thermal protections operating for semiconductor power converters are introduced. Simulation of combined electromagnetic and thermal processes in buck converter operating with both thermal management systems in overlapping environments MATLAB/Simulink and PLECS showed the possibility to significantly reduce thermal shock on semiconductor components. Using the system of filter parameters normalisation decreases the temperature of the crystal from 210°C to 85°C, using the adaptive soft start system decreases the temperature from 180°C to 80°C. The simulation results are confirmed by tests on real devices.

  1. Fault Diagnosis of Power Systems Using Intelligent Systems

    Science.gov (United States)

    Momoh, James A.; Oliver, Walter E. , Jr.

    1996-01-01

    The power system operator's need for a reliable power delivery system calls for a real-time or near-real-time Al-based fault diagnosis tool. Such a tool will allow NASA ground controllers to re-establish a normal or near-normal degraded operating state of the EPS (a DC power system) for Space Station Alpha by isolating the faulted branches and loads of the system. And after isolation, re-energizing those branches and loads that have been found not to have any faults in them. A proposed solution involves using the Fault Diagnosis Intelligent System (FDIS) to perform near-real time fault diagnosis of Alpha's EPS by downloading power transient telemetry at fault-time from onboard data loggers. The FDIS uses an ANN clustering algorithm augmented with a wavelet transform feature extractor. This combination enables this system to perform pattern recognition of the power transient signatures to diagnose the fault type and its location down to the orbital replaceable unit. FDIS has been tested using a simulation of the LeRC Testbed Space Station Freedom configuration including the topology from the DDCU's to the electrical loads attached to the TPDU's. FDIS will work in conjunction with the Power Management Load Scheduler to determine what the state of the system was at the time of the fault condition. This information is used to activate the appropriate diagnostic section, and to refine if necessary the solution obtained. In the latter case, if the FDIS reports back that it is equally likely that the faulty device as 'start tracker #1' and 'time generation unit,' then based on a priori knowledge of the system's state, the refined solution would be 'star tracker #1' located in cabinet ITAS2. It is concluded from the present studies that artificial intelligence diagnostic abilities are improved with the addition of the wavelet transform, and that when such a system such as FDIS is coupled to the Power Management Load Scheduler, a faulty device can be located and isolated

  2. Optical Communication System for Remote Monitoring and Adaptive Control of Distributed Ground Sensors Exhibiting Collective Intelligence

    Energy Technology Data Exchange (ETDEWEB)

    Cameron, S.M.; Stantz, K.M.; Trahan, M.W.; Wagner, J.S.

    1998-11-01

    Comprehensive management of the battle-space has created new requirements in information management, communication, and interoperability as they effect surveillance and situational awareness. The objective of this proposal is to expand intelligent controls theory to produce a uniquely powerful implementation of distributed ground-based measurement incorporating both local collective behavior, and interoperative global optimization for sensor fusion and mission oversight. By using a layered hierarchal control architecture to orchestrate adaptive reconfiguration of autonomous robotic agents, we can improve overall robustness and functionality in dynamic tactical environments without information bottlenecks. In this concept, each sensor is equipped with a miniaturized optical reflectance modulator which is interactively monitored as a remote transponder using a covert laser communication protocol from a remote mothership or operative. Robot data-sharing at the ground level can be leveraged with global evaluation criteria, including terrain overlays and remote imaging data. Information sharing and distributed intelli- gence opens up a new class of remote-sensing applications in which small single-function autono- mous observers at the local level can collectively optimize and measure large scale ground-level signals. AS the need for coverage and the number of agents grows to improve spatial resolution, cooperative behavior orchestrated by a global situational awareness umbrella will be an essential ingredient to offset increasing bandwidth requirements within the net. A system of the type described in this proposal will be capable of sensitively detecting, tracking, and mapping spatial distributions of measurement signatures which are non-stationary or obscured by clutter and inter- fering obstacles by virtue of adaptive reconfiguration. This methodology could be used, for example, to field an adaptive ground-penetrating radar for detection of underground structures in

  3. The Dynamic Interplay among EFL Learners' Ambiguity Tolerance, Adaptability, Cultural Intelligence, Learning Approach, and Language Achievement

    Science.gov (United States)

    Alahdadi, Shadi; Ghanizadeh, Afsaneh

    2017-01-01

    A key objective of education is to prepare individuals to be fully-functioning learners. This entails developing the cognitive, metacognitive, motivational, cultural, and emotional competencies. The present study aimed to examine the interrelationships among adaptability, tolerance of ambiguity, cultural intelligence, learning approach, and…

  4. The Relation between Intelligence and Adaptive Behavior: A Meta-Analysis

    Science.gov (United States)

    Alexander, Ryan M.

    2017-01-01

    Intelligence tests and adaptive behavior scales measure vital aspects of the multidimensional nature of human functioning. Assessment of each is a required component in the diagnosis or identification of intellectual disability, and both are frequently used conjointly in the assessment and identification of other developmental disabilities. The…

  5. Road Nail: Experimental Solar Powered Intelligent Road Marking System

    Science.gov (United States)

    Samardžija, Dragan; Teslić, Nikola; Todorović, Branislav M.; Kovač, Erne; Isailović, Đorđe; Miladinović, Bojan

    2012-03-01

    Driving in low visibility conditions (night time, fog or heavy precipitation) is particularly challenging task with an increased probability of traffic accidents and possible injuries. Road Nail is a solar powered intelligent road marking system of wirelessly networked signaling devices that improve driver safety in low visibility conditions along hazardous roadways. Nails or signaling devices are autonomous nodes with capability to accumulate energy, exchange wireless messages, detect approaching vehicles and emit signalization light. We have built an experimental test-bed that consists of 20 nodes and a cellular gateway. Implementation details of the above system, including extensive measurements and performance evaluations in realistic field deployments are presented. A novel distributed network topology discovery scheme is proposed which integrates both sensor and wireless communication aspects, where nodes act autonomously. Finally, integration of the Road Nail system with the cellular network and the Internet is described.

  6. ARTIFICIAL INTELLIGENT SYSTEM FOR MEASUREMENT OF HARMONIC POWERS

    Directory of Open Access Journals (Sweden)

    Jovitha Jerome

    2017-11-01

    Full Text Available The importance of the electric power quality (PQ demands new methodologies and measurement tools in the power industry for the analysis and measurement of the basic electric magnitudes necessary. This paper presents a new measurement procedure based on neural networks for the estimation of harmonic amplitudes of current/voltage and respective harmonic powers. The measurement scheme is built with two neural network modules. The first module is an adaptive linear neuron (ADALINE that is the kernel part of estimation of complex harmonic coefficients of the current/voltage. The second module is feedforward neural network that obtains the harmonic active/reactive powers. In order to perform digital simulation the Feedforward and Adaline neural network tools were developed in LabVIEW. This measurement algorithm was tested for the practical cases and found to be robust, computationally fast and efficient.

  7. Fluid intelligence and neural mechanisms of conflict adaptation

    DEFF Research Database (Denmark)

    Liu, Tongran; Xiao, Tong; Jiannong, Shi

    2016-01-01

    The current study investigated whether adolescents with different intellectual levels have different conflict adaptation processes. Adolescents with high and average IQ abilities were enrolled, and their behavioral responses and event-related potentials (ERPs) were recorded during a modified...... Eriksen flanker task. Both groups showed reliable conflict adaptation effects (CAE) with regard to the reaction time (RT), and they showed a faster response to the cC condition than to the iC condition and faster response to the iI condition than to the cI condition. The IQ-related findings showed...... that high IQ adolescents had shorter RTs than their average-IQ counterparts in the cI, iC, and iI conditions, with smaller RT-CAE values. These findings indicated that high IQ adolescents had superior conflict adaptation processes. The electrophysiological findings showed that the cI condition required more...

  8. A new approach to PWR power control using intelligent techniques

    International Nuclear Information System (INIS)

    Boroushaki, M.; Ghofrani, M.B.; Lucas, C.; Yazdanpanah, M.J.; Sadati, N.

    2004-01-01

    Improved load following capability is one of the main technical performances of advanced PWR(APWR). Controlling the nuclear reactor core during load following operation encounters some difficulties. These difficulties mainly arise from nuclear reactor core limitations in local power peaking, while the core is subject to large and sharp variation of local power density during transients. Axial offset (A.O) is the parameter usually used to represent of core power peaking, in form of a practical parameter. This paper, proposes a new intelligent approach to A.o control of PWR nuclear reactors core during load following operation. This method uses a neural network model of the core to predict the dynamic behavior of the core and a fuzzy critic based on the operator knowledge and experience for the purpose of decision-making during load following operations. Simulation results show that this method can use optimum control rod groups maneuver with variable overlapping and may improve the reactor load following capability

  9. Intelligent control of non-linear dynamical system based on the adaptive neurocontroller

    Science.gov (United States)

    Engel, E.; Kovalev, I. V.; Kobezhicov, V.

    2015-10-01

    This paper presents an adaptive neuro-controller for intelligent control of non-linear dynamical system. The formed as the fuzzy selective neural net the adaptive neuro-controller on the base of system's state, creates the effective control signal under random perturbations. The validity and advantages of the proposed adaptive neuro-controller are demonstrated by numerical simulations. The simulation results show that the proposed controller scheme achieves real-time control speed and the competitive performance, as compared to PID, fuzzy logic controllers.

  10. Intelligent fault recognition strategy based on adaptive optimized multiple centers

    Science.gov (United States)

    Zheng, Bo; Li, Yan-Feng; Huang, Hong-Zhong

    2018-06-01

    For the recognition principle based optimized single center, one important issue is that the data with nonlinear separatrix cannot be recognized accurately. In order to solve this problem, a novel recognition strategy based on adaptive optimized multiple centers is proposed in this paper. This strategy recognizes the data sets with nonlinear separatrix by the multiple centers. Meanwhile, the priority levels are introduced into the multi-objective optimization, including recognition accuracy, the quantity of optimized centers, and distance relationship. According to the characteristics of various data, the priority levels are adjusted to ensure the quantity of optimized centers adaptively and to keep the original accuracy. The proposed method is compared with other methods, including support vector machine (SVM), neural network, and Bayesian classifier. The results demonstrate that the proposed strategy has the same or even better recognition ability on different distribution characteristics of data.

  11. Intelligent Context-Aware and Adaptive Interface for Mobile LBS

    Directory of Open Access Journals (Sweden)

    Jiangfan Feng

    2015-01-01

    Full Text Available Context-aware user interface plays an important role in many human-computer Interaction tasks of location based services. Although spatial models for context-aware systems have been studied extensively, how to locate specific spatial information for users is still not well resolved, which is important in the mobile environment where location based services users are impeded by device limitations. Better context-aware human-computer interaction models of mobile location based services are needed not just to predict performance outcomes, such as whether people will be able to find the information needed to complete a human-computer interaction task, but to understand human processes that interact in spatial query, which will in turn inform the detailed design of better user interfaces in mobile location based services. In this study, a context-aware adaptive model for mobile location based services interface is proposed, which contains three major sections: purpose, adjustment, and adaptation. Based on this model we try to describe the process of user operation and interface adaptation clearly through the dynamic interaction between users and the interface. Then we show how the model applies users’ demands in a complicated environment and suggested the feasibility by the experimental results.

  12. Intelligent Context-Aware and Adaptive Interface for Mobile LBS.

    Science.gov (United States)

    Feng, Jiangfan; Liu, Yanhong

    2015-01-01

    Context-aware user interface plays an important role in many human-computer Interaction tasks of location based services. Although spatial models for context-aware systems have been studied extensively, how to locate specific spatial information for users is still not well resolved, which is important in the mobile environment where location based services users are impeded by device limitations. Better context-aware human-computer interaction models of mobile location based services are needed not just to predict performance outcomes, such as whether people will be able to find the information needed to complete a human-computer interaction task, but to understand human processes that interact in spatial query, which will in turn inform the detailed design of better user interfaces in mobile location based services. In this study, a context-aware adaptive model for mobile location based services interface is proposed, which contains three major sections: purpose, adjustment, and adaptation. Based on this model we try to describe the process of user operation and interface adaptation clearly through the dynamic interaction between users and the interface. Then we show how the model applies users' demands in a complicated environment and suggested the feasibility by the experimental results.

  13. Intelligent system to control electric power distribution networks

    Directory of Open Access Journals (Sweden)

    Pablo CHAMOSO

    2016-07-01

    Full Text Available The use of high voltage power lines transport involves some risks that may be avoided with periodic reviews as imposed by law in most countries. The objective of this work is to reduce the number of these periodic reviews so that the maintenance cost of power lines is also reduced. To reduce the number of transmission towers (TT to be reviewed, a virtual organization (VO based system of agents is proposed in conjunction with different artificial intelligence methods and algorithms. This system is able to propose a sample of TT from a selected set to be reviewed and to ensure that the whole set will have similar values without needing to review all the TT. As a result, the system provides a software solution to manage all the review processes and all the TT of Spain, allowing the review companies to use the application either when they initiate a new review process for a whole line or area of TT, or when they want to place an entirely new set of TT, in which case the system would recommend the best place and the best type of structure to use.

  14. The dynamic interplay among EFL learners’ ambiguity tolerance, adaptability, cultural intelligence, learning approach, and language achievement

    Directory of Open Access Journals (Sweden)

    Shadi Alahdadi

    2017-01-01

    Full Text Available A key objective of education is to prepare individuals to be fully-functioning learners. This entails developing the cognitive, metacognitive, motivational, cultural, and emotional competencies. The present study aimed to examine the interrelationships among adaptability, tolerance of ambiguity, cultural intelligence, learning approach, and language achievement as manifestations of the above competencies within a single model. The participants comprised one hundred eighty BA and MA Iranian university students studying English language teaching and translation. The instruments used in this study consisted of the translated versions of four questionnaires: second language tolerance of ambiguity scale, adaptability taken from emotional intelligence inventory, cultural intelligence (CQ inventory, and the revised study process questionnaire measuring surface and deep learning. The results estimated via structural equation modeling (SEM revealed that the proposed model containing the variables under study had a good fit with the data. It was found that all the variables except adaptability directly influenced language achievement with deep approach having the highest impact and ambiguity tolerance having the lowest influence. In addition, ambiguity tolerance was a positive and significant predictor of deep approach. CQ was found to be under the influence of both ambiguity tolerance and adaptability. The findings were discussed in the light of the yielded results.

  15. Application of MCU to intelligent interface of high precision magnet power supply

    International Nuclear Information System (INIS)

    Xu Ruinian; Li Deming

    2004-01-01

    Application of the high-capability MCU in the intelligent interface is introduced in this paper. A prototype of intelligent interface for high precision huge magnet power supply was developed successfully. This intelligent interface was composed of two parts: operation panel and main board, both of which adopt a MCU of PIC16F877 respectively. The interface has many advantages, such as small size, low cost and good interference immunity. (authors)

  16. Modeling Power Systems as Complex Adaptive Systems

    Energy Technology Data Exchange (ETDEWEB)

    Chassin, David P.; Malard, Joel M.; Posse, Christian; Gangopadhyaya, Asim; Lu, Ning; Katipamula, Srinivas; Mallow, J V.

    2004-12-30

    Physical analogs have shown considerable promise for understanding the behavior of complex adaptive systems, including macroeconomics, biological systems, social networks, and electric power markets. Many of today's most challenging technical and policy questions can be reduced to a distributed economic control problem. Indeed, economically based control of large-scale systems is founded on the conjecture that the price-based regulation (e.g., auctions, markets) results in an optimal allocation of resources and emergent optimal system control. This report explores the state-of-the-art physical analogs for understanding the behavior of some econophysical systems and deriving stable and robust control strategies for using them. We review and discuss applications of some analytic methods based on a thermodynamic metaphor, according to which the interplay between system entropy and conservation laws gives rise to intuitive and governing global properties of complex systems that cannot be otherwise understood. We apply these methods to the question of how power markets can be expected to behave under a variety of conditions.

  17. Cognitions as determinants of (mal)adaptive emotions and emotionally intelligent behavior in an organizational context.

    Science.gov (United States)

    Spörrle, Matthias; Welpe, Isabell M; Försterling, Friedrich

    2006-01-01

    This study applies the theoretical concepts of Rational Emotive Behavior Therapy (REBT; Ellis, 1962, 1994) to the analysis of functional and dysfunctional behaviour and emotions in the workplace and tests central assumptions of REBT in an organizational setting. We argue that Ellis' appraisal theory of emotion sheds light on some of the cognitive and emotional antecedents of emotional intelligence and emotionally intelligent behaviour. In an extension of REBT, we posit that adaptive emotions resulting from rational cognitions reflect more emotional intelligence than maladaptive emotions which result from irrational cognitions, because the former lead to functional behaviour. We hypothesize that semantically similar emotions (e.g. annoyance and rage) lead to different behavioural reactions and have a different functionality in an organizational context. The results of scenario experiments using organizational vignettes confirm the central assumptions of Ellis' appraisal theory and support our hypotheses of a correspondence between adaptive emotions and emotionally intelligent behaviour. Additionally, we find evidence that irrational job-related attitudes result in reduced work (but not life) satisfaction.

  18. Climate change, nuclear power, and the adaptation-mitigation dilemma

    International Nuclear Information System (INIS)

    Kopytko, Natalie; Perkins, John

    2011-01-01

    Many policy-makers view nuclear power as a mitigation for climate change. Efforts to mitigate and adapt to climate change, however, interact with existing and new nuclear power plants, and these installations must contend with dilemmas between adaptation and mitigation. This paper develops five criteria to assess the adaptation-mitigation dilemma on two major points: (1) the ability of nuclear power to adapt to climate change and (2) the potential for nuclear power operation to hinder climate change adaptation. Sea level rise models for nine coastal sites in the United States, a review of US Nuclear Regulatory Commission documents, and reports from France's nuclear regulatory agency provided insights into issues that have arisen from sea level rise, shoreline erosion, coastal storms, floods, and heat waves. Applying the criteria to inland and coastal nuclear power plants reveals several weaknesses. Safety stands out as the primary concern at coastal locations, while inland locations encounter greater problems with interrupted operation. Adapting nuclear power to climate change entails either increased expenses for construction and operation or incurs significant costs to the environment and public health and welfare. Mere absence of greenhouse gas emissions is not sufficient to assess nuclear power as a mitigation for climate change. - Research Highlights: → The adaptation-mitigation criteria reveal nuclear power's vulnerabilities. → Climate change adaptation could become too costly at many sites. → Nuclear power operation jeopardizes climate change adaptation. → Extreme climate events pose a safety challenge.

  19. Brief Report: Adaptation of the Italian Version of the Tromso Social Intelligence Scale to the Adolescent Population

    Science.gov (United States)

    Gini, Gianluca

    2006-01-01

    Social intelligence is a construct that has shown promising practical applications, but its use in research and applied settings has been limited by definitional problems and the complexity of most existing measures of social intelligence. The goal of the present study was to adapt the Italian version [Gini & Iotti (2004) "La Tromso…

  20. PowerPivot for Business Intelligence Using Excel and SharePoint

    CERN Document Server

    Ralston, Barry

    2011-01-01

    PowerPivot comprises a set of technologies for easy access to data mining and business intelligence analysis from Microsoft Excel and SharePoint. Power users and developers alike can create sophisticated, online analytic processing (OLAP) solutions using PowerPivot for Excel, and then share those solutions with other users via PowerPivot for SharePoint. Data can be pulled in from any of the leading database platforms, as well as from spreadsheets and flat files. PowerPivot for Business Intelligence Using Excel and SharePoint is your key to mastering PowerPivot. The book takes a scenario-based

  1. Can enriching emotional intelligence improve medical students? proactivity and adaptability during OB/GYN clerkships?

    OpenAIRE

    Guseh, Stephanie H.; Chen, Xiaodong P.; Johnson, Natasha R.

    2015-01-01

    Objectives: The purpose of this pilot study was to examine our hypothesis that enriching workplace emotional intelligence through resident coaches could improve third-year medical students’ adaptability and proactivity on the Obstetrics and Gynecology clerkship. Methods: An observational pilot study was conducted in a teaching hospital. Fourteen 3rd year medical students from two cohorts of clerkships were randomly divided into two groups, and equally assigned to trained resident coaches and ...

  2. Development of an intelligent controller for power generators

    International Nuclear Information System (INIS)

    Maxted, Clive; Waller, Winston

    2005-01-01

    This paper is a description of the development of an embedded controller for high power industrial diesel generators. The aim of the project was to replace the existing discrete logic design by an intelligent versatile and user configurable control system. A prototype embedded PC controlled system was developed, capable of fully replacing the existing system, with a colour TFT display and keypad. Features include fully automatic generator control as before with status and alarm display and monitoring of engine parameters, along with data logging, remote communications and a means of analysing data. The unit was tested on the bench and on diesel generators for the core controlling functionality to prove compliance with the specifications. The results of the testing proved the unit's suitability as a replacement for the existing system in its intended environment. The significance of this study is that a low cost replacement solution has been found for an industrial application by transferring modern technological knowledge to a small business. The company are now able to build on the design and take it into production, reducing servicing and production costs

  3. Military Intelligence : Telling Telling Truth to Power to Bewilderment

    NARCIS (Netherlands)

    Baudet, Floribert; Braat, E.C.; van Woensel, Jeoffrey; Wever, Aad

    2017-01-01

    This introductory chapter discusses 100 years of military intelligence and outlines the main changes that distinguish the post-Cold war period from the preceding one. This is characterised by a blurring of the boundaries between civilian and military intelligence, between investigative services and

  4. "Intelligent Ensemble" Projections of Precipitation and Surface Radiation in Support of Agricultural Climate Change Adaptation

    Science.gov (United States)

    Taylor, Patrick C.; Baker, Noel C.

    2015-01-01

    Earth's climate is changing and will continue to change into the foreseeable future. Expected changes in the climatological distribution of precipitation, surface temperature, and surface solar radiation will significantly impact agriculture. Adaptation strategies are, therefore, required to reduce the agricultural impacts of climate change. Climate change projections of precipitation, surface temperature, and surface solar radiation distributions are necessary input for adaption planning studies. These projections are conventionally constructed from an ensemble of climate model simulations (e.g., the Coupled Model Intercomparison Project 5 (CMIP5)) as an equal weighted average, one model one vote. Each climate model, however, represents the array of climate-relevant physical processes with varying degrees of fidelity influencing the projection of individual climate variables differently. Presented here is a new approach, termed the "Intelligent Ensemble, that constructs climate variable projections by weighting each model according to its ability to represent key physical processes, e.g., precipitation probability distribution. This approach provides added value over the equal weighted average method. Physical process metrics applied in the "Intelligent Ensemble" method are created using a combination of NASA and NOAA satellite and surface-based cloud, radiation, temperature, and precipitation data sets. The "Intelligent Ensemble" method is applied to the RCP4.5 and RCP8.5 anthropogenic climate forcing simulations within the CMIP5 archive to develop a set of climate change scenarios for precipitation, temperature, and surface solar radiation in each USDA Farm Resource Region for use in climate change adaptation studies.

  5. Prognostics-Enabled Power Supply for ADAPT Testbed, Phase II

    Data.gov (United States)

    National Aeronautics and Space Administration — Ridgetop's role is to develop electronic prognostics for sensing power systems in support of NASA/Ames ADAPT testbed. The prognostic enabled power systems from...

  6. Improvement of Transient Stability in a Hybrid Power Multi-System Using a Designed NIDC (Novel Intelligent Damping Controller

    Directory of Open Access Journals (Sweden)

    Ting-Chia Ou

    2017-04-01

    Full Text Available This paper endeavors to apply a novel intelligent damping controller (NIDC for the static synchronous compensator (STATCOM to reduce the power fluctuations, voltage support and damping in a hybrid power multi-system. In this paper, we discuss the integration of an offshore wind farm (OWF and a seashore wave power farm (SWPF via a high-voltage, alternating current (HVAC electric power transmission line that connects the STATCOM and the 12-bus hybrid power multi-system. The hybrid multi-system consists of a battery energy storage system (BESS and a micro-turbine generation (MTG. The proposed NIDC consists of a designed proportional–integral–derivative (PID linear controller, an adaptive critic network and a proposed functional link-based novel recurrent fuzzy neural network (FLNRFNN. Test results show that the proposed controller can achieve better damping characteristics and effectively stabilize the network under unstable conditions.

  7. Power cycling test and failure analysis of molded Intelligent Power IGBT Module under different temperature swing durations

    DEFF Research Database (Denmark)

    Choi, Uimin; Blaabjerg, Frede; Jørgensen, Søren

    2016-01-01

    on the lifetime of 600 V, 30 A, 3-phase molded Intelligent PowerModules (IPM) and their failuremechanismsare investigated. The study is based on the accelerated power cycling test results of 36 samples under 6 different conditions and tests are performed under realistic electrical conditions by an advanced power...

  8. Advance in study of intelligent diagnostic method for nuclear power plant

    International Nuclear Information System (INIS)

    Zhou Gang; Yang Li

    2008-01-01

    The advance of research on the application of three types of intelligent diagnostic approach based on neural network (ANN), fuzzy logic and expert system to the operation status monitoring and fault diagnosis of nuclear power plant (NPP) was reviewed. The research status and characters on status monitoring and fault diagnosis approaches based on neural network, fuzzy logic and expert system for nuclear power plant were analyzed. The development trend of applied research on intelligent diagnostic approaches for nuclear power plant was explored. The analysis results show that the research achievements on intelligent diagnostic approaches based on fuzzy logic and expert system for nuclear power plant are not much relatively. The research of intelligent diagnostic approaches for nuclear power plant concentrate on the aspect of operation status monitoring and fault diagnosis based on neural networks for nuclear power plant. The advancing tendency of intelligent diagnostic approaches for nuclear power plant is the combination of various intelligent diagnostic approaches, the combination of neural network diagnostic approaches and other diagnostic approaches as well as multiple neural network diagnostic approaches. (authors)

  9. Enhancing nuclear power plant performance through the use of artificial intelligence

    International Nuclear Information System (INIS)

    Maren, A.J.; Miller, L.F.; Tsoukalas, L.H.; Uhrig, R.E.; Upadhyaya, B.R.

    1992-01-01

    The objective of this research was to advance the state-of-the-art of applying artificial intelligence technology (both expert systems and neural networks) to enhancing the performance (safety, efficiency, control and management) of nuclear power plants. A second, but equally important objective, was to build a broadly based critical mass of expertise in the artificial intelligence field that can be brought to bear on the technology of nuclear power plants

  10. The intelligent system for accident identification in nuclear power plant

    International Nuclear Information System (INIS)

    Hernandez, Jorge Luis.

    1998-01-01

    Accidental situations in NPP are of greet concern for operators, the facility, regulatory bodies and the environment. This work proposes a design of intelligent system aimed to assist the operator in the process of decision making when initiator events with higher relative contribution to the reactor core damage occur. The intelligent System uses the results of the pre operational Probabilistic Safety Assessment and the Thermal hydraulic Safety Analyses of the NPP Juragua as source for building its knowledge base. The nucleus of the system is presented as a design of an intelligent hybrid system from the combination of the artificial intelligence techniques: fussy logic and artificial neural networks. The system works with variables from the process of the firsts circuit, second circuit and the containment and it is presented as a model for the integration of safety analyses in the process of decision making by the operator when tackling with accidental situations

  11. LEARNING STYLES BASED ADAPTIVE INTELLIGENT TUTORING SYSTEMS: DOCUMENT ANALYSIS OF ARTICLES PUBLISHED BETWEEN 2001. AND 2016.

    Directory of Open Access Journals (Sweden)

    Amit Kumar

    2017-12-01

    Full Text Available Actualizing instructional intercessions to suit learner contrasts has gotten extensive consideration. Among these individual contrast factors, the observational confirmation in regards to the academic benefit of learning styles has been addressed, yet the examination on the issue proceeds. Late improvements in web-based executions have driven researchers to re-examine the learning styles in adaptive tutoring frameworks. Adaptivity in intelligent tutoring systems is strongly influenced by the learning style of a learner. This study involved extensive document analysis of adaptive tutoring systems based on learning styles. Seventy-eight studies in literature from 2001 to 2016 were collected and classified under select parameters such as main focus, purpose, research types, methods, types and levels of participants, field/area of application, learner modelling, data gathering tools used and research findings. The current studies reveal that majority of the studies defined a framework or architecture of adaptive intelligent tutoring system (AITS while others focused on impact of AITS on learner satisfaction and academic outcomes. Currents trends, gaps in literature and ications were discussed.

  12. Intelligent control system for nuclear power plant mobile robot

    International Nuclear Information System (INIS)

    Koenig, A.; Lecoeur-Taibi, I.; Crochon, E.; Vacherand, F.

    1991-01-01

    In order to fully optimize the efficiency of the perception and navigation components available on a mobile robot, the upper level of a mobile robot control requires intelligence support to unload the work of the teleoperator. This knowledge-based system has to manage a priori data such as the map of the workspace, the mission, the characteristics of sensors and robot, but also, the current environment state and the running mission. It has to issue a plan to drive the sensors to focus on relevant objects or to scan the environment and to select the best algorithms depending on the current situation. The environment workspace is a nuclear power plant building. The teleoperated robot is a mobile wheeled or legged vehicle that moves inside the different floors of the building. There are three types of mission: radio-activity survey, inspection and intervention. To perform these goals the robot must avoid obstacles, pass through doors, possibly climb stairs and recognize valves and pipes. The perception control system has to provide the operator with a synthetic view of the surroundings. It manages background tasks such as obstacle detection and free space map building, and specific tasks such as beacon recognition for odometry relocalization and valve detection for maintenance. To do this, the system solves perception resources conflicts, taking into account the current states of the sensors and the current conditions such as lightness or darkness, cluttered scenes, sensor failure. A perception plan is issued from the mission goals, planned path, relocalization requirements and available perception resources. Basically, the knowledge-based system is implemented on a blackboard architecture which includes two parts: a top-down planning part and a bottom-up perception part. The results of the perception are continuously sent to the operator who can trigger new perception actions. (author)

  13. Simulation Modeling of Intelligent Control Algorithms for Constructing Autonomous Power Supply Systems with Improved Energy Efficiency

    Directory of Open Access Journals (Sweden)

    Gimazov Ruslan

    2018-01-01

    Full Text Available The paper considers the issue of supplying autonomous robots by solar batteries. Low efficiency of modern solar batteries is a critical issue for the whole industry of renewable energy. The urgency of solving the problem of improved energy efficiency of solar batteries for supplying the robotic system is linked with the task of maximizing autonomous operation time. Several methods to improve the energy efficiency of solar batteries exist. The use of MPPT charge controller is one these methods. MPPT technology allows increasing the power generated by the solar battery by 15 – 30%. The most common MPPT algorithm is the perturbation and observation algorithm. This algorithm has several disadvantages, such as power fluctuation and the fixed time of the maximum power point tracking. These problems can be solved by using a sufficiently accurate predictive and adaptive algorithm. In order to improve the efficiency of solar batteries, autonomous power supply system was developed, which included an intelligent MPPT charge controller with the fuzzy logic-based perturbation and observation algorithm. To study the implementation of the fuzzy logic apparatus in the MPPT algorithm, in Matlab/Simulink environment, we developed a simulation model of the system, including solar battery, MPPT controller, accumulator and load. Results of the simulation modeling established that the use of MPPT technology had increased energy production by 23%; introduction of the fuzzy logic algorithm to MPPT controller had greatly increased the speed of the maximum power point tracking and neutralized the voltage fluctuations, which in turn reduced the power underproduction by 2%.

  14. Power Adaptation Based on Truncated Channel Inversion for Hybrid FSO/RF Transmission With Adaptive Combining

    KAUST Repository

    Rakia, Tamer

    2015-07-23

    Hybrid free-space optical (FSO)/radio-frequency (RF) systems have emerged as a promising solution for high-data-rate wireless communications. In this paper, we consider power adaptation strategies based on truncated channel inversion for the hybrid FSO/RF system employing adaptive combining. Specifically, we adaptively set the RF link transmission power when FSO link quality is unacceptable to ensure constant combined signal-to-noise ratio (SNR) at the receiver. Two adaptation strategies are proposed. One strategy depends on the received RF SNR, whereas the other one depends on the combined SNR of both links. Analytical expressions for the outage probability of the hybrid system with and without power adaptation are obtained. Numerical examples show that the hybrid FSO/RF system with power adaptation achieves a considerable outage performance improvement over the conventional system.

  15. Power Adaptation Based on Truncated Channel Inversion for Hybrid FSO/RF Transmission With Adaptive Combining

    KAUST Repository

    Rakia, Tamer; Hong-Chuan Yang; Gebali, Fayez; Alouini, Mohamed-Slim

    2015-01-01

    Hybrid free-space optical (FSO)/radio-frequency (RF) systems have emerged as a promising solution for high-data-rate wireless communications. In this paper, we consider power adaptation strategies based on truncated channel inversion for the hybrid FSO/RF system employing adaptive combining. Specifically, we adaptively set the RF link transmission power when FSO link quality is unacceptable to ensure constant combined signal-to-noise ratio (SNR) at the receiver. Two adaptation strategies are proposed. One strategy depends on the received RF SNR, whereas the other one depends on the combined SNR of both links. Analytical expressions for the outage probability of the hybrid system with and without power adaptation are obtained. Numerical examples show that the hybrid FSO/RF system with power adaptation achieves a considerable outage performance improvement over the conventional system.

  16. Building an adaptive agent to monitor and repair the electrical power system of an orbital satellite

    Science.gov (United States)

    Tecuci, Gheorghe; Hieb, Michael R.; Dybala, Tomasz

    1995-01-01

    Over several years we have developed a multistrategy apprenticeship learning methodology for building knowledge-based systems. Recently we have developed and applied our methodology to building intelligent agents. This methodology allows a subject matter expert to build an agent in the same way in which the expert would teach a human apprentice. The expert will give the agent specific examples of problems and solutions, explanations of these solutions, or supervise the agent as it solves new problems. During such interactions, the agent learns general rules and concepts, continuously extending and improving its knowledge base. In this paper we present initial results on applying this methodology to build an intelligent adaptive agent for monitoring and repair of the electrical power system of an orbital satellite, stressing the interaction with the expert during apprenticeship learning.

  17. Emotional intelligence and features of social and psychological adaptation in adolescents with deviant behavior

    Directory of Open Access Journals (Sweden)

    Degtyarev A.V.,

    2014-11-01

    Full Text Available The problem of social-psychological adaptation of adolescents with deviant behavioral today is of particular relevance in relation to the current process of restructuring of educational institutions - the merging of general and specialized schools for adolescents with behavioral problems in a unified educational complexes. In these circumstances it is necessary to find an efficient tool that will simultaneously accelerate the process of adaptation and have a positive preventive effect. In this article, the author shows that such a tool can become the emotional intelligence as a construct that includes various abilities of the emotional sphere. The main hypothesis of the study was that the socio-psychological adaptation of adolescents with deviant behavior has its own characteristics, different from the norm group, and is interconnected with the components of emotional intelligence. The study was conducted on the basis of general education school № 2077 formed by the merger of five educational institutions: the former school № 738, № 703, № 702, № 7 and № 77. The study involved 222 teenagers from 14 to 16 years (111 girls and 111 boys.

  18. A generic architecture for an adaptive, interoperable and intelligent type 2 diabetes mellitus care system.

    Science.gov (United States)

    Uribe, Gustavo A; Blobel, Bernd; López, Diego M; Schulz, Stefan

    2015-01-01

    Chronic diseases such as Type 2 Diabetes Mellitus (T2DM) constitute a big burden to the global health economy. T2DM Care Management requires a multi-disciplinary and multi-organizational approach. Because of different languages and terminologies, education, experiences, skills, etc., such an approach establishes a special interoperability challenge. The solution is a flexible, scalable, business-controlled, adaptive, knowledge-based, intelligent system following a systems-oriented, architecture-centric, ontology-based and policy-driven approach. The architecture of real systems is described, using the basics and principles of the Generic Component Model (GCM). For representing the functional aspects of a system the Business Process Modeling Notation (BPMN) is used. The system architecture obtained is presented using a GCM graphical notation, class diagrams and BPMN diagrams. The architecture-centric approach considers the compositional nature of the real world system and its functionalities, guarantees coherence, and provides right inferences. The level of generality provided in this paper facilitates use case specific adaptations of the system. By that way, intelligent, adaptive and interoperable T2DM care systems can be derived from the presented model as presented in another publication.

  19. Qualitative Knowledge Representations for Intelligent Nuclear Power Plants

    International Nuclear Information System (INIS)

    Cha, Kyoungho; Huh, Young H.

    1993-01-01

    Qualitative Physics(QP) has systematically been approached to qualitative modeling of physical systems for recent two decades. Designing intelligent systems for NPP requires an efficient representation of qualitative knowledge about the behavior and structure of NPP or its components. A novel representation of qualitative knowledge also enables intelligent systems to derive meaningful conclusions from incomplete or uncertain knowledge of a plant behavior. We look mainly into representative QP works on nuclear applications and the representation of qualitative knowledge for the diagnostic model, the qualitative simulation of a mental model of NPP operator, and the qualitative interpretation of the measured raw data from NPP. We present the challenging areas for QP applications in nuclear industry. QP technology will make NPP more intelligent

  20. Adaptive Artificial intelligence based fuzzy logic MPPTcontrol for stande-alone photovoltaic system under different atmospheric conditions

    Directory of Open Access Journals (Sweden)

    Zaghba Layachi

    2015-08-01

    Full Text Available there is an increased need for analysing the effect of atmospheric variables on photovoltaic (PV production and performance. The outputs from the different PV cells in different atmospheric conditions, such as irradiation and temperature , differ from each other evidencing knowledge deficiency in PV systems [14]. Maximum power point tracking (MPPT methods are used to maximize the PV array output power by tracking continuously the maximum power point (MPP. Among all MPPT methods existing in the literature, perturb and observe (P&O is the most commonly used for its simplicity and ease of implementation; however, it presents drawbacks such as slow response speed, oscillation around the MPP in steady state, and even tracking in wrong way under rapidly changing atmospheric conditions. In order to allow a functioning around the optimal point Mopt, we have inserted a DC-DC converter (Buck–Boost for a better matching between the PV and the load. This paper, we study the Maximum power point tracking using adaptive Intelligent fuzzy logic and conventional (P&O control for stande-alone photovoltaic Array system .In particular, the performances of the controllers are analyzed under variation weather conditions with are constant temperature and variable irradiation. The proposed system is simulated by using MATLAB-SIMULINK. According to the results, fuzzy logic controller has shown better performance during the optimization.

  1. Adaptive decoupled power control method for inverter connected DG

    DEFF Research Database (Denmark)

    Sun, Xiaofeng; Tian, Yanjun; Chen, Zhe

    2014-01-01

    an adaptive droop control method based on online evaluation of power decouple matrix for inverter connected distributed generations in distribution system. Traditional decoupled power control is simply based on line impedance parameter, but the load characteristics also cause the power coupling, and alter...

  2. Systems with artificial intelligence in nuclear power plant operation

    International Nuclear Information System (INIS)

    Bastl, W.; Felkel, L.

    1989-01-01

    The authors first summarize some developments made by GRS teams which can be regarded as the precursors of systems with artificial intelligence, and explain the basic characteristics of artificial intelligence, referring in particular to possible applications in nuclear engineering. The systems described are arranged in four groups according to applicability as follows: plant diagnosis and failure analysis, information systems and operating systems, control systems, assessment and decision aids. The working principle of the systems is explained by some examples giving details of the database and the interference processes. (orig./DG) [de

  3. Intelligent speed adaptation as an assistive device for drivers with acquired brain injury

    DEFF Research Database (Denmark)

    Klarborg, Brith; Lahrmann, Harry Spaabæk; Agerholm, Niels

    2012-01-01

    Intelligent speed adaptation (ISA) was tested as an assistive device for drivers with an acquired brain injury (ABI). The study was part of the “Pay as You Speed” project (PAYS) and used the same equipment and technology as the main study (Lahrmann et al., in press-a, in press-b). Two drivers......, and in general they described driving with ISA as relaxed. ISA reduced the percentage of the total distance that was driven with a speed above the speed limit (PDA), but the subjects relapsed to their previous PDA level in Baseline 2. This suggests that ISA is more suited as a permanent assistive device (i...

  4. Can enriching emotional intelligence improve medical students’ proactivity and adaptability during OB/GYN clerkships?

    Science.gov (United States)

    Guseh, Stephanie H.; Chen, Xiaodong P.

    2015-01-01

    Objectives The purpose of this pilot study was to examine our hypothesis that enriching workplace emotional intelligence through resident coaches could improve third-year medical students’ adaptability and proactivity on the Obstetrics and Gynecology clerkship. Methods An observational pilot study was conducted in a teaching hospital. Fourteen 3rd year medical students from two cohorts of clerkships were randomly divided into two groups, and equally assigned to trained resident coaches and untrained resident coaches. Data was collected through onsite naturalistic observation of students’ adaptability and proactivity in clinical settings using a checklist with a 4-point Likert scale (1=poor to 4=excellent). Wilcoxon rank-sum test was used to compare the differences between these two groups. Results A total of 280 data points were collected through onsite observations conducted by investigators. All (n=14) students’ adaptability and proactivity performance significantly improved from an average of 3.04 to 3.45 (p=0.014) over 6-week clerkship. Overall, students with trained resident coaches adapted significantly faster and were more proactive in the obstetrics and gynecology clinical setting than the students with untrained coaches (3.31 vs. 3.24, p=0.019). Conclusions Findings from our pilot study supported our hypothesis that enriching workplace emotional intelligence knowledge through resident coaches was able to help medical students adapt into obstetrics and gynecology clinical settings faster and become more proactive in learning. Clerkship programs can incorporate the concept of a resident coach in their curriculum to help bridge medical students into clinical settings and to help them engage in self-directed learning throughout the rotation. PMID:26708233

  5. Can enriching emotional intelligence improve medical students' proactivity and adaptability during OB/GYN clerkships?

    Science.gov (United States)

    Guseh, Stephanie H; Chen, Xiaodong P; Johnson, Natasha R

    2015-12-26

    The purpose of this pilot study was to examine our hypothesis that enriching workplace emotional intelligence through resident coaches could improve third-year medical students' adaptability and proactivity on the Obstetrics and Gynecology clerkship. An observational pilot study was conducted in a teaching hospital. Fourteen 3rd year medical students from two cohorts of clerkships were randomly divided into two groups, and equally assigned to trained resident coaches and untrained resident coaches. Data was collected through onsite naturalistic observation of students' adaptability and proactivity in clinical settings using a checklist with a 4-point Likert scale (1=poor to 4=excellent). Wilcoxon rank-sum test was used to compare the differences between these two groups. A total of 280 data points were collected through onsite observations conducted by investigators. All (n=14) students' adaptability and proactivity performance significantly improved from an average of 3.04 to 3.45 (p=0.014) over 6-week clerkship. Overall, students with trained resident coaches adapted significantly faster and were more proactive in the obstetrics and gynecology clinical setting than the students with untrained coaches (3.31 vs. 3.24, p=0.019). Findings from our pilot study supported our hypothesis that enriching workplace emotional intelligence knowledge through resident coaches was able to help medical students adapt into obstetrics and gynecology clinical settings faster and become more proactive in learning. Clerkship programs can incorporate the concept of a resident coach in their curriculum to help bridge medical students into clinical settings and to help them engage in self-directed learning throughout the rotation.

  6. Method and apparatus for optimizing operation of a power generating plant using artificial intelligence techniques

    Science.gov (United States)

    Wroblewski, David [Mentor, OH; Katrompas, Alexander M [Concord, OH; Parikh, Neel J [Richmond Heights, OH

    2009-09-01

    A method and apparatus for optimizing the operation of a power generating plant using artificial intelligence techniques. One or more decisions D are determined for at least one consecutive time increment, where at least one of the decisions D is associated with a discrete variable for the operation of a power plant device in the power generating plant. In an illustrated embodiment, the power plant device is a soot cleaning device associated with a boiler.

  7. Intelligent Anti Misoperation System for Power Grid Dispatching of Regions and Counties

    Science.gov (United States)

    Ji, Yuan; Zhang, Yunju; Zhou, Siming; Wang, Xiangdong; Ma, Jianwei

    2018-01-01

    With the power system of large capacity, large units, high voltage development trend, dispatching operations becoming more frequent, complex, and probability of mistakes are increasing. For the existing grid dispatching integrated system loss of anti-error function, single dispatching function, low efficiency, according to the existing conditions of Anshun Power Supply Bureau, the Intelligent anti misoperation system for power grid dispatching of regions and counties is designed, introduced the technologies such as the intelligent anti misoperation analysis, automatic process control, and interactive constraint, the system has the advantages of scientific, reasonable and efficient, and providing the technical support for anti misoperation of regions and counties.

  8. Decentralized Adaptive Overcurrent Protection for Medium Voltage Maritime Power Systems

    DEFF Research Database (Denmark)

    Ciontea, Catalin-Iosif; Bak, Claus Leth; Blaabjerg, Frede

    2016-01-01

    the entire electrical network and changes the relay settings accordingly, but this approach is not adequate for the maritime power systems. This paper propose a decentralized adaptive protection method, where each protection relay is able to identify by itself the network status without the need of a central...... control unit. The new adaptive protection method is based on communication between the overcurrent relays and the equipment that could affect the protection system, such as circuit breakers and generators. Using PSCAD, the proposed method is implemented in a test medium voltage maritime power system......More and more maritime applications as marine vessels and offshore platforms need an adaptive protection power system. However, the adaptive protection is yet to be implemented in the maritime sector. Usually, the adaptive protection implies the existence of a central control unit that monitors...

  9. Delivering organisational adaptation through legislative mechanisms: Evidence from the Adaptation Reporting Power (Climate Change Act 2008).

    Science.gov (United States)

    Jude, S R; Drew, G H; Pollard, S J T; Rocks, S A; Jenkinson, K; Lamb, R

    2017-01-01

    There is increasing recognition that organisations, particularly in key infrastructure sectors, are potentially vulnerable to climate change and extreme weather events, and require organisational responses to ensure they are resilient and adaptive. However, detailed evidence of how adaptation is facilitated, implemented and reported, particularly through legislative mechanisms is lacking. The United Kingdom Climate Change Act (2008), introduced the Adaptation Reporting Power, enabling the Government to direct so-called reporting authorities to report their climate change risks and adaptation plans. We describe the authors' unique role and experience supporting the Department for Environment, Food and Rural Affairs (Defra) during the Adaptation Reporting Power's first round. An evaluation framework, used to review the adaptation reports, is presented alongside evidence on how the process provides new insights into adaptation activities and triggered organisational change in 78% of reporting authorities, including the embedding of climate risk and adaptation issues. The role of legislative mechanisms and risk-based approaches in driving and delivering adaptation is discussed alongside future research needs, including the development of organisational maturity models to determine resilient and well adapting organisations. The Adaptation Reporting Power process provides a basis for similar initiatives in other countries, although a clear engagement strategy to ensure buy-in to the process and research on its long-term legacy, including the potential merits of voluntary approaches, is required. Copyright © 2016 The Authors. Published by Elsevier B.V. All rights reserved.

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

    DEFF Research Database (Denmark)

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

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

  11. An Intelligent Sensor for the Ultra-High-Frequency Partial Discharge Online Monitoring of Power Transformers

    Directory of Open Access Journals (Sweden)

    Jian Li

    2016-05-01

    Full Text Available Ultra-high-frequency (UHF partial discharge (PD online monitoring is an effective way to inspect potential faults and insulation defects in power transformers. The construction of UHF PD online monitoring system is a challenge because of the high-frequency and wide-frequency band of the UHF PD signal. This paper presents a novel, intelligent sensor for UHF PD online monitoring based on a new method, namely a level scanning method. The intelligent sensor can directly acquire the statistical characteristic quantities and is characterized by low cost, few data to output and transmit, Ethernet functionality, and small size for easy installation. The prototype of an intelligent sensor was made. Actual UHF PD experiments with three typical artificial defect models of power transformers were carried out in a laboratory, and the waveform recording method and intelligent sensor proposed were simultaneously used for UHF PD measurement for comparison. The results show that the proposed intelligent sensor is qualified for the UHF PD online monitoring of power transformers. Additionally, three methods to improve the performance of intelligent sensors were proposed according to the principle of the level scanning method.

