Analysis of Resilience Situations for Complex Engineered Systems – the Resilience Holon

Improving the resilience of complex engineered and engineering systems (CES) includes planning for complex resilience situations, in which there may be multiple threats, interactions, and disruptions. One challenge in the modeling of CES is the identification of how interactions in a complex situation occur and their combined influence on CES resilience. This article presents a resilience holon that can be used to analyze complex resilience situations. It is made up of 24 elements (defining types of resilience, threats, interactions, and disruptions), which have varying importance to specific situations. Holons can be linked together hierarchically or in a network. An application of the resilience holon to a documented real-world resilience situation, widespread flooding in a city, illustrates its use. Pathways taken by threats and disruptions, as the flood effects cascaded through the city, are shown as connections between holons. The resilience holon could be used to decompose diverse resilience situations involving CES, to identify where critical vulnerability points are and how the whole resilience situation could be improved. The visual nature of the resilience holon could be used in an interactive way, allowing stakeholders to better understand the full resilience picture of CES that they use or operate

Self-organising multi-agent control for distribution networks with distributed energy resources

Recent years have seen an increase in the connection of dispersed distributed energy resources (DERs) and advanced control and operational components to the distribution network. These DERs can come in various forms, including distributed generation (DG), electric vehicles (EV), energy storage, etc. The conditions of these DERs can be varying and unpredictably intermittent. The integration of these distributed components adds more complexity and uncertainty to the operation of future power networks, such as voltage, frequency, and active/reactive power control. The stochastic and distributed nature of DGs and the difficulty in predicting EV charging patterns presents problems to the control and management of the distribution network. This adds more challenges to the planning and operation of such systems. Traditional methods for dealing with network problems such as voltage and power control could therefore be inadequate. In addition, conventional optimisation techniques will be difficult to apply successfully and will be accompanied with a large computational load. There is therefore a need for new control techniques that break the problem into smaller subsets and one that uses a multi-agent system (MAS) to implement distributed solutions. These groups of agents would coordinate amongst themselves, to regulate local resources and voltage levels in a distributed and adaptive manner considering varying conditions of the network. This thesis investigates the use of self-organising systems, presenting suitable approaches and identifying the challenges of implementing such techniques. It presents the development of fully functioning self-organising multi-agent control algorithms that can perform as effectively as full optimization techniques. It also demonstrates these new control algorithms on models of large and complex networks with DERs. Simulation results validate the autonomy of the system to control the voltage independently using only local DERs and proves the robustness and adaptability of the system by maintaining stable voltage control in response to network conditions over time.Recent years have seen an increase in the connection of dispersed distributed energy resources (DERs) and advanced control and operational components to the distribution network. These DERs can come in various forms, including distributed generation (DG), electric vehicles (EV), energy storage, etc. The conditions of these DERs can be varying and unpredictably intermittent. The integration of these distributed components adds more complexity and uncertainty to the operation of future power networks, such as voltage, frequency, and active/reactive power control. The stochastic and distributed nature of DGs and the difficulty in predicting EV charging patterns presents problems to the control and management of the distribution network. This adds more challenges to the planning and operation of such systems. Traditional methods for dealing with network problems such as voltage and power control could therefore be inadequate. In addition, conventional optimisation techniques will be difficult to apply successfully and will be accompanied with a large computational load. There is therefore a need for new control techniques that break the problem into smaller subsets and one that uses a multi-agent system (MAS) to implement distributed solutions. These groups of agents would coordinate amongst themselves, to regulate local resources and voltage levels in a distributed and adaptive manner considering varying conditions of the network. This thesis investigates the use of self-organising systems, presenting suitable approaches and identifying the challenges of implementing such techniques. It presents the development of fully functioning self-organising multi-agent control algorithms that can perform as effectively as full optimization techniques. It also demonstrates these new control algorithms on models of large and complex networks with DERs. Simulation results validate the autonomy of the system to control the voltage independently using only local DERs and proves the robustness and adaptability of the system by maintaining stable voltage control in response to network conditions over time

Generic architectures for open, multi-objective autonomic systems:application to smart micro-grids

Autonomic features, i.e. the capability of systems to manage themselves, are necessary to control complex systems, i.e. systems that are open, large scale, dynamic, comprise heterogeneous third-party sub-systems and follow multiple, sometimes conflicting objectives. In this thesis, we aim to provide generic reusable supports for designing complex autonomic systems. We propose a formalisation of management objectives, a generic architecture for designing adaptable multi-objective autonomic systems, and generic organisations integrating such autonomic systems. We apply our approach to the concrete case of smart micro-grids which is a relevant example of such complexity. We present a simulation platform we developped and illustrate our approach via several simulation scenarios

