Document from the year 2013 in the subject Engineering - Power Engineering, grade: Highest grade, University of Porto, language: English, abstract: Agent technology has been enlightened as the correct vector to promote decentralization, autonomous operation and active management activities in power distribution system operation. As a matter of fact, an adequate agent-based modeling can produce flexible, extensible, and robust systems, which are features of utmost importance to a smooth modernization of power systems. Moreover, the agent paradigm can provide a well-established notion of intelligence/smartness to be progressively applied along with the modernization of power distribution systems. Hence, in this document, an extensive survey about the applications of agent technology to power engineering is provided, aiming at helping engineers and academia to identify gaps in the state of the art to be explored in the future. This survey is presented and discussed highlighting the applications more directly related to the scope of the power distribution systems.

Agent-based technology provides a new computing paradigm, where intelligent agents can be used to perform tasks such as sensing, planning, scheduling, reasoning and decision-making. In an agent-based system, software agents with sufficient intelligence and autonomy can either work independently or coordinately with other agents to accomplish tasks and missions. In this book, we provide up-to-date practical applications of agent-based technology in various fields, such as electronic commerce, grid computing, and adaptive virtual environment. The selected applications are invaluable for researchers and practitioners to understand the practical usage of agent-based technology, and also to apply agent-based technology innovatively in different areas.

The world economy in which we are living poses challenges that lead to a realization that 'more of the same' will be difficult to sustain. This provides an illustration that, in order to create new or modified knowledge practices, strengthen customer relationships and thus positively influence customer satisfaction, organizations must be flexible in configuring (combining) knowledge and knowledge structures in a way that is appropriate for delivering value to the customer. It must simultaneously develop effective strategies for updating the knowledge of its staff members necessary for underpinning the creation and delivery of appropriate knowledge services. Thus, unlearning (forgetting) becomes a critical means for organizational success. The ECKM community of scholars has already initiated dialogue that links its particular strengths to innovation issues. This conference aims to further that dialogue by attracting leading edge work that leverages the ECKM community's in-depth understanding of learning and unlearning to better understand knowledge management. Our aim is to stimulate breakthrough research streams linking learning, unlearning and knowledge management. How can organizations tailor, use, and extend techniques and tools from knowledge management for improving their business practices and processes? Building upon existing work on knowledge management (KM) and organizational learning, the conference will promote interdisciplinary approaches from computer science and information systems, business, management and organization science as well as cognitive science. Emphasis will be put on systematic learning from experience, KM tools and KM success factors. A special interest belongs to knowledge management initiatives which are lightweight (i.e., do not place considerable additional burden on users and KM experts), allow an incremental adoption (i.e., do not require large up-front investment before any return of investment is at least visible), and are flexible regarding frequent changes in experts and topics. Continuing the success of the ECKM conference series since 2000, the 2015 conference will provide an international communication forum bringing together academia and industry for discussing the progress made and addressing the challenges faced by continuous learning in knowledge-intensive organizations.

This book constitutes the refereed proceedings of the 11 workshops co-located with the 16th International Conference on Practical Applications of Agents and Multi-Agent Systems, PAAMS 2018, held in Toledo, Spain, in June 2018. The 47 full papers presented were carefully reviewed and selected from 72 submissions. The volume presents the papers that have been accepted for the following workshops: Workshop on Agents and Multi-agent Systems for AAL and e-HEALTH; Workshop on Agent based Applications for Air Transport; Workshop on Agent-based Artificial Markets Computational Economics; Workshop on Agent-Based Solutions for Manufacturing and Supply Chain; Workshop on MAS for Complex Networks and Social Computation; Workshop on Intelligent Systems and Context Information Fusion; Workshop on Multi-agent based Applications for Energy Markets, Smart Grids and Sustainable Energy Systems; Workshop on Multiagent System based Learning Environments; Workshop on Smart Cities and Intelligent Agents; Workshop on Swarm Intelligence and Swarm Robotics; Workshop on Multi-Agent Systems and Simulation.