  12. Lifetime Maximizing Adaptive Power Control in Wireless Sensor Networks

    National Research Council Canada - National Science Library

    Sun, Fangting; Shayman, Mark

    2006-01-01

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

  13. Forecasting the natural gas demand in China using a self-adapting intelligent grey model

    International Nuclear Information System (INIS)

    Zeng, Bo; Li, Chuan

    2016-01-01

    Reasonably forecasting demands of natural gas in China is of significance as it could aid Chinese government in formulating energy policies and adjusting industrial structures. To this end, a self-adapting intelligent grey prediction model is proposed in this paper. Compared with conventional grey models which have the inherent drawbacks of fixed structure and poor adaptability, the proposed new model can automatically optimize model parameters according to the real data characteristics of modeling sequence. In this study, the proposed new model, discrete grey model, even difference grey model and classical grey model were employed, respectively, to simulate China's natural gas demands during 2002–2010 and forecast demands during 2011–2014. The results show the new model has the best simulative and predictive precision. Finally, the new model is used to forecast China's natural gas demand during 2015–2020. The forecast shows the demand will grow rapidly over the next six years. Therefore, in order to maintain the balance between the supplies and the demands for the natural gas in the future, Chinese government needs to take some measures, such as importing huge amounts of natural gas from abroad, increasing the domestic yield, using more alternative energy, and reducing the industrial reliance on natural gas. - Highlights: • A self-adapting intelligent grey prediction model (SIGM) is proposed in this paper. • The SIGM has the advantage of working with exponential functions and linear functions. • The SIGM solves the drawbacks of fixed structure and poor adaptability of grey models. • The demand of natural gas in China is successfully forecasted using the SIGM model. • The study findings can help Chinese government reasonably formulate energy policies.

  14. A new hybrid optimization method inspired from swarm intelligence: Fuzzy adaptive swallow swarm optimization algorithm (FASSO

    Directory of Open Access Journals (Sweden)

    Mehdi Neshat

    2015-11-01

    Full Text Available In this article, the objective was to present effective and optimal strategies aimed at improving the Swallow Swarm Optimization (SSO method. The SSO is one of the best optimization methods based on swarm intelligence which is inspired by the intelligent behaviors of swallows. It has been able to offer a relatively strong method for solving optimization problems. However, despite its many advantages, the SSO suffers from two shortcomings. Firstly, particles movement speed is not controlled satisfactorily during the search due to the lack of an inertia weight. Secondly, the variables of the acceleration coefficient are not able to strike a balance between the local and the global searches because they are not sufficiently flexible in complex environments. Therefore, the SSO algorithm does not provide adequate results when it searches in functions such as the Step or Quadric function. Hence, the fuzzy adaptive Swallow Swarm Optimization (FASSO method was introduced to deal with these problems. Meanwhile, results enjoy high accuracy which are obtained by using an adaptive inertia weight and through combining two fuzzy logic systems to accurately calculate the acceleration coefficients. High speed of convergence, avoidance from falling into local extremum, and high level of error tolerance are the advantages of proposed method. The FASSO was compared with eleven of the best PSO methods and SSO in 18 benchmark functions. Finally, significant results were obtained.

  15. Transmission Line Adapted Analytical Power Charts Solution

    Science.gov (United States)

    Sakala, Japhet D.; Daka, James S. J.; Setlhaolo, Ditiro; Malichi, Alec Pulu

    2017-08-01

    The performance of a transmission line has been assessed over the years using power charts. These are graphical representations, drawn to scale, of the equations that describe the performance of transmission lines. Various quantities that describe the performance, such as sending end voltage, sending end power and compensation to give zero voltage regulation, may be deduced from the power charts. Usually required values are read off and then converted using the appropriate scales and known relationships. In this paper, the authors revisit this area of circle diagrams for transmission line performance. The work presented here formulates the mathematical model that analyses the transmission line performance from the power charts relationships and then uses them to calculate the transmission line performance. In this proposed approach, it is not necessary to draw the power charts for the solution. However the power charts may be drawn for the visual presentation. The method is based on applying derived equations and is simple to use since it does not require rigorous derivations.

  16. Intelligent Vehicle Power Management Using Machine Learning and Fuzzy Logic

    National Research Council Canada - National Science Library

    Chen, ZhiHang; Masrur, M. A; Murphey, Yi L

    2008-01-01

    .... A machine learning algorithm, LOPPS, has been developed to learn about optimal power source combinations with respect to minimum power loss for all possible load requests and various system power states...

  17. Investigations on Incipient Fault Diagnosis of Power Transformer Using Neural Networks and Adaptive Neurofuzzy Inference System

    Directory of Open Access Journals (Sweden)

    Nandkumar Wagh

    2014-01-01

    Full Text Available Continuity of power supply is of utmost importance to the consumers and is only possible by coordination and reliable operation of power system components. Power transformer is such a prime equipment of the transmission and distribution system and needs to be continuously monitored for its well-being. Since ratio methods cannot provide correct diagnosis due to the borderline problems and the probability of existence of multiple faults, artificial intelligence could be the best approach. Dissolved gas analysis (DGA interpretation may provide an insight into the developing incipient faults and is adopted as the preliminary diagnosis tool. In the proposed work, a comparison of the diagnosis ability of backpropagation (BP, radial basis function (RBF neural network, and adaptive neurofuzzy inference system (ANFIS has been investigated and the diagnosis results in terms of error measure, accuracy, network training time, and number of iterations are presented.

  18. On introduction of artificial intelligence elements to heat power engineering

    Science.gov (United States)

    Dregalin, A. F.; Nazyrova, R. R.

    1993-10-01

    The basic problems of 'the thermodynamic intelligence' of personal computers have been outlined. The thermodynamic intellect of personal computers as a concept has been introduced to heat processes occurring in engines of flying vehicles. In particular, the thermodynamic intellect of computers is determined by the possibility of deriving formal relationships between thermodynamic functions. In chemical thermodynamics, a concept of a characteristic function has been introduced.

  19. A novel approach to painting powered by Ambient Intelligence

    Directory of Open Access Journals (Sweden)

    N. Partarakis

    2016-04-01

    Full Text Available Today, many forms of art are influenced by the emergence of interactive technologies, including the mixing of physical media with digital technology for forming new hybrid works of art and the usage of mobile phones to create art projected on public spaces. Many artists and painters use digital technology to augment their work creatively and technically. Many believe that the time of transition from traditional analogue art to postmodern digital art that is, to an art grounded in codes rather than images has arrived*. The research work described in this paper contributes towards supporting, through the use of Ambient Intelligence technologies, traditional painters’ creativity, as well as methods and techniques of art masters. The paper presents the design, implementation and evaluation of an intelligent environment and its software infrastructure, to form a digitally augmented Art Workshop. Its practical deployment was conducted in an Ambient Intelligence (AmI simulation space and four feasibility studies were conducted. In each of these studies an oil painting was created following an alternative, yet accredited by artists, approach. The workshop was also evaluated with the involvement of real users and artists in the context of a user based usability study.

  20. Classification of intelligence quotient via brainwave sub-band power ratio features and artificial neural network.

    Science.gov (United States)

    Jahidin, A H; Megat Ali, M S A; Taib, M N; Tahir, N Md; Yassin, I M; Lias, S

    2014-04-01

    This paper elaborates on the novel intelligence assessment method using the brainwave sub-band power ratio features. The study focuses only on the left hemisphere brainwave in its relaxed state. Distinct intelligence quotient groups have been established earlier from the score of the Raven Progressive Matrices. Sub-band power ratios are calculated from energy spectral density of theta, alpha and beta frequency bands. Synthetic data have been generated to increase dataset from 50 to 120. The features are used as input to the artificial neural network. Subsequently, the brain behaviour model has been developed using an artificial neural network that is trained with optimized learning rate, momentum constant and hidden nodes. Findings indicate that the distinct intelligence quotient groups can be classified from the brainwave sub-band power ratios with 100% training and 88.89% testing accuracies. Copyright © 2014 Elsevier Ireland Ltd. All rights reserved.

  1. Applications of Fuzzy adaptive PID control in the thermal power plant denitration liquid ammonia evaporation

    Directory of Open Access Journals (Sweden)

    Li Jing

    2016-01-01

    Full Text Available For the control of the liquid level of liquid ammonia in thermal power plant’s ammonia vaporization room, traditional PID controller parameter tuning is difficult to adapt to complex control systems, the setting of the traditional PID controller parameters is difficult to adapt to the complex control system. For the disadvantage of bad parameter setting, poor performance and so on the fuzzy adaptive PID control is proposed. Fuzzy adaptive PID control combines the advantages of traditional PID technology and fuzzy control. By using the fuzzy controller to intelligent control the object, the performance of the PID controller is further improved, and the control precision of the system is improved[1]. The simulation results show that the fuzzy adaptive PID controller not only has the advantages of high accuracy of PID controller, but also has the characteristics of fast and strong adaptability of fuzzy controller. It realizes the optimization of PID parameters which are in the optimal state, and the maximum increase production efficiency, so that are more suitable for nonlinear dynamic system.

  2. Interference mitigation through adaptive power control in wireless sensor networks

    NARCIS (Netherlands)

    Chincoli, M.; Bacchiani, C.; Syed, Aly; Exarchakos, G.; Liotta, A.

    2016-01-01

    Adaptive transmission power control schemes have been introduced in wireless sensor networks to adjust energy consumption under different network conditions. This is a crucial goal, given the constraints under which sensor communications operate. Power reduction may however have counter-productive

  3. Possible stimuli for strength and power adaptation : acute metabolic responses.

    Science.gov (United States)

    Crewther, Blair; Cronin, John; Keogh, Justin

    2006-01-01

    The metabolic response to resistance exercise, in particular lactic acid or lactate, has a marked influence upon the muscular environment, which may enhance the training stimulus (e.g. motor unit activation, hormones or muscle damage) and thereby contribute to strength and power adaptation. Hypertrophy schemes have resulted in greater lactate responses (%) than neuronal and dynamic power schemes, suggesting possible metabolic-mediated changes in muscle growth. Factors such as age, sex, training experience and nutrition may also influence the lactate responses to resistance exercise and thereafter, muscular adaptation. Although the importance of the mechanical and hormonal stimulus to strength and power adaptation is well recognised, the contribution of the metabolic stimulus is largely unknown. Relatively few studies for example, have examined metabolic change across neuronal and dynamic power schemes, and not withstanding the fact that those mechanisms underpinning muscular adaptation, in relation to the metabolic stimulus, remain highly speculative. Inconsistent findings and methodological limitations within research (e.g. programme design, sampling period, number of samples) make interpretation further difficult. We contend that strength and power research needs to investigate those metabolic mechanisms likely to contribute to weight-training adaptation. Further research is also needed to examine the metabolic responses to different loading schemes, as well as interactions across age, sex and training status, so our understanding of how to optimise strength and power development is improved.

  4. Adaptative Techniques to Reduce Power in Digital Circuits

    Directory of Open Access Journals (Sweden)

    Bharadwaj Amrutur

    2011-07-01

    Full Text Available CMOS chips are engineered with sufficient performance margins to ensure that they meet the target performance under worst case operating conditions. Consequently, excess power is consumed for most cases when the operating conditions are more benign. This article will review a suite of dynamic power minimization techniques, which have been recently developed to reduce power consumption based on actual operating conditions. We will discuss commonly used techniques like Dynamic Power Switching (DPS, Dynamic Voltage and Frequency Scaling (DVS and DVFS and Adaptive Voltage Scaling (AVS. Recent efforts to extend these to cover threshold voltage adaptation via Dynamic Voltage and Threshold Scaling (DVTS will also be presented. Computation rate is also adapted to actual work load requirements via dynamically changing the hardware parallelism or by controlling the number of operations performed. These will be explained with some examples from the application domains of media and wireless signal processing.

  5. Artificial intelligence and nuclear power. Report by the Technology Transfer Artificial Intelligence Task Team

    International Nuclear Information System (INIS)

    1985-06-01

    The Artificial Intelligence Task Team was organized to review the status of Artificial Intelligence (AI) technology, identify guidelines for AI work, and to identify work required to allow the nuclear industry to realize maximum benefit from this technology. The state of the nuclear industry was analyzed to determine where the application of AI technology could be of greatest benefit. Guidelines and criteria were established to focus on those particular problem areas where AI could provide the highest possible payoff to the industry. Information was collected from government, academic, and private organizations. Very little AI work is now being done to specifically support the nuclear industry. The AI Task Team determined that the establishment of a Strategic Automation Initiative (SAI) and the expansion of the DOE Technology Transfer program would ensure that AI technology could be used to develop software for the nuclear industry that would have substantial financial payoff to the industry. The SAI includes both long and short term phases. The short-term phase includes projects which would demonstrate that AI can be applied to the nuclear industry safely, and with substantial financial benefit. The long term phase includes projects which would develop AI technologies with specific applicability to the nuclear industry that would not be developed by people working in any other industry

  6. 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.

  7. A Model of Intelligent Fault Diagnosis of Power Equipment Based on CBR

    Directory of Open Access Journals (Sweden)

    Gang Ma

    2015-01-01

    Full Text Available Nowadays the demand of power supply reliability has been strongly increased as the development within power industry grows rapidly. Nevertheless such large demand requires substantial power grid to sustain. Therefore power equipment’s running and testing data which contains vast information underpins online monitoring and fault diagnosis to finally achieve state maintenance. In this paper, an intelligent fault diagnosis model for power equipment based on case-based reasoning (IFDCBR will be proposed. The model intends to discover the potential rules of equipment fault by data mining. The intelligent model constructs a condition case base of equipment by analyzing the following four categories of data: online recording data, history data, basic test data, and environmental data. SVM regression analysis was also applied in mining the case base so as to further establish the equipment condition fingerprint. The running data of equipment can be diagnosed by such condition fingerprint to detect whether there is a fault or not. Finally, this paper verifies the intelligent model and three-ratio method based on a set of practical data. The resulting research demonstrates that this intelligent model is more effective and accurate in fault diagnosis.

  8. Challenges in introduction of artificial intelligence in medical practice – a review of clinical trials concerning adaptation of artificial intelligence in medicine

    OpenAIRE

    Mielnik, Pawel Franciszek; Fojcik, Marcin; Kulbacki, Marek; Segen, Jakub

    2016-01-01

    An interest in Artificial Intelligence [AI] as science is growing in the last years. It has become gradually more used in the medicine. Methodology of development and testing of AI algorithms is generally well established. Use of AI in medicine requires elaboration of standards of its validation in clinical settings. This paper is a review of literature concerning clinical trials on AI adaptation in medicine

  9. The predictive power of zero intelligence in financial markets.

    Science.gov (United States)

    Farmer, J Doyne; Patelli, Paolo; Zovko, Ilija I

    2005-02-08

    Standard models in economics stress the role of intelligent agents who maximize utility. However, there may be situations where constraints imposed by market institutions dominate strategic agent behavior. We use data from the London Stock Exchange to test a simple model in which minimally intelligent agents place orders to trade at random. The model treats the statistical mechanics of order placement, price formation, and the accumulation of revealed supply and demand within the context of the continuous double auction and yields simple laws relating order-arrival rates to statistical properties of the market. We test the validity of these laws in explaining cross-sectional variation for 11 stocks. The model explains 96% of the variance of the gap between the best buying and selling prices (the spread) and 76% of the variance of the price diffusion rate, with only one free parameter. We also study the market impact function, describing the response of quoted prices to the arrival of new orders. The nondimensional coordinates dictated by the model approximately collapse data from different stocks onto a single curve. This work is important from a practical point of view, because it demonstrates the existence of simple laws relating prices to order flows and, in a broader context, suggests there are circumstances where the strategic behavior of agents may be dominated by other considerations.

  10. The predictive power of zero intelligence in financial markets

    Science.gov (United States)

    Farmer, J. Doyne; Patelli, Paolo; Zovko, Ilija I.

    2005-02-01

    Standard models in economics stress the role of intelligent agents who maximize utility. However, there may be situations where constraints imposed by market institutions dominate strategic agent behavior. We use data from the London Stock Exchange to test a simple model in which minimally intelligent agents place orders to trade at random. The model treats the statistical mechanics of order placement, price formation, and the accumulation of revealed supply and demand within the context of the continuous double auction and yields simple laws relating order-arrival rates to statistical properties of the market. We test the validity of these laws in explaining cross-sectional variation for 11 stocks. The model explains 96% of the variance of the gap between the best buying and selling prices (the spread) and 76% of the variance of the price diffusion rate, with only one free parameter. We also study the market impact function, describing the response of quoted prices to the arrival of new orders. The nondimensional coordinates dictated by the model approximately collapse data from different stocks onto a single curve. This work is important from a practical point of view, because it demonstrates the existence of simple laws relating prices to order flows and, in a broader context, suggests there are circumstances where the strategic behavior of agents may be dominated by other considerations. double auction market | market microstructure | agent-based models

  11. An intelligent man-machine system for future nuclear power plants

    International Nuclear Information System (INIS)

    Takizawa, Yoji; Hattori, Yoshiaki; Itoh, Juichiro; Fukumoto, Akira

    1994-01-01

    The objective of the development of an intelligent man-machine system for future nuclear power plants is enhancement of operational reliability by applying recent advances in cognitive science, artificial intelligence, and computer technologies. To realize this objective, the intelligent man-machine system, aiming to support a knowledge-based decision making process in an operator's supervisory plant control tasks, consists of three main functions, i.e., a cognitive model-based advisor, a robust automatic sequence controller, and an ecological interface. These three functions have been integrated into a console-type nuclear power plant monitoring and control system as a validation test bed. The validation tests in which experienced operator crews participated were carried out in 1991 and 1992. The test results show the usefulness of the support functions and the validity of the system design approach

  12. Risk and Disaster Management: From Planning and Expertise to Smart, Intelligent, and Adaptive Systems.

    Science.gov (United States)

    Benis, Arriel; Notea, Amos; Barkan, Refael

    2018-01-01

    "Disaster" means some surprising and misfortunate event. Its definition is broad and relates to complex environments. Medical Informatics approaches, methodologies and systems are used as a part of Disaster and Emergency Management systems. At the Holon Institute of Technology - HIT, Israel, in 2016 a National R&D Center: AFRAN was established to study the disaster's reduction aspects. The Center's designation is to investigate and produce new approaches, methodologies and to offer recommendations in the fields of disaster mitigation, preparedness, response and recovery and to disseminate disaster's knowledge. Adjoint to the Center a "Smart, Intelligent, and Adaptive Systems" laboratory (SIAS) was established with the goal to study the applications of Information and Communication Technologies (ICT) and Artificial Intelligence (AI) to Risk and Disaster Management (RDM). In this paper, we are redefining the concept of Disaster, pointing-out how ICT, AI, in the Big Data era, are central players in the RDM game. In addition we show the merit of the Center and lab combination to the benefit of the performed research projects.

  13. Intelligent control and adaptive systems; Proceedings of the Meeting, Philadelphia, PA, Nov. 7, 8, 1989

    Science.gov (United States)

    Rodriguez, Guillermo (Editor)

    1990-01-01

    Various papers on intelligent control and adaptive systems are presented. Individual topics addressed include: control architecture for a Mars walking vehicle, representation for error detection and recovery in robot task plans, real-time operating system for robots, execution monitoring of a mobile robot system, statistical mechanics models for motion and force planning, global kinematics for manipulator planning and control, exploration of unknown mechanical assemblies through manipulation, low-level representations for robot vision, harmonic functions for robot path construction, simulation of dual behavior of an autonomous system. Also discussed are: control framework for hand-arm coordination, neural network approach to multivehicle navigation, electronic neural networks for global optimization, neural network for L1 norm linear regression, planning for assembly with robot hands, neural networks in dynamical systems, control design with iterative learning, improved fuzzy process control of spacecraft autonomous rendezvous using a genetic algorithm.

  14. ISHM-oriented adaptive fault diagnostics for avionics based on a distributed intelligent agent system

    Science.gov (United States)

    Xu, Jiuping; Zhong, Zhengqiang; Xu, Lei

    2015-10-01

    In this paper, an integrated system health management-oriented adaptive fault diagnostics and model for avionics is proposed. With avionics becoming increasingly complicated, precise and comprehensive avionics fault diagnostics has become an extremely complicated task. For the proposed fault diagnostic system, specific approaches, such as the artificial immune system, the intelligent agents system and the Dempster-Shafer evidence theory, are used to conduct deep fault avionics diagnostics. Through this proposed fault diagnostic system, efficient and accurate diagnostics can be achieved. A numerical example is conducted to apply the proposed hybrid diagnostics to a set of radar transmitters on an avionics system and to illustrate that the proposed system and model have the ability to achieve efficient and accurate fault diagnostics. By analyzing the diagnostic system's feasibility and pragmatics, the advantages of this system are demonstrated.

  15. The person who eases your mind "Ibasyo" and emotional intelligence in interpersonal adaptation

    Directory of Open Access Journals (Sweden)

    Hiroshi Toyota

    2009-11-01

    Full Text Available The present study was carried out to examine the effect of the "Ibasyo" (the person who eases one's mind and emotional intelligence (EI on self-esteem and loneliness. Five hundred and eight Japanese undergraduates were asked to choose one of the alternatives (e. g., myself, mother, friend to answer the question "Who is the person that eases your mind?" Then, they were asked to rate items from scales corresponding to EI, self-esteem and loneliness. Multiple regression analyses indicated that both Ibasyo and EI explained 25% of loneliness, but only EI explained 25% of self-esteem. The analyses also showed differences of sub-abilities in EI that determined the level of loneliness and self-esteem among Ibasyo groups. These results are interpreted as showing the importance of EI in adaptation.

  16. Speed regulating Effects of Incentive-based Intelligent Speed Adaptation in the short and medium term

    DEFF Research Database (Denmark)

    Agerholm, Niels

    Speed regulating Effects of Incentive-based Intelligent Speed Adaptation in the short and medium term Despite massive improvements in vehicles’ safety equipment, more information and safer road network, inappropriate road safety is still causing that more than 250 people are killed and several...... thousands injured each year in Denmark. Until a few years ago the number of fatalities in most countries had decreased while the amount of traffic increased. However, this trend has been replaced by a more uncertain development towards a constant or even somewhat increasing risk. Inappropriate speeding...... is a central cause for the high number of fatalities on the roads. Despite speed limits, speed limit violating driving behaviour is still widespread in Denmark. Traditional solutions to prevent speed violation have been enforcement, information, and enhanced road design. It seems, however, hard to achieve...

  17. Intelligent PV Power Smoothing Control Using Probabilistic Fuzzy Neural Network with Asymmetric Membership Function

    Directory of Open Access Journals (Sweden)

    Faa-Jeng Lin

    2017-01-01

    Full Text Available An intelligent PV power smoothing control using probabilistic fuzzy neural network with asymmetric membership function (PFNN-AMF is proposed in this study. First, a photovoltaic (PV power plant with a battery energy storage system (BESS is introduced. The BESS consisted of a bidirectional DC/AC 3-phase inverter and LiFePO4 batteries. Then, the difference of the actual PV power and smoothed power is supplied by the BESS. Moreover, the network structure of the PFNN-AMF and its online learning algorithms are described in detail. Furthermore, the three-phase output currents of the PV power plant are converted to the dq-axis current components. The resulted q-axis current is the input of the PFNN-AMF power smoothing control, and the output is a smoothing PV power curve to achieve the effect of PV power smoothing. Comparing to the other smoothing methods, a minimum energy capacity of the BESS with a small fluctuation of the grid power can be achieved by the PV power smoothing control using PFNN-AMF. In addition, a personal computer- (PC- based PV power plant emulator and BESS are built for the experimentation. From the experimental results of various irradiance variation conditions, the effectiveness of the proposed intelligent PV power smoothing control can be verified.

  18. An adaptive predictive controller and its applications in power stations

    Energy Technology Data Exchange (ETDEWEB)

    Yang Zhiyuan; Lu Huiming; Zhang Xinggao [North China Electric Power University, Beijing (China); Song Chunping [Tsinghua University, Beijing (China). Dept. of Thermal Energy Engineering

    1999-07-01

    Based on the objective function in the form of integration of generalized model error, a globally convergent model reference adaptive predictive control algorithm (MRAPC) containing inertia-time compensators is presented in this paper. MRAPC has been successfully applied to control important thermal process of more than 20 units in many Chinese power stations. In this paper three representative examples are described. Continual operation results for years demonstrate that MRAPC is a successful attempt for the practical applications of adaptive control techniques. (author)

  19. Predicting speech intelligibility based on a correlation metric in the envelope power spectrum domain

    DEFF Research Database (Denmark)

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

    2016-01-01

    A speech intelligibility prediction model is proposed that combines the auditory processing front end of the multi-resolution speech-based envelope power spectrum model [mr-sEPSM; Jørgensen, Ewert, and Dau (2013). J. Acoust. Soc. Am. 134(1), 436–446] with a correlation back end inspired by the sh...

  20. Installation and evaluation of a nuclear power plant operator advisor based on artificial intelligence technology

    International Nuclear Information System (INIS)

    Hajek, B.K.; Miller, D.W.

    1989-01-01

    This report discusses the following topics on a Nuclear Power Plant operator advisor based on artificial Intelligence Technology; Workstation conversion; Software Conversion; V ampersand V Program Development Development; Simulator Interface Development; Knowledge Base Expansion; Dynamic Testing; Database Conversion; Installation at the Perry Simulator; Evaluation of Operator Interaction; Design of Man-Machine Interface; and Design of Maintenance Facility

  1. Development of an intelligent annunciation system for nuclear power plants

    International Nuclear Information System (INIS)

    Kim, Chang-Gi; Che, Myoung-Eun

    1997-01-01

    Yonggwang Nuclear Units 1 and 2 have developed an intelligent annunciation system to replace the existing obsolete system and to enhance operator support. The new annunciation system, which is currently operating at both units, uses the distributed control technology to enhance reliability and to provide versatile function to operations and maintenance personnel. The hardware and software configuration is based on redundancy so that a component failure would not initiate system malfunction. The data base of the new system provides, through a touch screen, an automatic alarm response procedure for selected alarms, which increases availability of information for plant operation. Other KEPCO nuclear units and the fossil plants are considering installing the new system. (author). 6 figs, 2 tabs

  2. Development of an intelligent annunciation system for nuclear power plants

    Energy Technology Data Exchange (ETDEWEB)

    Kim, Chang-Gi; Che, Myoung-Eun [Instrumentation and Control, Yonggwang Nuclear Units 1 and 2, Korea Electric Power Corp. (Korea, Republic of)

    1997-09-01

    Yonggwang Nuclear Units 1 and 2 have developed an intelligent annunciation system to replace the existing obsolete system and to enhance operator support. The new annunciation system, which is currently operating at both units, uses the distributed control technology to enhance reliability and to provide versatile function to operations and maintenance personnel. The hardware and software configuration is based on redundancy so that a component failure would not initiate system malfunction. The data base of the new system provides, through a touch screen, an automatic alarm response procedure for selected alarms, which increases availability of information for plant operation. Other KEPCO nuclear units and the fossil plants are considering installing the new system. (author). 6 figs, 2 tabs.

  3. The added value of a gaming context and intelligent adaptation for a mobile application for vocabulary learning

    NARCIS (Netherlands)

    Sandberg, J.; Maris, M.; Hoogendoorn, P.

    2014-01-01

    Two groups participated in a study on the added value of a gaming context and intelligent adaptation for a mobile learning application. The control group worked at home for a fortnight with the original Mobile English Learning application (MEL-original) developed in a previous project. The

  4. Emotional Intelligence and Adaptive Success of Nurses Caring for People with Mental Retardation and Severe Behavior Problems

    Science.gov (United States)

    Gerits, Linda; Derksen, Jan J. L.; Verbruggen, Antoine B.

    2004-01-01

    The emotional intelligence profiles, gender differences, and adaptive success of 380 Dutch nurses caring for people with mental retardation and accompanying severe behavior problems are reported. Data were collected with the Bar-On Emotional Quotient Inventory, Utrecht-Coping List, Utrecht-Burnout Scale, MMPI-2, and GAMA. Absence due to illness…

  5. Adaptive control of energy storage systems for power smoothing applications

    DEFF Research Database (Denmark)

    Meng, Lexuan; Dragicevic, Tomislav; Guerrero, Josep M.

    2017-01-01

    Energy storage systems (ESSs) are desired and widely applied for power smoothing especially in systems with renewable generation and pulsed loads. High-pass-filter (HPF) is commonly applied in those applications in which the HPF extracts the high frequency fluctuating power and uses...... that as the power reference for ESS. The cut-off frequency, as the critical parameter, actually decides the power/energy compensated by ESS. Practically the state-of-charge (SoC) of the ESS has to be limited for safety and life-cycle considerations. In this paper an adaptive cut-off frequency design is proposed...

  6. DOWNHOLE POWER GENERATION AND WIRELESS COMMUNICATIONS FOR INTELLIGENT COMPLETIONS APPLICATIONS

    Energy Technology Data Exchange (ETDEWEB)

    Paul Tubel

    2004-02-01

    The development work during this quarter was focused in the assembly of the downhole power generator hardware and its electronics module. The quarter was also spent in the development of the surface system electronics and software to extract the acoustic data transmitted from downhole to the surface from the noise generated by hydrocarbon flow in wells and to amplify very small acoustic signals to increase the distance between the downhole tool and the surface receiver. The tasks accomplished during this report period were: (1) Assembly of the downhole power generator mandrel for generation of electrical power due to flow in the wellbore. (2) Test the piezoelectric wafers to assure that they are performing properly prior to integrating them to the mechanical power generator mandrel. (3) Coat the power generator wafers to prevent water from shorting the power generator wafers. (4) Test of the power generator using a water tower and an electric pump to create a water flow loop. (5) Test the power harvesting electronics module. (6) Upgrade the signal condition and amplification from downhole into the surface system. (7) Upgrade the surface processing system capability to process data faster. (8) Create a new filtering technique to extract the signal from noise after the data from downhole is received at the surface system.

  7. 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...

  8. Development of an intelligent high-voltage direct-current power supply for nuclear detectors

    International Nuclear Information System (INIS)

    Zhao Xiuliang

    1997-01-01

    The operation and performances of a new type direct-current high-voltage power supply are described. The power supply with intelligent feature is controlled by a single-chip microcomputer (8031), and various kinds of output voltage can be preset. The output-voltage is monitored and regulated by the single-chip microcomputer and displayed by LED. The output voltage is stable when the load current is within the allowable limits

  9. Intelligent (Autonomous) Power Controller Development for Human Deep Space Exploration

    Science.gov (United States)

    Soeder, James; Raitano, Paul; McNelis, Anne

    2016-01-01

    As NASAs Evolvable Mars Campaign and other exploration initiatives continue to mature they have identified the need for more autonomous operations of the power system. For current human space operations such as the International Space Station, the paradigm is to perform the planning, operation and fault diagnosis from the ground. However, the dual problems of communication lag as well as limited communication bandwidth beyond GEO synchronous orbit, underscore the need to change the operation methodology for human operation in deep space. To address this need, for the past several years the Glenn Research Center has had an effort to develop an autonomous power controller for human deep space vehicles. This presentation discusses the present roadmap for deep space exploration along with a description of conceptual power system architecture for exploration modules. It then contrasts the present ground centric control and management architecture with limited autonomy on-board the spacecraft with an advanced autonomous power control system that features ground based monitoring with a spacecraft mission manager with autonomous control of all core systems, including power. It then presents a functional breakdown of the autonomous power control system and examines its operation in both normal and fault modes. Finally, it discusses progress made in the development of a real-time power system model and how it is being used to evaluate the performance of the controller and well as using it for verification of the overall operation.

  10. Advanced power cycler with intelligent monitoring strategy of IGBT module under test

    DEFF Research Database (Denmark)

    Choi, U. M.; Blaabjerg, F.; Iannuzzo, F.

    2017-01-01

    and diode, which for the wear-out condition monitoring are presented. This advanced power cycler allows to perform power cycling test cost-effectively under conditions close to real power converter applications. In addition, an intelligent monitoring strategy for the separation of package-related wear......-out failure mechanisms has been proposed. By means of the proposed method, the wear-out failure mechanisms of an IGBT module can be separated without any additional efforts during the power cycling tests. The validity and effectiveness of the proposed monitoring strategy are also verified by experiments....

  11. Survey of artificial intelligence methods for detection and identification of component faults in nuclear power plants

    International Nuclear Information System (INIS)

    Reifman, J.

    1997-01-01

    A comprehensive survey of computer-based systems that apply artificial intelligence methods to detect and identify component faults in nuclear power plants is presented. Classification criteria are established that categorize artificial intelligence diagnostic systems according to the types of computing approaches used (e.g., computing tools, computer languages, and shell and simulation programs), the types of methodologies employed (e.g., types of knowledge, reasoning and inference mechanisms, and diagnostic approach), and the scope of the system. The major issues of process diagnostics and computer-based diagnostic systems are identified and cross-correlated with the various categories used for classification. Ninety-five publications are reviewed

  12. Design of Intelligent Power Supply System for Expressway Tunnel

    Science.gov (United States)

    Wang, Li; Li, Yutong; Lin, Zimian

    2018-01-01

    Tunnel lighting program is one of the key points of tunnel infrastructure construction. As tunnels tend to handle remote locations, power supply line construction generally has been having the distance, investment, high cost characteristics. To solve this problem, we propose a green, environmentally friendly, energy-efficient lighting system. This program uses the piston-wind which cars within tunnel produce as the power and combines with solar energy, physical lighting to achieve it, which solves the problem of difficult and high cost of highway tunnel section, and provides new ideas for the future construction of tunnel power supply.

  13. Adaptive robust polynomial regression for power curve modeling with application to wind power forecasting

    DEFF Research Database (Denmark)

    Xu, Man; Pinson, Pierre; Lu, Zongxiang

    2016-01-01

    of the lack of time adaptivity. In this paper, a refined local polynomial regression algorithm is proposed to yield an adaptive robust model of the time-varying scattered power curve for forecasting applications. The time adaptivity of the algorithm is considered with a new data-driven bandwidth selection......Wind farm power curve modeling, which characterizes the relationship between meteorological variables and power production, is a crucial procedure for wind power forecasting. In many cases, power curve modeling is more impacted by the limited quality of input data rather than the stochastic nature...... of the energy conversion process. Such nature may be due the varying wind conditions, aging and state of the turbines, etc. And, an equivalent steady-state power curve, estimated under normal operating conditions with the intention to filter abnormal data, is not sufficient to solve the problem because...

  14. Adaptive control of a PWR core power using neural networks

    International Nuclear Information System (INIS)

    Arab-Alibeik, H.; Setayeshi, S.

    2005-01-01

    Reactor power control is important because of safety concerns and the call for regular and appropriate operation of nuclear power plants. It seems that the load-follow operation of these plants will be unavoidable in the future. Discrepancies between the real plant and the model used in controller design for load-follow operation encourage one to use auto-tuning and (or) adaptive techniques. Neural network technology shows great promise for addressing many problems in non-model-based adaptive control methods. Also, there has been a great attention to inverse control especially in the neural and fuzzy control context. Fortunately, online adaptation eliminates some limitations of inverse control and its shortcomings for real world applications. We use a neural adaptive inverse controller to control the power of a PWR reactor. The stability of the system and convergence of the controller parameters are guaranteed during online adaptation phase provided the controller is near the plant's real inverse after offline training period. The performance of the controller is verified using nonlinear simulations in diverse operating conditions

  15. A multi-resolution envelope-power based model for speech intelligibility

    DEFF Research Database (Denmark)

    Jørgensen, Søren; Ewert, Stephan D.; Dau, Torsten

    2013-01-01

    The speech-based envelope power spectrum model (sEPSM) presented by Jørgensen and Dau [(2011). J. Acoust. Soc. Am. 130, 1475-1487] estimates the envelope power signal-to-noise ratio (SNRenv) after modulation-frequency selective processing. Changes in this metric were shown to account well...... to conditions with stationary interferers, due to the long-term integration of the envelope power, and cannot account for increased intelligibility typically obtained with fluctuating maskers. Here, a multi-resolution version of the sEPSM is presented where the SNRenv is estimated in temporal segments...... with a modulation-filter dependent duration. The multi-resolution sEPSM is demonstrated to account for intelligibility obtained in conditions with stationary and fluctuating interferers, and noisy speech distorted by reverberation or spectral subtraction. The results support the hypothesis that the SNRenv...

  16. Utilization of artificial intelligence techniques for the Space Station power system

    Science.gov (United States)

    Evatt, Thomas C.; Gholdston, Edward W.

    1988-01-01

    Due to the complexity of the Space Station Electrical Power System (EPS) as currently envisioned, artificial intelligence/expert system techniques are being investigated to automate operations, maintenance, and diagnostic functions. A study was conducted to investigate this technology as it applies to failure detection, isolation, and reconfiguration (FDIR) and health monitoring of power system components and of the total system. Control system utilization of expert systems for load scheduling and shedding operations was also researched. A discussion of the utilization of artificial intelligence/expert systems for Initial Operating Capability (IOC) for the Space Station effort is presented along with future plans at Rocketdyne for the utilization of this technology for enhanced Space Station power capability.

  17. Enhancing nuclear power plant performance through the use of artificial intelligence

    International Nuclear Information System (INIS)

    Maren, A.J.; Miller, L.F.; Tsoukalas, L.H.; Uhrig, R.E.; Upadhyaya, B.R.

    1990-01-01

    The objective of this research is to advance the state-of-the-art of applying artificial intelligence technology (both expert systems and neural networks) to enhancing the performance (safety, efficiency, control and management) of nuclear power plants. A second, but equally important, objective is to build a broadly based critical mass of expertise in the artificial intelligence field that can be brought to bear on the technology of nuclear power plants. This means the production of graduates at the B.S., M.S., and Ph.D. levels in Nuclear Engineering and related fields. The research undertaken for this program is particularly appropriate for the M.S. theses and Ph.D. dissertations. A third objective is to transfer the technology developed to the ''nuclear power community,'' as well as the ''scientific and technological community,'' through publications in appropriate journals and proceedings and through presentations at national and international meetings

  18. Generative Adversarial Networks Based Heterogeneous Data Integration and Its Application for Intelligent Power Distribution and Utilization

    Directory of Open Access Journals (Sweden)

    Yuanpeng Tan

    2018-01-01

    Full Text Available Heterogeneous characteristics of a big data system for intelligent power distribution and utilization have already become more and more prominent, which brings new challenges for the traditional data analysis technologies and restricts the comprehensive management of distribution network assets. In order to solve the problem that heterogeneous data resources of power distribution systems are difficult to be effectively utilized, a novel generative adversarial networks (GANs based heterogeneous data integration method for intelligent power distribution and utilization is proposed. In the proposed method, GANs theory is introduced to expand the distribution of completed data samples. Then, a so-called peak clustering algorithm is proposed to realize the finite open coverage of the expanded sample space, and repair those incomplete samples to eliminate the heterogeneous characteristics. Finally, in order to realize the integration of the heterogeneous data for intelligent power distribution and utilization, the well-trained discriminator model of GANs is employed to check the restored data samples. The simulation experiments verified the validity and stability of the proposed heterogeneous data integration method, which provides a novel perspective for the further data quality management of power distribution systems.

  19. Service-oriented architecture of adaptive, intelligent data acquisition and processing systems for long-pulse fusion experiments

    International Nuclear Information System (INIS)

    Gonzalez, J.; Ruiz, M.; Barrera, E.; Lopez, J.M.; Arcas, G. de; Vega, J.

    2010-01-01

    The data acquisition systems used in long-pulse fusion experiments need to implement data reduction and pattern recognition algorithms in real time. In order to accomplish these operations, it is essential to employ software tools that allow for hot swap capabilities throughout the temporal evolution of the experiments. This is very important because processing needs are not equal during different phases of the experiment. The intelligent test and measurement system (ITMS) developed by UPM and CIEMAT is an example of a technology for implementing scalable data acquisition and processing systems based on PXI and CompactPCI hardware. In the ITMS platform, a set of software tools allows the user to define the processing algorithms associated with the different experimental phases using state machines driven by software events. These state machines are specified using the State Chart XML (SCXML) language. The software tools are developed using JAVA, JINI, an SCXML engine and several LabVIEW applications. Within this schema, it is possible to execute data acquisition and processing applications in an adaptive way. The power of SCXML semantics and the ability to work with XML user-defined data types allow for very easy programming of the ITMS platform. With this approach, the ITMS platform is a suitable solution for implementing scalable data acquisition and processing systems based on a service-oriented model with the ability to easily implement remote participation applications.

  20. Services oriented architecture for adaptive and intelligent data acquisition and processing systems in long pulse fusion experiments

    Energy Technology Data Exchange (ETDEWEB)

    Gonzalez, J.; Ruiz, M.; Barrera, E.; Lopez, J.M.; De Arcas, G. [Universidad Politecnica de Madrid (Spain); Vega, J. [Association EuratomCIEMAT para Fusion, Madrid (Spain)

    2009-07-01

    Data acquisition systems used in long pulse fusion experiments require to implement data reduction and pattern recognition algorithms in real time. In order to accomplish these operations is essential to dispose software tools that allow hot swap capabilities throughout the temporal evolution of the experiments. This is very important because the processing needs are not equal in the different experiment's phases. The intelligent test and measurement system (ITMS) developed by UPM and CIEMAT is an example of technology for implementing scalable data acquisition and processing systems based in PXI and compact PCI hardware. In the ITMS platform a set of software tools allows the user to define the processing associated with the different experiment's phases using state machines driven by software events. These state machines are specified using State Chart XML (SCXML) language. The software tools are developed using: JAVA, JINI, a SCXML engine and several LabVIEW applications. With this schema it is possible to execute data acquisition and processing applications in an adaptive way. The powerful of SCXML semantics and the possibility of to work with XML user defined data types allow a very easy programming of ITMS platform. With this approach ITMS platform is a suitable solution for implementing scalable data acquisition and processing systems, based in a services oriented model, with ease possibility for implement remote participation applications. (authors)

  1. Service-oriented architecture of adaptive, intelligent data acquisition and processing systems for long-pulse fusion experiments

    Energy Technology Data Exchange (ETDEWEB)

    Gonzalez, J. [Grupo de Investigacion en Instrumentacion y Acustica Aplicada. Universidad Politecnica de Madrid, Crta. Valencia Km-7 Madrid 28031 (Spain); Ruiz, M., E-mail: mariano.ruiz@upm.e [Grupo de Investigacion en Instrumentacion y Acustica Aplicada. Universidad Politecnica de Madrid, Crta. Valencia Km-7 Madrid 28031 (Spain); Barrera, E.; Lopez, J.M.; Arcas, G. de [Grupo de Investigacion en Instrumentacion y Acustica Aplicada. Universidad Politecnica de Madrid, Crta. Valencia Km-7 Madrid 28031 (Spain); Vega, J. [Asociacion EURATOM/CIEMAT para Fusion, Madrid (Spain)

    2010-07-15

    The data acquisition systems used in long-pulse fusion experiments need to implement data reduction and pattern recognition algorithms in real time. In order to accomplish these operations, it is essential to employ software tools that allow for hot swap capabilities throughout the temporal evolution of the experiments. This is very important because processing needs are not equal during different phases of the experiment. The intelligent test and measurement system (ITMS) developed by UPM and CIEMAT is an example of a technology for implementing scalable data acquisition and processing systems based on PXI and CompactPCI hardware. In the ITMS platform, a set of software tools allows the user to define the processing algorithms associated with the different experimental phases using state machines driven by software events. These state machines are specified using the State Chart XML (SCXML) language. The software tools are developed using JAVA, JINI, an SCXML engine and several LabVIEW applications. Within this schema, it is possible to execute data acquisition and processing applications in an adaptive way. The power of SCXML semantics and the ability to work with XML user-defined data types allow for very easy programming of the ITMS platform. With this approach, the ITMS platform is a suitable solution for implementing scalable data acquisition and processing systems based on a service-oriented model with the ability to easily implement remote participation applications.

  2. Intelligent solar-powered automobile-ventilation system

    International Nuclear Information System (INIS)

    Huang, K. David; Tzeng, S.-C.; Ma Weiping; Wu Mingfung

    2005-01-01

    This study adopts airflow management technology to improve the local temperature distributions in an automobile to counteract the greenhouse effect. The automobile's temperature can be reduced to almost the outside temperature before the driver or passenger gets into the vehicle. When the engine is idling, the greenhouse-control system can be activated to remove the hot air from the car. An appropriate negative pressure is maintained to prevent stuffiness and save energy. The greenhouse-control system requires electrical power when the engine is idle, and a battery cannot supply sufficient power. An auxiliary solar-power supply can save energy and reduce the greenhouse effect of sunlight, while creating a comfortable traveling environment. It ensures that the engine is not overburdened and increases its service life, conserving energy, protecting the environment and improving comfort

  3. Model-free adaptive control of advanced power plants

    Science.gov (United States)

    Cheng, George Shu-Xing; Mulkey, Steven L.; Wang, Qiang

    2015-08-18

    A novel 3-Input-3-Output (3.times.3) Model-Free Adaptive (MFA) controller with a set of artificial neural networks as part of the controller is introduced. A 3.times.3 MFA control system using the inventive 3.times.3 MFA controller is described to control key process variables including Power, Steam Throttle Pressure, and Steam Temperature of boiler-turbine-generator (BTG) units in conventional and advanced power plants. Those advanced power plants may comprise Once-Through Supercritical (OTSC) Boilers, Circulating Fluidized-Bed (CFB) Boilers, and Once-Through Supercritical Circulating Fluidized-Bed (OTSC CFB) Boilers.

  4. Revisiting the Psychology of Intelligence Analysis: From Rational Actors to Adaptive Thinkers

    Science.gov (United States)

    Puvathingal, Bess J.; Hantula, Donald A.

    2012-01-01

    Intelligence analysis is a decision-making process rife with ambiguous, conflicting, irrelevant, important, and excessive information. The U.S. Intelligence Community is primed for psychology to lend its voice to the "analytic transformation" movement aimed at improving the quality of intelligence analysis. Traditional judgment and decision making…

  5. Evolutionary Computing for Intelligent Power System Optimization and Control

    DEFF Research Database (Denmark)

    This new book focuses on how evolutionary computing techniques benefit engineering research and development tasks by converting practical problems of growing complexities into simple formulations, thus largely reducing development efforts. This book begins with an overview of the optimization the...... theory and modern evolutionary computing techniques, and goes on to cover specific applications of evolutionary computing to power system optimization and control problems....

  6. Protecting Intelligent Distributed Power Grids against Cyber Attacks

    Energy Technology Data Exchange (ETDEWEB)

    Dong Wei; Yan Lu; Mohsen Jafari; Paul Skare; Kenneth Rohde

    2010-12-31

    Like other industrial sectors, the electrical power industry is facing challenges involved with the increasing demand for interconnected operations and control. The electrical industry has largely been restructured due to deregulation of the electrical market and the trend of the Smart Grid. This moves new automation systems from being proprietary and closed to the current state of Information Technology (IT) being highly interconnected and open. However, while gaining all of the scale and performance benefits of IT, existing IT security challenges are acquired as well. The power grid automation network has inherent security risks due to the fact that the systems and applications for the power grid were not originally designed for the general IT environment. In this paper, we propose a conceptual layered framework for protecting power grid automation systems against cyber attacks. The following factors are taken into account: (1) integration with existing, legacy systems in a non-intrusive fashion; (2) desirable performance in terms of modularity, scalability, extendibility, and manageability; (3) alignment to the 'Roadmap to Secure Control Systems in the Energy Sector' and the future smart grid. The on-site system test of the developed prototype security system is briefly presented as well.

  7. Smart grids - intelligence for sustainable electrical power systems

    NARCIS (Netherlands)

    Slootweg, J.G.; Cordova, C.E.P.; Montes Portela, C.; Morren, J.

