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IEEE PES Transmission and Distribution Conference and Exposition

作者： Tiago Soares Pedro Faria Zita Vale Hugo Morais GECAD - Knowledge Engineering and Decision Support Research Center IPP - Polytechnic Institute of Porto Porto Portugal GECAD - Knowledge Engineering and Decision-Support Research Center / IPP - Polytechnic Institute of Porto Automation and Control Group / Technical University of Denmark (DTU) Elektrovej build. 326 DK 2800 Kgs. Lyngby Denmark

The use of distribution networks in the current scenario of high penetration of Distributed Generation (DG) is a problem of great importance. In the competitive environment of electricity markets and smart grids, Demand Response (DR) is also gaining notable impact with several benefits for the whole system. The work presented in this paper comprises a methodology able to define the cost allocation in distribution networks considering large integration of DG and DR resources. The proposed methodology is divided into three phases and it is based on an AC Optimal Power Flow (OPF) including the determination of topological distribution factors, and consequent application of the MW-mile method. The application of the proposed tariffs definition methodology is illustrated in a distribution network with 33 buses, 66 DG units, and 32 consumers with DR capacity.

关键词： Load flow Resource management Equations Pricing Mathematical model Load management

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Using personas for supporting user modeling on scheduling systems

Using personas for supporting user modeling on scheduling sy...

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International Conference on Hybrid Intelligent Systems (HIS)

作者： A. Madureira B. Cunha J.P. Pereira S. Gomes I. Pereira J.M. Santos A. Abraham GECAD - Knowledge Engineering and Decision Support Research Center Institute of Engineering Polytechnic of Porto (ISEP /IPP) Machine Intelligence Research Labs (MIR Labs) WA USA

User modeling and user adaptive interaction has become a central research issue to understand users as they interact with technology. The importance of the development of well adapted interfaces to several kinds of users and the differences that characterize them is the basis of the successful interaction. User Personas is a technique that allows the discovery and definition of the archetype users of a system. With that knowledge, the system should shape itself, inferring the user expertise to provide its users with the best possible experience. In this paper, an architecture that combines User Personas and a dynamic, evolving system is proposed, along with an evaluation by its target users. The proposed system is able to infer the user and its matching Persona, and keeps shaping itself in parallel with the user's discovery of the system.

关键词： Usability User centered design Adaptation models Computational modeling Adaptive systems Human computer interaction Standards

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Proceedings from the 9th annual conference on the science of dissemination and implementation: Washington, DC, USA. 14-15 December 2016

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Implement Sci 2017年第SUPPL 1期12卷 48-48页