The assembly of this study started in 2013 during the preparation of the foundation of the Flexible Electrical Networks (FEN) Research Campus, an institution supported by the German Federal Ministry of Education and Science, concentrating on DC technology in power grids as an enabler for the energy transition. It reflects the state-of-the-art and research needs of DC technology against the background of application in public grids up until the year 2015. Topics as components, control, management and automation, high-, medium, and low-voltage grid concepts as well as social dimensions, economics, and impact on living beings are considered. After substantial editorial effort, its first public edition has become ready now. The aim of FEN is to investigate and to develop flexible power grids. Such grid will safeguard the future energy supply with a high share of fluctuating and decentralized renewable energy sources. At the same time, these grids will enable a reliable and affordable energy supply in the future. The objective is to provide new technologies and concepts for the security and quality of the energy supply in the transmission and distribution grids. To pursue this goal, the use of direct-current (DC) technology, based on power electronics, automation and communication technologies, plays an important role. Although DC technology is not yet established as a standard technology in the public electrical power supply system, its high potential has been widely recognized. The use of DC is an enabler to make the future energy supply system more economical than a system based on alternating-current (AC), because of its superior properties in handling distributed and fluctuation power generation. Indeed, DC connections are already the most cost-efficient solution in cases of very high-power long-distance point-to-point transmission of electricity or via submarine cables. The objective of the FEN Research Campus is now to achieve and demonstrate feasibility of DC as a standard solution for future electrical grids, as described in this study.

Computational intelligence is a component of Encyclopedia of Technology, Information, and Systems Management Resources in the global Encyclopedia of Life Support Systems (EOLSS), which is an integrated compendium of twenty one Encyclopedias. Computational intelligence is a rapidly growing research field including a wide variety of problem-solving techniques inspired by nature. Traditionally computational intelligence consists of three major research areas: Neural Networks, Fuzzy Systems, and Evolutionary Computation. Neural networks are mathematical models inspired by brains. Neural networks have massively parallel network structures with many neurons and weighted connections. Whereas each neuron has a simple input-output relation, a neural network with many neurons can realize a highly non-linear complicated mapping. Connection weights between neurons can be adjusted in an automated manner by a learning algorithm to realize a non-linear mapping required in a particular application task. Fuzzy systems are mathematical models proposed to handle inherent fuzziness in natural language. For example, it is very difficult to mathematically define the meaning of “cold” in everyday conversations such as “It is cold today” and “Can I have cold water”. The meaning of “cold” may be different in a different situation. Even in the same situation, a different person may have a different meaning. Fuzzy systems offer a mathematical mechanism to handle inherent fuzziness in natural language. As a result, fuzzy systems have been successfully applied to real-world problems by extracting linguistic knowledge from human experts in the form of fuzzy IF-THEN rules. Evolutionary computation includes various population-based search algorithms inspired by evolution in nature. Those algorithms usually have the following three mechanisms: fitness evaluation to measure the quality of each solution, selection to choose good solutions from the current population, and variation operators to generate offspring from parents. Evolutionary computation has high applicability to a wide range of optimization problems with different characteristics since it does not need any explicit mathematical formulations of objective functions. For example, simulation-based fitness evaluation is often used in evolutionary design. Subjective fitness evaluation by a human user is also often used in evolutionary art and music. These volumes are aimed at the following five major target audiences: University and College students Educators, Professional practitioners, Research personnel and Policy analysts, managers, and decision makers.

Internet of Things: Challenges, Advances, and Applications provides a comprehensive introduction to IoT, related technologies, and common issues in the adoption of IoT on a large scale. It surveys recent technological advances and novel solutions for challenges in the IoT environment. Moreover, it provides detailed discussion of the utilization of IoT and its underlying technologies in critical application areas, such as smart grids, healthcare, insurance, and the automotive industry. The chapters of this book are authored by several international researchers and industry experts. This book is composed of 18 self-contained chapters that can be read, based on interest. Features: Introduces IoT, including its history, common definitions, underlying technologies, and challenges Discusses technological advances in IoT and implementation considerations Proposes novel solutions for common implementation issues Explores critical application domains, including large-scale electric power distribution networks, smart water and gas grids, healthcare and e-Health applications, and the insurance and automotive industries The book is an excellent reference for researchers and post-graduate students working in the area of IoT, or related areas. It also targets IT professionals interested in gaining deeper knowledge of IoT, its challenges, and application areas.