    2011-01-01

    Due to the adverse impacts of the consumption of fossil fuels on our environment, the quest for a more sustainable energy supply is increasingly intensifying. Many renewable energy sources, such as wind, solar and tidal power generate electricity. Therefore, the development towards a sustainable

  8. Development of intelligent MPPT (maximum power point tracking) control for a grid-connected hybrid power generation system

    International Nuclear Information System (INIS)

    Hong, Chih-Ming; Ou, Ting-Chia; Lu, Kai-Hung

    2013-01-01

    A hybrid power control system is proposed in the paper, consisting of solar power, wind power, and a diesel-engine. To achieve a fast and stable response for the real power control, an intelligent controller was proposed, which consists of the Wilcoxon (radial basis function network) RBFN and the improved (Elman neural network) ENN for (maximum power point tracking) MPPT. The pitch angle control of wind power uses improved ENN controller, and the output is fed to the wind turbine to achieve the MPPT. The solar array is integrated with an RBFN control algorithm to track the maximum power. MATLAB (MATrix LABoratory)/Simulink was used to build the dynamic model and simulate the solar and diesel-wind hybrid power system. - Highlights: ► To achieve a fast and stable response for the real power control. ► The pitch control of wind power uses improved ENN (Elman neural network) controller to achieve the MPPT (maximum power point tracking). ► The RBFN (radial basis function network) can quickly and accurately track the maximum power output for PV (photovoltaic) array. ► MATLAB was used to build the dynamic model and simulate the hybrid power system. ► This method can reach the desired performance even under different load conditions

  9. DOWNHOLE POWER GENERATION AND WIRELESS COMMUNICATIONS FOR INTELLIGENT COMPLETIONS APPLICATIONS

    Energy Technology Data Exchange (ETDEWEB)

    Paul Tubel

    2003-10-14

    The fourth quarter of the project was dedicated to the manufacturing of the mechanical system for wireless communications and the power generation module and inspection pre assembly of the mechanical components. Another emphasis for the quarter was the development of filter control and signal detection software. The tasks accomplished during this report period were: (1) Dimensional issues were resolved and revised drawings for manufacturing of the wireless communications gauge and power generator were completed and sent to a machine shop for manufacturing. (2) Finalized the requirements and fittings and connections for testing the tool in the Halliburton flow loop. (3) The new acoustic generator was manufactured successfully and it was delivered during this quarter. The assembly will be outsourced for plastic coating in preparation for hostile environment use. (4) The acoustic two-way communications development continued to progress. The real time firmware for the surface system was developed and the processor was able to detect and process the data frame transmitted from downhole. The analog section of the tool was also developed and it is being tested for filtering capabilities and signal detection and amplification. (5) The new transformer to drive the acoustic generator assembly was manufactured and was successfully tested. Spring mandrel design showed increased acoustic output on the pipe and was implemented. (6) PCBA board carrier with board set was tested for function and fit and is 100% complete. (7) Filter control software is complete and software to allow modification of communication parameters dynamically is 50% complete. (8) All mechanical parts to assemble the wireless gauge and power generator have been received and verified to be within specification. (9) Acoustic generator has been assembled in the tool mandrel and tested successfully. (10) The circuit required to harvest the power generated downhole has been designed and the power generator

  10. Predicting speech intelligibility based on the signal-to-noise envelope power ratio after modulation-frequency selective processing

    DEFF Research Database (Denmark)

    Jørgensen, Søren; Dau, Torsten

    2011-01-01

    A model for predicting the intelligibility of processed noisy speech is proposed. The speech-based envelope power spectrum model has a similar structure as the model of Ewert and Dau [(2000). J. Acoust. Soc. Am. 108, 1181-1196], developed to account for modulation detection and masking data. The ...... process provides a key measure of speech intelligibility. © 2011 Acoustical Society of America.......A model for predicting the intelligibility of processed noisy speech is proposed. The speech-based envelope power spectrum model has a similar structure as the model of Ewert and Dau [(2000). J. Acoust. Soc. Am. 108, 1181-1196], developed to account for modulation detection and masking data....... The model estimates the speech-to-noise envelope power ratio, SNR env, at the output of a modulation filterbank and relates this metric to speech intelligibility using the concept of an ideal observer. Predictions were compared to data on the intelligibility of speech presented in stationary speech...

  11. Flight Results of the NF-15B Intelligent Flight Control System (IFCS) Aircraft with Adaptation to a Longitudinally Destabilized Plant

    Science.gov (United States)

    Bosworth, John T.

    2008-01-01

    Adaptive flight control systems have the potential to be resilient to extreme changes in airplane behavior. Extreme changes could be a result of a system failure or of damage to the airplane. The goal for the adaptive system is to provide an increase in survivability in the event that these extreme changes occur. A direct adaptive neural-network-based flight control system was developed for the National Aeronautics and Space Administration NF-15B Intelligent Flight Control System airplane. The adaptive element was incorporated into a dynamic inversion controller with explicit reference model-following. As a test the system was subjected to an abrupt change in plant stability simulating a destabilizing failure. Flight evaluations were performed with and without neural network adaptation. The results of these flight tests are presented. Comparison with simulation predictions and analysis of the performance of the adaptation system are discussed. The performance of the adaptation system is assessed in terms of its ability to stabilize the vehicle and reestablish good onboard reference model-following. Flight evaluation with the simulated destabilizing failure and adaptation engaged showed improvement in the vehicle stability margins. The convergent properties of this initial system warrant additional improvement since continued maneuvering caused continued adaptation change. Compared to the non-adaptive system the adaptive system provided better closed-loop behavior with improved matching of the onboard reference model. A detailed discussion of the flight results is presented.

  12. An artificial intelligence approach towards disturbance analysis in nuclear power plants

    International Nuclear Information System (INIS)

    Lindner, A.; Klebau, J.; Fielder, U.; Baldeweg, F.

    1987-01-01

    The scale and degree of sophistication of technological plants, e.g. nuclear power plants, have been essentially increased during the last decades. Conventional disturbance analysis systems have proved to work successfully in wellknown situations. But in cases of emergencies, the operator staff needs a more advanced assistance in realizing diagnosis and therapy control. The significance of introducing artificial intelligence methods in nuclear power technology is emphasized. Main features of the on-line disturbance analysis system SAAP-2 are reported about. It is being developed for application in nuclear power plants. 9 refs. (author)

  13. Intelligent Sun Tracking for a CPV Power Plant

    International Nuclear Information System (INIS)

    Maqsood, Ishtiaq; Emziane, Mahieddine

    2010-01-01

    The output of a solar panel is strongly dependent on the amount of perpendicular light flux falling on its surface, and a tracking system tries to parallel the vector area of the solar panel surface to the incident solar flux. We present a tracking technique based on a two-axis sun sensor which can be used to increase the power output from a number of CPV arrays connected together in a solar power plant. The outdoor testing procedure of the developed two-axis sun sensor is discussed. The detail of the algorithm used together with the related sun tracking equipment is also presented and discussed for the new two axes sun tracking system.

  14. An intelligent design methodology for nuclear power systems

    International Nuclear Information System (INIS)

    Nassersharif, B.; Martin, R.P.; Portal, M.G.; Gaeta, M.J.

    1989-01-01

    The goal of this investigation is to research possible methodologies into automating the design of, specifically, nuclear power facilities; however, it is relevant to all thermal power systems. The strategy of this research has been to concentrate on individual areas of the thermal design process, investigate procedures performed, develop methodology to emulate that behavior, and prototype it in the form of a computer program. The design process has been generalized as follows: problem definition, design definition, component selection procedure, optimization and engineering analysis, testing and final design with the problem definition defining constraints that will be applied to the selection procedure as well as design definition. The result of this research is a prototype computer program applying an original procedure for the selection of the best set of real components that would be used in constructing a system with desired performance characteristics. The mathematical model used for the selection procedure is possibility theory

  15. Intelligent sensor and controller framework for the power grid

    Science.gov (United States)

    Akyol, Bora A.; Haack, Jereme Nathan; Craig, Jr., Philip Allen; Tews, Cody William; Kulkarni, Anand V.; Carpenter, Brandon J.; Maiden, Wendy M.; Ciraci, Selim

    2018-03-20

    Disclosed below are representative embodiments of methods, apparatus, and systems for monitoring and using data in an electric power grid. For example, one disclosed embodiment comprises a sensor for measuring an electrical characteristic of a power line, electrical generator, or electrical device; a network interface; a processor; and one or more computer-readable storage media storing computer-executable instructions. In this embodiment, the computer-executable instructions include instructions for implementing an authorization and authentication module for validating a software agent received at the network interface; instructions for implementing one or more agent execution environments for executing agent code that is included with the software agent and that causes data from the sensor to be collected; and instructions for implementing an agent packaging and instantiation module for storing the collected data in a data container of the software agent and for transmitting the software agent, along with the stored data, to a next destination.

  16. Intelligent control of energy-saving power generation system

    Energy Technology Data Exchange (ETDEWEB)

    Zhang, Zhiyuan; Zhang, Guoqing; Guo, Zhizhong [Harbin Institute of Technology, Harbin (China). Dept. of Electrical Engineering

    2013-07-01

    Highway power generation system which is environmentally friendly and sustainable provides an innovative method of energy conversion. It is also as a kind of city science and technology innovation, which has the characteristics of environmental protection and sustainable utilization. Making full use of vehicle impact speed control humps, we design a new kind of highway speed control humps combined with solar electric generation system integration. Developing green energy, energy saving and environment protection can be achieved.

  17. Flexible power delivery system and its intelligent functions

    International Nuclear Information System (INIS)

    Glamochanin, Vlastimir; Andonov, Dragan

    1996-01-01

    This paper presents some of the features and capabilities of the novel energy distribution system called FRIENDS. The main FRIENDS objective is distribution system reliability, with flexible system structure reconfiguration, inclusion of dispersed energy generation systems. Altogether, it represents a new concept of reliable and economic electric power delivery to end users. The FRIENDS project is a challenge for future research and development, including new technology and devices for the implementation of such an integrated system. (author)

  18. Intelligent power wheelchair use in long-term care: potential users' experiences and perceptions.

    Science.gov (United States)

    Rushton, Paula W; Mortenson, Ben W; Viswanathan, Pooja; Wang, Rosalie H; Miller, William C; Hurd Clarke, Laura

    2017-10-01

    Long-term care (LTC) residents with cognitive impairments frequently experience limited mobility and participation in preferred activities. Although a power wheelchair could mitigate some of these mobility and participation challenges, this technology is often not prescribed for this population due to safety concerns. An intelligent power wheelchair (IPW) system represents a potential intervention that could help to overcome these concerns. The purpose of this study was to explore a) how residents experienced an IPW that used three different modes of control and b) what perceived effect the IPW would have on their daily lives. We interviewed 10 LTC residents with mild or moderate cognitive impairment twice, once before and once after testing the IPW. Interviews were conducted using a semi-structured interview guide, audio recorded and transcribed verbatim for thematic analyses. Our analyses identified three overarching themes: (1) the difference an IPW would make, (2) the potential impact of the IPW on others and (3) IPW-related concerns. Findings from this study confirm the need for and potential benefits of IPW use in LTC. Future studies will involve testing IPW improvements based on feedback and insights from this study. Implications for rehabilitation Intelligent power wheelchairs may enhance participation and improve safety and feelings of well-being for long-term care residents with cognitive impairments. Intelligent power wheelchairs could potentially have an equally positive impact on facility staff, other residents, and family and friends by decreasing workload and increasing safety.

  19. Accelerator-control-system interface for intelligent power supplies

    International Nuclear Information System (INIS)

    Cohen, S.

    1992-01-01

    A number of high-current high-precision magnet power supplies have been installed at the proton storage ring at the Los Alamos National Laboratory Accelerator Complex. The units replace existing supplies, powering large dipole magnets in the ring. These bending magnets require a high-current supply that is precise and stable. The control and interface design for these power supplies represents a departure from all others on-site. The supplies have sophisticated microprocessor control on-board and communicate with the accelerator control system via RS-422 (serial communications). The units, built by Alpha Scientific Electronics, Hayward, CA use a high-level ASCII control protocol. The low-level ''front-end'' software used by the accelerator control system has been written to accommodate these new devices. They communicate with the control system through a terminal server port connected to the site-wide ethernet backbone. Details of the software implementation for the analog and digital control of the supplies through the accelerator control system will be presented

  20. The adaptation of the electric power companies to the power market

    International Nuclear Information System (INIS)

    Otterstad, B.; Ottosen, R.

    1993-02-01

    This report describes the challenges met by the Norwegian electric power companies in adapting to a more market oriented business and their possibilities and strategies when facing the uncertainties on the market side. The main principles of adaptation to the market are described and various strategies are illustrated by means of simple calculations and figures. The theoretical basis for analyses of adaptation to the market and for pricing period contracts and options are discussed. The report concludes with a discussion of the de-regulation of the North American gas market and draws parallels to the Norwegian power market. 17 figs

  1. An Adaptive and Integrated Low-Power Framework for Multicore Mobile Computing

    Directory of Open Access Journals (Sweden)

    Jongmoo Choi

    2017-01-01

    Full Text Available Employing multicore in mobile computing such as smartphone and IoT (Internet of Things device is a double-edged sword. It provides ample computing capabilities required in recent intelligent mobile services including voice recognition, image processing, big data analysis, and deep learning. However, it requires a great deal of power consumption, which causes creating a thermal hot spot and putting pressure on the energy resource in a mobile device. In this paper, we propose a novel framework that integrates two well-known low-power techniques, DPM (Dynamic Power Management and DVFS (Dynamic Voltage and Frequency Scaling for energy efficiency in multicore mobile systems. The key feature of the proposed framework is adaptability. By monitoring the online resource usage such as CPU utilization and power consumption, the framework can orchestrate diverse DPM and DVFS policies according to workload characteristics. Real implementation based experiments using three mobile devices have shown that it can reduce the power consumption ranging from 22% to 79%, while affecting negligibly the performance of workloads.

  2. Intelligent neural network and fuzzy logic control of industrial and power systems

    Science.gov (United States)

    Kuljaca, Ognjen

    The main role played by neural network and fuzzy logic intelligent control algorithms today is to identify and compensate unknown nonlinear system dynamics. There are a number of methods developed, but often the stability analysis of neural network and fuzzy control systems was not provided. This work will meet those problems for the several algorithms. Some more complicated control algorithms included backstepping and adaptive critics will be designed. Nonlinear fuzzy control with nonadaptive fuzzy controllers is also analyzed. An experimental method for determining describing function of SISO fuzzy controller is given. The adaptive neural network tracking controller for an autonomous underwater vehicle is analyzed. A novel stability proof is provided. The implementation of the backstepping neural network controller for the coupled motor drives is described. Analysis and synthesis of adaptive critic neural network control is also provided in the work. Novel tuning laws for the system with action generating neural network and adaptive fuzzy critic are given. Stability proofs are derived for all those control methods. It is shown how these control algorithms and approaches can be used in practical engineering control. Stability proofs are given. Adaptive fuzzy logic control is analyzed. Simulation study is conducted to analyze the behavior of the adaptive fuzzy system on the different environment changes. A novel stability proof for adaptive fuzzy logic systems is given. Also, adaptive elastic fuzzy logic control architecture is described and analyzed. A novel membership function is used for elastic fuzzy logic system. The stability proof is proffered. Adaptive elastic fuzzy logic control is compared with the adaptive nonelastic fuzzy logic control. The work described in this dissertation serves as foundation on which analysis of particular representative industrial systems will be conducted. Also, it gives a good starting point for analysis of learning abilities of

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

    Directory of Open Access Journals (Sweden)

    Haoran Zhao

    2018-03-01

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

  4. An Artificially Intelligent Physical Model-Checking Approach to Detect Switching-Related Attacks on Power Systems

    Energy Technology Data Exchange (ETDEWEB)

    El Hariri, Mohamad [Florida Intl Univ., Miami, FL (United States); Faddel, Samy [Florida Intl Univ., Miami, FL (United States); Mohammed, Osama [Florida Intl Univ., Miami, FL (United States)

    2017-11-01

    Decentralized and hierarchical microgrid control strategies have lain the groundwork for shaping the future smart grid. Such control approaches require the cooperation between microgrid operators in control centers, intelligent microcontrollers, and remote terminal units via secure and reliable communication networks. In order to enhance the security and complement the work of network intrusion detection systems, this paper presents an artificially intelligent physical model-checking that detects tampered-with circuit breaker switching control commands whether, due to a cyber-attack or human error. In this technique, distributed agents, which are monitoring sectionalized areas of a given microgrid, will be trained and continuously adapted to verify that incoming control commands do not violate the physical system operational standards and do not put the microgrid in an insecure state. The potential of this approach has been tested by deploying agents that monitor circuit breakers status commands on a 14-bus IEEE benchmark system. The results showed the accuracy of the proposed framework in characterizing the power system and successfully detecting malicious and/or erroneous control commands.

  5. CRISP. Requirements Specifications of Intelligent ICT Simulation Tools for Power Applications

    Energy Technology Data Exchange (ETDEWEB)

    Warmer, C.J.; Kester, J.C.P.; Kamphuis, I.G. [ECN Energy in the Built Environment and Networks, Petten (Netherlands); Carlsson, P [EnerSearch, Malmoe (Sweden); Fontela, M. [Laboratory of Electrical Engineering LEG, Grenoble (France); Gustavsson, R. [Blekinge Institute of Technology BTH, Karlskrona (Sweden)

    2003-10-15

    This report, deliverable D2.1 in the CRISP project, serves as a preparation report for the development of simulation tools and prototype software which will be developed in forthcoming stages of the CRISP project. Application areas for these simulations are: fault detection and diagnosis, supply and demand matching and intelligent load shedding. The context in which these applications function is the power network with a high degree of distributed generation, including renewables. In order to control a so called distributed grid we can benefit from a high level of distributed control and intelligence. This requires, on top of the power system network, an information and communication network.. We argue that such a network should be seen as an enabler of distributed control and intelligence. The applications, through which control and intelligence is implemented, then form a third network layer, the service oriented network. Building upon this three-layered network model we derive in this report the requirements for a simulation tool and experiments which study new techniques for fault detection and diagnostics and for simulation tools and experiments implementing intelligent load shedding and supply and demand matching scenarios. We also look at future implementation of these services within the three-layered network model and the requirements that follow for the core information and communication network and for the service oriented network. These requirements, supported by the studies performed in the CRISP Workpackage 1, serve as a basis for development of the simulation tools in the tasks 2.2 to 2.4.

  6. CRISP. Requirements Specifications of Intelligent ICT Simulation Tools for Power Applications

    International Nuclear Information System (INIS)

    Warmer, C.J.; Kester, J.C.P.; Kamphuis, I.G.; Carlsson, P; Fontela, M.; Gustavsson, R.

    2003-10-01

    This report, deliverable D2.1 in the CRISP project, serves as a preparation report for the development of simulation tools and prototype software which will be developed in forthcoming stages of the CRISP project. Application areas for these simulations are: fault detection and diagnosis, supply and demand matching and intelligent load shedding. The context in which these applications function is the power network with a high degree of distributed generation, including renewables. In order to control a so called distributed grid we can benefit from a high level of distributed control and intelligence. This requires, on top of the power system network, an information and communication network.. We argue that such a network should be seen as an enabler of distributed control and intelligence. The applications, through which control and intelligence is implemented, then form a third network layer, the service oriented network. Building upon this three-layered network model we derive in this report the requirements for a simulation tool and experiments which study new techniques for fault detection and diagnostics and for simulation tools and experiments implementing intelligent load shedding and supply and demand matching scenarios. We also look at future implementation of these services within the three-layered network model and the requirements that follow for the core information and communication network and for the service oriented network. These requirements, supported by the studies performed in the CRISP Workpackage 1, serve as a basis for development of the simulation tools in the tasks 2.2 to 2.4

  7. Intelligent Energy Management System for Virtual Power Plants

    DEFF Research Database (Denmark)

    Braun, Philipp

    demonstrated to be suitable storage technologies that have been integrated in power systems worldwide in recent years. Such storage systems are underlying a fast development track and have improved over the past decades considerably. This makes an increase in the number of VPPs more likely in future. Potential...... investors in VPPs face several questions before and after an investment decision for a specific BESS is made. This work addresses the following questions: 1. Is a VPP a profitable investment and if so, which technology or combination of different technologies of BESSs and which size should be purchased? 2...... questions depending on the input parameters provided to the model. The model focuses on the BESS including capacity fade which is a battery specific property. It determines the performance, live-time, and - most important - the annualized costs of the BESS. Modeling capacity fade opens up the possibility...

  8. Intelligent speed adaptation: Preliminary results of on-road study in Penang, Malaysia

    Directory of Open Access Journals (Sweden)

    S.M.R. Ghadiri

    2013-03-01

    Full Text Available The first field experiment with intelligent speed adaptation (ISA in Malaysia was held in December 2010 in the State of Penang. Eleven private cars were instrumented with an advisory system. The system used in the present study included a vocal warning message and a visual text message that is activated when the driver attempts to exceed the speed limit. When the driver decreases the speed, the warning stops; otherwise it is continuously repeated. The test drivers drove the vehicles for three months with the installed system, and the speed was continuously logged in all vehicles. The warning was however only activated in the second month of the three month period. The present study aimed to evaluate the effects of an advisory ISA on driving speed, traffic safety, and drivers' attitude, behavior, and acceptance of the system. To examine these effects, both the survey and the logged speed data were analyzed and explored. The results show a significant reduction in the mean, maximum and 85th percentile speed due to the use of the system. However, there was no long-lasting effect on the speed when the system was deactivated. In the post-trial survey, drivers declared that the system helped them well in following the speed limits and that it assisted them in driving more comfortably. Furthermore, the warning method was more accepted compared to a supportive system, such as active accelerator pedal (AAP. After the trial, most drivers were willing to keep an ISA system.

  9. Intelligence by design in an entropic power grid

    Science.gov (United States)

    Negrete-Pincetic, Matias Alejandro

    In this work, the term Entropic Grid is coined to describe a power grid with increased levels of uncertainty and dynamics. These new features will require the reconsideration of well-established paradigms in the way of planning and operating the grid and its associated markets. New tools and models able to handle uncertainty and dynamics will form the required scaffolding to properly capture the behavior of the physical system, along with the value of new technologies and policies. The leverage of this knowledge will facilitate the design of new architectures to organize power and energy systems and their associated markets. This work presents several results, tools and models with the goal of contributing to that design objective. A central idea of this thesis is that the definition of products is critical in electricity markets. When markets are constructed with appropriate product definitions in mind, the interference between the physical and the market/financial systems seen in today's markets can be reduced. A key element of evaluating market designs is understanding the impact that salient features of an entropic grid---uncertainty, dynamics, constraints---can have on the electricity markets. Dynamic electricity market models tailored to capture such features are developed in this work. Using a multi-settlement dynamic electricity market, the impact of volatility is investigated. The results show the need to implement policies and technologies able to cope with the volatility of renewable sources. Similarly, using a dynamic electricity market model in which ramping costs are considered, the impacts of those costs on electricity markets are investigated. The key conclusion is that those additional ramping costs, in average terms, are not reflected in electricity prices. These results reveal several difficulties with today's real-time markets. Elements of an alternative architecture to organize these markets are also discussed.

  10. Resonant power converter comprising adaptive dead-time control

    DEFF Research Database (Denmark)

    2017-01-01

    The invention relates in a first aspect to a resonant power converter comprising: a first power supply rail for receipt of a positive DC supply voltage and a second power supply rail for receipt of a negative DC supply voltage. The resonant power converter comprises a resonant network with an input...... terminal for receipt of a resonant input voltage from a driver circuit. The driver circuit is configured for alternatingly pulling the resonant input voltage towards the positive and negative DC supply voltages via first and second semiconductor switches, respectively, separated by intervening dead......-time periods in accordance with one or more driver control signals. A dead-time controller is configured to adaptively adjusting the dead-time periods based on the resonant input voltage....

  11. Low-power adaptive filter based on RNS components

    DEFF Research Database (Denmark)

    Bernocchi, Gian Luca; Cardarilli, Gian Carlo; Del Re, Andrea

    2007-01-01

    In this paper a low-power implementation of an adaptive FIR filter is presented. The filter is designed to meet the constraints of channel equalization for fixed wireless communications that typically requires a large number of taps, but a serial updating of the filter coefficients, based...... on the least mean squares (LMS) algorithm, is allowed. Previous work showed that the use of the residue number system (RNS) for the variable FIR filter grants advantages both in area and power consumption. On the other hand, the use of a binary serial implementation of the adaptation algorithm eliminates...... the need for complex scaling circuits in RNS. The advantages in terms of area and speed of the presented filter, with respect to its two's complement counterpart, are evaluated for implementations in standard cells....

  12. The role of short-time intensity and envelope power for speech intelligibility and psychoacoustic masking.

    Science.gov (United States)

    Biberger, Thomas; Ewert, Stephan D

    2017-08-01

    The generalized power spectrum model [GPSM; Biberger and Ewert (2016). J. Acoust. Soc. Am. 140, 1023-1038], combining the "classical" concept of the power-spectrum model (PSM) and the envelope power spectrum-model (EPSM), was demonstrated to account for several psychoacoustic and speech intelligibility (SI) experiments. The PSM path of the model uses long-time power signal-to-noise ratios (SNRs), while the EPSM path uses short-time envelope power SNRs. A systematic comparison of existing SI models for several spectro-temporal manipulations of speech maskers and gender combinations of target and masker speakers [Schubotz et al. (2016). J. Acoust. Soc. Am. 140, 524-540] showed the importance of short-time power features. Conversely, Jørgensen et al. [(2013). J. Acoust. Soc. Am. 134, 436-446] demonstrated a higher predictive power of short-time envelope power SNRs than power SNRs using reverberation and spectral subtraction. Here the GPSM was extended to utilize short-time power SNRs and was shown to account for all psychoacoustic and SI data of the three mentioned studies. The best processing strategy was to exclusively use either power or envelope-power SNRs, depending on the experimental task. By analyzing both domains, the suggested model might provide a useful tool for clarifying the contribution of amplitude modulation masking and energetic masking.

  13. Design of intelligent power consumption optimization and visualization management platform for large buildings based on internet of things

    Directory of Open Access Journals (Sweden)

    Gong Shulan

    2017-01-01

    Full Text Available The buildings provide a significant contribution to total energy consumption and CO2 emission. It has been estimated that the development of an intelligent power consumption monitor and control system will result in about 30% savings in energy consumption. This design innovatively integrates the advanced technologies such as the internet of things, the internet, intelligent buildings and intelligent electricity which can offer open, efficient, convenient energy consumption detection platform in demand side and visual management demonstration application platform in power enterprises side. The system was created to maximize the effective and efficient the use of energy resource. It was development around sensor networks and intelligent gateway and the monitoring center software. This will realize the highly integration and comprehensive application in energy and information to meet the needs with intelligent buildings

  14. Power adaptation for joint switched diversity and adaptive modulation schemes in spectrum sharing systems

    KAUST Repository

    Bouida, Zied

    2012-09-01

    Under the scenario of an underlay cognitive radio network, we propose in this paper an adaptive scheme using transmit power adaptation, switched transmit diversity, and adaptive modulation in order to improve the performance of existing switching efficient schemes (SES) and bandwidth efficient schemes (BES). Taking advantage of the channel reciprocity principle, we assume that the channel state information (CSI) of the interference link is available to the secondary transmitter. This information is then used by the secondary transmitter to adapt its transmit power, modulation constellation size, and used transmit branch. The goal of this joint adaptation is to minimize the average number of switched branches and the average system delay given the fading channel conditions, the required error rate performance, and a peak interference constraint to the primary receiver. We analyze the proposed scheme in terms of the average number of branch switching, average delay, and we provide a closed-form expression of the average bit error rate (BER). We demonstrate through numerical examples that the proposed scheme provides a compromise between the SES and the BES schemes. © 2012 IEEE.

  15. Power adaptation for joint switched diversity and adaptive modulation schemes in spectrum sharing systems

    KAUST Repository

    Bouida, Zied; Tourki, Kamel; Ghrayeb, Ali A.; Qaraqe, Khalid A.; Alouini, Mohamed-Slim

    2012-01-01

    Under the scenario of an underlay cognitive radio network, we propose in this paper an adaptive scheme using transmit power adaptation, switched transmit diversity, and adaptive modulation in order to improve the performance of existing switching efficient schemes (SES) and bandwidth efficient schemes (BES). Taking advantage of the channel reciprocity principle, we assume that the channel state information (CSI) of the interference link is available to the secondary transmitter. This information is then used by the secondary transmitter to adapt its transmit power, modulation constellation size, and used transmit branch. The goal of this joint adaptation is to minimize the average number of switched branches and the average system delay given the fading channel conditions, the required error rate performance, and a peak interference constraint to the primary receiver. We analyze the proposed scheme in terms of the average number of branch switching, average delay, and we provide a closed-form expression of the average bit error rate (BER). We demonstrate through numerical examples that the proposed scheme provides a compromise between the SES and the BES schemes. © 2012 IEEE.

  16. Development of an Intelligent Maximum Power Point Tracker Using an Advanced PV System Test Platform

    DEFF Research Database (Denmark)

    Spataru, Sergiu; Amoiridis, Anastasios; Beres, Remus Narcis

    2013-01-01

    The performance of photovoltaic systems is often reduced by the presence of partial shadows. The system efficiency and availability can be improved by a maximum power point tracking algorithm that is able to detect partial shadow conditions and to optimize the power output. This work proposes...... an intelligent maximum power point tracking method that monitors the maximum power point voltage and triggers a current-voltage sweep only when a partial shadow is detected, therefore minimizing power loss due to repeated current-voltage sweeps. The proposed system is validated on an advanced, flexible...... photovoltaic inverter system test platform that is able to reproduce realistic partial shadow conditions, both in simulation and on hardware test system....

  17. Integrating wind power using intelligent electric water heating

    International Nuclear Information System (INIS)

    Fitzgerald, Niall; Foley, Aoife M.; McKeogh, Eamon

    2012-01-01

    Dwindling fossil fuel resources and pressures to reduce greenhouse gas emissions will result in a more diverse range of generation portfolios for future electricity systems. Irrespective of the portfolio mix the overarching requirement for all electricity suppliers and system operators is to instantaneously meet demand, to operate to standards and reduce greenhouse gas emissions. Therefore all electricity market participants will ultimately need to use a variety of tools to balance the power system. Thus the role of demand side management with energy storage will be paramount to integrate future diverse generation portfolios. Electric water heating has been studied previously, particularly at the domestic level to provide load control, peak shave and to benefit end-users financially with lower bills, particularly in vertically integrated monopolies. In this paper a number of continuous direct load control demand response based electric water heating algorithms are modelled to test the effectiveness of wholesale electricity market signals to study the system benefits. The results are compared and contrasted to determine which control algorithm showed the best potential for energy savings, system marginal price savings and wind integration.

  18. Modeling speech intelligibility based on the signal-to-noise envelope power ratio

    DEFF Research Database (Denmark)

    Jørgensen, Søren

    of modulation frequency selectivity in the auditory processing of sound with a decision metric for intelligibility that is based on the signal-to-noise envelope power ratio (SNRenv). The proposed speech-based envelope power spectrum model (sEPSM) is demonstrated to account for the effects of stationary...... through three commercially available mobile phones. The model successfully accounts for the performance across the phones in conditions with a stationary speech-shaped background noise, whereas deviations were observed in conditions with “Traffic” and “Pub” noise. Overall, the results of this thesis...

  19. Cellular computational generalized neuron network for frequency situational intelligence in a multi-machine power system.

    Science.gov (United States)

    Wei, Yawei; Venayagamoorthy, Ganesh Kumar

    2017-09-01

    To prevent large interconnected power system from a cascading failure, brownout or even blackout, grid operators require access to faster than real-time information to make appropriate just-in-time control decisions. However, the communication and computational system limitations of currently used supervisory control and data acquisition (SCADA) system can only deliver delayed information. However, the deployment of synchrophasor measurement devices makes it possible to capture and visualize, in near-real-time, grid operational data with extra granularity. In this paper, a cellular computational network (CCN) approach for frequency situational intelligence (FSI) in a power system is presented. The distributed and scalable computing unit of the CCN framework makes it particularly flexible for customization for a particular set of prediction requirements. Two soft-computing algorithms have been implemented in the CCN framework: a cellular generalized neuron network (CCGNN) and a cellular multi-layer perceptron network (CCMLPN), for purposes of providing multi-timescale frequency predictions, ranging from 16.67 ms to 2 s. These two developed CCGNN and CCMLPN systems were then implemented on two different scales of power systems, one of which installed a large photovoltaic plant. A real-time power system simulator at weather station within the Real-Time Power and Intelligent Systems (RTPIS) laboratory at Clemson, SC, was then used to derive typical FSI results. Copyright © 2017 Elsevier Ltd. All rights reserved.

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

    Directory of Open Access Journals (Sweden)

    Jianzhou Wang

    2014-01-01

    Full Text Available Swarm intelligence (SI is widely and successfully applied in the engineering field to solve practical optimization problems because various hybrid models, which are based on the SI algorithm and statistical models, are developed to further improve the predictive abilities. In this paper, hybrid intelligent forecasting models based on the cuckoo search (CS as well as the singular spectrum analysis (SSA, time series, and machine learning methods are proposed to conduct short-term power load prediction. The forecasting performance of the proposed models is augmented by a rolling multistep strategy over the prediction horizon. The test results are representative of the out-performance of the SSA and CS in tuning the seasonal autoregressive integrated moving average (SARIMA and support vector regression (SVR in improving load forecasting, which indicates that both the SSA-based data denoising and SI-based intelligent optimization strategy can effectively improve the model’s predictive performance. Additionally, the proposed CS-SSA-SARIMA and CS-SSA-SVR models provide very impressive forecasting results, demonstrating their strong robustness and universal forecasting capacities in terms of short-term power load prediction 24 hours in advance.

  1. Knowledge Is Power for Medical Assistants: Crystallized and Fluid Intelligence As Predictors of Vocational Knowledge.

    Science.gov (United States)

    Moehring, Anne; Schroeders, Ulrich; Wilhelm, Oliver

    2018-01-01

    Medical education research has focused almost entirely on the education of future physicians. In comparison, findings on other health-related occupations, such as medical assistants, are scarce. With the current study, we wanted to examine the knowledge-is-power hypothesis in a real life educational setting and add to the sparse literature on medical assistants. Acquisition of vocational knowledge in vocational education and training (VET) was examined for medical assistant students ( n = 448). Differences in domain-specific vocational knowledge were predicted by crystallized and fluid intelligence in the course of VET. A multiple matrix design with 3 year-specific booklets was used for the vocational knowledge tests of the medical assistants. The unique and joint contributions of the predictors were investigated with structural equation modeling. Crystallized intelligence emerged as the strongest predictor of vocational knowledge at every stage of VET, while fluid intelligence only showed weak effects. The present results support the knowledge-is-power hypothesis, even in a broad and more naturalistic setting. This emphasizes the relevance of general knowledge for occupations, such as medical assistants, which are more focused on learning hands-on skills than the acquisition of academic knowledge.

  2. Knowledge Is Power for Medical Assistants: Crystallized and Fluid Intelligence As Predictors of Vocational Knowledge

    Directory of Open Access Journals (Sweden)

    Anne Moehring

    2018-02-01

    Full Text Available Medical education research has focused almost entirely on the education of future physicians. In comparison, findings on other health-related occupations, such as medical assistants, are scarce. With the current study, we wanted to examine the knowledge-is-power hypothesis in a real life educational setting and add to the sparse literature on medical assistants. Acquisition of vocational knowledge in vocational education and training (VET was examined for medical assistant students (n = 448. Differences in domain-specific vocational knowledge were predicted by crystallized and fluid intelligence in the course of VET. A multiple matrix design with 3 year-specific booklets was used for the vocational knowledge tests of the medical assistants. The unique and joint contributions of the predictors were investigated with structural equation modeling. Crystallized intelligence emerged as the strongest predictor of vocational knowledge at every stage of VET, while fluid intelligence only showed weak effects. The present results support the knowledge-is-power hypothesis, even in a broad and more naturalistic setting. This emphasizes the relevance of general knowledge for occupations, such as medical assistants, which are more focused on learning hands-on skills than the acquisition of academic knowledge.

  3. An adaptive crystal bender for high power synchrotron radiation beams

    International Nuclear Information System (INIS)

    Berman, L.E.; Hastings, J.B.

    1992-01-01

    Perfect crystal monochromators cannot diffract x-rays efficiently, nor transmit the high source brightness available at synchrotron radiation facilities, unless surface strains within the beam footprint are maintained within a few arcseconds. Insertion devices at existing synchrotron sources already produce x-ray power density levels that can induce surface slope errors of several arcseconds on silicon monochromator crystals at room temperature, no matter how well the crystal is cooled. The power density levels that will be produced by insertion devices at the third-generation sources will be as much as a factor of 100 higher still. One method of restoring ideal x-ray diffraction behavior, while coping with high power levels, involves adaptive compensation of the induced thermal strain field. The design and performance, using the X25 hybrid wiggler beam line at the National Synchrotron Light Source (NSLS), of a silicon crystal bender constructed for this purpose are described

  4. Coordinated Scheme of Under-Frequency Load Shedding with Intelligent Appliances in a Cyber Physical Power System

    Directory of Open Access Journals (Sweden)

    Qi Wang

    2016-08-01

    Full Text Available The construction of a cyber physical system in a power grid provides more potential control strategies for the power grid. With the rapid employment of intelligent terminal equipment (e.g., smart meters and intelligent appliances in the environment of a smart grid, abundant dynamic response information could be introduced to support a secure and stable power system. Combining demand response technology with the traditional under-frequency load shedding (UFLS scheme, a new UFLS strategy-determining method involving intelligent appliances is put forward to achieve the coordinated control of quick response resources and the traditional control resources. Based on this method, intelligent appliances can be used to meet the regulatory requirements of system operation in advance and prevent significant frequency drop, thereby improving the flexibility and stability of the system. Time-domain simulation verifies the effectiveness of the scheme, which is able to mitigate frequency drop and reduce the amount of load shedding.

  5. Requirement analysis for autonomous systems and intelligent agents in future Danish electric power systems

    DEFF Research Database (Denmark)

    Saleem, Arshad; Lind, Morten

    2010-01-01

    we review innovative control architectures in electric power systems such as Microgrids, Virtual power plants and Cell based systems. We evaluate application of autonomous systems and intelligent agents in each of these control architectures particularly in the context of Denmark's strategic energy...... plans. The second part formulates a flexible control architecture for electric power systems with very high penetration of distributed generation. This control architecture is based upon the requirements identified in the first part. We also present development of a software framework to test......Denmark has already achieved a record of 20% penetration of wind power and now moving towards even higher targets with an increasing part of the electricity produced by distributed generators (DGs). In this paper we report work from a sub activity "subgrid design" of the EcoGrid.dk project. First...

  6. Integration of artificial intelligence systems for nuclear power plants surveillance and diagnostics

    International Nuclear Information System (INIS)

    Chetry, Moon K.

    2012-01-01

    The objective of this program is to design, construct operate, test, and evaluate a prototype integrated monitoring and diagnostic system for a nuclear power plant. It is anticipated that this technology will have wide application to other complex systems (e.g., fossil power plants, chemical processing plants, and possibly air traffic control systems). Over the past decade, the University of Tennessee (UT) and others have carried out many projects utilizing various methodologies of artificial intelligence (expert systems, neural networks, fuzzy systems and genetic algorithms) to enhance the performance (safety, efficiency, reliability, and availability) of nuclear power plants. Investigations and studies have included a) instrumentation surveillance and calibration validation, b) inferential sensing to calibration of feed water venture flow during fouling, c) thermodynamic performance modeling with iterative improvement of plant heat rate, d) diagnosis of nuclear power plant transients

  7. Nuclear power and climate change: The cost of adaptation

    International Nuclear Information System (INIS)

    Pailiere, H.

    2012-01-01

    For more than a decade, the international community has been voicing concern over growing greenhouse gas (GHG) emissions, which are believed to be the largest contributor to global warming and more generally to climate change. According to the Intergovernmental Panel on Climate Change (IPCC), an increase in the frequency of heat waves and droughts is expected in many parts of the world, as is that of storms, flooding and cold episodes. The potential consequences of this projected climate change have prompted calls to reduce the use of fossil fuels and to promote low-carbon energy sources such as renewables and nuclear power. At the same time, there has also been growing concern that without a rapid decrease in GHG emissions, climate change could occur at such a scale that it will have a significant impact on major economic sectors including the power generation sector. Although the expanded use of renewables will reduce emissions from the power sector, it will also increase the dependence of distribution systems and electricity production on climatic conditions. Thermal power plants, such as fossil fuel and nuclear, will be affected primarily by the diminishing availability of water and the increasing likelihood of heat waves, which will have an impact on the cooling capabilities and power output of plants. In its 2012 edition of the World Energy Outlook, the IEA underlined the need to address an additional challenge, the water-energy nexus: water needs for energy production are set to grow at twice the rate of energy demands over the next decades. It has thus become clear that the availability of water for cooling will be an important criterion for assessing the viability of energy projects. Given the long operating life of nuclear reactors (60 years for Generation III designs), the possible impact of climate change on the operation and safety of nuclear power plants needs to be addressed at the design and siting stages in order to limit costly adaptation measures

  8. Adaptive Modeling of the International Space Station Electrical Power System

    Science.gov (United States)

    Thomas, Justin Ray

    2007-01-01

    Software simulations provide NASA engineers the ability to experiment with spacecraft systems in a computer-imitated environment. Engineers currently develop software models that encapsulate spacecraft system behavior. These models can be inaccurate due to invalid assumptions, erroneous operation, or system evolution. Increasing accuracy requires manual calibration and domain-specific knowledge. This thesis presents a method for automatically learning system models without any assumptions regarding system behavior. Data stream mining techniques are applied to learn models for critical portions of the International Space Station (ISS) Electrical Power System (EPS). We also explore a knowledge fusion approach that uses traditional engineered EPS models to supplement the learned models. We observed that these engineered EPS models provide useful background knowledge to reduce predictive error spikes when confronted with making predictions in situations that are quite different from the training scenarios used when learning the model. Evaluations using ISS sensor data and existing EPS models demonstrate the success of the adaptive approach. Our experimental results show that adaptive modeling provides reductions in model error anywhere from 80% to 96% over these existing models. Final discussions include impending use of adaptive modeling technology for ISS mission operations and the need for adaptive modeling in future NASA lunar and Martian exploration.

  9. Evolutionary Developmental Soft Robotics As a Framework to Study Intelligence and Adaptive Behavior in Animals and Plants

    Directory of Open Access Journals (Sweden)

    Francesco Corucci

    2017-07-01

    Full Text Available In this paper, a comprehensive methodology and simulation framework will be reviewed, designed in order to study the emergence of adaptive and intelligent behavior in generic soft-bodied creatures. By incorporating artificial evolutionary and developmental processes, the system allows to evolve complete creatures (brain, body, developmental properties, sensory, control system, etc. for different task environments. Whether the evolved creatures will resemble animals or plants is in general not known a priori, and depends on the specific task environment set up by the experimenter. In this regard, the system may offer a unique opportunity to explore differences and similarities between these two worlds. Different material properties can be simulated and optimized, from a continuum of soft/stiff materials, to the interconnection of heterogeneous structures, both found in animals and plants alike. The adopted genetic encoding and simulation environment are particularly suitable in order to evolve distributed sensory and control systems, which play a particularly important role in plants. After a general description of the system some case studies will be presented, focusing on the emergent properties of the evolved creatures. Particular emphasis will be on some unifying concepts that are thought to play an important role in the emergence of intelligent and adaptive behavior across both the animal and plant kingdoms, such as morphological computation and morphological developmental plasticity. Overall, with this paper, we hope to draw attention on set of tools, methodologies, ideas and results, which may be relevant to researchers interested in plant-inspired robotics and intelligence.

  10. Adaptations in athletic performance after ballistic power versus strength training.

    Science.gov (United States)

    Cormie, Prue; McGuigan, Michael R; Newton, Robert U

    2010-08-01

    To determine whether the magnitude of improvement in athletic performance and the mechanisms driving these adaptations differ in relatively weak individuals exposed to either ballistic power training or heavy strength training. Relatively weak men (n = 24) who could perform the back squat with proficient technique were randomized into three groups: strength training (n = 8; ST), power training (n = 8; PT), or control (n = 8). Training involved three sessions per week for 10 wk in which subjects performed back squats with 75%-90% of one-repetition maximum (1RM; ST) or maximal-effort jump squats with 0%-30% 1RM (PT). Jump and sprint performances were assessed as well as measures of the force-velocity relationship, jumping mechanics, muscle architecture, and neural drive. Both experimental groups showed significant (P training with no significant between-group differences evident in either jump (peak power: ST = 17.7% +/- 9.3%, PT = 17.6% +/- 4.5%) or sprint performance (40-m sprint: ST = 2.2% +/- 1.9%, PT = 3.6% +/- 2.3%). ST also displayed a significant increase in maximal strength that was significantly greater than the PT group (squat 1RM: ST = 31.2% +/- 11.3%, PT = 4.5% +/- 7.1%). The mechanisms driving these improvements included significant (P force-velocity relationship, jump mechanics, muscle architecture, and neural activation that showed a degree of specificity to the different training stimuli. Improvements in athletic performance were similar in relatively weak individuals exposed to either ballistic power training or heavy strength training for 10 wk. These performance improvements were mediated through neuromuscular adaptations specific to the training stimulus. The ability of strength training to render similar short-term improvements in athletic performance as ballistic power training, coupled with the potential long-term benefits of improved maximal strength, makes strength training a more effective training modality for relatively weak individuals.

  11. Designing an Adaptive Nuero-Fuzzy Inference System for Evaluating the Business Intelligence System Implementation in Software Industry

    Directory of Open Access Journals (Sweden)

    Iman Raeesi Vanani

    2015-03-01

    Full Text Available The main goal of research is designing an adaptive nuero-fuzzy inference system for evaluating the implementation of business intelligence systems in software industry. Iranian software development organizations have been facing a lot of problems in case of implementing business intelligence systems. This system would be helpful in recognizing the conditions and prerequisites of success or failure. Organizations can recalculate the neuro-fuzzy system outputs with some considerations on various inputs to figure out which inputs have the most effect on the implementation outputs. By resolving the problems on inputs, organizations can achieve a better level of implementation success. The designed system has been trained by a data set and afterwards, it has been evaluated. The trained system has reached the error value of 0.08. Eventually, some recommendations have been provided for software development firms on the areas that might need more considerations and improvements.

  12. Use of artificial intelligence to enhance the safety of nuclear power plants

    International Nuclear Information System (INIS)

    Uhrig, R.E.

    1989-01-01

    In the operation of a nuclear power plant, the sheer magnitude of the number of process parameters and systems interactions poses difficulties for the operators, particularly during abnormal or emergency situations. Recovery from an upset situation depends upon the facility with which the available raw data can be converted into and assimilated as meaningful knowledge. Plant personnel are sometimes affected by stress and emotion, which may have varying degrees of influence on their performance. Expert systems can take some of the uncertainty and guesswork out of their decisions by providing expert advice and rapid access to a large information base. Application of artificial intelligence technologies, particularly expert systems, to control room activities in a nuclear power plant has the potential to reduce operator error and improve power plant safety and reliability

  13. Use of artificial intelligence to enhance the safety of nuclear power plants

    International Nuclear Information System (INIS)

    Uhrig, R.E.

    1988-01-01

    In the operation of a nuclear power plant, the sheer magnitude of the number of process parameters and systems interactions poses difficulties for the operators, particularly during abnormal or emergency situations. Recovery from an upset situation depends upon the facility with which the available raw data can be converted into and assimilated as meaningful knowledge. Plant personnel are sometimes affected by stress and emotion, which may have varying degrees of influence on their performance. Expert systems can take some of the uncertainty and guesswork out of their decisions by providing expert advice and rapid access to a large information base. Application of artificial intelligence technologies, particularly expert systems, to control room activities in a nuclear power plant has the potential to reduce operator error and improve power plant safety and reliability. 12 refs

  14. Monitoring and operational support on nuclear power plants using an artificial intelligence system

    International Nuclear Information System (INIS)

    Bianchi, P.H.; Baptista Filho, B.D.