作者： David Chambers Lisa Simpson Gila Neta Ulrica von Thiele Schwarz Antoinette Percy-Laurry Gregory A. Aarons Ross Brownson Amanda Vogel Shannon Wiltsey Stirman Kenneth Sherr Rachel Sturke Wynne E. Norton Allyson Varley Cynthia Vinson Lisa Klesges Suzanne Heurtin-Roberts M. Rashad Massoud Leighann Kimble Arne Beck Claire Neely Jennifer Boggs Carmel Nichols Wen Wan Erin Staab Neda Laiteerapong Nathalie Moise Ravi Shah Susan Essock Margaret Handley Amy Jones Jay Carruthers Karina Davidson Lauren Peccoralo Lloyd Sederer Todd Molfenter Ashley Scudder Sarah Taber-Thomas Kristen Schaffner Amy Herschell Eva Woodward Jeffery Pitcock Mona Ritchie JoAnn Kirchner Julia E. Moore Sobia Khan Shusmita Rashid Jamie Park Melissa Courvoisier Sharon Straus Daniel Blonigen Allison Rodriguez Luisa Manfredi Andrea Nevedal Joel Rosenthal David Smelson Christine Timko Nicole Stadnick Jennifer Regan Miya Barnett Anna Lau Lauren Brookman-Frazee Erick Guerrero Karissa Fenwick Yinfei Kong Gregory Aarons Rebecca Lengnick-Hall Benjamin Henwood Nina Sayer Craig Rosen Robert Orazem Brandy Smith Lindsey Zimmerman David Lounsbury Rachel Kimerling Jodie A. Trafton Steven Lindley Rahul Bhargava Hal Roberts Laura Gibson Gabriel J. Escobar Vincent Liu Benjamin Turk Arona Ragins Patricia Kipnis Ashley Ketterer Gruszkowski Michael W. Kennedy Emily Rentschler Drobek Lior Turgeman Aleksandra Sasha Milicevic Terrence L. Hubert Larissa Myaskovsky Youxu C. Tjader Robert J. Monte Kathryn G. Sapnas Edmond Ramly Diane R Lauver Christie M Bartels Shereef Elnahal Andrea Ippolito Hillary Peabody Carolyn Clancy Randall Cebul Thomas Love Douglas Einstadter Shari Bolen Brook Watts Vera Yakovchenko Angela Park William Lukesh Donald R. Miller David Thornton Mari-Lynn Drainoni Allen L. Gifford Shawna Smith Julia Kyle Mark S Bauer Daniel Eisenberg Celeste Liebrecht Michelle Barbaresso Amy Kilbourne Elyse Park Giselle Perez Jamie Ostroff Sarah Greene Michael Parchman Brian Austin Eric Larson Stefanie Ferreri Chris Shea Megan Smith Kea Turner Jennifer Bacci Kyle Bigham Geoffr Division of Cancer Control and Population Sciences National Cancer Institute Rockville MD 20850 USA AcademyHealth Washington DC 20009 USA Department of Learning Informatics Management and Ethics Karolinska Institutet Stockholm 17177 Sweden Department of Psychiatry University of California San Diego San Diego CA 92093 USA George Warren Brown School of Social Work Washington University in St. Louis St. Louis MO 63130 USA Center for Global Health National Cancer Institute Rockville MD 20850 USA Dissemination and Training Division VA National Center for PTSD Palo Alto CA 94305 USA Department of Global Health University of Washington Seattle WA 98105 USA Center for Global Health Studies Fogarty International Center National Institutes of Health Bethesda MD 20912 USA School of Public Health University of Alabama at Birmingham Birmingham AL 35243 USA School of Public Health University of Memphis Memphis TN 38152 USA USAID Applying Science to Strengthen and Improve Systems (ASSIST) Project Bethesda Maryland 20814 USA Institute for Health Research Kaiser Permanente Denver CO 80231 USA ICSI Institute for Clinical Systems Improvement Bloomington MN 55425 USA Medicine University of Chicago Chicago IL 60637 USA Medicine Columbia University Medical Center New York NY 10032 USA Psychiatry Columbia University New York NY 10032 USA General Internal Medicine Epidemiology and Biostatistics University of California San Francisco San Francisco CA 94110 USA New York State Office of Mental Health New York NY 10001 USA Medicine Icahn School of Medicine at Mount Sinai New York NY 10029 USA Center for Health Enhancement System Studies University of Wisconsin Madison WI 53706 USA Department of Psychiatry University of Pittsburgh Pittsburgh PA 15213 USA Psychology University at Buffalo Buffalo NY 14260 USA Department of Psychology West Virginia University Morgantown WV 26506 USA MIRECC VA North Little Rock AR 72114 USA QUERI for Team-Based Behavioral Health Centr

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Towards a Unified European Electricity Market: The Contribution of Data-mining to support Realistic Simulation Studies

Towards a Unified European Electricity Market: The Contribut...