Control Architecture Modeling for Future Power Systems

Uncontrollable power generation, distributed energy resources, controllable demand, etc. are fundamental aspects of energy systems largely based on renewable energy supply. These technologies have in common that they contradict the conventional categories of electric power system operation. As their introduction has proceeded incrementally in the past, operation strategies of the power system could be adapted. For example much more wind power could be integrated than originally anticipated, largely due to the flexibility reserves already present in the power system, and the possibility of interregional electricity exchange. However, at the same time, it seems that the overall system design cannot keep up by simply adapting in response to changes, but that also new strategies have to be designed in anticipation. Changes to the electricity markets have been suggested to adapt to the limited predictability of wind power, and several new control strategies have been proposed, in particular to enable the control of distributed energy resources, including for example, distributed generation or electric vehicles. Market designs addressing the procurement of balancing resources are highly dependent on the operation strategies specifying the resource requirements. How should one decide which control strategy and market configuration is best for a future power system? Most research up to this point has addressed single isolated aspects of this design problem. Those of the ideas that fit with current markets and operation concepts are lucky; they can be evaluated on the present design. But how could they be evaluated on a potential future power system? Approaches are required that support the design and evaluation of power system operation and control in context of future energy scenarios. This work addresses this challenge, not by providing a universal solution, but by providing basic modeling methodology that enables better problem formulation and by suggesting an approach to addressing the general chicken/egg problem of planning and re-design of system operation and control. The dissertation first focuses on the development of models, diagrams, that support the conceptual design of control and operation strategies, where a central theme is the focus on modeling system goals and functions rather than system structure. The perspective is then shifted toward long-term energy scenarios and adaptation of power system operation, considering the integration of energy scenario models with the re-design of operation strategies. The main contributions in the first part are, firstly, by adaptation of an existing functional modeling approach called Multilevel Flow Modeling (MFM) to the power systems domain, identifying the means-ends composition of control levels and development of principles for the consistent modeling of control structures, a formalization of control-as-a-service; secondly, the formal mapping of fluctuating and controllable resources to a multi-scale and multi-stage representation of control and operation structures; and finally the application to some concrete study cases, including a present system balancing, and proposed control structures such as Microgrids and Cells. In the second part, the main contributions are the outline of a formation strategy, integrating the design and model-based evaluation of future power system operation concepts with iterative energy scenario development. Finally, a new modeling framework for development and evaluation of power system operation in context of energy-storage based power system balancing is introduced.<br/

The Age of Sustainability

With transitions to more sustainable ways of living already underway, this book examines how we understand the underlying dynamics of the transitions that are unfolding. Without this understanding, we enter the future in a state of informed bewilderment. Every day we are bombarded by reports about ecosystem breakdown, social conflict, economic stagnation and a crisis of identity. There is mounting evidence that deeper transitions are underway that suggest we may be entering another period of great transformation equal in significance to the agricultural revolution some 13,000 years ago or the Industrial Revolution 250 years ago. This book helps readers make sense of our global crisis and the dynamics of transition that could result in a shift from the industrial epoch that we live in now to a more sustainable and equitable age. The global renewable energy transition that is already underway holds the key to the wider just transition. However, the evolutionary potential of the present also manifests in the mushrooming of ecocultures, new urban visions, sustainability-oriented developmental states and new ways of learning and researching. Shedding light on the highly complex challenge of a sustainable and just transition, this book is essential reading for anyone concerned with establishing a more sustainable and equitable world. Ultimately, this is a book about hope but without easy answers

A Formal Holon Model for Operating Future Energy Grids During Blackouts

Modern energy grids introduce local energy producers into city networks. Whenever a city network is disconnected from the distribution grid, a blackout occurs and local producers are disabled. Micro grids circumvent blackouts by leveraging these local producers to power a fixed subset of consumers. In this paper, we evolve micro grids to Holons, which overcome the need for fixed subsets and power as much of the city network as possible. We contribute a formal model of Holons and investigate the impact of the Holon concept in a simulation with 10,000 randomly generated city networks. These city networks are based on parameters obtained from a real-world test site in a medium-sized German city. Our results show that the Holon approach can supply an average fraction of 22.08% of any city network, even when fixed micro grids would fail to power the city network as a whole