    2009-01-01

    The monitoring task in nuclear power plants is of crucial importance with respect to safety and efficient operation. The operators have a wide range of variables to observe and analyze; the quantity of variables and their behavior determine the time they have to take correct decisions. The complexity of such aspects in a nuclear power plant influences both, the plant operational efficiency and the general safety issues. This paper describes an experimental system developed by the authors which aims to assist the operators of nuclear power plants to take quick and safe decisions. The system maps the status of plant and helps the operators to make quick judgments by using artificial intelligence methods. The method makes use of a small set of monitored variables and presents a map of the plant status in a friendly manner. This system uses an architecture that has multiple self-organizing maps to perform these tasks. (author)

  15. Monitoring and operational support on nuclear power plants using an artificial intelligence system

    Energy Technology Data Exchange (ETDEWEB)

    Bianchi, Paulo H.; Baptista Filho, Benedito D., E-mail: phbianchi@gmail.co, E-mail: bdbfilho@ipen.b [Instituto de Pesquisas Energeticas e Nucleares (IPEN/CNEN-SP), Sao Paulo, SP (Brazil)

    2009-07-01

    The monitoring task in nuclear power plants is of crucial importance with respect to safety and efficient operation. The operators have a wide range of variables to observe and analyze; the quantity of variables and their behavior determine the time they have to take correct decisions. The complexity of such aspects in a nuclear power plant influences both, the plant operational efficiency and the general safety issues. This paper describes an experimental system developed by the authors which aims to assist the operators of nuclear power plants to take quick and safe decisions. The system maps the status of plant and helps the operators to make quick judgments by using artificial intelligence methods. The method makes use of a small set of monitored variables and presents a map of the plant status in a friendly manner. This system uses an architecture that has multiple self-organizing maps to perform these tasks. (author)

  16. Intelligent Control Framework for the Feeding System in the Biomass Power Plant

    Directory of Open Access Journals (Sweden)

    Sun Jin

    2015-01-01

    Full Text Available This paper proposes an intelligent control framework for biomass drying process with flue gases based on FLC (fuzzy logic controller and CAN (Controller Area Network bus. In the operation of a biomass drying process, in order to get the biomass with the set-point low moisture content dried by waste high temperature flue gases, it is necessary to intelligent control for the biomass flow rate. Use of an experiment with varied materials at different initial moisture contents enables acquisition of the biomass flow rates as initial setting values. Set the error between actual straw moisture content and set-point, and rate of change of error as two inputs. the biomass flow rate can be acquired by the fuzzy logic computing as the output. Since the length of dryer is more than twenty meters, the integration by the CAN bus can ensure real-time reliable data acquisition and processing. The control framework for biomass drying process can be applied to a variety of biomass, such as, cotton stalk, corn stalk, rice straw, wheat straw, sugar cane. It has strong potential for practical applications because of its advantages on intelligent providing the set-point low moisture content of biomass feedstock for power generation equipment.

  17. Research on intelligent monitor for 3D power distribution of reactor core

    International Nuclear Information System (INIS)

    Xia, Hong; Li, Bin; Liu, Jianxin

    2014-01-01

    Highlights: • Core power distribution of ex-core measurement system has been reconstructed. • Building up an artificial intelligence model for 3-D core power distribution. • Error of the experiments has been reduced to 0.76%. • Methods for improving the accuracy of the model have been obtained. - Abstract: A real-time monitor for 3D reactor power distribution is critical for nuclear safety and high efficiency of NPP’s operation as well as for optimizing the control system, especially when the nuclear power plant (NPP) works at a certain power level or it works in load following operation. This paper was based on analyzing the monitor for 3D reactor power distribution technologies used in modern NPPs. Furthermore, considering the latest research outcomes, the paper proposed a method based on using an ex-core neutron detector system and a neural network to set up a real time monitor system for reactor’s 3D power distribution supervision. The results of the experiments performed on a reactor simulation machine illustrated that the new monitor system worked very well for a certain burn-up range during the fuel cycle. In addition, this new model could reduce the errors associated with the fitting of the distribution effectively, and several optimization methods were also obtained to improve the accuracy of the simulation model

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

    Science.gov (United States)

    Mohamed, Ahmed

    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

  19. The development of advanced robotic technology. A study on the tele-existence and intelligent control of a robot system for nuclear power plants

    Energy Technology Data Exchange (ETDEWEB)

    Chung, Myung Jin; Byun, Jueng Nam; Kim, Jong Hwan; Lee, Ju Jang; Bang, Seok Won; Chu, Gil Hwan; Park, Jong Cheol; Choi, Jong Seok; Yang, Jung Min; Hong, Sun Ki [Korea Advanced Institute of Science and Technology, Taejon (Korea, Republic of)

    1995-07-01

    To increase the efficiency of human intelligence it is required to develop an intelligent monitoring and system. In this research, we develop intelligent control methods related with tele-operation, tele-existence, real-time control technique, and intelligent control technique. Those are key techniques in tele-operation, especially for the repair and maintenance of nuclear power plants. The objective of this project is to develop of the tele-existence and intelligent control system for a robot used in the nuclear power plants. (author). 20 refs.

  20. Overview of Intelligent Power Controller Development for Human Deep Space Exploration

    Science.gov (United States)

    Soeder, James F.; Dever, Timothy P.; McNelis, Anne M.; Beach, Raymond F.; Trase, Larry M.; May, Ryan D.

    2014-01-01

    Intelligent or autonomous control of an entire spacecraft is a major technology that must be developed to enable NASA to meet its human exploration goals. NASA's current long term human space platform, the International Space Station, is in low Earth orbit with almost continuous communication with the ground based mission control. This permits the near real-time control by the ground of all of the core systems including power. As NASA moves beyond low Earth orbit, the issues of communication time-lag and lack of communication bandwidth beyond geosynchronous orbit does not permit this type of operation. This paper presents the work currently ongoing at NASA to develop an architecture for an autonomous power control system as well as the effort to assemble that controller into the framework of the vehicle mission manager and other subsystem controllers to enable autonomous control of the complete spacecraft. Due to the common problems faced in both space power systems and terrestrial power system, the potential for spin-off applications of this technology for use in micro-grids located at the edge or user end of terrestrial power grids for peak power accommodation and reliability are described.

  1. Integration of artificial intelligence systems for nuclear power plant surveillance and diagnostics

    International Nuclear Information System (INIS)

    Uhrig, R.E.; Hines, J.W.; Nelson, W.R.

    1998-01-01

    The objective of this program is to design, construct, operate, test, and evaluate a prototype integrated monitoring and diagnostic system for a nuclear power plant. It is anticipated that this technology will have wide application to other complex systems (e.g., fossil power plants, chemical processing plants, and possibly air traffic control systems). Over the past decade, the University of Tennessee (UT) and others have carried out many projects utilizing various methodologies of artificial intelligence (expert systems, neural networks, fuzzy systems, and genetic algorithms) to enhance the performance (safety, efficiency, reliability, and availability) of nuclear power plants. Investigations and studies have included a) instrumentation surveillance and calibration validation, b) inferential sensing to calibration of feedwater venturi flow during fouling, c) thermodynamic performance modeling with iterative improvement of plant beat rate, d) diagnosis of nuclear power plant transients, and e) increase in thermal power through monitoring of DNBR (Departure from Nucleate Boiling Regime). To increase the likelihood of these individual systems being used in a nuclear power plant, they must be integrated into a single system that operates virtually autonomously, collecting, interpreting, and providing information to the operators in a simple and understandable format. (author)

  2. Intelligent Control of UPFC for Enhancing Transient Stability on Multi-Machine Power Systems

    Directory of Open Access Journals (Sweden)

    Hassan Barati

    2010-01-01

    Full Text Available One of the benefit of FACTS devices is increase of stability in power systems with control active and reactive power at during the fault in power system. Although, the power system stabilizers (PSSs have been one of the most common controls used to damp out oscillations, this device may not produce enough damping especially to inter-area mode and therefore, there is an increasing interest in using FACTS devices to aid in damping of these oscillations. In This paper, UPFC is used for damping oscillations and to enhance the transient stability performance of power systems. The controller parameters are designed using an efficient version of the Takagi-Sugeno fuzzy control scheme. The function based Takagi-Sugeno-Kang (TSK fuzzy controller uses. For optimization parameters of fuzzy PI controller, the GA, PSO and HGAPSO algorithms are used. The computer simulation results, the effect of UPFC with conventional PI controller, fuzzy PI controller and intelligent controllers (GA, PSO and HGAPSO for damping the local-mode and inter-area mode of under large and small disturbances in the four-machine two-area power system evaluated and compared.

  3. Integration of artificial intelligence systems for nuclear power plant surveillance and diagnostics

    Energy Technology Data Exchange (ETDEWEB)

    Uhrig, R.E.; Hines, J.W.; Nelson, W.R.

    1998-07-01

    The objective of this program is to design, construct, operate, test, and evaluate a prototype integrated monitoring and diagnostic system for a nuclear power plant. It is anticipated that this technology will have wide application to other complex systems (e.g., fossil power plants, chemical processing plants, and possibly air traffic control systems). Over the past decade, the University of Tennessee (UT) and others have carried out many projects utilizing various methodologies of artificial intelligence (expert systems, neural networks, fuzzy systems, and genetic algorithms) to enhance the performance (safety, efficiency, reliability, and availability) of nuclear power plants. Investigations and studies have included a) instrumentation surveillance and calibration validation, b) inferential sensing to calibration of feedwater venturi flow during fouling, c) thermodynamic performance modeling with iterative improvement of plant beat rate, d) diagnosis of nuclear power plant transients, and e) increase in thermal power through monitoring of DNBR (Departure from Nucleate Boiling Regime). To increase the likelihood of these individual systems being used in a nuclear power plant, they must be integrated into a single system that operates virtually autonomously, collecting, interpreting, and providing information to the operators in a simple and understandable format. (author)

  4. Design of intelligent comfort control system with human learning and minimum power control strategies

    International Nuclear Information System (INIS)

    Liang, J.; Du, R.

    2008-01-01

    This paper presents the design of an intelligent comfort control system by combining the human learning and minimum power control strategies for the heating, ventilating and air conditioning (HVAC) system. In the system, the predicted mean vote (PMV) is adopted as the control objective to improve indoor comfort level by considering six comfort related variables, whilst a direct neural network controller is designed to overcome the nonlinear feature of the PMV calculation for better performance. To achieve the highest comfort level for the specific user, a human learning strategy is designed to tune the user's comfort zone, and then, a VAV and minimum power control strategy is proposed to minimize the energy consumption further. In order to validate the system design, a series of computer simulations are performed based on a derived HVAC and thermal space model. The simulation results confirm the design of the intelligent comfort control system. In comparison to the conventional temperature controller, this system can provide a higher comfort level and better system performance, so it has great potential for HVAC applications in the future

  5. SIMON [Semi-Intelligent Mobile Observing Navigator] combines radiation hardness with computer power

    International Nuclear Information System (INIS)

    Weber, P.J.; Vanecek, C.W.

    1990-01-01

    SIMON - the Semi-Intelligent Mobile Observing Navigator - has been under development at the US Department of Energy's (DoE's) Savannah River Laboratory for four years. The robot's on-board intelligence units are designed to be radiation-resistant, making it able to function for extended periods within a remotely operated facility. In its current form, SIMON is being developed by the laboratory's Robotics Group for use in the site's production reactors, but it can be adapted for use in any nuclear facility, including commercial reactors. The challenge for Savannah River Laboratory engineers was to eliminate the need for human inspection of certain components. To do this, they designed a robot that could do three things for reactor operators: measure radiation; measure temperature; and provide televised views inside the reactor facility. To be useful, the robot has to be extremely mobile, and its components had to be able to survive months without maintenance in the radiation, temperature and humidity encountered in nuclear facilities. The robot also had to be cost-effective. (author)

  6. Neuromechanical adaptations during a robotic powered exoskeleton assisted walking session.

    Science.gov (United States)

    Ramanujam, Arvind; Cirnigliaro, Christopher M; Garbarini, Erica; Asselin, Pierre; Pilkar, Rakesh; Forrest, Gail F

    2017-04-20

    To evaluate gait parameters and neuromuscular profiles of exoskeleton-assisted walking under Max Assist condition during a single-session for; (i) able bodied (AB) individuals walking assisted with (EXO) and without (non-EXO) a powered exoskeleton, (ii) non-ambulatory SCI individuals walking assisted with a powered exoskeleton. Single-session. Motion analysis laboratory. Four AB individuals and four individuals with SCI. Powered lower extremity exoskeleton. Temporal-spatial parameters, kinematics, walking velocity and electromyography data. AB individuals in exoskeleton showed greater stance time and a significant reduction in walking velocity (P exoskeleton movements, they walked with an increased velocity and lowered stance time to resemble that of slow walking. For SCI individuals, mean percent stance time was higher and walking velocity was lower compared to all AB walking conditions (P exoskeleton and moreover with voluntary control there is a greater temporal-spatial response of the lower limbs. Also, there are neuromuscular phasic adaptions for both AB and SCI groups while walking in the exoskeleton that are inconsistent to non-EXO gait muscle activation.

  7. Discrete rate and variable power adaptation for underlay cognitive networks

    KAUST Repository

    Abdallah, Mohamed M.

    2010-01-01

    We consider the problem of maximizing the average spectral efficiency of a secondary link in underlay cognitive networks. In particular, we consider the network setting whereby the secondary transmitter employs discrete rate and variable power adaptation under the constraints of maximum average transmit power and maximum average interference power allowed at the primary receiver due to the existence of an interference link between the secondary transmitter and the primary receiver. We first find the optimal discrete rates assuming a predetermined partitioning of the signal-to-noise ratio (SNR) of both the secondary and interference links. We then present an iterative algorithm for finding a suboptimal partitioning of the SNR of the interference link assuming a fixed partitioning of the SNR of secondary link selected for the case where no interference link exists. Our numerical results show that the average spectral efficiency attained by using the iterative algorithm is close to that achieved by the computationally extensive exhaustive search method for the case of Rayleigh fading channels. In addition, our simulations show that selecting the optimal partitioning of the SNR of the secondary link assuming no interference link exists still achieves the maximum average spectral efficiency for the case where the average interference constraint is considered. © 2010 IEEE.

  8. The Import-Substitution Adaptation of Power Engineering Programs

    Directory of Open Access Journals (Sweden)

    Aleksandr N. Kuzminov

    2017-03-01

    Full Text Available The realization problem of the import substitution policy in the context of existing programs for the individual branches development is considered in the paper on the example of power engineering. There is a contradiction to the objective of programs reflected in the process of alignment, which consists in stabilizing on the one hand and on the development of innovative on the other hand. In addition, the analysis of the implementation of power engineering of the Russian Federation for 2010-2020 and up to 2030 revealed significant shortcomings and deficiencies that reinforce the negative trends of this pairing. Classification of problems and purpose allowed choosing the most significant conceptual directions, methodologically based on the ideas of self-organization and balance, which can get instrumentality software by adapting programs for the development of power engineering in the system of the European model of Industry 4.0. As a fundamental position addresses the need for such a project, which would ensure the greatest impact with limited resources, including public funding, which lags far behind foreign. It is proposed to transform the efforts to implement the existing strategies of industry development in view of the policy of import substitution based on the implementation of the program of production of a balanced range of innovative products and providing replacement of imported equipment and the formation of the technological basis for the development of the industry

  9. Development of intelligent database program for PSI/ISI data management of nuclear power plant

    International Nuclear Information System (INIS)

    Um, Byong Guk; Park, Un Su; Park, Ik Keun; Park, Yun Won; Kang, Suk Chul

    1998-01-01

    An intelligent database program has been developed under fully compatible with windows 95 for the construction of total support system and the effective management of Pre-/In-Service Inspection data. Using the database program, it can be executed the analysis and multi-dimensional evaluation of the defects detected during PSI/ISI in the pipe and the pressure vessel of the nuclear power plants. And also it can be used to investigate the NDE data inspected repetitively and the contents of treatment, and to offer the fundamental data for application of evaluation data related to Fracture Mechanics Analysis(FMA). Furthermore, the PSI/ISI database loads and material properties can be utilized to secure the higher degree of safety, integrity, reliability, and life-prediction of components and systems in nuclear power plant.

  10. Proposition of a scheme for adaptive/intelligent analog-to-digital converters

    International Nuclear Information System (INIS)

    Vaidya, P.P.; Kataria, S.K.

    2001-01-01

    The paper proposes design of a new class of Analog to Digital Converters (ADC's) which we call as Intelligent ADC's with moving resolution. Unlike presently available ADC's which are designed for specific range of applications and give fixed resolution and conversion time, the intelligent ADC's described here can adjust their resolution during the process of conversion, depending upon nature of input signal to make optimum use of the hard-ware. It is possible to use an intelligent ADC to give resolution ranging from 8 bit to 16 bit and conversion time ranging from few nano sec. to few micro secs. These ADC's have significant advantages over conventional ones when used for nuclear pulse spectroscopy as well as for process control applications. (author)

  11. Dynamic assessment of intelligence is a better reply to adaptive behavior and cognitive plasticity.

    Science.gov (United States)

    Fabio, Rosa Angela

    2005-01-01

    In the present study, the author conducted 3 experiments to examine the dynamic testing of potential intelligence. She investigated the relationship between dynamic measures and other factors such as (a) static measures of intelligence (Raven's Colored Progressive Matrices Test [J. C. Raven, J. H. Court, & J. Raven, 1979] and the D48 [J. D. Black, 1961]) and (b) codifying speed, codifying accuracy, and school performance. The participants were kindergarten children (n = 150), primary school children (n = 287), and teenaged students (n = 198) who were all trained to master problem solving tests with dynamic measures of intelligence. The results showed that dynamic measures predict more accurately the relationships of codifying speed, codifying accuracy, and school performance.

  12. A Fuzzy ANP Model Integrated with Benefits, Opportunities, Costs, and Risks to Prioritize Intelligent Power Grid Systems

    Directory of Open Access Journals (Sweden)

    Hsing Hung Chen

    2013-01-01

    Full Text Available Although growth of renewable energy is envisaged, many concerns are critical like the ability to maintain the balance between demands and supply and the variability, noncontrollability, and flexibility of the sources. Then, what will be the future concerns about the main composition of intelligent power grid systems in the future? There is no such research tackled before. Thus, this paper first finds critical success criteria of intelligent power grid systems and then constructs a multiple criteria and decision making model to help in identifying the suitable trends under complex economic performance, environmental impacts, and rapid technological and marketing changes. After empirical demonstration, the paper summarizes that the most suitable composition of future intelligent power grid systems should be constituted by “DHT” P2P grid, “C&D workflow” P2P scheduling, “GARCM” trustworthy P2P grid, and “multipurpose” grid applications in the future.

  13. Intelligent Monitoring System with High Temperature Distributed Fiberoptic Sensor for Power Plant Combustion Processes

    Energy Technology Data Exchange (ETDEWEB)

    Kwang Y. Lee; Stuart S. Yin; Andre Boehman

    2006-09-26

    The objective of the proposed work is to develop an intelligent distributed fiber optical sensor system for real-time monitoring of high temperature in a boiler furnace in power plants. Of particular interest is the estimation of spatial and temporal distributions of high temperatures within a boiler furnace, which will be essential in assessing and controlling the mechanisms that form and remove pollutants at the source, such as NOx. The basic approach in developing the proposed sensor system is three fold: (1) development of high temperature distributed fiber optical sensor capable of measuring temperatures greater than 2000 C degree with spatial resolution of less than 1 cm; (2) development of distributed parameter system (DPS) models to map the three-dimensional (3D) temperature distribution for the furnace; and (3) development of an intelligent monitoring system for real-time monitoring of the 3D boiler temperature distribution. Under Task 1, we have set up a dedicated high power, ultrafast laser system for fabricating in-fiber gratings in harsh environment optical fibers, successfully fabricated gratings in single crystal sapphire fibers by the high power laser system, and developed highly sensitive long period gratings (lpg) by electric arc. Under Task 2, relevant mathematical modeling studies of NOx formation in practical combustors have been completed. Studies show that in boiler systems with no swirl, the distributed temperature sensor may provide information sufficient to predict trends of NOx at the boiler exit. Under Task 3, we have investigated a mathematical approach to extrapolation of the temperature distribution within a power plant boiler facility, using a combination of a modified neural network architecture and semigroup theory. Given a set of empirical data with no analytic expression, we first developed an analytic description and then extended that model along a single axis.

  14. Robust Adaptive Reactive Power Control for Doubly Fed Induction Generator

    Directory of Open Access Journals (Sweden)

    Huabin Wen

    2014-01-01

    Full Text Available The problem of reactive power control for mains-side inverter (MSI in doubly fed induction generator (DFIG is studied in this paper. To accommodate the modelling nonlinearities and inherent uncertainties, a novel robust adaptive control algorithm for MSI is proposed by utilizing Lyapunov theory that ensures asymptotic stability of the system under unpredictable external disturbances and significant parametric uncertainties. The distinguishing benefit of the aforementioned scheme consists in its capabilities to maintain satisfactory performance under varying operation conditions without the need for manually redesigning or reprogramming the control gains in contrast to the commonly used PI/PID control. Simulations are also built to confirm the correctness and benefits of the control scheme.

  15. Adaptive metal mirror for high-power CO2 lasers

    Science.gov (United States)

    Jarosch, Uwe-Klaus

    1996-08-01

    Spherical mirrors with a variable radius of curvature are used inside laser resonators as well as in the beam path between the laser and the workpiece. Commercially-available systems use piezoelectric actuators, or the pressure of the coolant, to deform the mirror surface. In both cases, the actuator and the cooling system influence each other. This interaction is avoided through the integration of the cooling system with the flexible mirror membrane. A multi- channel design leads to an optimized cooling effect, which is necessary for high power applications. The contour of the variable metal mirror depends on the mounting between the membrane and the mirror body and on the distribution of forces. Four cases of deformation can be distinguished for a circular elastic membrane. The realization of an adaptive metal mirror requires a technical compromise to be made. A mechanical construction is presented which combines an elastic hinge with the inlet and outlet of the coolant. For the deformation of the mirror membranes two actuators with different character of deformation are used. The superposition of the two deformations results in smaller deviations from the spherical surface shape than can be achieved using a single actuator. DC proportional magnets have been introduced as cheap and rigid actuators. The use of this adaptive mirror, either in a low pressure atmosphere of a gas laser resonator, or in an extra-cavity beam path is made possible through the use of a ventilation system.

  16. Intelligent Hybrid Vehicle Power Control - Part 1: Machine Learning of Optimal Vehicle Power

    Science.gov (United States)

    2012-06-30

    the motor or both can provide the traction power to the drivetrain. During vehicle deceleration, the regenerative braking power is captured to charge...and Amax is the maximum acceleration. The 11 drive cycles are divided into four categories of roadway types and traffic congestion levels, freeway...freeway ramp, arterial, and local. Two of the categories , freeway and arterial, are further divided into subcategories based on a qualitative measure

  17. Real time Intelligent Control Laboratory (RT-ICL) of PowerLabDK for smart grid technology development

    DEFF Research Database (Denmark)

    Ostergaard, Jacob; Wu, Qiuwei; Garcia-Valle, Rodrigo

    2012-01-01

    This paper presents the Intelligent Control Laboratory (ICL) of the PowerLabDK and describes examples of ongoing research work utilizing the ICL. The ICL is comprised of a real time digital simulator (RTDS) with 5 racks, a full scale SCADA system and experimental control room with a link to the B......This paper presents the Intelligent Control Laboratory (ICL) of the PowerLabDK and describes examples of ongoing research work utilizing the ICL. The ICL is comprised of a real time digital simulator (RTDS) with 5 racks, a full scale SCADA system and experimental control room with a link...

  18. Reliability, construct and criterion-related validity of the Serbian adaptation of the trait emotional intelligence questionnaire (TEIQue

    Directory of Open Access Journals (Sweden)

    Jolić-Marjanović Zorana

    2014-01-01

    Full Text Available This paper presents evidence on the reliability and validity of the Serbian adaptation of the Trait Emotional Intelligence Questionnaire (TEIQue, an instrument designed to comprehensively assess emotional intelligence conceived as a constellation of emotionrelated self-perceptions. Study participants were 254 adults, who completed the Serbian TEIQue, NEO-FFI, MSCEIT, EQ-short, and RSPWB. The results indicate that the adapted TEIQue is a psychometrically sound assessment tool: internal consistencies were mostly acceptable at facet, generally good at factor, and excellent at whole-scale level; the fourfactor structure was confirmed by means of CFA; convergent-discriminant validity was established through meaningful associations with related constructs, indicating that trait EI is closely aligned with affect and self-efficacy related constructs from the realm of personality (i.e., E, N, C, and Empathy, but shows only moderate overlap with ability EI; finally, incremental validity was demonstrated in the prediction of psychological wellbeing, over and above the Big Five. [Projekat Ministarstva nauke Republike Srbije, br. 179018

  19. Optimal reactive power and voltage control in distribution networks with distributed generators by fuzzy adaptive hybrid particle swarm optimisation method

    DEFF Research Database (Denmark)

    Chen, Shuheng; Hu, Weihao; Su, Chi

    2015-01-01

    A new and efficient methodology for optimal reactive power and voltage control of distribution networks with distributed generators based on fuzzy adaptive hybrid PSO (FAHPSO) is proposed. The objective is to minimize comprehensive cost, consisting of power loss and operation cost of transformers...... that the proposed method can search a more promising control schedule of all transformers, all capacitors and all distributed generators with less time consumption, compared with other listed artificial intelligent methods....... algorithm is implemented in VC++ 6.0 program language and the corresponding numerical experiments are finished on the modified version of the IEEE 33-node distribution system with two newly installed distributed generators and eight newly installed capacitors banks. The numerical results prove...

  20. The Lateral Tracking Control for the Intelligent Vehicle Based on Adaptive PID Neural Network.

    Science.gov (United States)

    Han, Gaining; Fu, Weiping; Wang, Wen; Wu, Zongsheng

    2017-05-30

    The intelligent vehicle is a complicated nonlinear system, and the design of a path tracking controller is one of the key technologies in intelligent vehicle research. This paper mainly designs a lateral control dynamic model of the intelligent vehicle, which is used for lateral tracking control. Firstly, the vehicle dynamics model (i.e., transfer function) is established according to the vehicle parameters. Secondly, according to the vehicle steering control system and the CARMA (Controlled Auto-Regression and Moving-Average) model, a second-order control system model is built. Using forgetting factor recursive least square estimation (FFRLS), the system parameters are identified. Finally, a neural network PID (Proportion Integral Derivative) controller is established for lateral path tracking control based on the vehicle model and the steering system model. Experimental simulation results show that the proposed model and algorithm have the high real-time and robustness in path tracing control. This provides a certain theoretical basis for intelligent vehicle autonomous navigation tracking control, and lays the foundation for the vertical and lateral coupling control.

  1. The Lateral Tracking Control for the Intelligent Vehicle Based on Adaptive PID Neural Network

    Directory of Open Access Journals (Sweden)

    Gaining Han

    2017-05-01

    Full Text Available The intelligent vehicle is a complicated nonlinear system, and the design of a path tracking controller is one of the key technologies in intelligent vehicle research. This paper mainly designs a lateral control dynamic model of the intelligent vehicle, which is used for lateral tracking control. Firstly, the vehicle dynamics model (i.e., transfer function is established according to the vehicle parameters. Secondly, according to the vehicle steering control system and the CARMA (Controlled Auto-Regression and Moving-Average model, a second-order control system model is built. Using forgetting factor recursive least square estimation (FFRLS, the system parameters are identified. Finally, a neural network PID (Proportion Integral Derivative controller is established for lateral path tracking control based on the vehicle model and the steering system model. Experimental simulation results show that the proposed model and algorithm have the high real-time and robustness in path tracing control. This provides a certain theoretical basis for intelligent vehicle autonomous navigation tracking control, and lays the foundation for the vertical and lateral coupling control.

  2. Cross-Cultural Adaptation of the Intelligibility in Context Scale for South Africa

    Science.gov (United States)

    Pascoe, Michelle; McLeod, Sharynne

    2016-01-01

    The Intelligibility in Context Scale (ICS) is a screening questionnaire that focuses on parents' perceptions of children's speech in different contexts. Originally developed in English, it has been translated into 60 languages and the validity and clinical utility of the scale has been documented in a range of countries. In South Africa, there are…

  3. Intelligent Modeling Combining Adaptive Neuro Fuzzy Inference System and Genetic Algorithm for Optimizing Welding Process Parameters

    Science.gov (United States)

    Gowtham, K. N.; Vasudevan, M.; Maduraimuthu, V.; Jayakumar, T.

    2011-04-01

    Modified 9Cr-1Mo ferritic steel is used as a structural material for steam generator components of power plants. Generally, tungsten inert gas (TIG) welding is preferred for welding of these steels in which the depth of penetration achievable during autogenous welding is limited. Therefore, activated flux TIG (A-TIG) welding, a novel welding technique, has been developed in-house to increase the depth of penetration. In modified 9Cr-1Mo steel joints produced by the A-TIG welding process, weld bead width, depth of penetration, and heat-affected zone (HAZ) width play an important role in determining the mechanical properties as well as the performance of the weld joints during service. To obtain the desired weld bead geometry and HAZ width, it becomes important to set the welding process parameters. In this work, adaptative neuro fuzzy inference system is used to develop independent models correlating the welding process parameters like current, voltage, and torch speed with weld bead shape parameters like depth of penetration, bead width, and HAZ width. Then a genetic algorithm is employed to determine the optimum A-TIG welding process parameters to obtain the desired weld bead shape parameters and HAZ width.

  4. Robust data reconciliation and outlier detection with swarm intelligence in a thermal reactor power calculation

    Energy Technology Data Exchange (ETDEWEB)

    Valdetaro, Eduardo Damianik, E-mail: valdtar@eletronuclear.gov.br [ELETRONUCLEAR - ELETROBRAS, Angra dos Reis, RJ (Brazil). Angra 2 Operating Dept.; Coordenacao dos Programas de Pos-Graduacao de Engenharia (PEN/COPPE/UFRJ), RJ (Brazil). Programa de Engenharia Nuclear; Schirru, Roberto, E-mail: schirru@lmp.ufrj.br [Coordenacao dos Programas de Pos-Graduacao de Engenharia (PEN/COPPE/UFRJ), RJ (Brazil). Programa de Engenharia Nuclear

    2011-07-01

    In Nuclear power plants, Data Reconciliation (DR) and Gross Errors Detection (GED) are techniques of increasing interest and are primarily used to keep mass and energy balance into account, which brings outcomes as a direct and indirect financial benefits. Data reconciliation is formulated by a constrained minimization problem, where the constraints correspond to energy and mass balance model. Statistical methods are used combined with the minimization of quadratic error form. Solving nonlinear optimization problem using conventional methods can be troublesome, because a multimodal function with differentiated solutions introduces some difficulties to search an optimal solution. Many techniques were developed to solve Data Reconciliation and Outlier Detection, some of them use, for example, Quadratic Programming, Lagrange Multipliers, Mixed-Integer Non Linear Programming and others use evolutionary algorithms like Genetic Algorithms (GA) and recently the use of the Particle Swarm Optimization (PSO) showed to be a potential tool as a global optimization algorithm when applied to data reconciliation. Robust Statistics is also increasing in interest and it is being used when measured data are contaminated by random errors and one can not assume the error is normally distributed, situation which reflects real problems situation. The aim of this work is to present a brief comparison between the classical data reconciliation technique and the robust data reconciliation and gross error detection with swarm intelligence procedure in calculating the thermal reactor power for a simplified heat circuit diagram of a steam turbine plant using real data obtained from Angra 2 Nuclear power plant. The main objective is to test the potential of the robust DR and GED method in a integrated framework using swarm intelligence and the three part redescending estimator of Hampel when applied to a real process condition. The results evaluate the potential use of the robust technique in

  5. Robust data reconciliation and outlier detection with swarm intelligence in a thermal reactor power calculation

    International Nuclear Information System (INIS)

    Valdetaro, Eduardo Damianik; Coordenacao dos Programas de Pos-Graduacao de Engenharia; Schirru, Roberto

    2011-01-01

    In Nuclear power plants, Data Reconciliation (DR) and Gross Errors Detection (GED) are techniques of increasing interest and are primarily used to keep mass and energy balance into account, which brings outcomes as a direct and indirect financial benefits. Data reconciliation is formulated by a constrained minimization problem, where the constraints correspond to energy and mass balance model. Statistical methods are used combined with the minimization of quadratic error form. Solving nonlinear optimization problem using conventional methods can be troublesome, because a multimodal function with differentiated solutions introduces some difficulties to search an optimal solution. Many techniques were developed to solve Data Reconciliation and Outlier Detection, some of them use, for example, Quadratic Programming, Lagrange Multipliers, Mixed-Integer Non Linear Programming and others use evolutionary algorithms like Genetic Algorithms (GA) and recently the use of the Particle Swarm Optimization (PSO) showed to be a potential tool as a global optimization algorithm when applied to data reconciliation. Robust Statistics is also increasing in interest and it is being used when measured data are contaminated by random errors and one can not assume the error is normally distributed, situation which reflects real problems situation. The aim of this work is to present a brief comparison between the classical data reconciliation technique and the robust data reconciliation and gross error detection with swarm intelligence procedure in calculating the thermal reactor power for a simplified heat circuit diagram of a steam turbine plant using real data obtained from Angra 2 Nuclear power plant. The main objective is to test the potential of the robust DR and GED method in a integrated framework using swarm intelligence and the three part redescending estimator of Hampel when applied to a real process condition. The results evaluate the potential use of the robust technique in

  6. Durham Zoo: Powering a Search-&-Innovation Engine with Collective Intelligence

    Directory of Open Access Journals (Sweden)

    Richard Absalom

    2015-02-01

    Full Text Available Purpose – Durham Zoo (hereinafter – DZ is a project to design and operate a concept search engine for science and technology. In DZ, a concept includes a solution to a problem in a particular context.Design – Concept searching is rendered complex by the fuzzy nature of a concept, the many possible implementations of the same concept, and the many more ways that the many implementations can be expressed in natural language. An additional complexity is the diversity of languages and formats, in which the concepts can be disclosed.Humans understand language, inference, implication and abstraction and, hence, concepts much better than computers, that in turn are much better at storing and processing vast amounts of data.We are 7 billion on the planet and we have the Internet as the backbone for Collective Intelligence. So, our concept search engine uses humans to store concepts via a shorthand that can be stored, processed and searched by computers: so, humans IN and computers OUT.The shorthand is classification: metadata in a structure that can define the content of a disclosure. The classification is designed to be powerful in terms of defining and searching concepts, whilst suited to a crowdsourcing effort. It is simple and intuitive to use. Most importantly, it is adapted to restrict ambiguity, which is the poison of classification, without imposing a restrictive centralised management.In the classification scheme, each entity is shown together in a graphical representation with related entities. The entities are arranged on a sliding scale of similarity. This sliding scale is effectively fuzzy classification.Findings – The authors of the paper have been developing a first classification scheme for the technology of traffic cones, this in preparation for a trial of a working system. The process has enabled the authors to further explore the practicalities of concept classification. The CmapTools knowledge modelling kit to develop the

  7. Indirect adaptive soft computing based wavelet-embedded control paradigms for WT/PV/SOFC in a grid/charging station connected hybrid power system.

    Directory of Open Access Journals (Sweden)

    Sidra Mumtaz

    Full Text Available This paper focuses on the indirect adaptive tracking control of renewable energy sources in a grid-connected hybrid power system. The renewable energy systems have low efficiency and intermittent nature due to unpredictable meteorological conditions. The domestic load and the conventional charging stations behave in an uncertain manner. To operate the renewable energy sources efficiently for harvesting maximum power, instantaneous nonlinear dynamics should be captured online. A Chebyshev-wavelet embedded NeuroFuzzy indirect adaptive MPPT (maximum power point tracking control paradigm is proposed for variable speed wind turbine-permanent synchronous generator (VSWT-PMSG. A Hermite-wavelet incorporated NeuroFuzzy indirect adaptive MPPT control strategy for photovoltaic (PV system to extract maximum power and indirect adaptive tracking control scheme for Solid Oxide Fuel Cell (SOFC is developed. A comprehensive simulation test-bed for a grid-connected hybrid power system is developed in Matlab/Simulink. The robustness of the suggested indirect adaptive control paradigms are evaluated through simulation results in a grid-connected hybrid power system test-bed by comparison with conventional and intelligent control techniques. The simulation results validate the effectiveness of the proposed control paradigms.

  8. Indirect adaptive soft computing based wavelet-embedded control paradigms for WT/PV/SOFC in a grid/charging station connected hybrid power system.

    Science.gov (United States)

    Mumtaz, Sidra; Khan, Laiq; Ahmed, Saghir; Bader, Rabiah

    2017-01-01

    This paper focuses on the indirect adaptive tracking control of renewable energy sources in a grid-connected hybrid power system. The renewable energy systems have low efficiency and intermittent nature due to unpredictable meteorological conditions. The domestic load and the conventional charging stations behave in an uncertain manner. To operate the renewable energy sources efficiently for harvesting maximum power, instantaneous nonlinear dynamics should be captured online. A Chebyshev-wavelet embedded NeuroFuzzy indirect adaptive MPPT (maximum power point tracking) control paradigm is proposed for variable speed wind turbine-permanent synchronous generator (VSWT-PMSG). A Hermite-wavelet incorporated NeuroFuzzy indirect adaptive MPPT control strategy for photovoltaic (PV) system to extract maximum power and indirect adaptive tracking control scheme for Solid Oxide Fuel Cell (SOFC) is developed. A comprehensive simulation test-bed for a grid-connected hybrid power system is developed in Matlab/Simulink. The robustness of the suggested indirect adaptive control paradigms are evaluated through simulation results in a grid-connected hybrid power system test-bed by comparison with conventional and intelligent control techniques. The simulation results validate the effectiveness of the proposed control paradigms.

  9. Indirect adaptive soft computing based wavelet-embedded control paradigms for WT/PV/SOFC in a grid/charging station connected hybrid power system

    Science.gov (United States)

    Khan, Laiq; Ahmed, Saghir; Bader, Rabiah

    2017-01-01

    This paper focuses on the indirect adaptive tracking control of renewable energy sources in a grid-connected hybrid power system. The renewable energy systems have low efficiency and intermittent nature due to unpredictable meteorological conditions. The domestic load and the conventional charging stations behave in an uncertain manner. To operate the renewable energy sources efficiently for harvesting maximum power, instantaneous nonlinear dynamics should be captured online. A Chebyshev-wavelet embedded NeuroFuzzy indirect adaptive MPPT (maximum power point tracking) control paradigm is proposed for variable speed wind turbine-permanent synchronous generator (VSWT-PMSG). A Hermite-wavelet incorporated NeuroFuzzy indirect adaptive MPPT control strategy for photovoltaic (PV) system to extract maximum power and indirect adaptive tracking control scheme for Solid Oxide Fuel Cell (SOFC) is developed. A comprehensive simulation test-bed for a grid-connected hybrid power system is developed in Matlab/Simulink. The robustness of the suggested indirect adaptive control paradigms are evaluated through simulation results in a grid-connected hybrid power system test-bed by comparison with conventional and intelligent control techniques. The simulation results validate the effectiveness of the proposed control paradigms. PMID:28877191

  10. Development of Intelligent Database Program for PSI/ISI Data Management of Nuclear Power Plant

    International Nuclear Information System (INIS)

    Park, Un Su; Park, Ik Keun; Um, Byong Guk; Park, Yun Won; Kang, Suk Chul

    1998-01-01

    For an effective and efficient management of large amounts of preservice/inservice inspection(PSI/ISI) data in nuclear power plants, an intelligent Windows 95-based data management program was developed. This program enables the prompt extraction of previously conducted PSI/ISI conditions and results so that the time-consuming data management, painstaking data processing and analysis in the past are avoided. The program extracts, and the associated remedies. Furthermore, additional inspection data and comments can be easily added or deleted for subsequent PSI/ISI operation. Although the initial version of the program was applied to Kori nuclear power plant, this program can be equally applied to other nuclear power plant. And also this program can be used to offer the fundamental data for application of evaluation data related to fracture mechanics analysis(FMA), probabilistic reliability assessment(PRA) of PSI/ISI results, performance demonstration initiative(PDI) and risk-informed ISI based on probability of detection(POD) information of ultrasonic examination. Besides, the program can be further developed as a unique PSI/ISI data management expert system that can be apart of PSI/ISI data management expert system that can be a part of PSI/ISI Total Support System(TSS) for Korean nuclear power plants

  11. Long Term Analysis of Adaptive Low-Power Instrument Platform Power and Battery Performance

    Science.gov (United States)

    Edwards, T.; Bowman, J. R.; Clauer, C. R.

    2017-12-01

    Operation of the Autonomous Adaptive Low-Power Instrument Platform (AAL-PIP) by the Magnetosphere-Ionosphere Science Team (MIST) at Virginia Tech has been ongoing for about 10 years. These instrument platforms are deployed on the East Antarctic Plateau in remote locations that are difficult to access regularly. The systems have been designed to operate unattended for at least 5 years. During the Austral summer, the systems charge batteries using solar panels and power is provided by the batteries during the winter months. If the voltage goes below a critical level, the systems go into hibernation and wait for voltage from the solar panels to initiate a restart sequence to begin operation and battery charging. Our first system was deployed on the East Antarctic Plateau in 2008 and we report here on an analysis of the power and battery performance over multiple years and provide an estimate for how long these systems can operate before major battery maintenance must be performed.

  12. Comparison of adaptive critic-based and classical wide-area controllers for power systems.

    Science.gov (United States)

    Ray, Swakshar; Venayagamoorthy, Ganesh Kumar; Chaudhuri, Balarko; Majumder, Rajat

    2008-08-01

    An adaptive critic design (ACD)-based damping controller is developed for a thyristor-controlled series capacitor (TCSC) installed in a power system with multiple poorly damped interarea modes. The performance of this ACD computational intelligence-based method is compared with two classical techniques, which are observer-based state-feedback (SF) control and linear matrix inequality LMI-H(infinity) robust control. Remote measurements are used as feedback signals to the wide-area damping controller for modulating the compensation of the TCSC. The classical methods use a linearized model of the system whereas the ACD method is purely measurement-based, leading to a nonlinear controller with fixed parameters. A comparative analysis of the controllers' performances is carried out under different disturbance scenarios. The ACD-based design has shown promising performance with very little knowledge of the system compared to classical model-based controllers. This paper also discusses the advantages and disadvantages of ACDs, SF, and LMI-H(infinity).

  13. Energy scavenging using piezoelectric sensors to power in pavement intelligent vehicle detection systems

    Science.gov (United States)

    Parhad, Ashutosh

    Intelligent transportation systems use in-pavement inductive loop sensors to collect real time traffic data. This method is very expensive in terms of installation and maintenance. Our research is focused on developing advanced algorithms capable of generating high amounts of energy that can charge a battery. This electromechanical energy conversion is an optimal way of energy scavenging that makes use of piezoelectric sensors. The power generated is sufficient to run the vehicle detection module that has several sensors embedded together. To achieve these goals, we have developed a simulation module using software's like LabVIEW and Multisim. The simulation module recreates a practical scenario that takes into consideration vehicle weight, speed, wheel width and frequency of the traffic.

  14. Intelligent software system for the advanced control room of a nuclear power plant

    Energy Technology Data Exchange (ETDEWEB)

    Chang, Soon Heung; Choi, Seong Soo; Park, Jin Kyun; Heo, Gyung Young [Korea Advanced Institute of Science and Technology, Taejon (Korea, Republic of); Kim, Han Gon [Korea Electric Power Research Institute, Taejon (Korea, Republic of)

    1997-12-31

    The intelligent software system for nuclear power plants (NPPs) has been conceptually designed in this study. Its design goals are to operate NPPs in an improved manner and to support operators` cognitive takes. It consists of six major modules such as {sup I}nformation Processing,{sup {sup A}}larm Processing,{sup {sup P}}rocedure Tracking,{sup {sup P}}erformance Diagnosis,{sup a}nd {sup E}vent Diagnosis{sup m}odules for operators and {sup M}alfunction Diagnosis{sup m}odule for maintenance personnel. Most of the modules have been developed for several years and the others are under development. After the completion of development, they will be combined into one system that would be main parts of advanced control rooms in NPPs. 5 refs., 4 figs. (Author)

  15. Guiding rules for development of intelligent monitoring system of nuclear power plants

    International Nuclear Information System (INIS)

    Kitamura, M.; Furukawa, H.; Kozma, R.; Washio, T.

    1996-01-01

    General frameworks and major component techniques for intelligent monitoring of nuclear power plants are presented. The key concept, diversity-based design, is to provide advisory information through consensus of multiple agents, each performing operational decision-making by focusing on mutually different information obtained from the plant. The multi-agent design scheme allows to attain high credibility and tolerance against sensor failure in fault detection and causal reasoning. The advantage of the proposed scheme realized by multiple neural networks was clearly demonstrated through numerical experiments with anomalies in a pressurized water reactor. Relevant techniques are also introduced for diagnostic information evaluation in specified symptoms, and for remedial procedure synthesis. A new architecture for future implementation of the proposed scheme, worm-type multi-agent system, is also proposed as a promising candidate. (author)

  16. Predicting speech intelligibility in adverse conditions: evaluation of the speech-based envelope power spectrum model

    DEFF Research Database (Denmark)

    Jørgensen, Søren; Dau, Torsten

    2011-01-01

    conditions by comparing predictions to measured data from [Kjems et al. (2009). J. Acoust. Soc. Am. 126 (3), 1415-1426] where speech is mixed with four different interferers, including speech-shaped noise, bottle noise, car noise, and cafe noise. The model accounts well for the differences in intelligibility......The speech-based envelope power spectrum model (sEPSM) [Jørgensen and Dau (2011). J. Acoust. Soc. Am., 130 (3), 1475–1487] estimates the envelope signal-to-noise ratio (SNRenv) of distorted speech and accurately describes the speech recognition thresholds (SRT) for normal-hearing listeners...... observed for the different interferers. None of the standardized models successfully describe these data....

  17. Interoperable Cloud Networking for intelligent power supply; Interoperables Cloud Networking fuer intelligente Energieversorgung

    Energy Technology Data Exchange (ETDEWEB)

    Hardin, Dave [Invensys Operations Management, Foxboro, MA (United States)

    2010-09-15

    Intelligent power supply by a so-called Smart Grid will make it possible to control consumption by market-based pricing and signals for load reduction. This necessitates that both the energy rates and the energy information are distributed reliably and in real time to automation systems in domestic and other buildings and in industrial plants over a wide geographic range and across the most varied grid infrastructures. Effective communication at this level of complexity necessitates computer and grid resources that are normally only available in the computer centers of big industries. The cloud computing technology, which is described here in some detail, has all features to provide reliability, interoperability and efficiency for large-scale smart grid applications, at lower cost than traditional computer centers. (orig.)

  18. Intelligent software system for the advanced control room of a nuclear power plant

    Energy Technology Data Exchange (ETDEWEB)

    Chang, Soon Heung; Choi, Seong Soo; Park, Jin Kyun; Heo, Gyung Young [Korea Advanced Institute of Science and Technology, Taejon (Korea, Republic of); Kim, Han Gon [Korea Electric Power Research Institute, Taejon (Korea, Republic of)

    1998-12-31

    The intelligent software system for nuclear power plants (NPPs) has been conceptually designed in this study. Its design goals are to operate NPPs in an improved manner and to support operators` cognitive takes. It consists of six major modules such as {sup I}nformation Processing,{sup {sup A}}larm Processing,{sup {sup P}}rocedure Tracking,{sup {sup P}}erformance Diagnosis,{sup a}nd {sup E}vent Diagnosis{sup m}odules for operators and {sup M}alfunction Diagnosis{sup m}odule for maintenance personnel. Most of the modules have been developed for several years and the others are under development. After the completion of development, they will be combined into one system that would be main parts of advanced control rooms in NPPs. 5 refs., 4 figs. (Author)

  19. Nuclear power plant monitoring and fault diagnosis methods based on the artificial intelligence technique

    International Nuclear Information System (INIS)

    Yoshikawa, S.; Saiki, A.; Ugolini, D.; Ozawa, K.

    1996-01-01

    The main objective of this paper is to develop an advanced diagnosis system based on the artificial intelligence technique to monitor the operation and to improve the operational safety of nuclear power plants. Three different methods have been elaborated in this study: an artificial neural network local diagnosis (NN ds ) scheme that acting at the component level discriminates between normal and abnormal transients, a model-based diagnostic reasoning mechanism that combines a physical causal network model-based knowledge compiler (KC) that generates applicable diagnostic rules from widely accepted physical knowledge compiler (KC) that generates applicable diagnostic rules from widely accepted physical knowledge. Although the three methods have been developed and verified independently, they are highly correlated and, when connected together, form a effective and robust diagnosis and monitoring tool. (authors)

  20. Mathematic Modeling and Performance Analysis of an Adaptive Congestion Control in Intelligent Transportation Systems

    OpenAIRE

    Naja, Rola; Université de Versailles

    2015-01-01

    In this paper, we develop a preventive congestion control mechanism applied at highway entrances and devised for Intelligent Transportation Systems (ITS). The proposed mechanism provides a vehicular admission control, regulates input traffic and performs vehicular traffic shaping. Our congestion control mechanism includes two classes of vehicles and is based on a specific priority ticket pool scheme with queue-length threshold scheduling policy, tailored to vehicular networks. In an attempt t...

