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Erratum to: Theories in Business and Information Systems engineering

Business & Information Systems engineering 2016年第5期58卷 327-328页

作者： Martin Bichler Ulrich Frank David Avison Julien Malaurent Peter Fettke Dirk Hovorka Jan Krämer Daniel Schnurr Benjamin Müller Leena Suhl Bernhard Thalheim Department of Informatics Technical University of Munich Garching/Munich Germany Chair of Information Systems and Enterprise Modelling Institute for Computer Science and Business Information Systems University of Duisburg-Essen Essen Germany Department of Information Systems Decision Sciences and Statistics ESSEC Business School Cergy Pontoise Cedex France German Research Center for Artificial Intelligence (DFKI GmbH) and Saarland University Saarbrücken Germany Business Information Systems The University of Sydney Business School The University of Sydney Sydney Australia Chair of Internet and Telecommunications Business Faculty of Business Administration and Economics University of Passau Passau Germany Innovation Management and Strategy Faculty of Economics and Business University of Groningen Groningen The Netherlands Decision Support and Operations Research Lab Department Business Information Systems Universität Paderborn Paderborn Germany Information Systems Engineering (ISE) Institut für Informatik Christian-Albrechts-Universität zu Kiel Kiel Germany

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Understanding decision quality through satisfaction

Communications in Computer and Information Science

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Communications in Computer and Information Science 2014年 430卷 368-377页

作者： Carneiro, João Santos, Ricardo Marreiros, Goreti Novais, Paulo GECAD - Knowledge Engineering and Decision Support Group Institute of Engineering - Polytechnic of Porto Porto Portugal CIICESI School of Technology and Management of Felgueiras Polytechnic of Porto Felgueiras Portugal CCTC - Computer Science and Technology Center University of Minho Braga Portugal

ISBN: (纸本)9783319077666

One of the most important factors to determine the success of an organization is the quality of decisions made. In order to improve the decisions taken and to strengthen the competitiveness of organizations, systems such as Group decision support Systems (GDSSs) have been strongly developed and studied in recent decades. The amount of GDSSs incorporating automatic negotiation mechanisms, such as argumentation, is increasing nowadays. The evaluation of these mechanisms and the understanding of their real benefits for the organizations is still a hard challenge. In this article, we propose a model that allows a GDSS to measure the participant's satisfaction with the decision, considering aspects such as problem evaluation, personality, emotions and expectations. This model is intended to enable the understanding of the decision's quality achieved with an argumentation system and to evaluate its capability to potentiate the decision's quality. The proposed model validates all the assumptions found in the literature regarding the participant's satisfaction. © Springer International Publishing Switzerland 2014.

关键词： decision support systems

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Multiagent System Architecture for Short-term Operation of Integrated Microgrids

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IFAC Proceedings Volumes 2014年第3期47卷 6355-6360页

作者： Mohammad Ali Fotouhi Ghazvini Reza Abedini Tiago Pinto Zita Vale GECAD – Knowledge Engineering and Decision-Support Research Center IPP - Polytechnic Institute of Porto Porto Portugal

The forthcoming smart grids are comprised of integrated microgrids operating in grid-connected and isolated mode with local generation, storage and demand response (DR) programs. The proposed model is based on three successive complementary steps for power transaction in the market environment. The first step is characterized as a microgrid's internal market; the second concerns negotiations between distinct interconnected microgrids; and finally, the third refers to the actual electricity market. The proposed approach is modeled and tested using a MAS framework directed to the study of the smart grids environment, including the simulation of electricity markets. This is achieved through the integration of the proposed approach with the MASGriP (Multi-Agent Smart Grid Platform) system.

关键词： Day-ahead market Electricity market Microgrids Multiagent systems Smart grids

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Quantum-based PSO applied to Hour-Ahead Scheduling in the Context of Smart Grid Management

Quantum-based PSO applied to Hour-Ahead Scheduling in the Co...

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IEEE Eindhoven PowerTech Conference

作者： Joao Soares Marco Silva Zita Vale P. B. de Moura Oliveira GECAD - Knowledge Engineering and Decision-Support Research Centre Porto Portugal INESC TEC - INESC Technology and Science UTAD University Vila Real Portugal

This paper presents a Quantum Particle Swarm Optimization (QPSO) applied to hour-ahead scheduling in Smart Grid (SG). The unforeseen events not considered in day-ahead scheduling, must be overcome when approaching intraday operation. This implies new constraints in hour-ahead formulation. The developed methodology aims to complement the day-ahead scheduling tools already available on the literature. The unforeseen events in the hour-ahead can include change of forecasted load demand, market prices and availability of renewable generation. The QPSO solves the problem in adequate execution time under the hour-ahead time scale. This is demonstrated using a scenario with high penetration of distributed generation and gridable vehicles. Furthermore, a comparison with GAMS is presented.