Collective intelligence: creating a prosperous world at peace

XXXII, 612 p. ; 24 cmLibro ElectrónicoEn este documento se plantea un tema de interes general mas como lo es especificamente el tema de la evolucion de la sociedad en materia de industria y crecimiento de las actividades humanas en el aspecto de desarrollo de la creatividad enfocada a los mercadosedited by Mark Tovey ; foreword by Yochai Benkler (re-mixed by Hassan Masum) ; prefaces by Thomas Malone, Tom Atlee & Pierre Levy ; afterword by Paul Martin & Thomas Homer-Dixon.The era of collective intelligence has begun in earnest. While others have written about the wisdom of crowds, an army of Davids, and smart mobs, this collection of essays for the first time brings together fifty-five pioneers in the emerging discipline of collective intelligence. They provide a base of tools for connecting people, producing high-functioning teams, collaborating at multiple scales, and encouraging effective peer-production. Emerging models are explored for digital deliberative democracy, self-governance, legislative transparency, true-cost accounting, and the ethical use of open sources and methods. Collective Intelligence is the first of a series of six books, which will also include volumes on Peace Intelligence, Commercial Intelligence, Gift Intelligence, Cultural Intelligence, and Global Intelligence.Table of Contents Dedication i Publisher’s Preface iii Foreword by Yochai Benkler Remix Hassan Masum xi The Wealth of Networks: Highlights remixed Editor’s Preface xxi Table of Contents xxv A What is collective intelligence and what will we do 1 about it? (Thomas W. Malone, MIT Center for Collective Intelligence) B Co-Intelligence, collective intelligence, and conscious 5 evolution (Tom Atlee, Co-Intelligence Institute) C A metalanguage for computer augmented collective 15 intelligence (Prof. Pierre Lévy, Canada Research Chair in Collective Intelligence, FRSC) I INDIVIDUALS & GROUPS I-01 Foresight I-01-01 Safety Glass (Karl Schroeder, science fiction author 23 and foresight consultant) I-01-02 2007 State of the Future (Jerome C. Glenn & 29 Theodore J. Gordon, United Nations Millennium Project) I-02 Dialogue & Deliberation I-02-01 Thinking together without ego: Collective intelligence 39 as an evolutionary catalyst (Craig Hamilton and Claire Zammit, Collective-Intelligence.US) I-02-02 The World Café: Awakening collective intelligence 47 and committed action (Juanita Brown, David Isaacs and the World Café Community) I-02-03 Collective intelligence and the emergence of 55 wholeness (Peggy Holman, Nexus for Change, The Change Handbook) I-02-04 Knowledge creation in collective intelligence (Bruce 65 LaDuke, Fortune 500, HyperAdvance.com) I-02-05 The Circle Organization: Structuring for collective 75 wisdom (Jim Rough, Dynamic Facilitation & The Center for Wise Democracy) I-03 Civic Intelligence I-03-01 Civic intelligence and the public sphere (Douglas 83 Schuler, Evergreen State College, Public Sphere Project) I-03-02 Civic intelligence and the security of the homeland 95 (John Kesler with Carole and David Schwinn, IngeniusOnline) I-03-03 Creating a Smart Nation (Robert Steele, OSS.Net) 107 I-03-04 University 2.0: Informing our collective intelligence 131 (Nancy Glock-Grueneich, HIGHEREdge.org) I-03-05 Producing communities of communications and 145 foreknowledge (Jason “JZ” Liszkiewicz, Reconfigure.org) I-03-06 Global Vitality Report 2025: Learning to transform I-04 Electronic Communities & Distributed Cognition I-04-01 Attentional capital and the ecology of online social 163 conflict and think together effectively (Peter+Trudy networks (Derek Lomas, Social Movement Lab, Johnson-Lenz, Johnson-Lenz.com ) UCSD) I-04-02 A slice of life in my virtual community (Howard 173 Rheingold, Whole Earth Review, Author & Educator) I-04-03 Shared imagination (Dr. Douglas C. Engelbart, 197 Bootstrap) I-05 Privacy & Openness I-05-01 We’re all swimming in media: End-users must be able 201 to keep secrets (Mitch Ratcliffe, BuzzLogic & Tetriad) I-05-02 Working openly (Lion Kimbro, Programmer and 205 Activist) I-06 Integral Approaches & Global Contexts I-06-01 Meta-intelligence for analyses, decisions, policy, and 213 action: The Integral Process for working on complex issues (Sara Nora Ross, Ph.D. ARINA & Integral Review) I-06-02 Collective intelligence: From pyramidal to global 225 (Jean-Francois Noubel, The Transitioner) I-06-03 Cultivating collective intelligence: A core leadership 