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

    International Nuclear Information System (INIS)

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

    2017-01-01

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

  2. Artificial intelligence utilization in power generation units control systems; Utilizacao de inteligencia artificial em sistemas de controle de unidades geradoras

    Energy Technology Data Exchange (ETDEWEB)

    Souza, G N [CEPEL, Rio de Janeiro, RJ (Brazil); Mendes, S B [Universidade Federal, Rio de Janeiro, RJ (Brazil). Coordenacao dos Programas de Pos-graduacao de Engenharia

    1992-12-31

    To the implementation of the logics of control in a hydroelectric power plant artificial languages or complexes formalisms are used which cause error introduction in the description process of such logic. This work suggests the use of an intelligent and interactive system with interface in natural language to the control description as a solution to this problem. 28 refs., 3 figs.

  3. Artificial intelligence utilization in power generation units control systems; Utilizacao de inteligencia artificial em sistemas de controle de unidades geradoras

    Energy Technology Data Exchange (ETDEWEB)

    Souza, G.N. [CEPEL, Rio de Janeiro, RJ (Brazil); Mendes, S.B. [Universidade Federal, Rio de Janeiro, RJ (Brazil). Coordenacao dos Programas de Pos-graduacao de Engenharia

    1991-12-31

    To the implementation of the logics of control in a hydroelectric power plant artificial languages or complexes formalisms are used which cause error introduction in the description process of such logic. This work suggests the use of an intelligent and interactive system with interface in natural language to the control description as a solution to this problem. 28 refs., 3 figs.

  4. Star Power: Providing for the Gifted & Talented. Module 3. Applications of Theories of Intelligence to the Gifted/Talented.

    Science.gov (United States)

    Heinemann, Alison; Mallis, Jackie

    The document presents Module 3, applications of theories of intelligence to the gifted/talented, of the Star Power modules developed for school personnel who have an interest in or a need to explore the area of gifted and talented education. It is explained in an introductory section that the modules can be used for independent study, for small…

  5. The potential impact of intelligent power wheelchair use on social participation: perspectives of users, caregivers and clinicians.

    Science.gov (United States)

    Rushton, Paula W; Kairy, Dahlia; Archambault, Philippe; Pituch, Evelina; Torkia, Caryne; El Fathi, Anas; Stone, Paula; Routhier, François; Forget, Robert; Pineau, Joelle; Gourdeau, Richard; Demers, Louise

    2015-05-01

    To explore power wheelchair users', caregivers' and clinicians' perspectives regarding the potential impact of intelligent power wheelchair use on social participation. Semi-structured interviews were conducted with power wheelchair users (n = 12), caregivers (n = 4) and clinicians (n = 12). An illustrative video was used to facilitate discussion. The transcribed interviews were analyzed using thematic analysis. Three main themes were identified based on the experiences of the power wheelchair users, caregivers and clinicians: (1) increased social participation opportunities, (2) changing how social participation is experienced and (3) decreased risk of accidents during social participation. Findings from this study suggest that an intelligent power wheelchair would enhance social participation in a variety of important ways, thereby providing support for continued design and development of this assistive technology. An intelligent power wheelchair has the potential to: Increase social participation opportunities by overcoming challenges associated with navigating through crowds and small spaces. Change how social participation is experienced through "normalizing" social interactions and decreasing the effort required to drive a power wheelchair. Decrease the risk of accidents during social participation by reducing the need for dangerous compensatory strategies and minimizing the impact of the physical environment.

  6. Intelligent system for a remote diagnosis of a photovoltaic solar power plant

    International Nuclear Information System (INIS)

    Sanz-Bobi, M A; San Roque, A Muñoz; Marcos, A de; Bada, M

    2012-01-01

    Usually small and mid-sized photovoltaic solar power plants are located in rural areas and typically they operate unattended. Some technicians are in charge of the supervision of these plants and, if an alarm is automatically issued, they try to investigate the problem and correct it. Sometimes these anomalies are detected some hours or days after they begin. Also the analysis of the causes once the anomaly is detected can take some additional time. All these factors motivated the development of a methodology able to perform continuous and automatic monitoring of the basic parameters of a photovoltaic solar power plant in order to detect anomalies as soon as possible, to diagnose their causes, and to immediately inform the personnel in charge of the plant. The methodology proposed starts from the study of the most significant failure modes of a photovoltaic plant through a FMEA and using this information, its typical performance is characterized by the creation of its normal behaviour models. They are used to detect the presence of a failure in an incipient or current form. Once an anomaly is detected, an automatic and intelligent diagnosis process is started in order to investigate the possible causes. The paper will describe the main features of a software tool able to detect anomalies and to diagnose them in a photovoltaic solar power plant.

  7. Envisioning engineering education and practice in the coming intelligence convergence era — a complex adaptive systems approach

    Science.gov (United States)

    Noor, Ahmed K.

    2013-12-01

    Some of the recent attempts for improving and transforming engineering education are reviewed. The attempts aim at providing the entry level engineers with the skills needed to address the challenges of future large-scale complex systems and projects. Some of the frontier sectors and future challenges for engineers are outlined. The major characteristics of the coming intelligence convergence era (the post-information age) are identified. These include the prevalence of smart devices and environments, the widespread applications of anticipatory computing and predictive / prescriptive analytics, as well as a symbiotic relationship between humans and machines. Devices and machines will be able to learn from, and with, humans in a natural collaborative way. The recent game changers in learnscapes (learning paradigms, technologies, platforms, spaces, and environments) that can significantly impact engineering education in the coming era are identified. Among these are open educational resources, knowledge-rich classrooms, immersive interactive 3D learning, augmented reality, reverse instruction / flipped classroom, gamification, robots in the classroom, and adaptive personalized learning. Significant transformative changes in, and mass customization of, learning are envisioned to emerge from the synergistic combination of the game changers and other technologies. The realization of the aforementioned vision requires the development of a new multidisciplinary framework of emergent engineering for relating innovation, complexity and cybernetics, within the future learning environments. The framework can be used to treat engineering education as a complex adaptive system, with dynamically interacting and communicating components (instructors, individual, small, and large groups of learners). The emergent behavior resulting from the interactions can produce progressively better, and continuously improving, learning environment. As a first step towards the realization of

  8. Outage Performance of Hybrid FSO/RF System with Low-Complexity Power Adaptation

    KAUST Repository

    Rakia, Tamer

    2016-02-26

    Hybrid free-space optical (FSO) / radio-frequency (RF) systems have emerged as a promising solution for high data- rate wireless communication systems. We consider truncated channel inversion based power adaptation strategy for coherent and non- coherent hybrid FSO/RF systems, employing an adaptive combining scheme. Specifically, we activate the RF link along with the FSO link when FSO link quality is unacceptable, and adaptively set RF transmission power to ensure constant combined signal-to-noise ratio at receiver terminal. Analytical expressions for the outage probability of the hybrid system with and without power adaptation are derived. Numerical examples show that, the hybrid FSO/RF systems with power adaptation achieve considerable outage performance improvement over conventional hybrid FSO/RF systems without power adaptation. © 2015 IEEE.

  9. Swarm Intelligence: New Techniques for Adaptive Systems to Provide Learning Support

    Science.gov (United States)

    Wong, Lung-Hsiang; Looi, Chee-Kit

    2012-01-01

    The notion of a system adapting itself to provide support for learning has always been an important issue of research for technology-enabled learning. One approach to provide adaptivity is to use social navigation approaches and techniques which involve analysing data of what was previously selected by a cluster of users or what worked for…

  10. Research on intelligent power consumption strategy based on time-of-use pricing

    Science.gov (United States)

    Fu, Wei; Gong, Li; Chen, Heli; He, Yu

    2017-06-01

    In this paper, through the analysis of shortcomings of the current domestic and foreign household power consumption strategy: Passive way of power consumption, ignoring the different priority of electric equipment, neglecting the actual load pressure of the grid, ignoring the interaction with the user, to decrease the peak-valley difference and improve load curve in residential area by demand response (DR technology), an intelligent power consumption scheme based on time-of-use(TOU) pricing for household appliances is proposed. The main contribution of this paper is: (1) Three types of household appliance loads are abstracted from different operating laws of various household appliances, and the control models and DR strategies corresponding to these types are established. (2) The fuzzified processing for the information of TOU price, which is based on the time intervals, is performed to get the price priority, in accordance with such DR events as the maximum restricted load of DR, the time of DR and the duration of interruptible load and so on, the DR control rule and pre-scheduling mechanism are led in. (3) The dispatching sequence of household appliances in the control and scheduling queue are switched and controlled to implement the equilibrium of peak and valley loads. The equilibrium effects and economic benefits of power system by pre-scheduling and DR dispatching are compared and analyzed by simulation example, and the results show that using the proposed household appliance control (HAC) scheme the overall cost of consumers can be reduced and the power system load can be alleviated, so the proposed household appliance control (HAC) scheme is feasible and reasonable.

  11. Installation and evaluation of a nuclear power plant Operator Advisor based on artificial intelligence technology

    International Nuclear Information System (INIS)

    Hajek, B.K.; Miller, D.W.

    1993-02-01

    The Artificial Intelligence Group in the Nuclear Engineering Program has designed and built an Operator Advisor (OA), an AI system to monitor nuclear power plant parameters, detect component and system malfunctions, dispose their causes, and provide the plant operators with the correct procedures for mitigating the consequences of the malfunctions. It then monitors performance of the procedures, and provides backup steps when specific operator actions fail. The OA has been implemented on Sun 4 workstations in Common Lisp, and has been interfaced to run in real time on the Perry Nuclear Power Plant full-function simulator in the plant training department. The eventual goal for a fully functioning Operator Advisor would be to have reactor operators receive direction for all plant operations. Such a goal requires considerable testing of the system within limited malfunction boundaries, an extensive Verification ampersand Validation (V ampersand V) effort, a large knowledge base development effort, and development of tools as part of the system to automate its maintenance. Clearly, these efforts are beyond the scope of the feasibility effort expended during this project period. However, as a result of this project, we have an AI based platform upon which a complete system can be built

  12. Intelligent Flood Adaptive Context-aware System: How Wireless Sensors Adapt their Configuration based on Environmental Phenomenon Events

    Directory of Open Access Journals (Sweden)

    Jie SUN

    2016-11-01

    Full Text Available Henceforth, new generations of Wireless Sensor Networks (WSN have to be able to adapt their behavior to collect, from the study phenomenon, quality data for long periods of time. We have thus proposed a new formalization for the design and the implementation of context-aware systems relying on a WSN for the data collection. To illustrate this proposal, we also present an environmental use case: the study of flood events in a watershed. In this paper, we detail the simulation tool that we have developed in order to implement our model. We simulate several scenarios of context-aware systems to monitor a watershed. The data used for the simulation are the observation data of the French Orgeval watershed.

  13. Validation of the Serbian adaptation of the Trait Emotional Intelligence Questionnaire-Child Form (TEIQue-CF

    Directory of Open Access Journals (Sweden)

    Banjac Sonja

    2016-01-01

    Full Text Available This study investigated trait EI in childhood in a Serbian population by validating a Serbian adaptation of the Trait Emotional Intelligence Questionnaire - Child Form (TEIQue-CF. All 606 participants (Mage = 10.33, SD = 1.55 completed the TEIQue-CF, the Reading the Mind in the Eyes Test (revised version, and the Guess Who peer assessment. Data on academic achievement and truancy were also obtained. The Serbian TEIQue-CF demonstrated robust psychometric properties with satisfactory internal consistencies and extensive evidence of validity in relation to criteria such as emotion recognition, academic grades, truancy rates, and peer ratings. Factor analyses suggested a two-factor solution for the total sample, but a unifactorial structure for the two groups of younger children aged 8 to 9 and 10 to 11. Overall, the results corroborate the validity of the Serbian adaptation and the theoretical and practical importance of the construct of trait EI in children. [Projekat Ministarstva nauke Republike Srbije, br. 179018

  14. Cross-layer combining of power control and adaptive modulation with truncated ARQ for cognitive radios

    Institute of Scientific and Technical Information of China (English)

    CHENG Shi-lun; YANG Zhen

    2008-01-01

    To maximize throughput and to satisfy users' requirements in cognitive radios, a cross-layer optimization problem combining adaptive modulation and power control at the physical layer and truncated automatic repeat request at the medium access control layer is proposed. Simulation results show the combination of power control, adaptive modulation, and truncated automatic repeat request can regulate transmitter powers and increase the total throughput effectively.

  15. The ongoing adaptive evolution of ASPM and Microcephalin is not explained by increased intelligence.

    NARCIS (Netherlands)

    Mekel-Bobrov, N.; Posthuma, D.; Gilbert, S.L.; Lind, P.; Gosso, M.F.; Luciano, M.; Harris, S.E.; Bates, T.C.; Polderman, T.J.C.; Whalley, L.J.; Fox, H.; Starr, J.M.; Evans, P.D.; Montgomery, GW; Fernandes, C.; Heutink, P.; Martin, N.G.; Boomsma, D.I.; Deary, I.J.; Wright, M.J.; de Geus, E.J.C.; Lahn, B.T.

    2007-01-01

    Recent studies have made great strides towards identifying putative genetic events underlying the evolution of the human brain and its emergent cognitive capacities. One of the most intriguing findings is the recurrent identification of adaptive evolution in genes associated with primary

  16. Artificial intelligence application to diagnosis and supervision of nuclear power plants

    International Nuclear Information System (INIS)

    Corvalan, P.J.

    1991-06-01

    A diagnostic expert system was developed, in the Process Control Division at the Centro Atomico Bariloche, for the Embalse nuclear power plant simulator. The diagnostic system task is to interpret and show the probable cause of an abnormal transitory behaviour in the simulated process. The system was developed using artificial intelligence techniques such as: knowledge representation using rules, heuristic programming, inference under uncertainty and fuzzy sets. The diagnostic technique used consists of finding the possible cause of failure using the fault hypothesis confirmation. The faults hypothesis are organized in hierarchical form into a tree structure. The Best First search strategy is used to direct the search to those hypothesis which are confirmed with a higher degree of certainty. The diagnostic is finished when a specific hypothesis is confirmed with a high certainty factor. The diagnostic result obtained by different process fault simulation is shown. An alternative diagnostic technique is presented where the knowlegde of process structure and behaviour are represented in the form of mathematical constraints. This diagnostic method detects a suspicious component through constraints satisfaction and localizes it through constraints suspension. The validity of the method is shown by an easy example. (Author) [es

  17. Games and Machine Learning: A Powerful Combination in an Artificial Intelligence Course

    Science.gov (United States)

    Wallace, Scott A.; McCartney, Robert; Russell, Ingrid

    2010-01-01

    Project MLeXAI [Machine Learning eXperiences in Artificial Intelligence (AI)] seeks to build a set of reusable course curriculum and hands on laboratory projects for the artificial intelligence classroom. In this article, we describe two game-based projects from the second phase of project MLeXAI: Robot Defense--a simple real-time strategy game…

  18. Intelligent Photovoltaic Maximum Power Point Tracking Controller for Energy Enhancement in Renewable Energy System

    Directory of Open Access Journals (Sweden)

    Subiyanto

    2013-01-01

    Full Text Available Photovoltaic (PV system is one of the promising renewable energy technologies. Although the energy conversion efficiency of the system is still low, but it has the advantage that the operating cost is free, very low maintenance and pollution-free. Maximum power point tracking (MPPT is a significant part of PV systems. This paper presents a novel intelligent MPPT controller for PV systems. For the MPPT algorithm, an optimized fuzzy logic controller (FLC using the Hopfield neural network is proposed. It utilizes an automatically tuned FLC membership function instead of the trial-and-error approach. The MPPT algorithm is implemented in a new variant of coupled inductor soft switching boost converter with high voltage gain to increase the converter output from the PV panel. The applied switching technique, which includes passive and active regenerative snubber circuits, reduces the insulated gate bipolar transistor switching losses. The proposed MPPT algorithm is implemented using the dSPACE DS1104 platform software on a DS1104 board controller. The prototype MPPT controller is tested using an agilent solar array simulator together with a 3 kW real PV panel. Experimental test results show that the proposed boost converter produces higher output voltages and gives better efficiency (90% than the conventional boost converter with an RCD snubber, which gives 81% efficiency. The prototype MPPT controller is also found to be capable of tracking power from the 3 kW PV array about 2.4 times more than that without using the MPPT controller.

  19. Intelligent Mechanical Fault Diagnosis Based on Multiwavelet Adaptive Threshold Denoising and MPSO

    Directory of Open Access Journals (Sweden)

    Hao Sun

    2014-01-01

    Full Text Available The condition diagnosis of rotating machinery depends largely on the feature analysis of vibration signals measured for the condition diagnosis. However, the signals measured from rotating machinery usually are nonstationary and nonlinear and contain noise. The useful fault features are hidden in the heavy background noise. In this paper, a novel fault diagnosis method for rotating machinery based on multiwavelet adaptive threshold denoising and mutation particle swarm optimization (MPSO is proposed. Geronimo, Hardin, and Massopust (GHM multiwavelet is employed for extracting weak fault features under background noise, and the method of adaptively selecting appropriate threshold for multiwavelet with energy ratio of multiwavelet coefficient is presented. The six nondimensional symptom parameters (SPs in the frequency domain are defined to reflect the features of the vibration signals measured in each state. Detection index (DI using statistical theory has been also defined to evaluate the sensitiveness of SP for condition diagnosis. MPSO algorithm with adaptive inertia weight adjustment and particle mutation is proposed for condition identification. MPSO algorithm effectively solves local optimum and premature convergence problems of conventional particle swarm optimization (PSO algorithm. It can provide a more accurate estimate on fault diagnosis. Practical examples of fault diagnosis for rolling element bearings are given to verify the effectiveness of the proposed method.

  20. Reliability and efficiency upgrades of power systems operation by implementing intelligent electronic devices with synchrophasor measurement technology support

    Directory of Open Access Journals (Sweden)

    Mokeev Alexey

    2017-01-01

    Full Text Available This paper reviews issues of reliability and efficiency upgrades of power systems functions by means of a widespread implementation of intelligent electronic devices (IED in various purposes supporting synchrophasor measurement technology. Thus, such issues as IED’s operational analysis in the conditions of electromagnetic and electromechanical transient processes and synthesis of digital filters that improve static and dynamic responses of these devices play an important role in their development.

  1. Reliability and efficiency upgrades of power systems operation by implementing intelligent electronic devices with synchrophasor measurement technology support

    OpenAIRE

    Mokeev Alexey

    2017-01-01

    This paper reviews issues of reliability and efficiency upgrades of power systems functions by means of a widespread implementation of intelligent electronic devices (IED) in various purposes supporting synchrophasor measurement technology. Thus, such issues as IED’s operational analysis in the conditions of electromagnetic and electromechanical transient processes and synthesis of digital filters that improve static and dynamic responses of these devices play an important role in their devel...

  2. Intelligent Optics Laboratory

    Data.gov (United States)

    Federal Laboratory Consortium — The Intelligent Optics Laboratory supports sophisticated investigations on adaptive and nonlinear optics; advancedimaging and image processing; ground-to-ground and...

  3. A Long-Distance RF-Powered Sensor Node with Adaptive Power Management for IoT Applications.

    Science.gov (United States)

    Pizzotti, Matteo; Perilli, Luca; Del Prete, Massimo; Fabbri, Davide; Canegallo, Roberto; Dini, Michele; Masotti, Diego; Costanzo, Alessandra; Franchi Scarselli, Eleonora; Romani, Aldo

    2017-07-28

    We present a self-sustained battery-less multi-sensor platform with RF harvesting capability down to -17 dBm and implementing a standard DASH7 wireless communication interface. The node operates at distances up to 17 m from a 2 W UHF carrier. RF power transfer allows operation when common energy scavenging sources (e.g., sun, heat, etc.) are not available, while the DASH7 communication protocol makes it fully compatible with a standard IoT infrastructure. An optimized energy-harvesting module has been designed, including a rectifying antenna (rectenna) and an integrated nano-power DC/DC converter performing maximum-power-point-tracking (MPPT). A nonlinear/electromagnetic co-design procedure is adopted to design the rectenna, which is optimized to operate at ultra-low power levels. An ultra-low power microcontroller controls on-board sensors and wireless protocol, to adapt the power consumption to the available detected power by changing wake-up policies. As a result, adaptive behavior can be observed in the designed platform, to the extent that the transmission data rate is dynamically determined by RF power. Among the novel features of the system, we highlight the use of nano-power energy harvesting, the implementation of specific hardware/software wake-up policies, optimized algorithms for best sampling rate implementation, and adaptive behavior by the node based on the power received.

  4. A Long-Distance RF-Powered Sensor Node with Adaptive Power Management for IoT Applications

    Directory of Open Access Journals (Sweden)

    Matteo Pizzotti

    2017-07-01

    Full Text Available We present a self-sustained battery-less multi-sensor platform with RF harvesting capability down to −17 dBm and implementing a standard DASH7 wireless communication interface. The node operates at distances up to 17 m from a 2 W UHF carrier. RF power transfer allows operation when common energy scavenging sources (e.g., sun, heat, etc. are not available, while the DASH7 communication protocol makes it fully compatible with a standard IoT infrastructure. An optimized energy-harvesting module has been designed, including a rectifying antenna (rectenna and an integrated nano-power DC/DC converter performing maximum-power-point-tracking (MPPT. A nonlinear/electromagnetic co-design procedure is adopted to design the rectenna, which is optimized to operate at ultra-low power levels. An ultra-low power microcontroller controls on-board sensors and wireless protocol, to adapt the power consumption to the available detected power by changing wake-up policies. As a result, adaptive behavior can be observed in the designed platform, to the extent that the transmission data rate is dynamically determined by RF power. Among the novel features of the system, we highlight the use of nano-power energy harvesting, the implementation of specific hardware/software wake-up policies, optimized algorithms for best sampling rate implementation, and adaptive behavior by the node based on the power received.

  5. PEAC: A Power-Efficient Adaptive Computing Technology for Enabling Swarm of Small Spacecraft and Deployable Mini-Payloads

    Data.gov (United States)

    National Aeronautics and Space Administration — This task is to develop and demonstrate a path-to-flight and power-adaptive avionics technology PEAC (Power Efficient Adaptive Computing). PEAC will enable emerging...

  6. Adaptive control method for core power control in TRIGA Mark II reactor

    Science.gov (United States)

    Sabri Minhat, Mohd; Selamat, Hazlina; Subha, Nurul Adilla Mohd

    2018-01-01

    The 1MWth Reactor TRIGA PUSPATI (RTP) Mark II type has undergone more than 35 years of operation. The existing core power control uses feedback control algorithm (FCA). It is challenging to keep the core power stable at the desired value within acceptable error bands to meet the safety demand of RTP due to the sensitivity of nuclear research reactor operation. Currently, the system is not satisfied with power tracking performance and can be improved. Therefore, a new design core power control is very important to improve the current performance in tracking and regulate reactor power by control the movement of control rods. In this paper, the adaptive controller and focus on Model Reference Adaptive Control (MRAC) and Self-Tuning Control (STC) were applied to the control of the core power. The model for core power control was based on mathematical models of the reactor core, adaptive controller model, and control rods selection programming. The mathematical models of the reactor core were based on point kinetics model, thermal hydraulic models, and reactivity models. The adaptive control model was presented using Lyapunov method to ensure stable close loop system and STC Generalised Minimum Variance (GMV) Controller was not necessary to know the exact plant transfer function in designing the core power control. The performance between proposed adaptive control and FCA will be compared via computer simulation and analysed the simulation results manifest the effectiveness and the good performance of the proposed control method for core power control.

  7. Adaptive Home Automation System by Using ‎Smart Phone Based Artificial Intelligent

    Directory of Open Access Journals (Sweden)

    Osama Qasim Jumah

    2017-12-01

    Full Text Available The system of Home Automation consider nowadays as a promise technology for living a comfortable life and minimizing the cost of the user homeowner. The system might be accomplished by controlling the heating, ventilation, air conditioning, shading, and lightening. The energy consumed efficiency is get better also the protection system is exists. In this work, a Home Automation System is proposed, so that it performs automatically controlling to some of the appliances in the home. In addition, the proposed system will discover any undesirable movement or fire when the person is out of his home by taking a suitable decision instead of homeowner. The control unit uses a Smart Phone (Android Mobile. In this work, to gather readings of movements, heating, and lightening, a number of nodes are used (three nodes. Also a Microcontroller uses especial sensors to collect this information, after that sends them wirelessly through WIFI to the Smart Phone for manipulation and taking a convenience decision. Delta Neural Network Learning Rule is use for the first time as the intelligent algorithm to give the decisions for all the readings of sensors, so that it learned after 113259 which take 2280 seconds. In addition, it turns out the automated system to be further smart such that if there is fire or movement into the house, the application will distinguish if this movement for example dangerous or not. The mobile (through the application then gives a command to send a message (GSM to the homeowner (Police, or fire station telling the new situation. Furthermore, the controlling of all convenient appliances at the home automatically for each state. JAVA Program is use for manipulation process, and then by employing Eclipse Juno IDE program it turn into to an android application that installed into the Mobile. The Microcontroller is Arduino with WIFI shield and Xbee.

  8. Extending the applied software in the contemporary thermal power plants for increasing the intelligence of the automatic control system

    Science.gov (United States)

    Krokhin, G.; Pestunov, A.; Arakelyan, E.; Mukhin, V.

    2017-11-01

    During the last decades, there can be noticed an increase of interest concerning various aspects of intellectual diagnostics and management in thermal power engineering according the hybrid principle. It is conditioned by the fact that conservative static methods does not allow to reflect the actual power installation state adequately. In order to improve the diagnostics quality, we use various fuzzy systems apparatus. In this paper, we introduce the intellectual system, called SKAIS, which is intended for quick and precise diagnostics of thermal power equipment. This system was developed as the result of the research carried out by specialists from National Research University “Moscow Power Engineering Institute” and Novosibirsk State University of Economics and Management. It drastically increases the level of intelligence of the automatic power plant control system.

  9. Towards intelligent automation of power plant design and operations: The role of interactive simulations and distributed expert systems

    International Nuclear Information System (INIS)

    Otaduy, P.J.

    1992-01-01

    The design process of a power plant can be viewed as machine- chromosome engineering: When the final layout is implemented, the lifetime operating characteristics, constraints, strengths, and weaknesses of the resulting power-plant-specimen are durably determined. Hence, the safety, operability, maneuverability, availability, maintenance requirements, and costs of a power plant are directly related to the goodness of its electromechanical-genes. This paper addresses the desirability of incorporating distributed computing, distributed object management, and multimedia technologies to power plant engineering, in particular, to design and operations. The promise these technologies have for enhancing the quality and amount of engineering knowledge available, concurrently, online, to plant designers, maintenance crews, and operators is put into perspective. The role that advanced interactive simulations and expert systems will play in the intelligent automation of power plant design and operations is discussed

  10. A Statistical Model for Uplink Intercell Interference with Power Adaptation and Greedy Scheduling

    KAUST Repository

    Tabassum, Hina

    2012-10-03

    This paper deals with the statistical modeling of uplink inter-cell interference (ICI) considering greedy scheduling with power adaptation based on channel conditions. The derived model is implicitly generalized for any kind of shadowing and fading environments. More precisely, we develop a generic model for the distribution of ICI based on the locations of the allocated users and their transmit powers. The derived model is utilized to evaluate important network performance metrics such as ergodic capacity, average fairness and average power preservation numerically. Monte-Carlo simulation details are included to support the analysis and show the accuracy of the derived expressions. In parallel to the literature, we show that greedy scheduling with power adaptation reduces the ICI, average power consumption of users, and enhances the average fairness among users, compared to the case without power adaptation. © 2012 IEEE.

  11. A Statistical Model for Uplink Intercell Interference with Power Adaptation and Greedy Scheduling

    KAUST Repository

    Tabassum, Hina; Yilmaz, Ferkan; Dawy, Zaher; Alouini, Mohamed-Slim

    2012-01-01

    This paper deals with the statistical modeling of uplink inter-cell interference (ICI) considering greedy scheduling with power adaptation based on channel conditions. The derived model is implicitly generalized for any kind of shadowing and fading environments. More precisely, we develop a generic model for the distribution of ICI based on the locations of the allocated users and their transmit powers. The derived model is utilized to evaluate important network performance metrics such as ergodic capacity, average fairness and average power preservation numerically. Monte-Carlo simulation details are included to support the analysis and show the accuracy of the derived expressions. In parallel to the literature, we show that greedy scheduling with power adaptation reduces the ICI, average power consumption of users, and enhances the average fairness among users, compared to the case without power adaptation. © 2012 IEEE.

  12. Overall intelligent hybrid control system for a fossil-fuel power unit

    Energy Technology Data Exchange (ETDEWEB)

    Garduno-Ramirez, Raul

    2000-08-01

    This research present a methodology to design a generalized overall unit control system for a fossil fuel power unit (FFPU), and develops a minimum prototype to demonstrate its feasibility. Toward the above goal, the associated research project was undertaken as a technology innovation process with its two ends identified as follows. First, it is recognized that the coordinated control strategies constitute the uppermost control level in current FFPUs, and so, are responsible for driving the boiler-turbine-generator set as a single entity. Second, a FFPU is envisioned as a complex process, subject to multiple changing operating conditions, that should perform as an intelligent system, for which an advanced integral control concept is needed. Therefore, as an outcome of the innovation process, a generalized unit control concept that extends the capabilities of current coordinated control schemes is proposed. This concept is presented as the Intelligent Coordinated Control System (ICCS) paradigm, which establishes an open reference framework for the development of overall unit control schemes. The ICCS's system goals are identified using power plant process engineering concepts, and intelligent control systems engineering concepts are used to identify main tasks and to achieve system functional decomposition. A software engineering agency concept is used to identify and group agents according to their knowledge and purpose interactions. The resultant ICCS structure is an open set of functionally grouped agent clusters in a two-level hierarchical system. The upper level, mainly characterized for knowledge-driven processes, performs the supervisory functions needed to provide self governing operation characteristics, while the lower level, mainly characterized for data-driven processes, performs the fast reactive behavior functions necessary for hybrid real-time control and protection. Developed through several stages, the ICCS-MP finally implements a two

  13. Intelligent Broadcasting in Mobile Ad Hoc Networks: Three Classes of Adaptive Protocols

    Directory of Open Access Journals (Sweden)

    Michael D. Colagrosso

    2006-11-01

    Full Text Available Because adaptability greatly improves the performance of a broadcast protocol, we identify three ways in which machine learning can be applied to broadcasting in a mobile ad hoc network (MANET. We chose broadcasting because it functions as a foundation of MANET communication. Unicast, multicast, and geocast protocols utilize broadcasting as a building block, providing important control and route establishment functionality. Therefore, any improvements to the process of broadcasting can be immediately realized by higher-level MANET functionality and applications. While efficient broadcast protocols have been proposed, no single broadcasting protocol works well in all possible MANET conditions. Furthermore, protocols tend to fail catastrophically in severe network environments. Our three classes of adaptive protocols are pure machine learning, intra-protocol learning, and inter-protocol learning. In the pure machine learning approach, we exhibit a new approach to the design of a broadcast protocol: the decision of whether to rebroadcast a packet is cast as a classification problem. Each mobile node (MN builds a classifier and trains it on data collected from the network environment. Using intra-protocol learning, each MN consults a simple machine model for the optimal value of one of its free parameters. Lastly, in inter-protocol learning, MNs learn to switch between different broadcasting protocols based on network conditions. For each class of learning method, we create a prototypical protocol and examine its performance in simulation.

  14. Intelligent Broadcasting in Mobile Ad Hoc Networks: Three Classes of Adaptive Protocols

    Directory of Open Access Journals (Sweden)

    Colagrosso Michael D

    2007-01-01

    Full Text Available Because adaptability greatly improves the performance of a broadcast protocol, we identify three ways in which machine learning can be applied to broadcasting in a mobile ad hoc network (MANET. We chose broadcasting because it functions as a foundation of MANET communication. Unicast, multicast, and geocast protocols utilize broadcasting as a building block, providing important control and route establishment functionality. Therefore, any improvements to the process of broadcasting can be immediately realized by higher-level MANET functionality and applications. While efficient broadcast protocols have been proposed, no single broadcasting protocol works well in all possible MANET conditions. Furthermore, protocols tend to fail catastrophically in severe network environments. Our three classes of adaptive protocols are pure machine learning, intra-protocol learning, and inter-protocol learning. In the pure machine learning approach, we exhibit a new approach to the design of a broadcast protocol: the decision of whether to rebroadcast a packet is cast as a classification problem. Each mobile node (MN builds a classifier and trains it on data collected from the network environment. Using intra-protocol learning, each MN consults a simple machine model for the optimal value of one of its free parameters. Lastly, in inter-protocol learning, MNs learn to switch between different broadcasting protocols based on network conditions. For each class of learning method, we create a prototypical protocol and examine its performance in simulation.

  15. Cultural Intelligence and Social Adaptability: A Comparison between Iranian and Non-Iranian Dormitory Students of Isfahan University of Medical Sciences.

    Science.gov (United States)

    Soltani, Batoul; Keyvanara, Mahmoud

    2013-01-01

    At the modern age, to acquire knowledge and experience, the individuals with their own specific culture have to enter contexts with cultural diversity, adapt to different cultures and have social interactions to be able to have effective inter-cultural relationships.To have such intercultural associations and satisfy individual needs in the society, cultural intelligence and social adaptability are deemed as inevitable requirements, in particular for those who enter a quite different culture. Hence, the present study tries to compare the cultural intelligence and its aspects and social adaptability in Iranian and non-Iranian dormitory students of Isfahan University of Medical Sciences in 2012. The study was of descriptiveanalytical nature. The research population consisted of Iranian and non-Iranian students resided in the dormitories of Isfahan University of Medical Sciences which are 2500, totally. For Iranian students, two-stage sampling method was adopted. At the first stage, classified sampling and at the second stage, systematic random sampling was conducted. In this way, 441 students were selected. To form non-Iranian students' sample, consensus sampling method was applied and a sample of 37 students were obtained. The research data was collected by using Earley & Ang's Cultural Intelligence Questionnaire with the Cronbach's coefficient α of 76% and California Social Adaptability Standard Questionnaire with the Cronbach's coefficient α of over 70%. Then, the data were put into SPSS software to be analyzed. Finally, the results were presented by descriptive and inferential statistics methods. The study findings revealed that there was no statistically significant difference between cultural intelligence and cognitive aspect of cultural intelligence in Iranian and non-Iranian students (P≥0/05). However, Iranian and non-Iranian students statistically differed in terms of the following aspects of cultural intelligence: meta-cognitive aspect (61.8% for

  16. Self Adaptive Safe Provisioning of Wireless Power Using DCOPs

    NARCIS (Netherlands)

    Leeuwen, C.J. van; Yildirim, K.S.; Pawelczak, P.

    2017-01-01

    Wireless Power Transfer (WPT) technologies aim at getting rid of cables used by consumer devices for energy provision. As long distance WPT is becoming mature, the health impact of WPT becomes increasingly important to consider. In this paper we look at how to maximize the wireless power transfer to

  17. Outage Performance of Hybrid FSO/RF System with Low-Complexity Power Adaptation

    KAUST Repository

    Rakia, Tamer; Yang, Hong-Chuan; Gebali, Fayez; Alouini, Mohamed-Slim

    2016-01-01

    Hybrid free-space optical (FSO) / radio-frequency (RF) systems have emerged as a promising solution for high data- rate wireless communication systems. We consider truncated channel inversion based power adaptation strategy for coherent and non

  18. Power Line Interference Removal from Electrocardiogram Using a Simplified Lattice Based Adaptive IIR Notch Filter

    National Research Council Canada - National Science Library

    Dhillon, Santpal

    2001-01-01

    ...) notch filter with a simplified adaptation algorithm for removal of power line frequency from ECG signals, The performance of this filter is better as compared to a second order infinite impulse response (IIR...

  19. Mitigation and adaptation in polycentric systems : sources of power in the pursuit of collective goals

    NARCIS (Netherlands)

    Morrison, Tiffany H.; Adger, W. Neil; Brown, Katrina; Lemos, Maria Carmen; Huitema, Dave; Hughes, Terry P.

    2017-01-01

    Polycentric governance involves multiple actors at multiple scales beyond the state. The potential of polycentric governance for promoting both climate mitigation and adaptation is well established. Yet, dominant conceptualizations of polycentric governance pay scant attention to how power dynamics

  20. NEURAL NETWORKS CONTROL OF THE HYBRID POWER UNIT BASED ON THE METHOD OF ADAPTIVE CRITICS

    Directory of Open Access Journals (Sweden)

    S. Serikov

    2012-01-01

    Full Text Available The formal statement of the optimization problem of hybrid vehicle power unit control is given. Its solving by neural networks method application on the basis of adaptive critic is considered.

  1. Adaptable AES implementation with power-gating support

    DEFF Research Database (Denmark)

    Banik, Subhadeep; Bogdanov, Andrey; Fanni, Tiziana

    2016-01-01

    In this paper, we propose a reconfigurable design of the Ad-vanced Encryption Standard capable of adapting at run-Time to the requirements of the target application. Reconfiguration is achieved by activating only a specific subset of all the instantiated processing elements. Further, we explore...

  2. Adaptive Control of Wind Turbines for Maximum Power Point Tracking

    DEFF Research Database (Denmark)

    Zhao, Haoran; Wu, Qiuwei

    2018-01-01

    induction generator (SCIG) is used to illustrate the generator control system for a variable‐speed WECS. The chapter also presents case studies have been carried out to verify the developed adaptive controller for WECSs. WECSs are non‐linear systems with parameter uncertainties and which are subject...... to disturbances, in the form of non‐linear and unmodeled aerodynamics....

  3. A novel adaptive joint power control algorithm with channel estimation in a CDMA cellular system

    Institute of Scientific and Technical Information of China (English)

    2005-01-01

    Joint power control has advantages of multi-user detection and power control; and it can combat the multi-access interference and the near-far problem. A novel adaptive joint power control algorithm with channel estimation in a CDMA cellular system was designed. Simulation results show that the algorithm can control the power not only quickly but also precisely with a time change. The method is useful for increasing system capacity.

  4. Career Adaptability Development in Adolescence: Multiple Predictors and Effect on Sense of Power and Life Satisfaction

    Science.gov (United States)

    Hirschi, Andreas

    2009-01-01

    This longitudinal panel study investigated predictors of career adaptability development and its effect on development of sense of power and experience of life satisfaction among 330 Swiss eighth graders. A multivariate measure of career adaptability consisting of career choice readiness, planning, exploration, and confidence was applied. Based on…

  5. Power through Things: Following Traces of Collective Intelligence in Internet of Things

    Directory of Open Access Journals (Sweden)

    Monika Mačiulienė

    2014-10-01

    Full Text Available Purpose – it is becoming increasingly difficult to ignore the input Internet of Things (IoT has to offer in development of public, business and other societal structures. Therefore, paper seeks to determine the current state of knowledge in the field of IoT terms of wisdom creation and emergence of collective intelligence. First, we discuss concept of collective intelligence, then we define phenomena of IoT and identify areas of its application. Later, the author reviews how intelligent outputs of IoT are defined in scientific literature. These findings of theoretical investigation may shed some light on research field that is promising but still very vague.Design/methodology/approach – this article provides a general overview of IoT concept and its growing relation to collective intelligence. Methods of document analysis and content analysis were applied. Theoretical analysis enabled recognition of IoT phenomena in relation to wisdom creation and emergence of collective intelligence.Findings – general overview of the field revealed that new understanding of collective intelligence surfaces. Often intelligent behavior and decisions emerge from ever increasing cooperation between ‘things’ and humans. The variety of new concepts and authors trying to describe relationship of ‘things’ with each other and humans when creating intelligent outcomes revealed that this field is still in its very infancy and still needs considerable amount of industry and scientific efforts to be understood and executed.Research limitations – although the paper has successfully demonstrated that IoT provides vast amounts of data for people to process and create knowledge this could be considered only as initial phase in studying the field. IoT and its intelligent outcomes need more investigations in terms of real life case studies and industry reviews in order to create valid definitions, models and future guidelines. Practical implications – this

  6. An Adaptive Intelligent Integrated Lighting Control Approach for High-Performance Office Buildings

    Science.gov (United States)

    Karizi, Nasim

    An acute and crucial societal problem is the energy consumed in existing commercial buildings. There are 1.5 million commercial buildings in the U.S. with only about 3% being built each year. Hence, existing buildings need to be properly operated and maintained for several decades. Application of integrated centralized control systems in buildings could lead to more than 50% energy savings. This research work demonstrates an innovative adaptive integrated lighting control approach which could achieve significant energy savings and increase indoor comfort in high performance office buildings. In the first phase of the study, a predictive algorithm was developed and validated through experiments in an actual test room. The objective was to regulate daylight on a specified work plane by controlling the blind slat angles. Furthermore, a sensor-based integrated adaptive lighting controller was designed in Simulink which included an innovative sensor optimization approach based on genetic algorithm to minimize the number of sensors and efficiently place them in the office. The controller was designed based on simple integral controllers. The objective of developed control algorithm was to improve the illuminance situation in the office through controlling the daylight and electrical lighting. To evaluate the performance of the system, the controller was applied on experimental office model in Lee et al.'s research study in 1998. The result of the developed control approach indicate a significantly improvement in lighting situation and 1-23% and 50-78% monthly electrical energy savings in the office model, compared to two static strategies when the blinds were left open and closed during the whole year respectively.

  7. Adaptive discrete rate and power transmission for spectrum sharing systems

    KAUST Repository

    Abdallah, Mohamed M.; Salem, Ahmed H.; Alouini, Mohamed-Slim; Qaraqe, Khalid A.

    2012-01-01

    channels available at the secondary transmitter. We consider the problem under the constraints of maximum average interference power levels at the primary receiver. We develop a sub-optimal computationally efficient iterative algorithm for finding

  8. Discrete rate and variable power adaptation for underlay cognitive networks

    KAUST Repository

    Abdallah, Mohamed M.; Salem, Ahmed H.; Alouini, Mohamed-Slim; Qaraqe, Khalid A.

    2010-01-01

    We consider the problem of maximizing the average spectral efficiency of a secondary link in underlay cognitive networks. In particular, we consider the network setting whereby the secondary transmitter employs discrete rate and variable power

  9. A Novel Technique for Maximum Power Point Tracking of a Photovoltaic Based on Sensing of Array Current Using Adaptive Neuro-Fuzzy Inference System (ANFIS)

    Science.gov (United States)

    El-Zoghby, Helmy M.; Bendary, Ahmed F.

    2016-10-01

    Maximum Power Point Tracking (MPPT) is now widely used method in increasing the photovoltaic (PV) efficiency. The conventional MPPT methods have many problems concerning the accuracy, flexibility and efficiency. The MPP depends on the PV temperature and solar irradiation that randomly varied. In this paper an artificial intelligence based controller is presented through implementing of an Adaptive Neuro-Fuzzy Inference System (ANFIS) to obtain maximum power from PV. The ANFIS inputs are the temperature and cell current, and the output is optimal voltage at maximum power. During operation the trained ANFIS senses the PV current using suitable sensor and also senses the temperature to determine the optimal operating voltage that corresponds to the current at MPP. This voltage is used to control the boost converter duty cycle. The MATLAB simulation results shows the effectiveness of the ANFIS with sensing the PV current in obtaining the MPPT from the PV.

  10. Intelligent Condition Diagnosis Method Based on Adaptive Statistic Test Filter and Diagnostic Bayesian Network.

    Science.gov (United States)

    Li, Ke; Zhang, Qiuju; Wang, Kun; Chen, Peng; Wang, Huaqing

    2016-01-08

    A new fault diagnosis method for rotating machinery based on adaptive statistic test filter (ASTF) and Diagnostic Bayesian Network (DBN) is presented in this paper. ASTF is proposed to obtain weak fault features under background noise, ASTF is based on statistic hypothesis testing in the frequency domain to evaluate similarity between reference signal (noise signal) and original signal, and remove the component of high similarity. The optimal level of significance α is obtained using particle swarm optimization (PSO). To evaluate the performance of the ASTF, evaluation factor Ipq is also defined. In addition, a simulation experiment is designed to verify the effectiveness and robustness of ASTF. A sensitive evaluation method using principal component analysis (PCA) is proposed to evaluate the sensitiveness of symptom parameters (SPs) for condition diagnosis. By this way, the good SPs that have high sensitiveness for condition diagnosis can be selected. A three-layer DBN is developed to identify condition of rotation machinery based on the Bayesian Belief Network (BBN) theory. Condition diagnosis experiment for rolling element bearings demonstrates the effectiveness of the proposed method.

  11. Intelligent Condition Diagnosis Method Based on Adaptive Statistic Test Filter and Diagnostic Bayesian Network

    Directory of Open Access Journals (Sweden)

    Ke Li

    2016-01-01

    Full Text Available A new fault diagnosis method for rotating machinery based on adaptive statistic test filter (ASTF and Diagnostic Bayesian Network (DBN is presented in this paper. ASTF is proposed to obtain weak fault features under background noise, ASTF is based on statistic hypothesis testing in the frequency domain to evaluate similarity between reference signal (noise signal and original signal, and remove the component of high similarity. The optimal level of significance α is obtained using particle swarm optimization (PSO. To evaluate the performance of the ASTF, evaluation factor Ipq is also defined. In addition, a simulation experiment is designed to verify the effectiveness and robustness of ASTF. A sensitive evaluation method using principal component analysis (PCA is proposed to evaluate the sensitiveness of symptom parameters (SPs for condition diagnosis. By this way, the good SPs that have high sensitiveness for condition diagnosis can be selected. A three-layer DBN is developed to identify condition of rotation machinery based on the Bayesian Belief Network (BBN theory. Condition diagnosis experiment for rolling element bearings demonstrates the effectiveness of the proposed method.

  12. Intelligent Condition Diagnosis Method Based on Adaptive Statistic Test Filter and Diagnostic Bayesian Network

    Science.gov (United States)

    Li, Ke; Zhang, Qiuju; Wang, Kun; Chen, Peng; Wang, Huaqing

    2016-01-01

    A new fault diagnosis method for rotating machinery based on adaptive statistic test filter (ASTF) and Diagnostic Bayesian Network (DBN) is presented in this paper. ASTF is proposed to obtain weak fault features under background noise, ASTF is based on statistic hypothesis testing in the frequency domain to evaluate similarity between reference signal (noise signal) and original signal, and remove the component of high similarity. The optimal level of significance α is obtained using particle swarm optimization (PSO). To evaluate the performance of the ASTF, evaluation factor Ipq is also defined. In addition, a simulation experiment is designed to verify the effectiveness and robustness of ASTF. A sensitive evaluation method using principal component analysis (PCA) is proposed to evaluate the sensitiveness of symptom parameters (SPs) for condition diagnosis. By this way, the good SPs that have high sensitiveness for condition diagnosis can be selected. A three-layer DBN is developed to identify condition of rotation machinery based on the Bayesian Belief Network (BBN) theory. Condition diagnosis experiment for rolling element bearings demonstrates the effectiveness of the proposed method. PMID:26761006

  13. An Effective Wormhole Attack Defence Method for a Smart Meter Mesh Network in an Intelligent Power Grid

    Directory of Open Access Journals (Sweden)

    Jungtaek Seo

    2012-08-01

    Full Text Available Smart meters are one of the key components of intelligent power grids. Wireless mesh networks based on smart meters could provide customer-oriented information on electricity use to the operational control systems, which monitor power grid status and estimate electric power demand. Using this information, an operational control system could regulate devices within the smart grid in order to provide electricity in a cost-efficient manner. Ensuring the availability of the smart meter mesh network is therefore a critical factor in securing the soundness of an intelligent power system. Wormhole attacks can be one of the most difficult-to-address threats to the availability of mesh networks, and although many methods to nullify wormhole attacks have been tried, these have been limited by high computational resource requirements and unnecessary overhead, as well as by the lack of ability of such methods to respond to attacks. In this paper, an effective defense mechanism that both detects and responds to wormhole attacks is proposed. In the proposed system, each device maintains information on its neighbors, allowing each node to identify replayed packets. The effectiveness and efficiency of the proposed method is analyzed in light of additional computational message and memory complexities.

  14. An Adaptive Impedance Matching Network with Closed Loop Control Algorithm for Inductive Wireless Power Transfer.

    Science.gov (United States)

    Miao, Zhidong; Liu, Dake; Gong, Chen

    2017-08-01

    For an inductive wireless power transfer (IWPT) system, maintaining a reasonable power transfer efficiency and a stable output power are two most challenging design issues, especially when coil distance varies. To solve these issues, this paper presents a novel adaptive impedance matching network (IMN) for IWPT system. In our adaptive IMN IWPT system, the IMN is automatically reconfigured to keep matching with the coils and to adjust the output power adapting to coil distance variation. A closed loop control algorithm is used to change the capacitors continually, which can compensate mismatches and adjust output power simultaneously. The proposed adaptive IMN IWPT system is working at 125 kHz for 2 W power delivered to load. Comparing with the series resonant IWPT system and fixed IMN IWPT system, the power transfer efficiency of our system increases up to 31.79% and 60% when the coupling coefficient varies in a large range from 0.05 to 0.8 for 2 W output power.