关键词： Electric Vehicles Energy Resource Management Hour-Ahead Scheduling Quantum PSO Smart Grid

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Real-time simulation of real-time pricing demand response to meet wind variations

Real-time simulation of real-time pricing demand response to...

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IEEE PES Innovative Smart Grid Technologies Conference Europe (ISGT Europe)

作者： L. Gomes F. Fernandes P. Faria M. Silva Z. Vale C. Ramos GECAD - Knowledge Engineering and Decision Support Research Center Polytechnic of Porto (IPP) Porto Portugal

Recent changes of paradigm in power systems opened the opportunity to the active participation of new players. The small and medium players gain new opportunities while participating in demand response programs. This paper explores the optimal resources scheduling in two distinct levels. First, the network operator facing large wind power variations makes use of real time pricing to induce consumers to meet wind power variations. Then, at the consumer level, each load is managed according to the consumer preferences. The two-level resources schedule has been implemented in a real-time simulation platform, which uses hardware for consumer' loads control. The illustrative example includes a situation of large lack of wind power and focuses on a consumer with 18 loads.

关键词： Optimization Electricity Wind power generation Load modeling Real-time systems Wind forecasting

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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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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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Dynamic approach and testbed for small and medium players simulation in smart grid environments 19

Dynamic approach and testbed for small and medium players si...

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19th IFAC World Congress on International Federation of Automatic Control, IFAC 2014

作者： Gomes, Luis Amaral, Haroldo L.M. Fernandes, Filipe Faria, Pedro Vale, Zita Ramos, Carlos De Souza, André N. 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

ISBN: (纸本)9783902823625

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. © IFAC.

关键词： Smart power grids

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An architecture for user modeling on Intelligent and Adaptive Scheduling Systems

An architecture for user modeling on Intelligent and Adaptiv...

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World Congress on Nature & Biologically Inspired Computing (NaBIC)

作者： A. Madureira B. Cunha J.P. Pereira I. Pereira S. Gomes GECAD – Knowledge Engineering and Decision Support Research Center Institute of Engineering Polytechnic of Porto (ISEP/IPP) Porto Portugal

User modeling and user adaptive interaction research areas are becoming crucial applied issues to understand and support users as they interact with technology. Modeling the decisions to be made and the constraints placed by market globalization in a way that can address the needs of all stakeholders has been a long time area of academic and industrial research, mainly for Planning, Scheduling, and Strategic decision making areas. Business analysts, developers, and organizations involved in all phases of the business value chain have requirements for applied business insight through modeling. In this paper, an architecture for user modeling on Intelligent and Adaptive Scheduling System is proposed.

关键词： Adaptive scheduling Human computer interaction Runtime

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Distributed intelligent management of microgrids using a multi-agent simulation platform

Distributed intelligent management of microgrids using a mul...

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IEEE Symposium on Intelligent Agents, IA

作者： Luis Gomes Tiago Pinto Pedro Faria Zita Vale Polytechnic of Porto (ISEP/IPP) GECAD - Knowledge Engineering and Decision Support Research Center of the Institute of Engineering Porto Portugal

Multi-agent approaches have been widely used to model complex systems of distributed nature with a large amount of interactions between the involved entities. Power systems are a reference case, mainly due to the increasing use of distributed energy sources, largely based on renewable sources, which have potentiated huge changes in the power systems' sector. Dealing with such a large scale integration of intermittent generation sources led to the emergence of several new players, as well as the development of new paradigms, such as the microgrid concept, and the evolution of demand response programs, which potentiate the active participation of consumers. This paper presents a multi-agent based simulation platform which models a microgrid environment, considering several different types of simulated players. These players interact with real physical installations, creating a realistic simulation environment with results that can be observed directly in the reality. A case study is presented considering players' responses to a demand response event, resulting in an intelligent increase of consumption in order to face the wind generation surplus.

关键词： Load modeling Logic gates Microgrids Load management Hardware Real-time systems Schedules

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