235 competence in a complex world (George Pór, Fellow at Universiteit van Amsterdam) II LARGE-SCALE COLLABORATION II-01 Altruism, Group IQ, and Adaptation II-01-01 Empowering individuals towards collective online 245 production (Keith Hopper, KeithHopper.com) II-01-02 Who’s smarter: chimps, baboons or bacteria? The 251 power of Group IQ (Howard Bloom, author) II-01-03 A collectively generated model of the world (Marko 261 A. Rodriguez, Los Alamos National Laboratory) II-02 Crowd Wisdom and Cognitive Bias II-02-01 Science of CI: Resources for change (Norman L 265 Johnson, Chief Scientist at Referentia Systems, former LANL) II-02-02 Collectively intelligent systems (Jennifer H. Watkins, 275 Los Alamos National Laboratory) II-02-03 A contrarian view (Jaron Lanier, scholar-in-residence, 279 CET, UC Berkeley & Discover Magazine) II-03 Semantic Structures & The Semantic Web II-03-01 Information Economy Meta Language (Interview with 283 Professor Pierre Lévy, by George Pór) II-03-02 Harnessing the collective intelligence of the World- 293 Wide Web (Nova Spivack, RadarNetworks, Web 3.0) II-03-03 The emergence of a global brain (Francis Heylighen, 305 Free University of Brussels) II-04 Information Networks II-04-01 Networking and mobilizing collective intelligence (G. Parker Rossman, Future of Learning Pioneer) II-04-02 Toward high-performance organizations: A strategic 333 role for Groupware (Douglas C. Engelbart, Bootstrap) II-04-03 Search panacea or ploy: Can collective intelligence 375 improve findability? (Stephen E. Arnold, Arnold IT, Inc.) II-05 Global Games, Local Economies, & WISER II-05-01 World Brain as EarthGame (Robert Steele and many 389 others, Earth Intelligence Network) II-05-02 The Interra Project (Jon Ramer and many others) 399 II-05-03 From corporate responsibility to Backstory 409 Management (Alex Steffen, Executive Editor, Worldchanging.com) II-05-04 World Index of Environmental & Social 413 Responsibility (WISER) By the Natural Capital Institute II-06 Peer-Production & Open Source Hardware II-06-01 The Makers’ Bill of Rights (Jalopy, Torrone, and Hill) 421 II-06-02 3D Printing and open source design (James Duncan, 423 VP of Technology at Marketingisland) II-06-03 REBEARTHTM: 425 II-07 Free Wireless, Open Spectrum, and Peer-to-Peer II-07-01 Montréal Community Wi-Fi (Île Sans Fil) (Interview 433 with Michael Lenczner by Mark Tovey) II-07-02 The power of the peer-to-peer future (Jock Gill, 441 Founder, Penfield Gill Inc.) Growing a world 6.6 billion people would want to live in (Marc Stamos, B-Comm, LL.B) II-07-03 Open spectrum (David Weinberger) II-08 Mass Collaboration & Large-Scale Argumentation II-08-01 Mass collaboration, open source, and social 455 entrepreneurship (Mark Tovey, Advanced Cognitive Engineering Lab, Institute of Cognitive Science, Carleton University) II-08-02 Interview with Thomas Homer-Dixon (Hassan 467 Masum, McLaughlin-Rotman Center for Global Health) II-08-03 Achieving collective intelligence via large-scale argumentation (Mark Klein, MIT Center for Collective Intelligence) II-08-04 Scaling up open problem solving (Hassan Masum & 485 Mark Tovey) D Afterword: The Internet and the revitalization of 495 democracy (The Rt. Honourable Paul Martin & Thomas Homer-Dixon) E Epilogue by Tom Atlee 513 F Three Lists 515 1. Strategic Reading Categories 2. Synopsis of the New Progressives 3. Fifty-Two Questions that Matter G Glossary 519 H Index 52

Generalized averaged Gaussian quadrature and applications

A simple numerical method for constructing the optimal generalized averaged Gaussian quadrature formulas will be presented. These formulas exist in many cases in which real positive GaussKronrod formulas do not exist, and can be used as an adequate alternative in order to estimate the error of a Gaussian rule. We also investigate the conditions under which the optimal averaged Gaussian quadrature formulas and their truncated variants are internal

MS FT-2-2 7 Orthogonal polynomials and quadrature: Theory, computation, and applications

Quadrature rules find many applications in science and engineering. Their analysis is a classical area of applied mathematics and continues to attract considerable attention. This seminar brings together speakers with expertise in a large variety of quadrature rules. It is the aim of the seminar to provide an overview of recent developments in the analysis of quadrature rules. The computation of error estimates and novel applications also are described