  15. An Adaptive Impedance Matching Network with Closed Loop Control Algorithm for Inductive Wireless Power Transfer

    Science.gov (United States)

    Miao, Zhidong; Liu, Dake

    2017-01-01

    For an inductive wireless power transfer (IWPT) system, maintaining a reasonable power transfer efficiency and a stable output power are two most challenging design issues, especially when coil distance varies. To solve these issues, this paper presents a novel adaptive impedance matching network (IMN) for IWPT system. In our adaptive IMN IWPT system, the IMN is automatically reconfigured to keep matching with the coils and to adjust the output power adapting to coil distance variation. A closed loop control algorithm is used to change the capacitors continually, which can compensate mismatches and adjust output power simultaneously. The proposed adaptive IMN IWPT system is working at 125 kHz for 2 W power delivered to load. Comparing with the series resonant IWPT system and fixed IMN IWPT system, the power transfer efficiency of our system increases up to 31.79% and 60% when the coupling coefficient varies in a large range from 0.05 to 0.8 for 2 W output power. PMID:28763011

  16. Low-power, enhanced-gain adaptive-biasing-based Operational Transconductance Amplifiers

    DEFF Research Database (Denmark)

    Moradi, Farshad

    A symmetrical PMOS OTA (Operational Transconductance Amplifier) is used to build an advanced rail-to-rail amplifier with improved DC-gain and reduced power consumption. By using the adaptive biasing circuit for two differential inputs, a low stand-by current can be achieved, reducing power...

  17. Adaptive control of power supply for integrated circuits

    NARCIS (Netherlands)

    2012-01-01

    The present invention relates to a circuit arrangement and method for controlling power supply in an integrated circuit wherein at least one working parameter of at least one electrically isolated circuit region (10) is monitored, and the conductivity of a variable resistor means is locally

  18. The development of the intelligent diagnostic expert system for high power dye-laser MOPA system

    International Nuclear Information System (INIS)

    Liu Lianhua; Yang Wenxi; Zhang Xiaowei; Dan Yongjun

    2014-01-01

    A intelligent diagnostic expert system was required to simulate the expert thinking process of solving problem in experiment and to real-time judge the running state of the experiment system. The intelligent diagnostic expert system for dye-laser MOPA system was build with the modular design of separated knowledge base and inference engine, the RETE algorithm rules match, the asynchronous operation, and multithreading technology. The experiment result indicated that the system could real-time analysis and diagnose the running state of dye-laser MOPA system with advantages of high diagnosis efficiency, good instantaneity and strong expansibility. (authors)

  19. Social collective intelligence combining the powers of humans and machines to build a smarter society

    CERN Document Server

    Miorandi, Daniele; Rovatsos, Michael

    2014-01-01

    The book focuses on Social Collective Intelligence, a term used to denote a class of socio-technical systems that combine, in a coordinated way, the strengths of humans, machines and collectives in terms of competences, knowledge and problem solving capabilities with the communication, computing and storage capabilities of advanced ICT.Social Collective Intelligence opens a number of challenges for researchers in both computer science and social sciences; at the same time it provides an innovative approach to solve challenges in diverse application domains, ranging from health to education

  20. Adaptive discrete rate and power transmission for spectrum sharing systems

    KAUST Repository

    Abdallah, Mohamed M.

    2012-04-01

    In this paper we develop a framework for optimizing the performance of the secondary link in terms of the average spectral efficiency assuming quantized channel state information (CSI) of the secondary and the secondary-to-primary interference channels available at the secondary transmitter. We consider the problem under the constraints of maximum average interference power levels at the primary receiver. We develop a sub-optimal computationally efficient iterative algorithm for finding the optimal CSI quantizers as well as the discrete power and rate employed at the cognitive transmitter for each quantized CSI level so as to maximize the average spectral efficiency. We show via analysis and simulations that the proposed algorithm converges for Rayleigh fading channels. Our numerical results give the number of bits required to sufficiently represent the CSI to achieve almost the maximum average spectral efficiency attained using full knowledge of the CSI. © 2012 IEEE.

  1. Performance analysis of joint diversity combining, adaptive modulation, and power control schemes

    KAUST Repository

    Qaraqe, Khalid A.

    2011-01-01

    Adaptive modulation and diversity combining represent very important adaptive solutions for future generations of wireless communication systems. Indeed, in order to improve the performance and the efficiency of these systems, these two techniques have been recently used jointly in new schemes named joint adaptive modulation and diversity combining (JAMDC) schemes. Considering the problem of finding low hardware complexity, bandwidth-efficient, and processing-power efficient transmission schemes for a downlink scenario and capitalizing on some of these recently proposed JAMDC schemes, we propose and analyze in this paper three joint adaptive modulation, diversity combining, and power control (JAMDCPC) schemes where a constant-power variable-rate adaptive modulation technique is used with an adaptive diversity combining scheme and a common power control process. More specifically, the modulation constellation size, the number of combined diversity paths, and the needed power level are jointly determined to achieve the highest spectral efficiency with the lowest possible processing power consumption quantified in terms of the average number of combined paths, given the fading channel conditions and the required bit error rate (BER) performance. In this paper, the performance of these three JAMDCPC schemes is analyzed in terms of their spectral efficiency, processing power consumption, and error-rate performance. Selected numerical examples show that these schemes considerably increase the spectral efficiency of the existing JAMDC schemes with a slight increase in the average number of combined paths for the low signal-to-noise ratio range while maintaining compliance with the BER performance and a low radiated power which yields to a substantial decrease in interference to co-existing users and systems. © 2011 IEEE.

  2. Performance assessment of electric power generations using an adaptive neural network algorithm and fuzzy DEA

    Energy Technology Data Exchange (ETDEWEB)

    Javaheri, Zahra

    2010-09-15

    Modeling, evaluating and analyzing performance of Iranian thermal power plants is the main goal of this study which is based on multi variant methods analysis. These methods include fuzzy DEA and adaptive neural network algorithm. At first, we determine indicators, then data is collected, next we obtained values of ranking and efficiency by Fuzzy DEA, Case study is thermal power plants In view of the fact that investment to establish on power plant is very high, and maintenance of power plant causes an expensive expenditure, moreover using fossil fuel effected environment hence optimum produce of current power plants is important.

  3. Adaptation of thermal power plants: The (ir)relevance of climate (change) information

    International Nuclear Information System (INIS)

    Bogmans, Christian W.J.; Dijkema, Gerard P.J.; Vliet, Michelle T.H. van

    2017-01-01

    When does climate change information lead to adaptation? We analyze thermal power plant adaptation by means of investing in water-saving (cooling) technology to prevent a decrease in plant efficiency and load reduction. A comprehensive power plant investment model, forced with downscaled climate and hydrological projections, is then numerically solved to analyze the adaptation decisions of a selection of real power plants. We find that operators that base their decisions on current climatic conditions are likely to make identical choices and perform just as well as operators that are fully ‘informed’ about climate change. Where electricity supply is mainly generated by thermal power plants, heat waves, droughts and low river flow may impact electricity supply for decades to come. - Highlights: • We analyze adaptation to climate change by thermal power plants. • A numerical investment model is applied to a coal plant and a nuclear power plant. • The numerical analysis is based on climate and hydrological projections. • Climate change information has a relatively small effect on a power plant's NPV. • Uncertainty and no-regret benefits lower the value of climate change information.

  4. Development of Intelligent Database Program for PSI/ISI Data Management of Nuclear Power Plant (Part II)

    International Nuclear Information System (INIS)

    Park, Un Su; Park, Ik Keun; Um, Byong Guk; Lee, Jong Po; Han, Chi Hyun

    2000-01-01

    In a previous paper, we have discussed the intelligent Windows 95-based data management program(IDPIN) which was developed for effective and efficient management of large amounts of pre-/in-service inspection(PSI/ISI) data of Kori nuclear power plants. The IDPIN program enables the prompt extraction of previously conducted PSI/ISI conditions and results so that the time-consuming data management, painstaking data processing and analysis of the past are avoided. In this study, the intelligent Windows based data management program(WS-IDPIN) has been developed as an effective data management of PSI/ISI data for the Wolsong nuclear power plants. The WS-IDPIN program includes the modules of comprehensive management and analysis of PSI/ISI results, statistical reliability assessment program of PSI/ISI results(depth and length sizing performance etc), standardization of UT report form and computerization of UT results. In addition, the program can be further developed as a unique PSI/ISI data management expert system which can be part of the PSI/ISI total support system for Korean nuclear power plants

  5. Development of Power Controller System based on Model Reference Adaptive Control for a Nuclear Reactor

    International Nuclear Information System (INIS)

    Mohd Sabri Minhat; Izhar Abu Hussin; Ridzuan Abdul Mutalib

    2014-01-01

    The Reactor TRIGA PUSPATI (RTP)-type TRIGA Mark II was installed in the year 1982. The Power Controller System (PCS) or Automated Power Controller System (APCS) is very important for reactor operation and safety reasons. It is a function of controlled reactivity and reactor power. The existing power controller system is under development and due to slow response, low accuracy and low stability on reactor power control affecting the reactor safety. The nuclear reactor is a nonlinear system in nature, and it is power increases continuously with time. The reactor parameters vary as a function of power, fuel burnup and control rod worth. The output power value given by the power control system is not exactly as real value of reactor power. Therefore, controller system design is very important, an adaptive controller seems to be inevitable. The method chooses is a linear controller by using feedback linearization, for example Model Reference Adaptive Control. The developed APCS for RTP will be design by using Model Reference Adaptive Control (MRAC). The structured of RTP model to produce the dynamic behaviour of RTP on entire operating power range from 0 to 1MWatt. The dynamic behavior of RTP model is produced by coupling of neutronic and thermal-hydraulics. It will be developed by using software MATLAB/Simulink and hardware module card to handle analog input signal. A new algorithm for APCS is developed to control the movement of control rods with uniformity and orderly for RTP. Before APCS test to real plant, simulation results shall be obtained from RTP model on reactor power, reactivity, period, control rod positions, fuel and coolant temperatures. Those data are comparable with the real data for validation. After completing the RTP model, APCS will be tested to real plant on power control system performance by using real signal from RTP including fail-safe operation, system reliable, fast response, stability and accuracy. The new algorithm shall be a satisfied

  6. Is adaptation of the word accentuation test of premorbid intelligence necessary for use among older, Spanish-speaking immigrants in the United States?

    Science.gov (United States)

    Schrauf, Robert W; Weintraub, Sandra; Navarro, Ellen

    2006-05-01

    Adaptations of the National Adult Reading Test (NART) for assessing premorbid intelligence in languages other than English requires (a) generating word-items that are rare and do not follow grapheme-to-phoneme mappings common in that language, and (b) subsequent validation against a cognitive battery normed on the population of interest. Such tests exist for Italy, France, Spain, and Argentina, all normed against national versions of the Wechsler Adult Intelligence Scale. Given the varieties of Spanish spoken in the United States, the adaptation of the Spanish Word Accentuation Test (WAT) requires re-validating the original word list, plus possible new items, against a cognitive battery that has been normed on Spanish-speakers from many countries. This study reports the generation of 55 additional words and revalidation in a sample of 80 older, Spanish-dominant immigrants. The Batería Woodcock-Muñoz Revisada (BWM-R), normed on Spanish speakers from six countries and five U.S. states, was used to establish criterion validity. The original WAT word list accounted for 77% of the variance in the BWM-R and 58% of the variance in Ravens Colored Progressive Matrices, suggesting that the unmodified list possesses adequate predictive validity as an indicator of intelligence. Regression equations are provided for estimating BWM-R and Ravens scores from WAT scores.

  7. An Adaptive Power Efficient Packet Scheduling Algorithm for Wimax Networks

    OpenAIRE

    R Murali Prasad; P. Satish Kumar

    2010-01-01

    Admission control schemes and scheduling algorithms are designed to offer QoS services in 802.16/802.16e networks and a number of studies have investigated these issues. But the channel condition and priority of traffic classes are very rarely considered in the existing scheduling algorithms. Although a number of energy saving mechanisms have been proposed for the IEEE 802.16e, to minimize the power consumption of IEEE 802.16e mobile stations with multiple real-time connections has not yet be...

  8. General William Slim and the Power of Emotional and Cultural Intelligence in Multinational and Multicultural Operations

    Science.gov (United States)

    2015-06-12

    other six intelligences identified by Gardner were musical -rhythmic, visual-spatial, verbal-linguistic, logical-mathematical, bodily-kinesthetic and...support those traditions by officially sanctioning cultural festivals and respecting the religious diversity of the Indian subcontinent. Of course...

  9. Social collective intelligence: combining the powers of humans and machines to build a smarter society

    NARCIS (Netherlands)

    Miorandi, Daniele; Maltese, Vincenzo; Rovatsos, Michael; Nijholt, Antinus; Stewart, James

    2014-01-01

    The book focuses on Social Collective Intelligence, a term used to denote a class of socio-technical systems that combine, in a coordinated way, the strengths of humans, machines and collectives in terms of competences, knowledge and problem solving capabilities with the communication, computing and

  10. The application of artificial intelligence chemistry diagnostic system to nuclear power plants

    International Nuclear Information System (INIS)

    Chen Meizhen

    1996-01-01

    By processing water chemistry data to diagnose sensor and equipment malfunctions in realtime, artificial intelligence chemistry diagnostic system helps to reduce the plant downtime due to steam generator tubing failures and other accidents. A typical processing system of water chemistry data is presented

  11. Validating Intelligent Power and Energy Systems { A Discussion of Educational Needs

    DEFF Research Database (Denmark)

    Kotsampopoulos, P.; Hatziargyriou, N.; Strasser, T. I.

    2017-01-01

    /future researchers and engineers is becoming more and more necessary. This paper identifies educational and training needs addressing the higher complexity of intelligent energy systems. Education needs and requirements are discussed, such as the development of systems-oriented skills and cross-disciplinary learning...

  12. An adaptive interface (KNOWBOT) for nuclear power industry data bases

    International Nuclear Information System (INIS)

    Heger, A.S.

    1989-01-01

    An adaptive interface, KNOWBOT, has been designed to solve some of the problems that face the users of large centralized databases. The interface applies the neural network approach to information retrieval from a database. The database is a subset of the Nuclear Plant Reliability Data System (NPRDS). KNOWBOT preempts an existing database interface and works in conjunction with it. By design, KNOWBOT starts as a tabula rasa but acquires knowledge through its interactions with the user and the database. The interface uses its gained knowledge to personalize the database retrieval process and to induce new queries. In addition, the interface forgets the information that is no longer needed by the user. These self-organizing features of the interface reduce the scope of the database to the subsets that are highly relevant to the user needs. A proof-of-principle version of this interface has been implemented in Common LISP on a Texas Instruments Explorer I workstation. Experiments with KNOWBOT have successfully demonstrated the robustness of the model especially with induction and self-organization

  13. Design of an Adaptive Power Regulation Mechanism and a Nozzle for a Hydroelectric Power Plant Turbine Test Rig

    Science.gov (United States)

    Mert, Burak; Aytac, Zeynep; Tascioglu, Yigit; Celebioglu, Kutay; Aradag, Selin; ETU Hydro Research Center Team

    2014-11-01

    This study deals with the design of a power regulation mechanism for a Hydroelectric Power Plant (HEPP) model turbine test system which is designed to test Francis type hydroturbines up to 2 MW power with varying head and flow(discharge) values. Unlike the tailor made regulation mechanisms of full-sized, functional HEPPs; the design for the test system must be easily adapted to various turbines that are to be tested. In order to achieve this adaptability, a dynamic simulation model is constructed in MATLAB/Simulink SimMechanics. This model acquires geometric data and hydraulic loading data of the regulation system from Autodesk Inventor CAD models and Computational Fluid Dynamics (CFD) analysis respectively. The dynamic model is explained and case studies of two different HEPPs are performed for validation. CFD aided design of the turbine guide vanes, which is used as input for the dynamic model, is also presented. This research is financially supported by Turkish Ministry of Development.

  14. Adaptive neuro-fuzzy inference system to improve the power quality of a split shaft microturbine power generation system

    Science.gov (United States)

    Oğuz, Yüksel; Üstün, Seydi Vakkas; Yabanova, İsmail; Yumurtaci, Mehmet; Güney, İrfan

    2012-01-01

    This article presents design of adaptive neuro-fuzzy inference system (ANFIS) for the turbine speed control for purpose of improving the power quality of the power production system of a split shaft microturbine. To improve the operation performance of the microturbine power generation system (MTPGS) and to obtain the electrical output magnitudes in desired quality and value (terminal voltage, operation frequency, power drawn by consumer and production power), a controller depended on adaptive neuro-fuzzy inference system was designed. The MTPGS consists of the microturbine speed controller, a split shaft microturbine, cylindrical pole synchronous generator, excitation circuit and voltage regulator. Modeling of dynamic behavior of synchronous generator driver with a turbine and split shaft turbine was realized by using the Matlab/Simulink and SimPowerSystems in it. It is observed from the simulation results that with the microturbine speed control made with ANFIS, when the MTPGS is operated under various loading situations, the terminal voltage and frequency values of the system can be settled in desired operation values in a very short time without significant oscillation and electrical production power in desired quality can be obtained.

  15. Adaptations of renewable energy policies to unstable macroeconomic situations - case study: wind power in Brazil

    Energy Technology Data Exchange (ETDEWEB)

    Kissel, J.M. [Technical University, Berlin (Germany). Dept. of Renewable Energies; Federal University, Rio de Janeiro (Brazil); World Council for Renewable Energy, Rio de Janeiro (Brazil); Krauter, S.C.W. [Technical University, Berlin (Germany). Dept. of Renewable Energies; World Council for Renewable Energy, Rio de Janeiro (Brazil); State University of Ceara (Brazil). Dept. of Physics

    2006-12-15

    Despite the massive cost reduction in the last decade, wind power generation is generally still more expensive than conventional energy sources which benefit from the exclusion of externality costs in the price structure. Support policies for renewable energies guarantee the economic viability of this type of electrical power generation in many European countries. In Latin America, Brazil has become the pioneer state for renewable energy with the implementation of the PROINFA programme that supports, among other sources, wind power development of 1100 MW. This article presents an overview of the differences between the German and Brazilian wind power promotion policies with a special focus on how PROINFA can be adapted to the unstable macroeconomic situation of Brazil. The document specifically examines the adaptation of wind power promotion policies to large inflation and interest rates in Brazil. (author)

  16. Adaptations of renewable energy policies to unstable macroeconomic situations-Case study: Wind power in Brazil

    Energy Technology Data Exchange (ETDEWEB)

    Kissel, Johannes M. [Department of Renewable Energies, Institute for Energy and Control Technology, Technical University Berlin (TUB), Sec. EM 4, Einsteinufer 11, D-10587 Berlin (Germany) and Federal University of Rio de Janeiro (UFRJ-COPPE), Programme for Energy Planning, Rio de Janeiro-RJ (Brazil) and World Council for Renewable Energy-Latin America - WCRE LA, c/o Rio Solar Ltda./PML, Av. Rio Branco, 25/18o andar, 20093-900 Rio de Janeiro-RJ (Brazil)]. E-mail: jo.kissel@gmx.net; Krauter, Stefan C.W. [Department of Renewable Energies, Institute for Energy and Control Technology, Technical University Berlin (TUB), Sec. EM 4, Einsteinufer 11, D-10587 Berlin (Germany) and World Council for Renewable Energy-Latin America (WCRE LA), c/o Rio Solar Ltda./PML, Av. Rio Branco, 25/18o andar, 20093-900 Rio de Janeiro-RJ (Brazil) and Department of Physics, State University of Ceara - UECE, Alternative Energy Group, Av. Paranjana 1700, Campus do Itaperi, Fortaleza 60740-000 CE (Brazil)]. E-mail: krauter@uece.br

    2006-12-15

    Despite the massive cost reduction in the last decade, wind power generation is generally still more expensive than conventional energy sources which benefit from the exclusion of externality costs in the price structure. Support policies for renewable energies guarantee the economic viability of this type of electrical power generation in many European countries. In Latin America, Brazil has become the pioneer state for renewable energy with the implementation of the PROINFA programme that supports, among other sources, wind power development of 1100 MW. This article presents an overview of the differences between the German and Brazilian wind power promotion policies with a special focus on how PROINFA can be adapted to the unstable macroeconomic situation of Brazil. The document specifically examines the adaptation of wind power promotion policies to large inflation and interest rates in Brazil.

  17. Adaptations of renewable energy policies to unstable macroeconomic situations-Case study: Wind power in Brazil

    International Nuclear Information System (INIS)

    Kissel, Johannes M.; Krauter, Stefan C.W.

    2006-01-01

    Despite the massive cost reduction in the last decade, wind power generation is generally still more expensive than conventional energy sources which benefit from the exclusion of externality costs in the price structure. Support policies for renewable energies guarantee the economic viability of this type of electrical power generation in many European countries. In Latin America, Brazil has become the pioneer state for renewable energy with the implementation of the PROINFA programme that supports, among other sources, wind power development of 1100 MW. This article presents an overview of the differences between the German and Brazilian wind power promotion policies with a special focus on how PROINFA can be adapted to the unstable macroeconomic situation of Brazil. The document specifically examines the adaptation of wind power promotion policies to large inflation and interest rates in Brazil

  18. Adaptive Reactive Power Control of PV Power Plants for Improved Power Transfer Capability under Ultra-Weak Grid Conditions

    DEFF Research Database (Denmark)

    Yang, Dongsheng; Wang, Xiongfei; Liu, Fangcheng

    2018-01-01

    with the unity power factor. Then, considering the reactive power compensation from PV inverters, the minimum SCR in respect to Power Factor (PF) is derived, and the optimized coordination of the active and reactive power is exploited. It is revealed that the power transfer capability of PV power plant under...... of a 200 MW PV power plant demonstrate that the proposed method can ensure the rated power transfer of PV power plant with the SCR of 1.25, provided that the PV inverters are operated with the minimal PF=0.9.......This paper analyzes the power transfer limitation of the PV power plant under the ultra-weak grid condition, i.e., when the Short-Circuit Ratio (SCR) is close to 1. It explicitly identifies that a minimum SCR of 2 is required for the PV power plant to deliver the rated active power when operating...

  19. Adaptive Transcutaneous Power Transfer to Implantable Devices: A State of the Art Review.

    Science.gov (United States)

    Bocan, Kara N; Sejdić, Ervin

    2016-03-18

    Wireless energy transfer is a broad research area that has recently become applicable to implantable medical devices. Wireless powering of and communication with implanted devices is possible through wireless transcutaneous energy transfer. However, designing wireless transcutaneous systems is complicated due to the variability of the environment. The focus of this review is on strategies to sense and adapt to environmental variations in wireless transcutaneous systems. Adaptive systems provide the ability to maintain performance in the face of both unpredictability (variation from expected parameters) and variability (changes over time). Current strategies in adaptive (or tunable) systems include sensing relevant metrics to evaluate the function of the system in its environment and adjusting control parameters according to sensed values through the use of tunable components. Some challenges of applying adaptive designs to implantable devices are challenges common to all implantable devices, including size and power reduction on the implant, efficiency of power transfer and safety related to energy absorption in tissue. Challenges specifically associated with adaptation include choosing relevant and accessible parameters to sense and adjust, minimizing the tuning time and complexity of control, utilizing feedback from the implanted device and coordinating adaptation at the transmitter and receiver.

  20. Adaptive Transcutaneous Power Transfer to Implantable Devices: A State of the Art Review

    Directory of Open Access Journals (Sweden)

    Kara N. Bocan

    2016-03-01

    Full Text Available Wireless energy transfer is a broad research area that has recently become applicable to implantable medical devices. Wireless powering of and communication with implanted devices is possible through wireless transcutaneous energy transfer. However, designing wireless transcutaneous systems is complicated due to the variability of the environment. The focus of this review is on strategies to sense and adapt to environmental variations in wireless transcutaneous systems. Adaptive systems provide the ability to maintain performance in the face of both unpredictability (variation from expected parameters and variability (changes over time. Current strategies in adaptive (or tunable systems include sensing relevant metrics to evaluate the function of the system in its environment and adjusting control parameters according to sensed values through the use of tunable components. Some challenges of applying adaptive designs to implantable devices are challenges common to all implantable devices, including size and power reduction on the implant, efficiency of power transfer and safety related to energy absorption in tissue. Challenges specifically associated with adaptation include choosing relevant and accessible parameters to sense and adjust, minimizing the tuning time and complexity of control, utilizing feedback from the implanted device and coordinating adaptation at the transmitter and receiver.

  1. Adaptive automatic generation control with superconducting magnetic energy storage in power systems

    International Nuclear Information System (INIS)

    Tripathy, S.C.; Balasubramanian, R.; Nair, P.S.C.

    1992-01-01

    An improved automatic generation control (AGC) employing self-tuning adaptive control for both main AGC loop and superconducting magnetic energy storage (SMES) is presented in this paper. Computer simulations on a two-area interconnected power system show that the proposed adaptive control scheme is very effective in damping out oscillations caused by load disturbances and its performance is quite insensitive to controller gain parameter changes of SMES. A comprehensive comparative performance evaluation of control schemes using adaptive and non-adaptive controllers in the main AGC and in the SMES control loops is presented. The improvement in performance brought in by the adaptive scheme is particularly pronounced for load changes of random magnitude and duration. The proposed controller can be easily implemented using microprocessors

  2. Intelligent Sensors for Integrated Systems Health Management (ISHM)

    Science.gov (United States)

    Schmalzel, John L.

    2008-01-01

    IEEE 1451 Smart Sensors contribute to a number of ISHM goals including cost reduction achieved through: a) Improved configuration management (TEDS); and b) Plug-and-play re-configuration. Intelligent Sensors are adaptation of Smart Sensors to include ISHM algorithms; this offers further benefits: a) Sensor validation. b) Confidence assessment of measurement, and c) Distributed ISHM processing. Space-qualified intelligent sensors are possible a) Size, mass, power constraints. b) Bus structure/protocol.

  3. Games and machine learning: a powerful combination in an artificial intelligence course

    Science.gov (United States)

    Wallace, Scott A.; McCartney, Robert; Russell, Ingrid

    2010-03-01

    Project MLeXAI (Machine Learning eXperiences in Artificial Intelligence (AI)) seeks to build a set of reusable course curriculum and hands on laboratory projects for the artificial intelligence classroom. In this article, we describe two game-based projects from the second phase of project MLeXAI: Robot Defense - a simple real-time strategy game and Checkers - a classic turn-based board game. From the instructors' prospective, we examine aspects of design and implementation as well as the challenges and rewards of using the curricula. We explore students' responses to the projects via the results of a common survey. Finally, we compare the student perceptions from the game-based projects to non-game based projects from the first phase of Project MLeXAI.

  4. Expert systems intelligent tutoring systems and the power industry: A future scenario

    International Nuclear Information System (INIS)

    Bloom, C.P.; Bullemer, P.T.; Cochran, E.L.

    1990-01-01

    One use to which fielded expert systems have been put is the training of less experienced personnel. However, since expert systems are not developed for the purpose of training, their knowledge contains gaps, particularly in the areas of explanation and reasoning-essential components of expertise. The incidental learning that results from interacting with an expert system produces a memorization of the expert system's procedures without an understanding of the logic behind those procedures. Although learning without comprehension can provide adequate task performance, it affords inadequate transfer or generalization of knowledge, producing task-specific learning. In other words, the expert system user performs the task like an expert, but has not really become an expert. To become an expert, specialized training is required. This training could be provided by professional educators, or, in the future, by artificial intelligence programs, called intelligent tutoring systems, specifically designed for training

  5. Economic power schedule and transactive energy through an intelligent centralized energy management system for a DC residential distribution system

    DEFF Research Database (Denmark)

    Yue, Jingpeng; Hu, Zhijian; Li, Chendan

    2017-01-01

    Direct current (DC) residential distribution systems (RDS) consisting of DC living homes will be a significant integral part of future green transmission. Meanwhile, the increasing number of distributed resources and intelligent devices will change the power flow between the main grid...... (CEMS), but also a control approach to implement and ensure DG output voltages to various DC buses in a DC RDS. Based on data collection, prediction and a certain objectives, the expert system in a CEMS can work out the optimization schedule, after this, the voltage droop control for steady voltage...... is aligned with the command of the unit power schedule. In this work, a DC RDS is used as a case study to demonstrate the process, the RDS is associated with unit economic models, and a cost minimization objective is proposed that is to be achieved based on the real-time electrical price. The results show...

  6. Intelligent Speed Adaptation

    DEFF Research Database (Denmark)

    Madsen, Jesper Runge

    2002-01-01

    This paper presents a research project developed at Aalborg University in Denmark. The paper describes how log data from a system was handled after collection while also analysing some of the behavioral changes from the test-drivers....

  7. Flight Test Results from the NF-15B Intelligent Flight Control System (IFCS) Project with Adaptation to a Simulated Stabilator Failure

    Science.gov (United States)

    Bosworth, John T.; Williams-Hayes, Peggy S.

    2010-01-01

    Adaptive flight control systems have the potential to be more resilient to extreme changes in airplane behavior. Extreme changes could be a result of a system failure or of damage to the airplane. A direct adaptive neural-network-based flight control system was developed for the National Aeronautics and Space Administration NF-15B Intelligent Flight Control System airplane and subjected to an inflight simulation of a failed (frozen) (unmovable) stabilator. Formation flight handling qualities evaluations were performed with and without neural network adaptation. The results of these flight tests are presented. Comparison with simulation predictions and analysis of the performance of the adaptation system are discussed. The performance of the adaptation system is assessed in terms of its ability to decouple the roll and pitch response and reestablish good onboard model tracking. Flight evaluation with the simulated stabilator failure and adaptation engaged showed that there was generally improvement in the pitch response; however, a tendency for roll pilot-induced oscillation was experienced. A detailed discussion of the cause of the mixed results is presented.

  8. Intelligence in Artificial Intelligence

    OpenAIRE

    Datta, Shoumen Palit Austin

    2016-01-01

    The elusive quest for intelligence in artificial intelligence prompts us to consider that instituting human-level intelligence in systems may be (still) in the realm of utopia. In about a quarter century, we have witnessed the winter of AI (1990) being transformed and transported to the zenith of tabloid fodder about AI (2015). The discussion at hand is about the elements that constitute the canonical idea of intelligence. The delivery of intelligence as a pay-per-use-service, popping out of ...

  9. Intelligent speed adaptation as an assistive device for drivers with acquired brain injury: a single-case field experiment.

    Science.gov (United States)

    Klarborg, Brith; Lahrmann, Harry; NielsAgerholm; Tradisauskas, Nerius; Harms, Lisbeth

    2012-09-01

    Intelligent speed adaptation (ISA) was tested as an assistive device for drivers with an acquired brain injury (ABI). The study was part of the "Pay as You Speed" project (PAYS) and used the same equipment and technology as the main study (Lahrmann et al., in press-a, in press-b). Two drivers with ABI were recruited as subjects and had ISA equipment installed in their private vehicle. Their speed was logged with ISA equipment for a total of 30 weeks of which 12 weeks were with an active ISA user interface (6 weeks=Baseline 1; 12 weeks=ISA period; 12 weeks=Baseline 2). The subjects participated in two semi-structured interviews concerning their strategies for driving with ABI and for driving with ISA. Furthermore, they gave consent to have data from their clinical journals and be a part of the study. The two subjects did not report any instances of being distracted or confused by ISA, and in general they described driving with ISA as relaxed. ISA reduced the percentage of the total distance that was driven with a speed above the speed limit (PDA), but the subjects relapsed to their previous PDA level in Baseline 2. This suggests that ISA is more suited as a permanent assistive device (i.e. cognitive prosthesis) than as a temporary training device. As ABI is associated with a multitude of cognitive deficits, we developed a conceptual framework, which focused on the cognitive parameters that have been shown to relate to speeding behaviour, namely "intention to speed" and "inattention to speeding". The subjects' combined status on the two independent parameters made up their "speeding profile". A comparison of the speeding profiles and the speed logs indicated that ISA in the present study was more efficient in reducing inattention to speeding than affecting intention to speed. This finding suggests that ISA might be more suited for some neuropsychological profiles than for others, and that customisation of ISA for different neuropsychological profiles may be required

  10. An Energy-Efficient Link with Adaptive Transmit Power Control for Long Range Networks

    DEFF Research Database (Denmark)

    Lynggaard, P.; Blaszczyk, Tomasz

    2016-01-01

    A considerable amount of research is carried out to develop a reliable smart sensor system with high energy efficiency for battery operated wireless IoT devices in the agriculture sector. However, only a limited amount of research has covered automatic transmission power adjustment schemes...... and algorithms which are essential for deployment of wireless IoT nodes. This paper presents an adaptive link algorithm for farm applications with emphasis on power adjustment for long range communication networks....

  11. Adaptive reactive power control of PV power plants for improved power transfer capability under ultra-weak grid conditions

    DEFF Research Database (Denmark)

    Yang, Dongsheng; Wang, Xiongfei; Liu, Fangcheng

    2017-01-01

    The Photovoltaic (PV) power plants are usually deployed in remote areas with the high solar irradiance, and their power transfer capabilities can be greatly limited by the large impedance of long-distance transmission lines. This paper investigates first the power transfer limit of the PV power p...

  12. Climate and water resource change impacts and adaptation potential for US power supply

    Science.gov (United States)

    Miara, Ariel; Macknick, Jordan E.; Vörösmarty, Charles J.; Tidwell, Vincent C.; Newmark, Robin; Fekete, Balazs

    2017-11-01

    Power plants that require cooling currently (2015) provide 85% of electricity generation in the United States. These facilities need large volumes of water and sufficiently cool temperatures for optimal operations, and projected climate conditions may lower their potential power output and affect reliability. We evaluate the performance of 1,080 thermoelectric plants across the contiguous US under future climates (2035-2064) and their collective performance at 19 North American Electric Reliability Corporation (NERC) sub-regions. Joint consideration of engineering interactions with climate, hydrology and environmental regulations reveals the region-specific performance of energy systems and the need for regional energy security and climate-water adaptation strategies. Despite climate-water constraints on individual plants, the current power supply infrastructure shows potential for adaptation to future climates by capitalizing on the size of regional power systems, grid configuration and improvements in thermal efficiencies. Without placing climate-water impacts on individual plants in a broader power systems context, vulnerability assessments that aim to support adaptation and resilience strategies misgauge the extent to which regional energy systems are vulnerable. Climate-water impacts can lower thermoelectric reserve margins, a measure of systems-level reliability, highlighting the need to integrate climate-water constraints on thermoelectric power supply into energy planning, risk assessments, and system reliability management.

  13. A novel power swing blocking scheme using adaptive neuro-fuzzy inference system

    Energy Technology Data Exchange (ETDEWEB)

    Zadeh, Hassan Khorashadi; Li, Zuyi [Illinois Institute of Technology, Department of Electrical and Computer Engineering, 3301 S. Dearborn Street, Chicago, IL 60616 (United States)

    2008-07-15

    A power swing may be caused by any sudden change in the configuration or the loading of an electrical network. During a power swing, the impedance locus moves along an impedance circle with possible encroachment into the distance relay zone, which may cause an unnecessary tripping. In order to prevent the distance relay from tripping under such condition, a novel power swing blocking (PSB) scheme is proposed in this paper. The proposed scheme uses an adaptive neuro-fuzzy inference systems (ANFIS) for preventing distance relay from tripping during power swings. The input signals to ANFIS, include the change of positive sequence impedance, positive and negative sequence currents, and power swing center voltage. Extensive tests show that the proposed PSB has two distinct features that are advantageous over existing schemes. The first is that the proposed scheme is able to detect various kinds of power swings thus block distance relays during power swings, even if the power swings are fast or the power swings occur during single pole open conditions. The second distinct feature is that the proposed scheme is able to clear the blocking if faults occur within the relay trip zone during power swings, even if the faults are high resistance faults, or the faults occur at the power swing center, or the faults occur when the power angle is close to 180 . (author)

  14. On the proposal of an intelligent support system with a cognitive architecture based on contextual modules for the operators of nuclear power plants

    International Nuclear Information System (INIS)

    Soares, Herculano Vieira; Alvarenga, Marco Antonio Bayout; Schirru, Roberto

    2007-01-01

    The operators' actions in a control room of a nuclear power plant are controlled by production rules in the emergency procedures of the operation manual. For each accident, there is a specific group of safety tasks composed of a set of specified actions. In this work we propose an intelligent support system based on a cognitive architecture composed of contextual modules, instead of functional modules. This approach consists on the determination of a task space, where we can define subspaces. In the subspaces where the set of values of the parameters is familiar, at least one of the rules in the procedural memory has its conditions completely satisfied. In this context, the proposed support system will be guided by an expert system, with a procedural memory composed of IF - THEN rules, that contains the input conditions with strict values of the parameters in the IF part, and a corresponding safety task in the THEN part. When the operator is in a situation in which the set of values of those variables falls in a non-familiar context, none of the rules in the procedural memory will have its conditions completely satisfied. In this context, it will be, then, utilized the connectionist part of the architecture, a fuzzy neural network (with radial activation functions), to classify the set of parameters and to choose a set of safety tasks applicable to the situation. The fuzzy logic provides an inference mechanism under uncertainty, while the neural network offers advantages of learning, adaptation, failure tolerance, parallelism and generalization. (author)

  15. Daily Average Wind Power Interval Forecasts Based on an Optimal Adaptive-Network-Based Fuzzy Inference System and Singular Spectrum Analysis

    Directory of Open Access Journals (Sweden)

    Zhongrong Zhang

    2016-01-01

    Full Text Available Wind energy has increasingly played a vital role in mitigating conventional resource shortages. Nevertheless, the stochastic nature of wind poses a great challenge when attempting to find an accurate forecasting model for wind power. Therefore, precise wind power forecasts are of primary importance to solve operational, planning and economic problems in the growing wind power scenario. Previous research has focused efforts on the deterministic forecast of wind power values, but less attention has been paid to providing information about wind energy. Based on an optimal Adaptive-Network-Based Fuzzy Inference System (ANFIS and Singular Spectrum Analysis (SSA, this paper develops a hybrid uncertainty forecasting model, IFASF (Interval Forecast-ANFIS-SSA-Firefly Alogorithm, to obtain the upper and lower bounds of daily average wind power, which is beneficial for the practical operation of both the grid company and independent power producers. To strengthen the practical ability of this developed model, this paper presents a comparison between IFASF and other benchmarks, which provides a general reference for this aspect for statistical or artificially intelligent interval forecast methods. The comparison results show that the developed model outperforms eight benchmarks and has a satisfactory forecasting effectiveness in three different wind farms with two time horizons.

  16. Adaptive control algorithm for improving power capture of wind turbines in turbulent winds

    DEFF Research Database (Denmark)

    Diaz-Guerra, Lluis; Adegas, Fabiano Daher; Stoustrup, Jakob

    2012-01-01

    , the complex and time-varying aerodynamics a WT face due to turbulent winds make their determination a hard task. The selected constant parameters may maximize energy for a particular, but not all, wind regime conditions. Adaptivity can modify the controller to increase power capture under variable wind...

  17. An adaptive control application in a large thermal combined power plant

    International Nuclear Information System (INIS)

    Kocaarslan, Ilhan; Cam, Ertugrul

    2007-01-01

    In this paper, an adaptive controller was applied to a 765 MW large thermal power plant to decrease operating costs, increase quality of generated electricity and satisfy environmental concerns. Since power plants may present several operating problems such as disturbances and severe effects at operating points, design of their controllers needs to be carried out adequately. For these reasons, first, a reduced mathematical model was developed under Computer Aided Analysis and Design Package for Control (CADACS), so that the results of the experimental model have briefly been discussed. Second, conventional PID and adaptive controllers were designed and implemented under the real-time environment of the CADACS software. Additionally, the design of the adaptive model-reference and conventional PID controllers used in the power plant for real-time control were theoretically presented. All processes were realized in real-time. Due to safety restrictions, a direct connection to the sensors and actuators of the plant was not allowed. Instead a coupling to the control system was realized. This offers, in addition, the usage of the supervisory functions of an industrial process computer system. Application of the controllers indicated that the proposed adaptive controller has better performances for rise and settling times of electrical power, and enthalpy outputs than the conventional PID controller does

  18. Adaptive collaborative governance of Nepal's community forests: shifting power, strenghtening livelihoods

    NARCIS (Netherlands)

    McDougall, C.L.

    2015-01-01

    Short Summary

    Cynthia McDougall--PhD Dissertation

    Knowledge, Technology, &Innovation Chairgroup (WASS)

    Adaptive collaborative governance of Nepal’s community forests: Shifting power, strengthening livelihoods

  19. Flexible Microgrid Power Quality Enhancement Using Adaptive Hybrid Voltage and Current Controller

    DEFF Research Database (Denmark)

    He, Jinwei; Li, Yun Wei; Blaabjerg, Frede

    2014-01-01

    -pass/bandpass filters in the DG unit digital controller. Moreover, phase-locked loops are not necessary as the microgrid frequency deviation can be automatically identified by the power control loop. Consequently, the proposed control method provides opportunities to reduce DG control complexity, without affecting......To accomplish superior harmonic compensation performance using distributed generation (DG) unit power electronics interfaces, an adaptive hybrid voltage and current controlled method (HCM) is proposed in this paper. It shows that the proposed adaptive HCM can reduce the numbers of low...... the harmonic compensation performance. Comprehensive simulated and experimental results from a single-phase microgrid are provided to verify the feasibility of the proposed adaptive HCM approach....

  20. TCSC Nonlinear Adaptive Damping Controller Design Based on RBF Neural Network to Enhance Power System Stability

    DEFF Research Database (Denmark)

    Yao, Wei; Fang, Jiakun; Zhao, Ping

    2013-01-01

    the characteristics of the conventional PID, but adjust the parameters of PID controller online using identified Jacobian information from RBFNN. Hence, it has strong adaptability to the variation of the system operating condition. The effectiveness of the proposed controller is tested on a two-machine five-bus power...... system and a four-machine two-area power system under different operating conditions in comparison with the lead-lag damping controller tuned by evolutionary algorithm (EA). Simulation results show that the proposed damping controller achieves good robust performance for damping the low frequency......In this paper, a nonlinear adaptive damping controller based on radial basis function neural network (RBFNN), which can infinitely approximate to nonlinear system, is proposed for thyristor controlled series capacitor (TCSC). The proposed TCSC adaptive damping controller can not only have...

  1. An intelligent switch with back-propagation neural network based hybrid power system

    Science.gov (United States)

    Perdana, R. H. Y.; Fibriana, F.

    2018-03-01

    The consumption of conventional energy such as fossil fuels plays the critical role in the global warming issues. The carbon dioxide, methane, nitrous oxide, etc. could lead the greenhouse effects and change the climate pattern. In fact, 77% of the electrical energy is generated from fossil fuels combustion. Therefore, it is necessary to use the renewable energy sources for reducing the conventional energy consumption regarding electricity generation. This paper presents an intelligent switch to combine both energy resources, i.e., the solar panels as the renewable energy with the conventional energy from the State Electricity Enterprise (PLN). The artificial intelligence technology with the back-propagation neural network was designed to control the flow of energy that is distributed dynamically based on renewable energy generation. By the continuous monitoring on each load and source, the dynamic pattern of the intelligent switch was better than the conventional switching method. The first experimental results for 60 W solar panels showed the standard deviation of the trial at 0.7 and standard deviation of the experiment at 0.28. The second operation for a 900 W of solar panel obtained the standard deviation of the trial at 0.05 and 0.18 for the standard deviation of the experiment. Moreover, the accuracy reached 83% using this method. By the combination of the back-propagation neural network with the observation of energy usage of the load using wireless sensor network, each load can be evenly distributed and will impact on the reduction of conventional energy usage.

  2. Dissolved Gas Analysis Principle-Based Intelligent Approaches to Fault Diagnosis and Decision Making for Large Oil-Immersed Power Transformers: A Survey

    Directory of Open Access Journals (Sweden)

    Lefeng Cheng

    2018-04-01

    Full Text Available Compared with conventional methods of fault diagnosis for power transformers, which have defects such as imperfect encoding and too absolute encoding boundaries, this paper systematically discusses various intelligent approaches applied in fault diagnosis and decision making for large oil-immersed power transformers based on dissolved gas analysis (DGA, including expert system (EPS, artificial neural network (ANN, fuzzy theory, rough sets theory (RST, grey system theory (GST, swarm intelligence (SI algorithms, data mining technology, machine learning (ML, and other intelligent diagnosis tools, and summarizes existing problems and solutions. From this survey, it is found that a single intelligent approach for fault diagnosis can only reflect operation status of the transformer in one particular aspect, causing various degrees of shortcomings that cannot be resolved effectively. Combined with the current research status in this field, the problems that must be addressed in DGA-based transformer fault diagnosis are identified, and the prospects for future development trends and research directions are outlined. This contribution presents a detailed and systematic survey on various intelligent approaches to faults diagnosing and decisions making of the power transformer, in which their merits and demerits are thoroughly investigated, as well as their improvement schemes and future development trends are proposed. Moreover, this paper concludes that a variety of intelligent algorithms should be combined for mutual complementation to form a hybrid fault diagnosis network, such that avoiding these algorithms falling into a local optimum. Moreover, it is necessary to improve the detection instruments so as to acquire reasonable characteristic gas data samples. The research summary, empirical generalization and analysis of predicament in this paper provide some thoughts and suggestions for the research of complex power grid in the new environment, as

  3. Application of semi-active RFID power meter in automatic verification pipeline and intelligent storage system

    Science.gov (United States)

    Chen, Xiangqun; Huang, Rui; Shen, Liman; chen, Hao; Xiong, Dezhi; Xiao, Xiangqi; Liu, Mouhai; Xu, Renheng

    2018-03-01

    In this paper, the semi-active RFID watt-hour meter is applied to automatic test lines and intelligent warehouse management, from the transmission system, test system and auxiliary system, monitoring system, realize the scheduling of watt-hour meter, binding, control and data exchange, and other functions, make its more accurate positioning, high efficiency of management, update the data quickly, all the information at a glance. Effectively improve the quality, efficiency and automation of verification, and realize more efficient data management and warehouse management.

  4. Fuzzy Adaptive Particle Swarm Optimization for Power Loss Minimisation in Distribution Systems Using Optimal Load Response

    DEFF Research Database (Denmark)

    Hu, Weihao; Chen, Zhe; Bak-Jensen, Birgitte

    2014-01-01

    Consumers may decide to modify the profile of their demand from high price periods to low price periods in order to reduce their electricity costs. This optimal load response to electricity prices for demand side management generates different load profiles and provides an opportunity to achieve...... power loss minimization in distribution systems. In this paper, a new method to achieve power loss minimization in distribution systems by using a price signal to guide the demand side management is proposed. A fuzzy adaptive particle swarm optimization (FAPSO) is used as a tool for the power loss...

  5. Rail-to-rail low-power fully differential OTA utilizing adaptive biasing and partial feedback

    DEFF Research Database (Denmark)

    Tuan Vu, Cao; Wisland, Dag T.; Lande, Tor Sverre

    A fully differential rail-to-rail Operational Transconductance Amplifier (OTA) with improved DC-gain and reduced power consumption is proposed in this paper. By using the adaptive biasing circuit and two differential inputs, a low stand-by current can be obtained together with reduced power...... consumption. The DC-gain of the proposed OTA is improved by adding a partial feedback loop. A Common-Mode Feedback (CMFB) circuit is required for fully differential rail-to-rail operation. Simulations show that the OTA topology has a low stand-by power consumption of 96μW and a high FoM of 3.84 [(V...

  6. Intelligent Control and Protection Methods for Modern Power Systems Based on WAMS

    DEFF Research Database (Denmark)

    Liu, Leo

    Continuously growing demand for electricity, driven by deregulated power markets, has forced power systems to operate closer to their security operation limits. Meanwhile, the increasing penetration of large scale renewable energy may impact the operation of power systems by bringing more...... vulnerability indices i.e. structural vulnerability index (SVI), contingency vulnerability index (CVI) and operational vulnerability index (OVI) are proposed to evaluate the impact of distributed generation (DG) on power system vulnerability. The assessment shows that DG units are able to shorten the electrical...... influencing factors to power system transient stability are also evaluated, e.g. power output of generators in central power plants (CPP), load consumption level and the power exchange in high voltage direct current (HVDC) links. Both structural and dynamic vulnerability assessment, aiming at providing...