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IEEE Power and Energy Society General Meeting

作者： Tiago Pinto Gabriel Santos Ivo F. Pereira Ricardo Fernandes Tiago M. Sousa Isabel Praca Zita Vale Hugo Morais GECAD - Knowledge Engineering and Decision Support Research Center Polytechnic of Porto (ISEP/IPP) Automation and Control Group Department of Electrical Engineering Technical University of Denmark (DTU)

ISBN: (纸本)9781479964161

Worldwide electricity markets have been evolving into regional and even continental scales. The aim at an efficient use of renewable based generation in places where it exceeds the local needs is one of the main reasons. A reference case of this evolution is the European Electricity Market, where countries are connected, and several regional markets were created, each one grouping several countries, and supporting transactions of huge amounts of electrical energy. The continuous transformations electricity markets have been experiencing over the years create the need to use simulation platforms to support operators, regulators, and involved players for understanding and dealing with this complex environment. This paper focuses on demonstrating the advantage that real electricity markets data has for the creation of realistic simulation scenarios, which allow the study of the impacts and implications that electricity markets transformations will bring to the participant countries. A case study using MASCEM (Multi-Agent System for Competitive Electricity Markets) is presented, with a scenario based on real data, simulating the European Electricity Market environment, and comparing its performance when using several different market mechanisms.

关键词： Data-Mining Electricity Markets Simulation Multi-Agent Systems Scenarios Generation

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Distributed Energy Resources Scheduling Considering Real-Time Resources Forecast

Distributed Energy Resources Scheduling Considering Real-Tim...

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IEEE Power and Energy Society General Meeting

作者： M. Silva T. Sousa S. Ramos Z. Vale H. Morais GECAD - Knowledge Engineering and Decision Support Research Center IPP - Polytechnic Institute of Porto Automation and Control Group Department of Electrical Engineering Technical University of Denmark (DTU)

ISBN: (纸本)9781479964161

Energy resource scheduling is becoming increasingly important, such as the use of more distributed generators and electric vehicles connected to the distribution network. This paper proposes a methodology to be used by Virtual Power Players (VPPs), regarding the energy resource scheduling in smart grids and considering day-ahead, hour-ahead and real-time time horizons. This method considers that energy resources are managed by a VPP which establishes contracts with their owners. The full AC power flow calculation included in the model takes into account network constraints. In this paper, distribution function errors are used to simulate variations between time horizons, and to measure the performance of the proposed methodology. A 33-bus distribution network with large number of distributed resources is used.

关键词： Distributed Energy Resources Energy Resource Management Smart Grid Virtual Power Player

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Realistic Traffic Scenarios Using a Census Methodology: Vila Real Case Study

Realistic Traffic Scenarios Using a Census Methodology: Vila...

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IEEE Power and Energy Society General Meeting

作者： Joao Soares Cristina Lobo Zita Vale P. B. de Moura Oliveira GECAD - Knowledge Engineering and Decision-Support Research Centre Polytechnic of Porto (ISEP/IPP) INESC TEC - INESC Technology and Science UTAD University

ISBN: (纸本)9781479964161

This paper presents the first phase of the redevelopment of the Electric Vehicle Scenario Simulator (EVeSSi) tool. A new methodology to generate traffic demand scenarios for the Simulation of Urban MObility (SUMO) tool for urban traffic simulation is described. This methodology is based on a Portugal census database to generate a synthetic population for a given area under study. A realistic case study of a Portuguese city, Vila Real, is assessed. For this area the road network was created along with a synthetic population and public transport. The traffic results were obtained and an electric buses fleet was evaluated assuming that the actual fleet would be replaced in a near future. The energy requirements to charge the electric fleet overnight were estimated in order to evaluate the impacts that it would cause in the local electricity network.

关键词： Electric buses Electric vehicles Simulation Traffic simulation

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Dynamic Approach and Testbed for Small and Medium Players Simulation in Smart Grid Environments

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IFAC Proceedings Volumes 2014年第3期47卷 31-36页

作者： Luis Gomes Haroldo L.M. Amaral Filipe Fernandes Pedro Faria Zita Vale Carlos Ramos André N. de Souza GECAD – Knowledge Engineering and Decision Support Research Center IPP - Polytechnic Institute of Porto Porto Portugal LSISPOTI - Laboratory of Power Systems and Intelligent Techniques UNESP - Universidade Estadual Paulista Bauru São Paulo Brazil

The Smart Grid environment allows the integration of resources of small and medium players through the use of Demand Response programs. Despite the clear advantages for the grid, the integration of consumers must be carefully done. This paper proposes a system which simulates small and medium players. The system is essential to produce tests and studies about the active participation of small and medium players in the Smart Grid environment. When comparing to similar systems, the advantages comprise the capability to deal with three types of loads – virtual, contextual and real. It can have several loads optimization modules and it can run in real time. The use of modules and the dynamic configuration of the player results in a system which can represent different players in an easy and independent way. This paper describes the system and all its capabilities.