  7. The SP Theory of Intelligence as a Foundation for the Development of a General, Human-Level Thinking Machine

    OpenAIRE

    Wolff, J Gerard

    2016-01-01

    This paper summarises how the "SP theory of intelligence" and its realisation in the "SP computer model" simplifies and integrates concepts across artificial intelligence and related areas, and thus provides a promising foundation for the development of a general, human-level thinking machine, in accordance with the main goal of research in artificial general intelligence. The key to this simplification and integration is the powerful concept of "multiple alignment", borrowed and adapted from...

  8. Optimized Adaptive Perturb and Observe Maximum Power Point Tracking Control for Photovoltaic Generation

    Directory of Open Access Journals (Sweden)

    Luigi Piegari

    2015-04-01

    Full Text Available The power extracted from PV arrays is usually maximized using maximum power point tracking algorithms. One of the most widely used techniques is the perturb & observe algorithm, which periodically perturbs the operating point of the PV array, sometime with an adaptive perturbation step, and compares the PV power before and after the perturbation. This paper analyses the most suitable perturbation step to optimize maximum power point tracking performance and suggests a design criterion to select the parameters of the controller. Using this proposed adaptive step, the MPPT perturb & observe algorithm achieves an excellent dynamic response by adapting the perturbation step to the actual operating conditions of the PV array. The proposed algorithm has been validated and tested in a laboratory using a dual input inductor push-pull converter. This particular converter topology is an efficient interface to boost the low voltage of PV arrays and effectively control the power flow when input or output voltages are variable. The experimental results have proved the superiority of the proposed algorithm in comparison of traditional perturb & observe and incremental conductance techniques.

  9. Transmit Antenna Selection for Power Adaptive Underlay Cognitive Radio with Instantaneous Interference Constraint

    KAUST Repository

    Hanif, Muhammad

    2017-03-31

    The high hardware cost associated with multiple antennas at the secondary transmitter of an underlay cognitive radio (CR) can be reduced by antenna selection. This paper analyzes different power adaptive transmit antenna selection (TAS) schemes for an underlay CR, which ensure that the instantaneous interference caused by the secondary transmitter to the primary receiver is below a predetermined level. We consider the optimal continuous power adaptive TAS and present a low-complexity antenna and power level selection scheme, named sequential antenna and power level selection scheme (SAPS), for discrete power adaptation. Exact statistical characterizations of the signal-to-interference plus noise ratio at the secondary receiver are derived for the considered schemes. Based on the newly derived statistics, we prove that the considered schemes achieve the highest diversity order equaling the number of antennas at the secondary transmitter. Further, we also derive a closed-form expression of the ergodic capacity for the underlay CR with SAPS scheme. Finally, we show that the proposed scheme outperforms existing schemes in terms of ergodic capacity.

  10. Optical power allocation for adaptive transmissions in wavelength-division multiplexing free space optical networks

    Directory of Open Access Journals (Sweden)

    Hui Zhou

    2015-08-01

    Full Text Available Attracting increasing attention in recent years, the Free Space Optics (FSO technology has been recognized as a cost-effective wireless access technology for multi-Gigabit rate wireless networks. Radio on Free Space Optics (RoFSO provides a new approach to support various bandwidth-intensive wireless services in an optical wireless link. In an RoFSO system using wavelength-division multiplexing (WDM, it is possible to concurrently transmit multiple data streams consisting of various wireless services at very high rate. In this paper, we investigate the problem of optical power allocation under power budget and eye safety constraints for adaptive WDM transmission in RoFSO networks. We develop power allocation schemes for adaptive WDM transmissions to combat the effect of weather turbulence on RoFSO links. Simulation results show that WDM RoFSO can support high data rates even over long distance or under bad weather conditions with an adequate system design.

  11. Design of an effective energy receiving adapter for microwave wireless power transmission application

    Directory of Open Access Journals (Sweden)

    Peng Xu

    2016-10-01

    Full Text Available In this paper, we demonstrate the viability of an energy receiving adapter in a 8×8 array form with high power reception efficiency with the resonator of artificial electromagnetic absorber being used as the element. Unlike the conventional reported rectifying antenna resonators, both the size of the element and the separations between the elements are electrically small in our design. The energy collecting process is explained with an equivalent circuit model, and a RF combining network is designed to combine the captured AC power from each element to one main terminal for AC-to-DC conversion. The energy receiving adapter yields a total reception efficiency of 67% (including the wave capture efficiency of 86% and the AC-to-DC conversion efficiency of 78%, which is quite promising for microwave wireless power transmission.

  12. Crystallized and fluid intelligence of university students with intellectual disability who are fully integrated versus those who studied in adapted enrichment courses.

    Science.gov (United States)

    Lifshitz, Hefziba; Verkuilen, Jay; Shnitzer-Meirovich, Shlomit; Altman, Carmit

    2018-01-01

    Inclusion of people with intellectual disability (ID) in higher postsecondary academic education is on the rise. However, there are no scientific criteria for determining the eligibility for full inclusion of students with ID in university courses. This study focuses on two models of academic inclusion for students with ID: (a) separate adapted enrichment model: students with ID study in separate enrichment courses adapted to their level; (b) full inclusion model: students with ID are included in undergraduate courses, receive academic credits and are expected to accumulate the amount of credits for a B.A. (a) To examine whether crystallized and fluid intelligence and cognitive tests can serve as screening tests for determining the appropriate placement of students with ID for the adapted enrichment model versus the full inclusion model. (b) To examine the attitudes towards the program of students with ID in the inclusion model. The sample included 31 adults with ID: students with ID who were fully included (N = 10) and students with ID who participated in the adapted enrichment model (N = 21). Crystallized and fluid intelligence were examined (WAIS-III, Wechsler, 1997) and Hebrew abstract verbal tests (Glanz, 1989). Semi-structured interviews were conducted in order to examine the attitudes of students in the inclusion model towards the program. The ANOVAs indicate that the most prominent difference between the groups was in vocabulary, knowledge and working memory. ROC analysis, a fundamental tool for diagnostic test evaluation, was used to determine the students' eligibility for appropriate placement in the two models. Seven tests distinguished between the groups in terms of sensitivity and specificity. The interviews were analyzed according to three phases. The results indicate that students with ID are able to participate in undergraduate courses and achieve academic goals. The general IQ and idioms test seem to be best determiners for appropriate placement of

  13. Application of the Fuzzy Computational Intelligence in Power Quality Data Management

    Directory of Open Access Journals (Sweden)

    Hoda Farag

    2017-03-01

    Full Text Available In Electrical Power Distribution System the sustained availability and quality of electric power are the main challenge they need to satisfy so overcoming the power quality (PQ degradation became an asset. This Paper addresses the perfect load management using the computational techniques by analyzing the data of the system taking into account the density of the  feeding nodes and its distribution  also the classification of major Power quality degradations such as power factor and harmonics in the System and The methodology will be illustrated, simulated and evaluated using the fuzzy technique clustering the data and on an Artificial Neural Network (ANN to achieve the optimum utilization of the energy loads and perfect load management and optimization. Simulation results demonstrate the effectiveness of the proposed algorithm in reducing the power and energy losses, improving the quality of the electric power system.

  14. WAMS Based Intelligent Operation and Control of Modern Power System with large Scale Renewable Energy Penetration

    DEFF Research Database (Denmark)

    Rather, Zakir Hussain

    security limits. Under such scenario, progressive displacement of conventional generation by wind generation is expected to eventually lead a complex power system with least presence of central power plants. Consequently the support from conventional power plants is expected to reach its all-time low...... system voltage control responsibility from conventional power plants to wind turbines. With increased wind penetration and displaced conventional central power plants, dynamic voltage security has been identified as one of the challenging issue for large scale wind integration. To address the dynamic...... security issue, a WAMS based systematic voltage control scheme for large scale wind integrated power system has been proposed. Along with the optimal reactive power compensation, the proposed scheme considers voltage support from wind farms (equipped with voltage support functionality) and refurbished...

  15. Perceived Task-Difficulty Recognition from Log-File Information for the Use in Adaptive Intelligent Tutoring Systems

    Science.gov (United States)

    Janning, Ruth; Schatten, Carlotta; Schmidt-Thieme, Lars

    2016-01-01

    Recognising students' emotion, affect or cognition is a relatively young field and still a challenging task in the area of intelligent tutoring systems. There are several ways to use the output of these recognition tasks within the system. The approach most often mentioned in the literature is using it for giving feedback to the students. The…

  16. Bifurcations, chaos and adaptive backstepping sliding mode control of a power system with excitation limitation

    Directory of Open Access Journals (Sweden)

    Fuhong Min

    2016-08-01

    Full Text Available The bifurcation and Lyapunov exponent for a single-machine-infinite bus system with excitation model are carried out by varying the mechanical power, generator damping factor and the exciter gain, from which periodic motions, chaos and the divergence of system are observed respectively. From given parameters and different initial conditions, the coexisting motions are developed in power system. The dynamic behaviors in power system may switch freely between the coexisting motions, which will bring huge security menace to protection operation. Especially, the angle divergences due to the break of stable chaotic oscillation are found which causes the instability of power system. Finally, a new adaptive backstepping sliding mode controller is designed which aims to eliminate the angle divergences and make the power system run in stable orbits. Numerical simulations are illustrated to verify the effectivity of the proposed method.

  17. Crew resource management training adapted to nuclear power plant operators for enhancing safety attitude

    International Nuclear Information System (INIS)

    Ishibashi, Akira; Kitamura, Masaharu; Takahashi, Makoto

    2015-01-01

    A conventional training program for nuclear power plant operators mainly focuses on the improvement of knowledge and skills of individual operators. Although it has certainly contributed to safety operation of nuclear power plants, some recent incidents have indicated the necessity of an additional training program aiming at the improvement of team performance. In the aviation domain, crew resource management (CRM) training has demonstrated the effectiveness in resolving team management issues of flight crews, aircraft maintenance crews, and so on. In the present research, we attempt to introduce the CRM concept into operator training in nuclear power plant for the training of conceptual skill (that is, non-technical skill). In this paper an adapted CRM training for nuclear power plant operators is proposed. The proposed training method has been practically utilized in the training course of the managers of nuclear power plants. (author)

  18. Bifurcations, chaos and adaptive backstepping sliding mode control of a power system with excitation limitation

    Energy Technology Data Exchange (ETDEWEB)

    Min, Fuhong, E-mail: minfuhong@njnu.edu.cn; Wang, Yaoda; Peng, Guangya; Wang, Enrong [School of Electrical and Automation Engineering, Nanjing Normal University, Jiangsu, 210042 (China)

    2016-08-15

    The bifurcation and Lyapunov exponent for a single-machine-infinite bus system with excitation model are carried out by varying the mechanical power, generator damping factor and the exciter gain, from which periodic motions, chaos and the divergence of system are observed respectively. From given parameters and different initial conditions, the coexisting motions are developed in power system. The dynamic behaviors in power system may switch freely between the coexisting motions, which will bring huge security menace to protection operation. Especially, the angle divergences due to the break of stable chaotic oscillation are found which causes the instability of power system. Finally, a new adaptive backstepping sliding mode controller is designed which aims to eliminate the angle divergences and make the power system run in stable orbits. Numerical simulations are illustrated to verify the effectivity of the proposed method.

  19. Study on intelligence fault diagnosis method for nuclear power plant equipment based on rough set and fuzzy neural network

    International Nuclear Information System (INIS)

    Liu Yongkuo; Xia Hong; Xie Chunli; Chen Zhihui; Chen Hongxia

    2007-01-01

    Rough set theory and fuzzy neural network are combined, to take full advantages of the two of them. Based on the reduction technology to knowledge of Rough set method, and by drawing the simple rule from a large number of initial data, the fuzzy neural network was set up, which was with better topological structure, improved study speed, accurate judgment, strong fault-tolerant ability, and more practical. In order to test the validity of the method, the inverted U-tubes break accident of Steam Generator and etc are used as examples, and many simulation experiments are performed. The test result shows that it is feasible to incorporate the fault intelligence diagnosis method based on rough set and fuzzy neural network in the nuclear power plant equipment, and the method is simple and convenience, with small calculation amount and reliable result. (authors)

  20. EDITORIAL: Adaptive and active materials: Selected papers from the ASME 2010 Conference on Smart Materials, Adaptive Structures and Intelligent Systems (SMASIS 10) (Philadelphia, PA, USA, 28 September-1 October 2010) Adaptive and active materials: Selected papers from the ASME 2010 Conference on Smart Materials, Adaptive Structures and Intelligent Systems (SMASIS 10) (Philadelphia, PA, USA, 28 September-1 October 2010)

    Science.gov (United States)

    Brei, Diann

    2011-09-01

    The third annual meeting of the AMSE/AIAA Smart Materials, Adaptive Structures and Intelligent Systems Conference (SMASIS) took place in the heart of historic Philadelphia's cultural district, and included a pioneer banquet in the National Constitutional Center. The applications emphasis of the 2010 conference was reflected in keynote talks by Dr Alan Taub, vice president of General Motors global research and development, 'Smart materials in the automotive industry'; Dr Charles R Farrar, engineering institute leader at Los Alamos National Laboratory, 'Future directions for structural health monitoring of civil engineering infrastructure'; and Professor Christopher S Lynch of the University of California Los Angeles, 'Ferroelectric materials and their applications'. The SMASIS conference was divided into six technical symposia each of which included basic research, applied technological design and development, and industrial and governmental integrated system and application demonstrations. The six symposia were: SYMP 1 Multifunctional Materials; SYMP 2 Active Materials, Mechanics and Behavior; SYMP 3 Modeling, Simulation and Control; SYMP 4 Enabling Technologies and Integrated System Design; SYMP 5 Structural Health Monitoring/NDE; and SYMP 6 Bio-inspired Smart Materials and Structures. In addition, the conference introduced a new student and young professional development symposium. Authors of papers in the materials areas (symposia 1, 2 and 6) were invited to write a full journal article on their presentation topic for publication in this special issue of Smart Materials and Structures. This set of papers demonstrates the exceptional quality and originality of the conference presentations. We are appreciative of their efforts in producing this collection of highly relevant articles on smart materials.

  1. Adaptive Fuzzy Control for Power-Frequency Characteristic Regulation in High-RES Power Systems

    Directory of Open Access Journals (Sweden)

    Evangelos Rikos

    2017-07-01

    Full Text Available Future power systems control will require large-scale activation of reserves at distribution level. Despite their high potential, distributed energy resources (DER used for frequency control pose challenges due to unpredictability, grid bottlenecks, etc. To deal with these issues, this study presents a novel strategy of power frequency characteristic dynamic adjustment based on the imbalance state. This way, the concerned operators become aware of the imbalance location but also a more accurate redistribution of responsibilities in terms of reserves activations is achieved. The proposed control is based on the concept of “cells” which are power systems with operating capabilities and responsibilities similar to control areas (CAs, but fostering the use of resources at all voltage levels, particularly distribution grids. Control autonomy of cells allows increased RES hosting. In this study, the power frequency characteristic of a cell is adjusted in real time by means of a fuzzy controller, which curtails part of the reserves, in order to avoid unnecessary deployment throughout a synchronous area, leading to a more localised activation and reducing losses, congestions and reserves exhaustion. Simulation tests in a four-cell reference power system prove that the controller significantly reduces the use of reserves without compromising the overall stability.

  2. Modelling traffic flows with intelligent cars and intelligent roads

    NARCIS (Netherlands)

    van Arem, Bart; Tampere, Chris M.J.; Malone, Kerry

    2003-01-01

    This paper addresses the modeling of traffic flows with intelligent cars and intelligent roads. It will describe the modeling approach MIXIC and review the results for different ADA systems: Adaptive Cruise Control, a special lane for Intelligent Vehicles, cooperative following and external speed

  3. Artificial intelligence applications to the surveillance and diagnostics of nuclear power plants

    International Nuclear Information System (INIS)

    Zwingelstein, G.; Monnier, B.

    1985-01-01

    Artificial intelligence has come of age; it can be applied with benefits in the nuclear industry for various applications to improve both plant safety and availability. This paper presents four rule-based expert systems currently under development at Electricite de France for the surveillance and the diagnostics of pressurized water reactors (PWRs). The objectives of these experiences with expert system projects are to demonstrate their feasibility, to provide an evaluation of their potential benefits through on-site implementation, to identify the problems due to the knowledge extraction and representation, and finally to specify the classes of problems where expert systems are needed and useful. The specific goals of these expert systems are to provide an aid for the detection and location of failures occurring in nuclear plants

  4. Dynamic modelling of water demand, water availability and adaptation strategies for power plants to global change

    International Nuclear Information System (INIS)

    Koch, Hagen; Voegele, Stefan

    2009-01-01

    According to the latest IPCC reports, the frequency of hot and dry periods will increase in many regions of the world in the future. For power plant operators, the increasing possibility of water shortages is an important challenge that they have to face. Shortages of electricity due to water shortages could have an influence on industries as well as on private households. Climate change impact analyses must analyse the climate effects on power plants and possible adaptation strategies for the power generation sector. Power plants have lifetimes of several decades. Their water demand changes with climate parameters in the short- and medium-term. In the long-term, the water demand will change as old units are phased out and new generating units appear in their place. In this paper, we describe the integration of functions for the calculation of the water demand of power plants into a water resources management model. Also included are both short-term reactive and long-term planned adaptation. This integration allows us to simulate the interconnection between the water demand of power plants and water resources management, i.e. water availability. Economic evaluation functions for water shortages are also integrated into the water resources management model. This coupled model enables us to analyse scenarios of socio-economic and climate change, as well as the effects of water management actions. (author)

  5. Smart grid communication-enabled intelligence for the electric power grid

    CERN Document Server

    Bush, Stephen F

    2014-01-01

    This book bridges the divide between the fields of power systems engineering and computer communication through the new field of power system information theory. Written by an expert with vast experience in the field, this book explores the smart grid from generation to consumption, both as it is planned today and how it will evolve tomorrow. The book focuses upon what differentiates the smart grid from the ""traditional"" power grid as it has been known for the last century. Furthermore, the author provides the reader with a fundamental understanding of both power systems and communication ne

  6. Planning and Resource Management in an Intelligent Automated Power Management System

    Science.gov (United States)

    Morris, Robert A.

    1991-01-01

    Power system management is a process of guiding a power system towards the objective of continuous supply of electrical power to a set of loads. Spacecraft power system management requires planning and scheduling, since electrical power is a scarce resource in space. The automation of power system management for future spacecraft has been recognized as an important R&D goal. Several automation technologies have emerged including the use of expert systems for automating human problem solving capabilities such as rule based expert system for fault diagnosis and load scheduling. It is questionable whether current generation expert system technology is applicable for power system management in space. The objective of the ADEPTS (ADvanced Electrical Power management Techniques for Space systems) is to study new techniques for power management automation. These techniques involve integrating current expert system technology with that of parallel and distributed computing, as well as a distributed, object-oriented approach to software design. The focus of the current study is the integration of new procedures for automatically planning and scheduling loads with procedures for performing fault diagnosis and control. The objective is the concurrent execution of both sets of tasks on separate transputer processors, thus adding parallelism to the overall management process.

  7. How to Improve Artificial Intelligence through Web

    OpenAIRE

    Adrian Lupasc

    2005-01-01

    Intelligent agents, intelligent software applications and artificial intelligent applications from artificial intelligence service providers may make their way onto the Web in greater number as adaptive software, dynamic programming languages and Learning Algorithms are introduced into Web Services. The evolution of Web architecture may allow intelligent applications to run directly on the Web by introducing XML, RDF and logic layer. The Intelligent Wireless Web’s significant potential for ra...

  8. Underwater wireless optical MIMO system with spatial modulation and adaptive power allocation

    Science.gov (United States)

    Huang, Aiping; Tao, Linwei; Niu, Yilong

    2018-04-01

    In this paper, we investigate the performance of underwater wireless optical multiple-input multiple-output communication system combining spatial modulation (SM-UOMIMO) with flag dual amplitude pulse position modulation (FDAPPM). Channel impulse response for coastal and harbor ocean water links are obtained by Monte Carlo (MC) simulation. Moreover, we obtain the closed-form and upper bound average bit error rate (BER) expressions for receiver diversity including optical combining, equal gain combining and selected combining. And a novel adaptive power allocation algorithm (PAA) is proposed to minimize the average BER of SM-UOMIMO system. Our numeric results indicate an excellent match between the analytical results and numerical simulations, which confirms the accuracy of our derived expressions. Furthermore, the results show that adaptive PAA outperforms conventional fixed factor PAA and equal PAA obviously. Multiple-input single-output system with adaptive PAA obtains even better BER performance than MIMO one, at the same time reducing receiver complexity effectively.

  9. Near optimal power allocation algorithm for OFDM-based cognitive using adaptive relaying strategy

    KAUST Repository

    Soury, Hamza; Bader, Faouzi; Shaat, Musbah M R; Alouini, Mohamed-Slim

    2012-01-01

    Relayed transmission increases the coverage and achievable capacity of communication systems. Adaptive relaying scheme is a relaying technique by which the benefits of the amplifying or decode and forward techniques can be achieved by switching the forwarding technique according to the quality of the signal. A cognitive Orthogonal Frequency-Division Multiplexing (OFDM) based adaptive relaying protocol is considered in this paper. The objective is to maximize the capacity of the cognitive radio system while ensuring that the interference introduced to the primary user is below the tolerated limit. A Near optimal power allocation in the source and the relay is presented for two pairing techniques such that the matching and random pairing. The simulation results confirm the efficiency of the proposed adaptive relaying protocol, and the consequence of choice of pairing technique. © 2012 ICST.

  10. Data Analytics Based Dual-Optimized Adaptive Model Predictive Control for the Power Plant Boiler

    Directory of Open Access Journals (Sweden)

    Zhenhao Tang

    2017-01-01

    Full Text Available To control the furnace temperature of a power plant boiler precisely, a dual-optimized adaptive model predictive control (DoAMPC method is designed based on the data analytics. In the proposed DoAMPC, an accurate predictive model is constructed adaptively by the hybrid algorithm of the least squares support vector machine and differential evolution method. Then, an optimization problem is constructed based on the predictive model and many constraint conditions. To control the boiler furnace temperature, the differential evolution method is utilized to decide the control variables by solving the optimization problem. The proposed method can adapt to the time-varying situation by updating the sample data. The experimental results based on practical data illustrate that the DoAMPC can control the boiler furnace temperature with errors of less than 1.5% which can meet the requirements of the real production process.

  11. On-line adaptive line frequency noise cancellation from a nuclear power measuring channel

    Directory of Open Access Journals (Sweden)

    Qadir Javed

    2011-01-01

    Full Text Available On-line software for adaptively canceling 50 Hz line frequency noise has been designed and tested at Pakistan Research Reactor 1. Line frequency noise causes much problem in weak signals acquisition. Sometimes this noise is so dominant that original signal is totally corrupted. Although notch filter can be used for eliminating this noise, but if signal of interest is in close vicinity of 50 Hz, then original signal is also attenuated and hence overall performance is degraded. Adaptive noise removal is a technique which could be employed for removing line frequency without degrading the desired signal. In this paper line frequency noise has been eliminated on-line from a nuclear power measuring channel. The adaptive LMS algorithm has been used to cancel 50 Hz noise. The algorithm has been implemented in labVIEW with NI 6024 data acquisition card. The quality of the acquired signal has been improved much as can be seen in experimental results.

  12. Thermal limits validation of gamma thermometer power adaption in CFE Laguna Verde 2 reactor core

    Energy Technology Data Exchange (ETDEWEB)

    Cuevas V, G.; Banfield, J. [GE-Hitachi Nuclear Energy Americas LLC, Global Nuclear Fuel, Americas LLC, 3901 Castle Hayne Road, Wilmingtonm, North Carolina (United States); Avila N, A., E-mail: Gabriel.Cuevas-Vivas@ge.com [Comision Federal de Electricidad, Central Nucleoelectrica Laguna Verde, Carretera Cardel-Nautla Km 42.5, Alto Lucero, Veracruz (Mexico)

    2016-09-15

    This paper presents the status of GEH work on Gamma Thermometer (GT) validation using the signals of the instruments installed in the Laguna Verde Unit 2 reactor core. The long-standing technical collaboration between Comision Federal de Electricidad (CFE), Global Nuclear Fuel - Americas LLC (GNF) and GE-Hitachi Nuclear Energy Americas LLC (GEH) is moving forward with solid steps to a final implementation of GTs in a nuclear reactor core. Each GT is integrated into a slightly modified Local Power Range Monitor (LPRM) assembly. Six instrumentation strings are equipped with two gamma field detectors for a total of twenty-four bundles whose calculated powers are adapted to the instrumentation readings in addition to their use as calibration instruments for LPRMs. Since November 2007, the six GT instrumentation strings have been operable with almost no degradation by the strong neutron and gamma fluxes in the Laguna Verde Unit 2 reactor core. In this paper, the thermal limits, Critical Power Ratio (CPR) and maximum Linear Heat Generation Rate (LHGR), of bundles directly monitored by either Traverse In-core Probes (TIPs) or GTs are used to establish validation results that confirm the viability of TIP system replacement with automatic fixed in-core probes (AFIPs, GTs, in a Boiling Water Reactor. The new GNF steady-state reactor core simulator AETNA02 is used to obtain power and exposure distribution. Using this code with an updated methodology for GT power adaption, a reduced value of the GT interpolation uncertainty is obtained that is fed into the LHGR calculation. This new method achieves margin recovery for the adapted thermal limits for use in the Economic Simplified Boiling Water Reactor (ESBWR) or any other BWR in the future that employs a GT based AFIP system for local power measurements. (Author)

  13. Thermal limits validation of gamma thermometer power adaption in CFE Laguna Verde 2 reactor core

    International Nuclear Information System (INIS)

    Cuevas V, G.; Banfield, J.; Avila N, A.

    2016-09-01

    This paper presents the status of GEH work on Gamma Thermometer (GT) validation using the signals of the instruments installed in the Laguna Verde Unit 2 reactor core. The long-standing technical collaboration between Comision Federal de Electricidad (CFE), Global Nuclear Fuel - Americas LLC (GNF) and GE-Hitachi Nuclear Energy Americas LLC (GEH) is moving forward with solid steps to a final implementation of GTs in a nuclear reactor core. Each GT is integrated into a slightly modified Local Power Range Monitor (LPRM) assembly. Six instrumentation strings are equipped with two gamma field detectors for a total of twenty-four bundles whose calculated powers are adapted to the instrumentation readings in addition to their use as calibration instruments for LPRMs. Since November 2007, the six GT instrumentation strings have been operable with almost no degradation by the strong neutron and gamma fluxes in the Laguna Verde Unit 2 reactor core. In this paper, the thermal limits, Critical Power Ratio (CPR) and maximum Linear Heat Generation Rate (LHGR), of bundles directly monitored by either Traverse In-core Probes (TIPs) or GTs are used to establish validation results that confirm the viability of TIP system replacement with automatic fixed in-core probes (AFIPs, GTs, in a Boiling Water Reactor. The new GNF steady-state reactor core simulator AETNA02 is used to obtain power and exposure distribution. Using this code with an updated methodology for GT power adaption, a reduced value of the GT interpolation uncertainty is obtained that is fed into the LHGR calculation. This new method achieves margin recovery for the adapted thermal limits for use in the Economic Simplified Boiling Water Reactor (ESBWR) or any other BWR in the future that employs a GT based AFIP system for local power measurements. (Author)

  14. Adaptive Control Design for Autonomous Operation of Multiple Energy Storage Systems in Power Smoothing Applications

    DEFF Research Database (Denmark)

    Meng, Lexuan; Dragicevic, Tomislav; Guerrero, Josep M.

    2018-01-01

    -pass-filter (HPF) structure. It generates the power reference according to the fluctuating power and provides a stabilization effect. The power and energy supplied by ESS are majorly configured by the cut-off frequency and gain of the HPF. Considering the operational limits on ESS state-of-charge (SoC), this paper...... proposes an adaptive cut-off frequency design method to realize communication-less and autonomous operation of a system with multiple distributed ESS. The experimental results demonstrate that the SoCs of all ESS units are kept within safe margins, while the SoC level and power of the paralleled units...... converge to the final state, providing a natural plug-and-play function....

  15. Adaptive co-channel interference cancelation for power-limited applications

    KAUST Repository

    Radaydeh, Redha Mahmoud Mesleh

    2010-09-01

    This paper proposes an adaptive co-channel interference -steering algorithm for highly correlated receive antenna channels with an aim of reducing the power consumption at the receiver. With this algorithm, the receiver activates as many antennas as necessary to maintain the residual total interference instantaneous power within a tolerable range, which can be set to guarantee a target performance level. The mode of operation does not require perfect knowledge of the statistical ordering of interfering signals instantaneous powers, which further reduces the complexity of implementation. It is shown that the arbitrary interference cancelation technique and no cancelation scenario can be studied as limiting cases of the proposed scheme. Analytical expressions for the statistics of the residual total interference instantaneous power are derived, which are then used to obtain results for the average number of active antennas and system outage performance. Numerical studies supported by simulations are presented to clarify the usefulness of the proposed scheme. ©2010 IEEE.

  16. Command Filtered Adaptive Fuzzy Neural Network Backstepping Control for Marine Power System

    Directory of Open Access Journals (Sweden)

    Xin Zhang

    2014-01-01

    Full Text Available In order to retrain chaotic oscillation of marine power system which is excited by periodic electromagnetism perturbation, a novel command-filtered adaptive fuzzy neural network backstepping control method is designed. First, the mathematical model of marine power system is established based on the two parallel nonlinear model. Then, main results of command-filtered adaptive fuzzy neural network backstepping control law are given. And the Lyapunov stability theory is applied to prove that the system can remain closed-loop asymptotically stable with this controller. Finally, simulation results indicate that the designed controller can suppress chaotic oscillation with fast convergence speed that makes the system return to the equilibrium point quickly; meanwhile, the parameter which induces chaotic oscillation can also be discriminated.

  17. Research and design of distributed intelligence fault diagnosis system in nuclear power plant

    International Nuclear Information System (INIS)

    Liu Yongkuo; Xie Chunli; Cheng Shouyu; Xia Hong

    2011-01-01

    In order to further reduce the misoperation after the faults occurring of nuclear power plant, according to the function distribution of nuclear power equipment and the distributed control features of digital instrument control system, a nuclear power plant distributed condition monitoring and fault diagnosis system was researched and designed. Based on decomposition-integrated diagnostic thinking, a fuzzy neural network and RBF neural network was presented to do the distributed local diagnosis and multi-source information fusion technology for the global integrated diagnosis. Simulation results show that the developed distributed status monitoring and fault diagnosis system can diagnose more typical accidents of PWR to provide effective diagnosis and operation information. (authors)

  18. Adaptation.

    Science.gov (United States)

    Broom, Donald M

    2006-01-01

    The term adaptation is used in biology in three different ways. It may refer to changes which occur at the cell and organ level, or at the individual level, or at the level of gene action and evolutionary processes. Adaptation by cells, especially nerve cells helps in: communication within the body, the distinguishing of stimuli, the avoidance of overload and the conservation of energy. The time course and complexity of these mechanisms varies. Adaptive characters of organisms, including adaptive behaviours, increase fitness so this adaptation is evolutionary. The major part of this paper concerns adaptation by individuals and its relationships to welfare. In complex animals, feed forward control is widely used. Individuals predict problems and adapt by acting before the environmental effect is substantial. Much of adaptation involves brain control and animals have a set of needs, located in the brain and acting largely via motivational mechanisms, to regulate life. Needs may be for resources but are also for actions and stimuli which are part of the mechanism which has evolved to obtain the resources. Hence pigs do not just need food but need to be able to carry out actions like rooting in earth or manipulating materials which are part of foraging behaviour. The welfare of an individual is its state as regards its attempts to cope with its environment. This state includes various adaptive mechanisms including feelings and those which cope with disease. The part of welfare which is concerned with coping with pathology is health. Disease, which implies some significant effect of pathology, always results in poor welfare. Welfare varies over a range from very good, when adaptation is effective and there are feelings of pleasure or contentment, to very poor. A key point concerning the concept of individual adaptation in relation to welfare is that welfare may be good or poor while adaptation is occurring. Some adaptation is very easy and energetically cheap and

  19. Climate change: assessment of the vulnerability of nuclear power and cost of adaptation

    Energy Technology Data Exchange (ETDEWEB)

    Paillere, H.; Cameron, R. [OECD Nuclear Energy Agency, Issy-les-Moulineaux, Paris (France); Caneill, J.-Y. [EDF Group, Paris, (France); Syri, S. [Aalto Univ., Dept. of Energy Technology, Aalto (Finland)

    2014-07-01

    This paper reports on the preliminary outcome of an OECD study (2013-14) aimed at assessing the vulnerability of nuclear power generation in the event of extreme weather events that could be induced by climate change. Nuclear power plants (NPPs), just as other energy infrastructures, can be affected by phenomena such as floods, storms, heat waves, droughts, etc. This paper reports on examples of extreme weather events that have affected the operation of NPPs, and describes the adaptation strategy that can be implemented to improve the resilience of existing generating assets as well as new infrastructures. (author)

  20. Adaptive double-integral-sliding-mode-maximum-power-point tracker for a photovoltaic system

    Directory of Open Access Journals (Sweden)

    Bidyadhar Subudhi

    2015-10-01

    Full Text Available This study proposed an adaptive double-integral-sliding-mode-controller-maximum-power-point tracker (DISMC-MPPT for maximum-power-point (MPP tracking of a photovoltaic (PV system. The objective of this study is to design a DISMC-MPPT with a new adaptive double-integral-sliding surface in order that MPP tracking is achieved with reduced chattering and steady-state error in the output voltage or current. The proposed adaptive DISMC-MPPT possesses a very simple and efficient PWM-based control structure that keeps switching frequency constant. The controller is designed considering the reaching and stability conditions to provide robustness and stability. The performance of the proposed adaptive DISMC-MPPT is verified through both MATLAB/Simulink simulation and experiment using a 0.2 kW prototype PV system. From the obtained results, it is found out that this DISMC-MPPT is found to be more efficient compared with that of Tan's and Jiao's DISMC-MPPTs.

  1. Speed adaptation in a powered transtibial prosthesis controlled with a neuromuscular model.

    Science.gov (United States)

    Markowitz, Jared; Krishnaswamy, Pavitra; Eilenberg, Michael F; Endo, Ken; Barnhart, Chris; Herr, Hugh

    2011-05-27

    Control schemes for powered ankle-foot prostheses would benefit greatly from a means to make them inherently adaptive to different walking speeds. Towards this goal, one may attempt to emulate the intact human ankle, as it is capable of seamless adaptation. Human locomotion is governed by the interplay among legged dynamics, morphology and neural control including spinal reflexes. It has been suggested that reflexes contribute to the changes in ankle joint dynamics that correspond to walking at different speeds. Here, we use a data-driven muscle-tendon model that produces estimates of the activation, force, length and velocity of the major muscles spanning the ankle to derive local feedback loops that may be critical in the control of those muscles during walking. This purely reflexive approach ignores sources of non-reflexive neural drive and does not necessarily reflect the biological control scheme, yet can still closely reproduce the muscle dynamics estimated from biological data. The resulting neuromuscular model was applied to control a powered ankle-foot prosthesis and tested by an amputee walking at three speeds. The controller produced speed-adaptive behaviour; net ankle work increased with walking speed, highlighting the benefits of applying neuromuscular principles in the control of adaptive prosthetic limbs.

  2. Analysis of adaptability of radioactive liquid effluent discharge under normal condition of inland nuclear power plant

    International Nuclear Information System (INIS)

    Xu Yueping; Zhang Bing; Chen Yang; Zhu Lingqing; Tao Yunliang; Shangguan Zhihong

    2011-01-01

    The discharge of radioactive liquid effluent from inland nuclear power plant under normal operation is an important part to be considered in environmental impact assessment. Requirements of newly revised and upcoming standards GB 6249 and GB 14587 are introduced in this paper. Through an example of an inland NPP siting in the preliminary feasibility study phase, the adaptability to the relevant regulations in the site selection is analyzed. Also, the concerned problems in the design of AP1000 units are addressed. (authors)

  3. Intelligent approach to maximum power point tracking control strategy for variable-speed wind turbine generation system

    Energy Technology Data Exchange (ETDEWEB)

    Lin, Whei-Min; Hong, Chih-Ming [Department of Electrical Engineering, National Sun Yat-Sen University, Kaohsiung 80424 (China)

    2010-06-15

    To achieve maximum power point tracking (MPPT) for wind power generation systems, the rotational speed of wind turbines should be adjusted in real time according to wind speed. In this paper, a Wilcoxon radial basis function network (WRBFN) with hill-climb searching (HCS) MPPT strategy is proposed for a permanent magnet synchronous generator (PMSG) with a variable-speed wind turbine. A high-performance online training WRBFN using a back-propagation learning algorithm with modified particle swarm optimization (MPSO) regulating controller is designed for a PMSG. The MPSO is adopted in this study to adapt to the learning rates in the back-propagation process of the WRBFN to improve the learning capability. The MPPT strategy locates the system operation points along the maximum power curves based on the dc-link voltage of the inverter, thus avoiding the generator speed detection. (author)

  4. Application of artificial intelligence for nuclear power plant surveillance and diagnosis problems

    International Nuclear Information System (INIS)

    Monnier, B.; Ricard, B.; Doutre, J.L.; Martin-Mattei, C.; Fernandes, A.

    1991-01-01

    This paper presents three expert systems in the field of surveillance and diagnosis of nuclear power plants. Each application is described from the point of view of knowledge modeling. Then, a general knowledge model is proposed for a class of diagnosis problems. At the end, the paper shows the future frame of the surveillance of the nuclear power plant main components at EDF in which the greatest part of those expert systems will run

  5. An Intelligent Approach to Strengthening of the Rural Electrical Power Supply Using Renewable Energy Resources

    Science.gov (United States)

    Robert, F. C.; Sisodia, G. S.; Gopalan, S.

    2017-08-01

    The healthy growth of economy lies in the balance between rural and urban development. Several developing countries have achieved a successful growth of urban areas, yet rural infrastructure has been neglected until recently. The rural electrical grids are weak with heavy losses and low capacity. Renewable energy represents an efficient way to generate electricity locally. However, the renewable energy generation may be limited by the low grid capacity. The current solutions focus on grid reinforcement only. This article presents a model for improving renewable energy integration in rural grids with the intelligent combination of three strategies: 1) grid reinforcement, 2) use of storage and 3) renewable energy curtailments. Such approach provides a solution to integrate a maximum of renewable energy generation on low capacity grids while minimising project cost and increasing the percentage of utilisation of assets. The test cases show that a grid connection agreement and a main inverter sized at 60 kW (resp. 80 kW) can accommodate a 100 kWp solar park (resp. 100 kW wind turbine) with minimal storage.

  6. Intelligent Management System of Power Network Information Collection Under Big Data Storage

    Directory of Open Access Journals (Sweden)

    Qin Yingying

    2017-01-01

    Full Text Available With the development of economy and society, big data storage in enterprise management has become a problem that can’t be ignored. How to manage and optimize the allocation of tasks better is an important factor in the sustainable development of an enterprise. Now the enterprise information intelligent management has become a hot spot of management mode and concept in the information age. It presents information to the business managers in a more efficient, lower cost, and global form. The system uses the SG-UAP development tools, which is based on Eclipse development environment, and suits for Windows operating system, with Oracle as database development platform, Tomcat network information service for application server. The system uses SOA service-oriented architecture, provides RESTful style service, and HTTP(S as the communication protocol, and JSON as the data format. The system is divided into two parts, the front-end and the backs-end, achieved functions like user login, registration, password retrieving, enterprise internal personnel information management and internal data display and other functions.

  7. Adaptation

    International Development Research Centre (IDRC) Digital Library (Canada)

    building skills, knowledge or networks on adaptation, ... the African partners leading the AfricaAdapt network, together with the UK-based Institute of Development Studies; and ... UNCCD Secretariat, Regional Coordination Unit for Africa, Tunis, Tunisia .... 26 Rural–urban Cooperation on Water Management in the Context of.

  8. Arrangement for adapting a wind wheel to an electric power generator

    Energy Technology Data Exchange (ETDEWEB)

    Beusse, H

    1977-08-11

    The invention is concerned with a device for adapting a wind wheel to an electric power generator in such a way that the wind wheel will always be operated with a maximum performance coefficient, that another source of energy, e.g. a prime mover, can supply the power deficit if the wind power is not sufficient, and that the generator at the output of the facility is kept mains-synchronous of constant speed and constant voltage. According to the invention, the shaft power of the wind power engine is transmitted to a first generator driving an electromotor. The motor is coupled to a second generator feeding into a consumer grid. By means of an anemometer the excitation output of the motor is controled in such manner that the speed of the generator is practically constant-provided a sufficient supply of wind is available. On the shaft of the output generator a prinse mover, e.g. a Diesel engine, is mounted being controllable for contant speed by means of a controll device in such a way that the prime mover takes over the missing amount of power if the wind supply falls short of the power taken off at the generator output.

  9. An architecture for object-oriented intelligent control of power systems in space

    Science.gov (United States)

    Holmquist, Sven G.; Jayaram, Prakash; Jansen, Ben H.

    1993-01-01

    A control system for autonomous distribution and control of electrical power during space missions is being developed. This system should free the astronauts from localizing faults and reconfiguring loads if problems with the power distribution and generation components occur. The control system uses an object-oriented simulation model of the power system and first principle knowledge to detect, identify, and isolate faults. Each power system component is represented as a separate object with knowledge of its normal behavior. The reasoning process takes place at three different levels of abstraction: the Physical Component Model (PCM) level, the Electrical Equivalent Model (EEM) level, and the Functional System Model (FSM) level, with the PCM the lowest level of abstraction and the FSM the highest. At the EEM level the power system components are reasoned about as their electrical equivalents, e.g, a resistive load is thought of as a resistor. However, at the PCM level detailed knowledge about the component's specific characteristics is taken into account. The FSM level models the system at the subsystem level, a level appropriate for reconfiguration and scheduling. The control system operates in two modes, a reactive and a proactive mode, simultaneously. In the reactive mode the control system receives measurement data from the power system and compares these values with values determined through simulation to detect the existence of a fault. The nature of the fault is then identified through a model-based reasoning process using mainly the EEM. Compound component models are constructed at the EEM level and used in the fault identification process. In the proactive mode the reasoning takes place at the PCM level. Individual components determine their future health status using a physical model and measured historical data. In case changes in the health status seem imminent the component warns the control system about its impending failure. The fault isolation

  10. Reactive power and voltage control strategy based on dynamic and adaptive segment for DG inverter

    Science.gov (United States)

    Zhai, Jianwei; Lin, Xiaoming; Zhang, Yongjun

    2018-03-01

    The inverter of distributed generation (DG) can support reactive power to help solve the problem of out-of-limit voltage in active distribution network (ADN). Therefore, a reactive voltage control strategy based on dynamic and adaptive segment for DG inverter is put forward to actively control voltage in this paper. The proposed strategy adjusts the segmented voltage threshold of Q(U) droop curve dynamically and adaptively according to the voltage of grid-connected point and the power direction of adjacent downstream line. And then the reactive power reference of DG inverter can be got through modified Q(U) control strategy. The reactive power of inverter is controlled to trace the reference value. The proposed control strategy can not only control the local voltage of grid-connected point but also help to maintain voltage within qualified range considering the terminal voltage of distribution feeder and the reactive support for adjacent downstream DG. The scheme using the proposed strategy is compared with the scheme without the reactive support of DG inverter and the scheme using the Q(U) control strategy with constant segmented voltage threshold. The simulation results suggest that the proposed method has a significant improvement on solving the problem of out-of-limit voltage, restraining voltage variation and improving voltage quality.

  11. Cognitive radio adaptation for power consumption minimization using biogeography-based optimization

    International Nuclear Information System (INIS)

    Qi Pei-Han; Zheng Shi-Lian; Yang Xiao-Niu; Zhao Zhi-Jin

    2016-01-01

    Adaptation is one of the key capabilities of cognitive radio, which focuses on how to adjust the radio parameters to optimize the system performance based on the knowledge of the radio environment and its capability and characteristics. In this paper, we consider the cognitive radio adaptation problem for power consumption minimization. The problem is formulated as a constrained power consumption minimization problem, and the biogeography-based optimization (BBO) is introduced to solve this optimization problem. A novel habitat suitability index (HSI) evaluation mechanism is proposed, in which both the power consumption minimization objective and the quality of services (QoS) constraints are taken into account. The results show that under different QoS requirement settings corresponding to different types of services, the algorithm can minimize power consumption while still maintaining the QoS requirements. Comparison with particle swarm optimization (PSO) and cat swarm optimization (CSO) reveals that BBO works better, especially at the early stage of the search, which means that the BBO is a better choice for real-time applications. (paper)

  12. Development of model reference adaptive control theory for electric power plant control applications

    Energy Technology Data Exchange (ETDEWEB)

    Mabius, L.E.

    1982-09-15

    The scope of this effort includes the theoretical development of a multi-input, multi-output (MIMO) Model Reference Control (MRC) algorithm, (i.e., model following control law), Model Reference Adaptive Control (MRAC) algorithm and the formulation of a nonlinear model of a typical electric power plant. Previous single-input, single-output MRAC algorithm designs have been generalized to MIMO MRAC designs using the MIMO MRC algorithm. This MRC algorithm, which has been developed using Command Generator Tracker methodologies, represents the steady state behavior (in the adaptive sense) of the MRAC algorithm. The MRC algorithm is a fundamental component in the MRAC design and stability analysis. An enhanced MRC algorithm, which has been developed for systems with more controls than regulated outputs, alleviates the MRC stability constraint of stable plant transmission zeroes. The nonlinear power plant model is based on the Cromby model with the addition of a governor valve management algorithm, turbine dynamics and turbine interactions with extraction flows. An application of the MRC algorithm to a linearization of this model demonstrates its applicability to power plant systems. In particular, the generated power changes at 7% per minute while throttle pressure and temperature, reheat temperature and drum level are held constant with a reasonable level of control. The enhanced algorithm reduces significantly control fluctuations without modifying the output response.

  13. An adaptive model for vanadium redox flow battery and its application for online peak power estimation

    Science.gov (United States)

    Wei, Zhongbao; Meng, Shujuan; Tseng, King Jet; Lim, Tuti Mariana; Soong, Boon Hee; Skyllas-Kazacos, Maria

    2017-03-01

    An accurate battery model is the prerequisite for reliable state estimate of vanadium redox battery (VRB). As the battery model parameters are time varying with operating condition variation and battery aging, the common methods where model parameters are empirical or prescribed offline lacks accuracy and robustness. To address this issue, this paper proposes to use an online adaptive battery model to reproduce the VRB dynamics accurately. The model parameters are online identified with both the recursive least squares (RLS) and the extended Kalman filter (EKF). Performance comparison shows that the RLS is superior with respect to the modeling accuracy, convergence property, and computational complexity. Based on the online identified battery model, an adaptive peak power estimator which incorporates the constraints of voltage limit, SOC limit and design limit of current is proposed to fully exploit the potential of the VRB. Experiments are conducted on a lab-scale VRB system and the proposed peak power estimator is verified with a specifically designed "two-step verification" method. It is shown that different constraints dominate the allowable peak power at different stages of cycling. The influence of prediction time horizon selection on the peak power is also analyzed.

  14. Power and Conflict in Adaptive Management: Analyzing the Discourse of Riparian Management on Public Lands

    Directory of Open Access Journals (Sweden)

    Jennifer S. Arnold

    2012-03-01

    Full Text Available Adaptive collaborative management emphasizes stakeholder engagement as a crucial component of resilient social-ecological systems. Collaboration among diverse stakeholders is expected to enhance learning, build social legitimacy for decision making, and establish relationships that support learning and adaptation in the long term. However, simply bringing together diverse stakeholders does not guarantee productive engagement. Using critical discourse analysis, we examined how diverse stakeholders negotiated knowledge and power in a workshop designed to inform adaptive management of riparian livestock grazing on a National Forest in the southwestern USA. Publicly recognized as a successful component of a larger collaborative effort, we found that the workshop effectively brought together diverse participants, yet still restricted dialogue in important ways. Notably, workshop facilitators took on the additional roles of riparian experts and instructors. As they guided workshop participants toward a consensus view of riparian conditions and management recommendations, they used their status as riparian experts to emphasize commonalities with stakeholders supportive of riparian grazing and accentuate differences with stakeholders skeptical of riparian grazing, including some Forest Service staff with power to influence management decisions. Ultimately, the management plan published one year later did not fully adopt the consensus view from the workshop, but rather included and acknowledged a broader diversity of stakeholder perspectives. Our findings suggest that leaders and facilitators of adaptive collaborative management can more effectively manage for productive stakeholder engagement and, thus, social-ecological resilience if they are more tentative in their convictions, more critical of the role of expert knowledge, and more attentive to the knowledge, interests, and power of diverse stakeholders.

  15. Mitigation of wind power fluctuations by intelligent response of demand and distributed generation

    NARCIS (Netherlands)

    MacDougall, P.A.; Warmer, C.; Kok, K.

    2011-01-01

    With the world becoming ever more conscious of the necessity for clean, sustainable energy sources, an increased proportion of energy produced by wind resources is expected. In the current power system, the integration of such large capacity of non-load-following and intermittent supply leads to

  16. Stochastic pattern recognition techniques and artificial intelligence for nuclear power plant surveillance and anomaly detection

    Energy Technology Data Exchange (ETDEWEB)

    Kemeny, L.G

    1998-12-31

    In this paper a theoretical and system conceptual model is outlined for the instrumentation, core assessment and surveillance and anomaly detection of a nuclear power plant. The system specified is based on the statistical on-line analysis of optimally placed instrumentation sensed fluctuating signals in terms of such variates as coherence, correlation function, zero-crossing and spectral density

  17. Stochastic pattern recognition techniques and artificial intelligence for nuclear power plant surveillance and anomaly detection

    International Nuclear Information System (INIS)

    Kemeny, L.G.

    1998-01-01

    In this paper a theoretical and system conceptual model is outlined for the instrumentation, core assessment and surveillance and anomaly detection of a nuclear power plant. The system specified is based on the statistical on-line analysis of optimally placed instrumentation sensed fluctuating signals in terms of such variates as coherence, correlation function, zero-crossing and spectral density

  18. PMU Measurement-Based Intelligent Strategy for Power System Controlled Islanding

    Directory of Open Access Journals (Sweden)

    Yi Tang

    2018-01-01

    Full Text Available Controlled islanding is an effective remedy to prevent large-area blackouts in a power system under a critically unstable condition. When and where to separate the power system are the essential issues facing controlled islanding. In this paper, both tasks are studied to ensure higher time efficiency and a better post-splitting restoration effect. A transient stability assessment model based on extreme learning machine (ELM and trajectory fitting (TF is constructed to determine the start-up criterion for controlled islanding. This model works through prompt stability status judgment with ELM and selective result amendment with TF to ensure that the assessment is both efficient and accurate. Moreover, a splitting surface searching algorithm, subject to minimal power disruption, is proposed for determination of the controlled islanding implementing locations. A highlight of this algorithm is a proposed modified electrical distance concept defined by active power magnitude and reactance on transmission lines that realize a computational burden reduction without feasible solution loss. Finally, the simulation results and comparison analysis based on the New England 39-bus test system validates the implementation effects of the proposed controlled islanding strategy.

  19. Low-power operation using self-timed circuits and adaptive scaling of the supply voltage

    DEFF Research Database (Denmark)

    Nielsen, Lars Skovby; Niessen, C.; Sparsø, Jens

    1994-01-01

    Recent research has demonstrated that for certain types of applications like sampled audio systems, self-timed circuits can achieve very low power consumption, because unused circuit parts automatically turn into a stand-by mode. Additional savings may be obtained by combining the self......-timed circuits with a mechanism that adaptively adjusts the supply voltage to the smallest possible, while maintaining the performance requirements. This paper describes such a mechanism, analyzes the possible power savings, and presents a demonstrator chip that has been fabricated and tested. The idea...... of voltage scaling has been used previously in synchronous circuits, and the contributions of the present paper are: 1) the combination of supply scaling and self-timed circuitry which has some unique advantages, and 2) the thorough analysis of the power savings that are possible using this technique.>...

  20. Adaptive Differential Evolution Approach for Constrained Economic Power Dispatch with Prohibited Operating Zones

    Directory of Open Access Journals (Sweden)

    Abdellatif HAMOUDA

    2011-12-01

    Full Text Available Economic power dispatch (EPD is one of the main tools for optimal operation and planning of modern power systems. To solve effectively the EPD problem, most of the conventional calculus methods rely on the assumption that the fuel cost characteristic of a generating unit is a continuous and convex function, resulting in inaccurate dispatch. This paper presents the design and application of efficient adaptive differential evolution (ADE algorithm for the solution of the economic power dispatch problem, where the non-convex characteristics of the generators, such us prohibited operating zones and ramp rate limits of the practical generator operation are considered. The 26 bus benchmark test system with 6 units having prohibited operating zones and ramp rate limits was used for testing and validation purposes. The results obtained demonstrate the effectiveness of the proposed method for solving the non-convex economic dispatch problem.

  1. Adaptive fuzzy control of neutron power of the TRIGA Mark III reactor

    International Nuclear Information System (INIS)

    Rojas R, E.

    2014-01-01

    The design and implementation of an identification and control scheme of the TRIGA Mark III research nuclear reactor of the Instituto Nacional de Investigaciones Nucleares (ININ) of Mexico is presented in this thesis work. The identification of the reactor dynamics is carried out using fuzzy logic based systems, in which a learning process permits the adjustment of the membership function parameters by means of techniques based on neural networks and bio-inspired algorithms. The resulting identification system is a useful tool that allows the emulation of the reactor power behavior when different types of insertions of reactivity are applied into the core. The identification of the power can also be used for the tuning of the parameters of a control system. On the other hand, the regulation of the reactor power is carried out by means of an adaptive and stable fuzzy control scheme. The control law is derived using the input-output linearization technique, which permits the introduction of a desired power profile for the plant to follow asymptotically. This characteristic is suitable for managing the ascent of power from an initial level n o up to a predetermined final level n f . During the increase of power, a constraint related to the rate of change in power is considered by the control scheme, thus minimizing the occurrence of a safety reactor shutdown due to a low reactor period value. Furthermore, the theory of stability in the sense of Lyapunov is used to obtain a supervisory control law which maintains the power error within a tolerance region, thus guaranteeing the stability of the power of the closed loop system. (Author)

  2. Multimedia transmission in MC-CDMA using adaptive subcarrier power allocation and CFO compensation

    Science.gov (United States)

    Chitra, S.; Kumaratharan, N.

    2018-02-01

    Multicarrier code division multiple access (MC-CDMA) system is one of the most effective techniques in fourth-generation (4G) wireless technology, due to its high data rate, high spectral efficiency and resistance to multipath fading. However, MC-CDMA systems are greatly deteriorated by carrier frequency offset (CFO) which is due to Doppler shift and oscillator instabilities. It leads to loss of orthogonality among the subcarriers and causes intercarrier interference (ICI). Water filling algorithm (WFA) is an efficient resource allocation algorithm to solve the power utilisation problems among the subcarriers in time-dispersive channels. The conventional WFA fails to consider the effect of CFO. To perform subcarrier power allocation with reduced CFO and to improve the capacity of MC-CDMA system, residual CFO compensated adaptive subcarrier power allocation algorithm is proposed in this paper. The proposed technique allocates power only to subcarriers with high channel to noise power ratio. The performance of the proposed method is evaluated using random binary data and image as source inputs. Simulation results depict that the bit error rate performance and ICI reduction capability of the proposed modified WFA offered superior performance in both power allocation and image compression for high-quality multimedia transmission in the presence of CFO and imperfect channel state information conditions.

  3. Motor modules during adaptation to walking in a powered ankle exoskeleton.

    Science.gov (United States)

    Jacobs, Daniel A; Koller, Jeffrey R; Steele, Katherine M; Ferris, Daniel P

    2018-01-03

    Modules of muscle recruitment can be extracted from electromyography (EMG) during motions, such as walking, running, and swimming, to identify key features of muscle coordination. These features may provide insight into gait adaptation as a result of powered assistance. The aim of this study was to investigate the changes (module size, module timing and weighting patterns) of surface EMG data during assisted and unassisted walking in an powered, myoelectric, ankle-foot orthosis (ankle exoskeleton). Eight healthy subjects wore bilateral ankle exoskeletons and walked at 1.2 m/s on a treadmill. In three training sessions, subjects walked for 40 min in two conditions: unpowered (10 min) and powered (30 min). During each session, we extracted modules of muscle recruitment via nonnegative matrix factorization (NNMF) from the surface EMG signals of ten muscles in the lower limb. We evaluated reconstruction quality for each muscle individually using R 2 and normalized root mean squared error (NRMSE). We hypothesized that the number of modules needed to reconstruct muscle data would be the same between conditions and that there would be greater similarity in module timings than weightings. Across subjects, we found that six modules were sufficient to reconstruct the muscle data for both conditions, suggesting that the number of modules was preserved. The similarity of module timings and weightings between conditions was greater then random chance, indicating that muscle coordination was also preserved. Motor adaptation during walking in the exoskeleton was dominated by changes in the module timings rather than module weightings. The segment number and the session number were significant fixed effects in a linear mixed-effect model for the increase in R 2 with time. Our results show that subjects walking in a exoskeleton preserved the number of modules and the coordination of muscles within the modules across conditions. Training (motor adaptation within the session and

  4. Modeling and simulation of adaptive Neuro-fuzzy based intelligent system for predictive stabilization in structured overlay networks

    Directory of Open Access Journals (Sweden)

    Ramanpreet Kaur

    2017-02-01

    Full Text Available Intelligent prediction of neighboring node (k well defined neighbors as specified by the dht protocol dynamism is helpful to improve the resilience and can reduce the overhead associated with topology maintenance of structured overlay networks. The dynamic behavior of overlay nodes depends on many factors such as underlying user’s online behavior, geographical position, time of the day, day of the week etc. as reported in many applications. We can exploit these characteristics for efficient maintenance of structured overlay networks by implementing an intelligent predictive framework for setting stabilization parameters appropriately. Considering the fact that human driven behavior usually goes beyond intermittent availability patterns, we use a hybrid Neuro-fuzzy based predictor to enhance the accuracy of the predictions. In this paper, we discuss our predictive stabilization approach, implement Neuro-fuzzy based prediction in MATLAB simulation and apply this predictive stabilization model in a chord based overlay network using OverSim as a simulation tool. The MATLAB simulation results present that the behavior of neighboring nodes is predictable to a large extent as indicated by the very small RMSE. The OverSim based simulation results also observe significant improvements in the performance of chord based overlay network in terms of lookup success ratio, lookup hop count and maintenance overhead as compared to periodic stabilization approach.

  5. A Decentralized Multivariable Robust Adaptive Voltage and Speed Regulator for Large-Scale Power Systems

    Science.gov (United States)

    Okou, Francis A.; Akhrif, Ouassima; Dessaint, Louis A.; Bouchard, Derrick

    2013-05-01

    This papter introduces a decentralized multivariable robust adaptive voltage and frequency regulator to ensure the stability of large-scale interconnnected generators. Interconnection parameters (i.e. load, line and transormer parameters) are assumed to be unknown. The proposed design approach requires the reformulation of conventiaonal power system models into a multivariable model with generator terminal voltages as state variables, and excitation and turbine valve inputs as control signals. This model, while suitable for the application of modern control methods, introduces problems with regards to current design techniques for large-scale systems. Interconnection terms, which are treated as perturbations, do not meet the common matching condition assumption. A new adaptive method for a certain class of large-scale systems is therefore introduces that does not require the matching condition. The proposed controller consists of nonlinear inputs that cancel some nonlinearities of the model. Auxiliary controls with linear and nonlinear components are used to stabilize the system. They compensate unknown parametes of the model by updating both the nonlinear component gains and excitation parameters. The adaptation algorithms involve the sigma-modification approach for auxiliary control gains, and the projection approach for excitation parameters to prevent estimation drift. The computation of the matrix-gain of the controller linear component requires the resolution of an algebraic Riccati equation and helps to solve the perturbation-mismatching problem. A realistic power system is used to assess the proposed controller performance. The results show that both stability and transient performance are considerably improved following a severe contingency.

  6. An Adaptive Estimation Scheme for Open-Circuit Voltage of Power Lithium-Ion Battery

    Directory of Open Access Journals (Sweden)

    Yun Zhang

    2013-01-01

    Full Text Available Open-circuit voltage (OCV is one of the most important parameters in determining state of charge (SoC of power battery. The direct measurement of it is costly and time consuming. This paper describes an adaptive scheme that can be used to derive OCV of the power battery. The scheme only uses the measurable input (terminal current and the measurable output (terminal voltage signals of the battery system and is simple enough to enable online implement. Firstly an equivalent circuit model is employed to describe the polarization characteristic and the dynamic behavior of the lithium-ion battery; the state-space representation of the electrical performance for the battery is obtained based on the equivalent circuit model. Then the implementation procedure of the adaptive scheme is given; also the asymptotic convergence of the observer error and the boundedness of all the parameter estimates are proven. Finally, experiments are carried out, and the effectiveness of the adaptive estimation scheme is validated by the experimental results.

  7. Criteria of diversity evaluation for intelligent diagnosis of nuclear power plants

    International Nuclear Information System (INIS)

    Washio, Takashi; Sakuma, Masatake; Furukawa, Hiroshi; Kitamura, Masaharu.

    1995-01-01

    One of important problems of a current operation support system for a nuclear power plant is that the credibility of its resultant suggestions is not always high sufficiently. The authors have proposed an efficient remedy called 'Diversity Criteria' for this issue in the previous works. It employs a variety of information resources and reasoning mechanisms for the system to enhance its entire credibility. Within this framework, a complementary combination of the resources and mechanisms is desired. The work presented here proposes systematic and quantitative measures determining the appropriate combinations. First, concrete and systematic guidelines are proposed for the detailed criteria of 'Information Diversity' and 'Methodology Diversity'. Next, two concepts of 'Orthogonality of Identified Result' and 'Orthogonality of Utilized Symptom' are presented together with their quantitative measures. These guidelines and measures have been applied to an example of failure diagnosis of a nuclear power plant, and their efficiency has been clearly confirmed. (author)

  8. Artificial intelligence expert system for nuclear power plant control and maintenance

    International Nuclear Information System (INIS)

    Westrom, G.B.

    1987-01-01

    A major concern in emergency response in a nuclear power plant is the lack of real experience with a catastrophic condition. Experts do more than just follow a set of rules. They have experience and insight into problems and are able to use their professional judgement. The objectives of this expert system are: Detect subtle off-normal trends in a reactor power plant system. Alert the operator with color graphics and synthesized voice commands. Identify the source of the problem and advise the operator on steps to restore the plant to normal operation. Provide an explanation facility and database to supply detailed information on component history and reasoning process. The RHRS (Residual Heat Removal System) was selected for the initial expert systems development because it is extremely important during refueling and cold shutdown operations

  9. Data-Centric Situational Awareness and Management in Intelligent Power Systems

    Science.gov (United States)

    Dai, Xiaoxiao

    The rapid development of technology and society has made the current power system a much more complicated system than ever. The request for big data based situation awareness and management becomes urgent today. In this dissertation, to respond to the grand challenge, two data-centric power system situation awareness and management approaches are proposed to address the security problems in the transmission/distribution grids and social benefits augmentation problem at the distribution-customer lever, respectively. To address the security problem in the transmission/distribution grids utilizing big data, the first approach provides a fault analysis solution based on characterization and analytics of the synchrophasor measurements. Specically, the optimal synchrophasor measurement devices selection algorithm (OSMDSA) and matching pursuit decomposition (MPD) based spatial-temporal synchrophasor data characterization method was developed to reduce data volume while preserving comprehensive information for the big data analyses. And the weighted Granger causality (WGC) method was investigated to conduct fault impact causal analysis during system disturbance for fault localization. Numerical results and comparison with other methods demonstrate the effectiveness and robustness of this analytic approach. As more social effects are becoming important considerations in power system management, the goal of situation awareness should be expanded to also include achievements in social benefits. The second approach investigates the concept and application of social energy upon the University of Denver campus grid to provide management improvement solutions for optimizing social cost. Social element--human working productivity cost, and economic element--electricity consumption cost, are both considered in the evaluation of overall social cost. Moreover, power system simulation, numerical experiments for smart building modeling, distribution level real-time pricing and social

  10. Acquisition of Real Time Simulator for Intelligent Power Networks in Operational Energy Applications

    Science.gov (United States)

    2017-12-05

    and fixed power installations to enhance DoD mission effectiveness. The long term goal of this effort is to create a strong research and education ...effort is to create a strong research and education center at UTSA focused on innovative technologies and solutions for Energy-Systems Management...in Real-Time. , Grid Low voltage dc = ~ Dual Active Bridge (DAB) With 3-Level NPC HV bridge and High frequency transformer High voltage dc

  11. Artificial Intelligence Based Control Power Optimization on Tailless Aircraft. [ARMD Seedling Fund Phase I

    Science.gov (United States)

    Gern, Frank; Vicroy, Dan D.; Mulani, Sameer B.; Chhabra, Rupanshi; Kapania, Rakesh K.; Schetz, Joseph A.; Brown, Derrell; Princen, Norman H.

    2014-01-01

    Traditional methods of control allocation optimization have shown difficulties in exploiting the full potential of controlling large arrays of control devices on innovative air vehicles. Artificial neutral networks are inspired by biological nervous systems and neurocomputing has successfully been applied to a variety of complex optimization problems. This project investigates the potential of applying neurocomputing to the control allocation optimization problem of Hybrid Wing Body (HWB) aircraft concepts to minimize control power, hinge moments, and actuator forces, while keeping system weights within acceptable limits. The main objective of this project is to develop a proof-of-concept process suitable to demonstrate the potential of using neurocomputing for optimizing actuation power for aircraft featuring multiple independently actuated control surfaces. A Nastran aeroservoelastic finite element model is used to generate a learning database of hinge moment and actuation power characteristics for an array of flight conditions and control surface deflections. An artificial neural network incorporating a genetic algorithm then uses this training data to perform control allocation optimization for the investigated aircraft configuration. The phase I project showed that optimization results for the sum of required hinge moments are improved by more than 12% over the best Nastran solution by using the neural network optimization process.

  12. Modular high-voltage bias generator powered by dual-looped self-adaptive wireless power transmission.

    Science.gov (United States)

    Xie, Kai; Huang, An-Feng; Li, Xiao-Ping; Guo, Shi-Zhong; Zhang, Han-Lu

    2015-04-01

    We proposed a modular high-voltage (HV) bias generator powered by a novel transmitter-sharing inductive coupled wireless power transmission technology, aimed to extend the generator's flexibility and configurability. To solve the problems caused through an uncertain number of modules, a dual-looped self-adaptive control method is proposed that is capable of tracking resonance frequency while maintaining a relatively stable induction voltage for each HV module. The method combines a phase-locked loop and a current feedback loop, which ensures an accurate resonance state and a relatively constant boost ratio for each module, simplifying the architecture of the boost stage and improving the total efficiency. The prototype was built and tested. The input voltage drop of each module is less than 14% if the module number varies from 3 to 10; resonance tracking is completed within 60 ms. The efficiency of the coupling structure reaches up to 95%, whereas the total efficiency approaches 73% for a rated output. Furthermore, this technology can be used in various multi-load wireless power supply applications.

  13. A novel optimized hybrid fuzzy logic intelligent PID controller for an interconnected multi-area power system with physical constraints and boiler dynamics.

    Science.gov (United States)

    Gomaa Haroun, A H; Li, Yin-Ya

    2017-11-01

    In the fast developing world nowadays, load frequency control (LFC) is considered to be a most significant role for providing the power supply with good quality in the power system. To deliver a reliable power, LFC system requires highly competent and intelligent control technique. Hence, in this article, a novel hybrid fuzzy logic intelligent proportional-integral-derivative (FLiPID) controller has been proposed for LFC of interconnected multi-area power systems. A four-area interconnected thermal power system incorporated with physical constraints and boiler dynamics is considered and the adjustable parameters of the FLiPID controller are optimized using particle swarm optimization (PSO) scheme employing an integral square error (ISE) criterion. The proposed method has been established to enhance the power system performances as well as to reduce the oscillations of uncertainties due to variations in the system parameters and load perturbations. The supremacy of the suggested method is demonstrated by comparing the simulation results with some recently reported heuristic methods such as fuzzy logic proportional-integral (FLPI) and intelligent proportional-integral-derivative (PID) controllers for the same electrical power system. the investigations showed that the FLiPID controller provides a better dynamic performance and outperform compared to the other approaches in terms of the settling time, and minimum undershoots of the frequency as well as tie-line power flow deviations following a perturbation, in addition to perform appropriate settlement of integral absolute error (IAE). Finally, the sensitivity analysis of the plant is inspected by varying the system parameters and operating load conditions from their nominal values. It is observed that the suggested controller based optimization algorithm is robust and perform satisfactorily with the variations in operating load condition, system parameters and load pattern. Copyright © 2017 ISA. Published by

  14. Time-optimal control of nuclear reactor power with adaptive proportional- integral-feedforward gains

    International Nuclear Information System (INIS)

    Park, Moon Ghu; Cho, Nam Zin

    1993-01-01

    A time-optimal control method which consists of coarse and fine control stages is described here. During the coarse control stage, the maximum control effort (time-optimal) is used to direct the system toward the switching boundary which is set near the desired power level. At this boundary, the controller is switched to the fine control stage in which an adaptive proportional-integral-feedforward (PIF) controller is used to compensate for any unmodeled reactivity feedback effects. This fine control is also introduced to obtain a constructive method for determining the (adaptive) feedback gains against the sampling effect. The feedforward control term is included to suppress the over-or undershoot. The estimation and feedback of the temperature-induced reactivity is also discussed

  15. Implementation of high-speed–low-power adaptive finite impulse response filter with novel architecture

    Directory of Open Access Journals (Sweden)

    Manish Jaiswal

    2015-03-01

    Full Text Available An energy efficient high-speed adaptive finite impulse response filter with novel architecture is developed. Synthesis results along with novel architecture on different complementary metal–oxide semiconductor (CMOS families are presented. Analysis is performed using Artix-7, Spartan-6 and Virtex-4 for most popular adaptive least mean square filter for different orders such as N = 8, 16, 32. The presented work is done using MATLAB (2013b and Xilinx (14.2. From the synthesis results, it can be found that CMOS (28 nm achieves the lowest power and critical path delay compared to others, and thus proves its efficiency in terms of energy. Different parameters are considered such as look up tables and input–output blocks, along with their optimised results.

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

    Science.gov (United States)

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

    2013-11-01

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

  17. Neural network for adapting nuclear power plant control for wide-range operation

    International Nuclear Information System (INIS)

    Ku, C.C.; Lee, K.Y.; Edwards, R.M.

    1991-01-01

    A new concept of using neural networks has been evaluated for optimal control of a nuclear reactor. The neural network uses the architecture of a standard backpropagation network; however, a new dynamic learning algorithm has been developed to capture the underlying system dynamics. The learning algorithm is based on parameter estimation for dynamic systems. The approach is demonstrated on an optimal reactor temperature controller by adjusting the feedback gains for wide-range operation. Application of optimal control to a reactor has been considered for improving temperature response using a robust fifth-order reactor power controller. Conventional gain scheduling can be employed to extend the range of good performance to accommodate large changes in power where nonlinear characteristics significantly modify the dynamics of the power plant. Gain scheduling is developed based on expected parameter variations, and it may be advantageous to further adapt feedback gains on-line to better match actual plant performance. A neural network approach is used here to adapt the gains to better accommodate plant uncertainties and thereby achieve improved robustness characteristics

  18. Fault-tolerant design of adaptive digital control systems for power plant components

    International Nuclear Information System (INIS)

    Parlos, A.G.; Menon, S.K.

    1992-01-01

    An adaptive controller has been designed for the water level of a Westinghouse type U-tube steam generator, and its operation has been demonstrated in the entire power range via computer simulations. The proposed design exhibits improved performance, at low operating powers, a,s compared to existing controller types. The continuous-time controller design is performed systematically via the Linear Quadratic Gaussian/Loop Transfer Recovery method, followed by gain adaptation allowing controller operation in the entire power range. Digital implementation of the controller is accomplished by a digital redesign which results in matching the digital and continuous-time system and controller states. It is only at this stage of the control system design process that issues such as microprocessor induced quantization effects are taken into account. The use of computer-aided-design software greatly expedites the design cycle, allowing the designer to maximize the controller stability robustness to uncertainties via numerous iterations. This inherent controller robustness can be exploited to tolerate incipient plant faults, such as deteriorating U-tube heat transfer properties, without significant loss of controller performance

  19. Adapt

    Science.gov (United States)

    Bargatze, L. F.

    2015-12-01

    Active Data Archive Product Tracking (ADAPT) is a collection of software routines that permits one to generate XML metadata files to describe and register data products in support of the NASA Heliophysics Virtual Observatory VxO effort. ADAPT is also a philosophy. The ADAPT concept is to use any and all available metadata associated with scientific data to produce XML metadata descriptions in a consistent, uniform, and organized fashion to provide blanket access to the full complement of data stored on a targeted data server. In this poster, we present an application of ADAPT to describe all of the data products that are stored by using the Common Data File (CDF) format served out by the CDAWEB and SPDF data servers hosted at the NASA Goddard Space Flight Center. These data servers are the primary repositories for NASA Heliophysics data. For this purpose, the ADAPT routines have been used to generate data resource descriptions by using an XML schema named Space Physics Archive, Search, and Extract (SPASE). SPASE is the designated standard for documenting Heliophysics data products, as adopted by the Heliophysics Data and Model Consortium. The set of SPASE XML resource descriptions produced by ADAPT includes high-level descriptions of numerical data products, display data products, or catalogs and also includes low-level "Granule" descriptions. A SPASE Granule is effectively a universal access metadata resource; a Granule associates an individual data file (e.g. a CDF file) with a "parent" high-level data resource description, assigns a resource identifier to the file, and lists the corresponding assess URL(s). The CDAWEB and SPDF file systems were queried to provide the input required by the ADAPT software to create an initial set of SPASE metadata resource descriptions. Then, the CDAWEB and SPDF data repositories were queried subsequently on a nightly basis and the CDF file lists were checked for any changes such as the occurrence of new, modified, or deleted

  20. Adaptation of fast responding power supply for radial position control in SST-1

    International Nuclear Information System (INIS)

    Sharma, Dinesh Kumar; Patel, Kiritkumar B.; Singh, Akhilesh Kumar; Dhongde, Jasraj

    2013-01-01

    A high current, fast responding power supply was installed in 2005 for vertical stabilization of elongated plasmas in SST-1 tokamak. Presently, during initial experiments of SST-1 tokamak the need for radial control during current build-up was envisaged. For this purpose the existing power supply was suitable and the same was re-commissioned and control adaptations were carried as per experimental requirements. This paper highlights the capabilities of the power supply and details the modifications in the control interfaces and test programs for the radial control purpose. Details of the operation of the power supply along with control interfaces with performance measurements are provided. The re-commissioning provided an opportunity in the trouble shooting methods and sequential operation of the system. With the operational use on the actual coil the mutual effects are understood better and appropriate test programs are prepared. The power supply provided satisfactory performance for the intended use. In additional the system is suitable to simulate a plasma current loop to enable the testing and calibration of Rogowski coil used for plasma current measurement. (author)

  1. Learning-Based Adaptive Imputation Methodwith kNN Algorithm for Missing Power Data

    Directory of Open Access Journals (Sweden)

    Minkyung Kim

    2017-10-01

    Full Text Available This paper proposes a learning-based adaptive imputation method (LAI for imputing missing power data in an energy system. This method estimates the missing power data by using the pattern that appears in the collected data. Here, in order to capture the patterns from past power data, we newly model a feature vector by using past data and its variations. The proposed LAI then learns the optimal length of the feature vector and the optimal historical length, which are significant hyper parameters of the proposed method, by utilizing intentional missing data. Based on a weighted distance between feature vectors representing a missing situation and past situation, missing power data are estimated by referring to the k most similar past situations in the optimal historical length. We further extend the proposed LAI to alleviate the effect of unexpected variation in power data and refer to this new approach as the extended LAI method (eLAI. The eLAI selects a method between linear interpolation (LI and the proposed LAI to improve accuracy under unexpected variations. Finally, from a simulation under various energy consumption profiles, we verify that the proposed eLAI achieves about a 74% reduction of the average imputation error in an energy system, compared to the existing imputation methods.

  2. Optic Nerve Stimulation System with Adaptive Wireless Powering and Data Telemetry

    Directory of Open Access Journals (Sweden)

    Xing Li

    2017-12-01

    Full Text Available To treat retinal degenerative diseases, a transcorneal electrical stimulation-based system is proposed, which consists of an eye implant and an external component. The eye implant is wirelessly powered and controlled by the external component to generate the required bi-polar current pattern for transcorneal stimulation with an amplitude range of 5 μA to 320 μA, a frequency range of 10 Hz to 160 Hz and a duty ratio range of 2.5% to 20%. Power delivery control includes power boosting in preparation for stimulation, and normal power regulation that adapts to both coupling and load variations. Only one pair of coils is used for both the power link and the bi-directional data link. Except for the secondary coil, the eye implant is fully integrated on chip and is fabricated using UMC (United Microelectronics Corporation, Hsinchu, Taiwan 0.13 μm complementary metal-oxide-semiconductor (CMOS process with a size of 1.5 mm × 1.5 mm. The secondary coil is fabricated on a printed circuit board (PCB with a diameter of only 4.4 mm. After coating with biocompatible silicone, the whole implant has dimensions of 6 mm in diameter with a thickness of less than 1 mm. The whole device can be put onto the sclera and beneath the eye’s conjunctiva. System functionality and electrical performance are demonstrated with measurement results.

  3. Fatigue distribution optimization for offshore wind farms using intelligent agent control

    DEFF Research Database (Denmark)

    Zhao, Rongyong; Shen, Wen Zhong; Knudsen, Torben

    2012-01-01

    with its neighbouring downwind turbines and organizes them adaptively into a wind delivery group along the wind direction. The agent attributes and the event structure are designed on the basis of the intelligent agent theory by using the unified modelling language. The control strategy of the intelligent......A novel control approach is proposed to optimize the fatigue distribution of wind turbines in a large‐scale offshore wind farm on the basis of an intelligent agent theory. In this approach, each wind turbine is considered to be an intelligent agent. The turbine at the farm boundary communicates...... coefficient for every wind turbine. The optimization is constrained such that the average fatigue for every turbine is smaller than what would be achieved by conventional dispatch and such that the total power loss of the wind farm is restricted to a few percent of the total power. This intelligent agent...

  4. Expert systems with fuzzy logic for intelligent diagnosis and control of nuclear power plants

    International Nuclear Information System (INIS)

    Abdelhai, M.I.; Upadhyaya, B.R.

    1990-01-01

    A model-based production-rule analysis system was developed for the tracking and diagnosis of the condition of a reactor coolant system (RCS) using a fuzzy logic algorithm. Since nuclear power plants are large and complex systems, it is natural that vagueness, uncertainty, and imprecision are introduced to such systems. Even in fully automated power plants, the critical diagnostic and control changes must be made by operators who usually express their diagnostic and control strategies linguistically as sets of heuristic decision rules. Therefore, additional imprecisions are introduced into the systems because of the imprecise nature of such qualitative strategies when they are converted into quantitative rules. Such problems, in which the source of imprecision is the absence of sharply defined criteria of class membership, could be dealt with using fuzzy set theory. Hence, a fuzzy logic algorithm could be initiated to implement a known heuristic whenever the given information is vague and qualitative, and it will allow operators to introduce certain linguistic assertions and commands to diagnose and control the system

  5. Impact of Nonlinear Power Amplifier on Link Adaptation Algorithm of OFDM Systems

    DEFF Research Database (Denmark)

    Das, Suvra S.; Tariq, Faisal; Rahman, Muhammad Imadur

    2007-01-01

    The impact of non linear distortion due to High Power Amplifier (HPA) on the performance of Link Adaptation (LA) - Orthogonal Frequency Division Multiplexing (OFDM) based wireless system is analyzed. The performance of both Forward Error Control Coding (FEC) en-coded and uncoded system is evaluated....... LA maximizes the throughput while maintaining a required Block Error Rate (BLER). It is found that when OFDM signal, which has high PAPR, suffers non linear distortion due to non ideal HPA, the LA fails to meet the target BLER. Detailed analysis of the distortion and effects on LA are presented...

  6. Adaptive control strategy for ECRH negative high-voltage power supply based on CMAC neural network

    International Nuclear Information System (INIS)

    Luo Xiaoping; Du Pengying; Du Shaowu

    2011-01-01

    In order to solve the problem that the negative high-voltage power supply in an electron cyclotron resonance heating (ECRH) system can not satisfy the requirements because of the nonlinearity and sensitivity, the direct inverse model control strategy was proposed by using cerebellar model articulation controller(CMAC) for better control, and experiments were carried out to study the system performances with CMAC tracing dynamic signals. The results show that this strategy is strong in self-learning and self-adaptation and easy to be realized. (authors)

  7. Design and simplification of Adaptive Neuro-Fuzzy Inference Controllers for power plants

    Energy Technology Data Exchange (ETDEWEB)

    Alturki, F.A.; Abdennour, A. [King Saud University, Riyadh (Saudi Arabia). Electrical Engineering Dept.

    1999-10-01

    This article presents the design of an Adaptive Neuro-Fuzzy Inference Controller (ANFIC) for a 160 MW power plant. The space of operating conditions of the plant is partitioned into five regions. For each of the regions, an optimal controller is designed to meet a set of design objectives. The resulting five linear controllers are used to train the ANFIC. To enhance the applicability of the control system, a new algorithm that reduces the fuzzy rules to the most essential ones is also presented. This algorithm offers substantial savings in computation time while maintaining the performance and robustness of the original controller. (author)

  8. EDITORIAL: Adaptive and active materials: Selected papers from the ASME 2011 Conference on Smart Materials, Adaptive Structures and Intelligent Systems (SMASIS 11) (Scottsdale, AZ, USA, 18-21 September 2011) Adaptive and active materials: Selected papers from the ASME 2011 Conference on Smart Materials, Adaptive Structures and Intelligent Systems (SMASIS 11) (Scottsdale, AZ, USA, 18-21 September 2011)

    Science.gov (United States)

    Brei, Diann

    2012-09-01

    The fourth annual meeting of the ASME/AIAA Smart Materials, Adaptive Structures and Intelligent Systems Conference (SMASIS) took place in sunny Scottsdale, Arizona. Each year we strive to grow and offer new experiences. This year we held a special Guest Symposium on Sustainability along with two focused topic tracks on energy harvesting and active composites to encourage cross-fertilization between these important fields and our community. This cross-disciplinary emphasis was reflected in keynote talks by Dr Wayne Brown, President and founder of Dynalloy, Inc., 'Cross-Discipline Sharing'; Dr Brad Allenby, Arizona State University, 'You Want the Future? You can't Handle the Future!'; and Professor Aditi Chattopadhyay, Arizona State University, 'A Multidisciplinary Approach to Structural Health Monitoring and Prognosis'. SMASIS continues to grow our community through both social and technical interchange. The conference location, the exotic Firesky Resort and Spa, exemplified the theme of our Guest Symposium on Sustainability, being the only Green Seal certified resort in Arizona, and highlighting four elements thought to represent all that exist: fire, water, earth and air. Several special events were held around this theme including the night at the oasis reception sponsored by General Motors, sustainability bingo, smart trivia and student networking lunches, and an Arizona pow-wow with a spectacular Indian hoop dance. Our student and young professional development continues to grow strong with best paper and hardware competitions, scavenger student outing and games night. We are very proud that our students and young professionals are always seeking out ways to give back to the community, including organizing outreach to local high school talent. We thank all of our sponsors who made these special events possible. We hope that these social events provided participants with the opportunity to expand their own personal community and broaden their horizons. Our

  9. Artificial Intelligence application to surveillance and diagnosis of nuclear power plants

    International Nuclear Information System (INIS)

    Brunet, E.; Monnier, B.; Zwingelstein, G.

    1986-01-01

    Acquisition and representation of knowledge are fundamental problems in Aritificial Intellegence and especially in expert system domain. In this article, the authors propose a conceptual model allowing to describe the universe the expert is working on when trying to make a diagnosis. The expert determines the descriptors and predicates with which he describes laws, states, objects involved in his reasoning. With this model, they are presenting design and development of Knowledge Acquisition Module allowing a dialogue in a specialized natural language used by the expert system to assist in the detection of loose parts in nuclear power plants. Using a classical lexical and syntactic analysis, they propose to associate grammatical semantic properties to the specialized language words. The method used allows the design of a sub expert system for understanding of the specialized natural language

  10. Testing and interfacing intelligent power supplies for the Los Alamos National Laboratory Accelerator Complex

    International Nuclear Information System (INIS)

    Sturrock, J.C.; Cohen, S.; Weintraub, B.L.; Hayden, D.J.; Archuleta, S.F.

    1992-01-01

    New high-current, high-precision microprocessor-controlled power supplies, built by Alpha Scientific Electronics of Hayward, CA, have been installed at the Los Alamos National Laboratory Accelerator Complex. Each unit has sophisticated microprocessor control on-board and communicates via RS-422 (serial communications). The units use a high level ASCII-based control protocol. Performance tests were conducted to verify adherence to specification and to ascertain ultimate long-term stability. The ''front-end'' software used by the accelerator control system has been written to accommodate these new devices. The supplies are interfaced to the control system through a terminal server port connected to the site-wide ediernet backbone. Test design and results as well as details of the software implementation for the analog and digital control of the supplies through the accelerator control system are presented

  11. Power plant experience with artificial intelligence based, on-line diagnostic systems

    International Nuclear Information System (INIS)

    Osborne, R.L.; Coffman, M.

    1987-01-01

    The utility industry is entering a period when generation equipment availability becomes increasingly critical due to the lack of new power plants being planned and built. The increasing percentage of all electric homes adding to peak demands requires more plant equipment to be used in a cyclic duty mode. Availability is on the increase with forced and planned maintenance hours decreasing. Factors that are contributing to this improvement are new units coming on-line with the latest in technology coupled with the installation of retrofit components containing that same technology such as the Rigi-Flex generators and ruggedized turbine rotors. In conjunction with hardware advances, technology advancements in monitoring and diagnostics are permitting the identification of potential malfunctions so that corrective actions can be taken, thus preventing lengthy outages. It is this last area that this paper will address

  12. Intelligent controller for load-tracking performance of an autonomous power system

    Directory of Open Access Journals (Sweden)

    Abhik Banerjee

    2014-12-01

    Full Text Available The design and performance analysis of a Sugeno fuzzy logic (SFL controller for an autonomous power system model is presented in this paper. In gravitational search algorithm (GSA, the searcher agents are collection of masses and their interactions are based on Newtonian laws of gravity and motion. The problem of obtaining the optimal tunable parameters of the studied model is formulated as an optimization problem and the same is solved by a novel opposition based GSA (OGSA. The proposed OGSA of the present work employs opposition-based learning for population initialization and also for generation jumping. In OGSA, opposite numbers are utilized to improve the convergence rate of the basic GSA. GSA and genetic algorithm are taken for the sake of comparison. Time-domain simulation reveals that the developed OGSA-SFL based on-line, off-nominal controller parameters for the studied model give real-time on-line terminal voltage response.

  13. Computational Intelligence Techniques Applied to the Day Ahead PV Output Power Forecast: PHANN, SNO and Mixed

    Directory of Open Access Journals (Sweden)

    Emanuele Ogliari

    2018-06-01

    Full Text Available An accurate forecast of the exploitable energy from Renewable Energy Sources is extremely important for the stability issues of the electric grid and the reliability of the bidding markets. This paper presents a comparison among different forecasting methods of the photovoltaic output power introducing a new method that mixes some peculiarities of the others: the Physical Hybrid Artificial Neural Network and the five parameters model estimated by the Social Network Optimization. In particular, the day-ahead forecasts evaluated against real data measured for two years in an existing photovoltaic plant located in Milan, Italy, are compared by means both new and the most common error indicators. Results reported in this work show the best forecasting capability of the new “mixed method” which scored the best forecast skill and Enveloped Mean Absolute Error on a yearly basis (47% and 24.67%, respectively.

  14. A wirelessly powered electro-acupuncture based on adaptive pulsewidth monophase stimulation.

    Science.gov (United States)

    Kiseok Song; Long Yan; Seulki Lee; Yoo, Jerald; Hoi-Jun Yoo

    2011-04-01

    A wirelessly powered electro-acupuncture (EA) system with adaptive-pulsewidth (APW) monophase stimulation is presented for convenient invasive medicine. The proposed system removes cumbersome wires connected between EA nodes and an EA controller in order to realize both patients' convenience and remedial values simultaneously. An ultra-low-power stimulator integrated circuit (IC) that is integrated on the flexible-printed-circuit board (F-PCB) is attached to the tip of a needle electrode. Combined with a conductive yarn helical antenna wound around the needle electrode, the EA node receives wireless power from the EA controller using 433 MHz with the maximum loss of 6 dB. A zero-Vth nMOS rectifier harvests a supply voltage of 1.0 V from a -16-dBm incoming power signal with 32% efficiency. To deal with a body impedance variation (BIV) in the range of 100-200 kΩ , the proposed APW stimulator IC, fabricated in a 0.18-μm 1P6M complementary metal-oxide semiconductor CMOS process and occupying 1.56 mm(2), enables constant charge injection of 80-nC/stimulation. To ensure the patients' safety, the EA node (a pair of EAs) shares ground and clock wires to operate in alternate monophase (AMP) fashion for neutralizing the injected charge. The proposed wirelessly powered EA node was verified by applying it to a chunk of pork as a body model with the wireless power supplied from an RF signal generator (output power of 10 dBm and located 30 cm away).

  15. Adapting AC Lines to DC Grids for Large-Scale Renewable Power Transmission

    Directory of Open Access Journals (Sweden)

    D. Marene Larruskain

    2014-10-01

    Full Text Available All over the world, governments of different countries are nowadays promoting the use of clean energies in order to achieve sustainable energy systems. In this scenario, since the installed capacity is continuously increasing, renewable sources can play an important role. Notwithstanding that, some important problems may appear when connecting these sources to the grid, being the overload of distribution lines one of the most relevant. In fact, renewable generation is usually connected to the nearest AC grid, although this HV system may not have been designed considering distributed generation. In the particular case of large wind farms, the electrical grid has to transmit all the power generated by wind energy and, as a consequence, the AC system may get overloaded. It is therefore necessary to determine the impact of wind power transmission so that appropriate measures can be taken. Not only are these measures influenced by the amount of power transmitted, but also by the quality of the transmitted power, due to the output voltage fluctuation caused by the highly variable nature of wind. When designing a power grid, although AC systems are usually the most economical solution because of its highly proven technology, HVDC may arise in some cases (e.g. offshore wind farms as an interesting alternative, offering some added values such as lower losses and better controllability. This way, HVDC technology can solve most of the aforementioned problems and has a good potential for future use. Additionally, the fast development of power electronics based on new and powerful semiconductor devices allow the spread of innovative technologies, such as VSC-HVDC, which can be applied to create DC grids. This paper focuses on the main aspects involved in adapting the existing overhead AC lines to DC grids, with the objective of improving the transmission of distributed renewable energy to the centers of consumption.

  16. Adaptive Home System Using Wireless Sensor Network And Multi Agent System

    OpenAIRE

    Jayarani Kamble; Prof.Nandini Dhole

    2014-01-01

    Smart Home is an emerging technology growing continuously which includes number of new technologies which helps to improve human’s quality of living. This paper proposes an adaptive home system for optimum utilization of power, through Artificial Intelligence and Wireless Sensor network. Artificial Intelligence is a technology for developing adaptive system that can perceive the enviornmrnt, learn from the environment and can make decision using Rule based system.Zigbee is a w...

  17. Using Artificial Intelligence to Control and Adapt Level of Difficulty in Computer Based, Cognitive Therapy – an Explorative Study

    DEFF Research Database (Denmark)

    Wilms, Inge Linda

    2011-01-01

    Prism Adaptation Therapy (PAT) is an intervention method in the treatment of the attention disorder neglect (Frassinetti, Angeli, Meneghello, Avanzi, & Ladavas, 2002; Rossetti, et al., 1998). The aim of this study was to investigate whether one session of PAT using a computer-attached touchscreen...

  18. Enhancing the Frequency Adaptability of Periodic Current Controllers for Grid-Connected Power Converters

    DEFF Research Database (Denmark)

    Yang, Yongheng; Zhou, Keliang; Blaabjerg, Frede

    2015-01-01

    It is mandatory for grid-connected power converters to synchronize the feed-in currents with the grid. Moreover, the power converters should produce feed-in currents with low total harmonic distortions according to the demands, by employing advanced current controllers, e.g., Proportional Resonant...... deviations. Experiments on a single-phase grid-connected inverter system are presented, which have verified the proposals and also the effectiveness of the frequency adaptive current controllers....... (PR) and Repetitive Controllers (RC). The synchronization is actually to detect the instantaneous grid information (e.g., frequency and phase of the grid voltage) for the current control, which is commonly performed by a Phase-Locked-Loop (PLL) system. As a consequence, harmonics and deviations...

  19. Intelligent sizing of a series hybrid electric power-train system based on Chaos-enhanced accelerated particle swarm optimization

    International Nuclear Information System (INIS)

    Zhou, Quan; Zhang, Wei; Cash, Scott; Olatunbosun, Oluremi; Xu, Hongming; Lu, Guoxiang

    2017-01-01

    Highlights: • A novel algorithm for hybrid electric powertrain intelligent sizing is introduced and applied. • The proposed CAPSO algorithm is capable of finding the real optimal result with much higher reputation. • Logistic mapping is the most effective strategy to build CAPSO. • The CAPSO gave more reliable results and increased the efficiency by 1.71%. - Abstract: This paper firstly proposed a novel HEV sizing method using the Chaos-enhanced Accelerated Particle Swarm Optimization (CAPSO) algorithm and secondly provided a demonstration on sizing a series hybrid electric powertrain with investigations of chaotic mapping strategies to achieve the global optimization. In this paper, the intelligent sizing of a series hybrid electric powertrain is formulated as an integer multi-objective optimization issue by modelling the powertrain system. The intelligent sizing mechanism based on APSO is then introduced, and 4 types of the most effective chaotic mapping strategy are investigated to upgrade the standard APSO into CAPSO algorithms for intelligent sizing. The evaluation of the intelligent sizing systems based on standard APSO and CAPSOs are then performed. The Monte Carlo analysis and reputation evaluation indicate that the CAPSO outperforms the standard APSO for finding the real optimal sizing result with much higher reputation, and CAPSO with logistic mapping strategy is the most effective algorithm for HEV powertrain components intelligent sizing. In addition, this paper also performs the sensitivity analysis and Pareto analysis to help engineers customize the intelligent sizing system.

  20. Basic tuning of hydrogen powered car and artificial intelligent prediction of hydrogen engine characteristics

    Energy Technology Data Exchange (ETDEWEB)

    Ho, Tien [School of Engineering, University of Tasmania, GPO Box 252-65, Hobart, Tasmania, 7001 (Australia); Karri, Vishy [Australian College of Kuwait, P.O. Box 1411, Safat 13015 (Kuwait)

    2010-09-15

    Many studies of renewable energy have shown hydrogen is one of the major green energy in the future. This has lead to the development of many automotive application of using hydrogen as a fuel especially in internal combustion engine. Nonetheless, there has been a slow growth and less knowledge details in building up the prototype and control methodology of the hydrogen internal combustion engine. In this paper, The Toyota Corolla 4 cylinder, 1.8l engine running on petrol was systematically modified in such a way that it could be operated on either gasoline or hydrogen at the choice of the driver. Within the scope of this project, several ancillary instruments such as a new inlet manifold, hydrogen fuel injection, storage system and leak detection safety system were implemented. Attention is directed towards special characteristics related to the basic tuning of hydrogen engine such as: air to fuel ratio operating conditions, ignition timing and injection timing in terms of different engine speed and throttle position. Based on the experimental data, a suite of neural network models were tested to accurately predict the effect of different engine operating conditions (speed and throttle position) on the hydrogen powered car engine characteristics. Predictions were found to be {+-}3% to the experimental values for all of case studies. This work provided better understanding of the effect of hydrogen engine characteristic parameters on different engine operating conditions. (author)