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Short-term wind speed forecasting using support Vector Machines

Short-term wind speed forecasting using Support Vector Machi...

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IEEE Symposium on Computational Intelligence in Dynamic and Uncertain Environments (CIDUE)

作者： Tiago Pinto Sérgio Ramos Tiago M. Sousa Zita Vale Polytechnic of Porto (ISEP/IPP) Knowledge Engineering and Decision Support Research Center of the Institute of Engineering Porto Portugal

Wind speed forecasting has been becoming an important field of research to support the electricity industry mainly due to the increasing use of distributed energy sources, largely based on renewable sources. This type of electricity generation is highly dependent on the weather conditions variability, particularly the variability of the wind speed. Therefore, accurate wind power forecasting models are required to the operation and planning of wind plants and power systems. A support Vector Machines (SVM) model for short-term wind speed is proposed and its performance is evaluated and compared with several artificial neural network (ANN) based approaches. A case study based on a real database regarding 3 years for predicting wind speed at 5 minutes intervals is presented.

关键词： Kernel support vector machines Forecasting Wind speed Artificial neural networks Wind forecasting Wind power generation

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Preliminary results on peculiar patterns in fractional coupled oscillators

Preliminary results on peculiar patterns in fractional coupl...

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IEEE International Conference on Automation, Quality and Testing, Robotics, AQTR

作者： Carla M. A. Pinto School of Engineering Polytechnic of Porto and Center of Mathematics University of Porto and GECAD - Knowledge Engineering and Decision Support Research Center Rua Dr António Bernardino de Almeida 431 4200-072 Porto Portugal

We study peculiar dynamical patterns of a fractional derivative of complex-order network. The network consists of two rings of cells coupled through a `buffer' cell, with Z 3 × Z 5 symmetry group. Each cell is modeled by the Chen oscillator. Numerical simulations expose interesting dynamical features, such as equilibria, periodic solutions and relaxation oscillations, for distinct value of the real part of the fractional derivative of complex-order. Further work is needed to enhance our knowledge of the underlying dynamics of the network.

关键词： Oscillators Time series analysis Mathematical model Differential equations Bifurcation Simulation Educational institutions

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Load profiling tool to support smart grid operation scenarios

Load profiling tool to support smart grid operation scenario...

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IEEE PES Transmission and Distribution Conference and Exposition

作者： Sérgio Ramos Isabel Praça Zita Vale Tiago M. Sousa Vera Faria GECAD - Knowledge Engineering and Decision-Support Research Center Institute of Engineering - Polytechnic of Porto (ISEP/IPP) Rua Dr. António Bernardino de Almeida 431 4200-072 Porto Portugal

This paper presents the characterization of high voltage (HV) electric power consumers based on a data clustering approach. The typical load profiles (TLP) are obtained selecting the best partition of a power consumption database among a pool of data partitions produced by several clustering algorithms. The choice of the best partition is supported using several cluster validity indices. The proposed data-mining (DM) based methodology, that includes all steps presented in the process of knowledge discovery in databases (KDD), presents an automatic data treatment application in order to preprocess the initial database in an automatic way, allowing time saving and better accuracy during this phase. These methods are intended to be used in a smart grid environment to extract useful knowledge about customers' consumption behavior. To validate our approach, a case study with a real database of 185 HV consumers was used.

关键词： Clustering algorithms Electricity Load modeling Databases Partitioning algorithms Smart grids Classification algorithms

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