Consumer behavior modeling for electrical energy systems : a complex systems approach

Orientador: Alexandre Rasi AokiCoorientador: Germano Lambert-TorresTese (doutorado) - Universidade Federal do Paraná, Setor de Tecnologia, Programa de Pós-Graduação em Engenharia Elétrica. Defesa : Curitiba, 27/02/2019Inclui referências: p. 141-154Resumo: Um sistema complexo é um sistema composto de muitas partes que interagem entre si, de modo que o comportamento coletivo emergente dessas partes é mais do que a soma de seus comportamentos individuais. O sistema elétrico de potência pode ser considerado um sistema complexo devido à sua diversidade de agentes heterogêneos inter-relacionados e a emergência de comportamento complexo. Sistemas de potência estão aumentando em complexidade com novos avanços relacionados à redes elétricas inteligentes tais como tecnologia de informação e comunicação, geração distribuída, veículos elétricos, armazenamento de energia e, especialmente, uma crescente interação e participação de um grande número de consumidores heterogêneos dispersos geograficamente. O sistema elétrico de potência pode ser estudado como um sistema técnico-socioeconômico complexo com múltiplas facetas, e a teoria de sistemas complexos pode fornecer uma base teórica sólida para seus desafios de modelagem e análise. O presente trabalho trata da aplicação da teoria de sistemas complexos em sistemas de potência, focando a análise no consumidor e no seu comportamento relacionado ao consumo de eletricidade, utilizando técnicas do campo da economia comportamental. Comportamentos complexos e emergentes sobre o consumo de eletricidade, bem como seu impacto nas redes elétricas, são analisados através da modelagem do comportamento dos cliente em uma simulação baseada em agentes, considerando quatro categorias de consumidores. A análise da simulação, aplicada a um estudo de caso em uma rede de distribuição de média tensão radial com dados reais, mostrou que premissas ligeiramente diferentes sobre o comportamento do consumidor no nível micro levam a resultados macro muito distintos e com comportamento não linear. Entender e modelar adequadamente o comportamento dos consumidores é de grande importância para o planejamento e operação de redes de energia, e a economia comportamental serve como uma base teórica promissora para modelar o comportamento no consumo de eletricidade. Os resultados deste trabalho mostraram que a teorias de sistemas complexos fornece ferramentas adequadas para lidar com sistemas de potência cada vez mais complexos, considerando-os não mais como um sistema independente agregado, mas como um sistema complexo integrado. Palavras-chave: distribuição de energia; consumo de eletricidade; teoria de sistemas complexos; simulação baseada em agentes; economia comportamental.Abstract: A complex system is a system composed of many interacting parts, such that the collective emergent behavior of those parts is more than the sum of their individual behaviors. Electrical energy systems may be considered a complex system due to its diversity of interrelated heterogeneous agents and emergent complex behavior. Energy systems are increasing in complexity with new advances related to the smart grid such as information and communication technology, distributed generation, electric vehicles, energy storage, and, especially, increasing interaction and participation of a large number of geographically distributed heterogeneous consumers. Power systems can be studied as a complex techno-socio-economical system with multiple facets, and Complex System Theory (CST) may provide a solid theoretical background for these modeling and analysis challenges. The present work deals with the application of CST into electrical energy systems, focusing the analysis on the consumer and their behavior on electricity consumption, using insights from the field of behavioral economics. Emergent complex behaviors on electricity consumption as well as its impact on power grids are analyzed by modeling customer behavior on an agent-based simulation, considering four different consumer categories. The analysis of the simulation, applied on a case study on a radial medium voltage distribution grid with real-world data, showed that slightly different assumptions on consumer behavior at the micro-level lead to very different and non-linear macro outcomes. To properly understand and model consumer behavior is of great importance to the planning and operation of electrical grids, and behavioral economics serves as a promising theoretical background to model behavior on electricity consumption. The results of this work showed that CST provides suitable tools to tackle electrical energy systems' increasing complexity, by considering the electrical power systems not as an aggregated independent system anymore, but as an integrated complex system. Keywords: power distribution; electricity consumption; complex systems theory; agent-based simulation; behavioral economics

A HOLISTIC APPROACH TO COMPUTER INTEGRATED MANUFACTURING ARCHITECTURE AND SYSTEMS DESIGN

This work addresses the problem of finding an improved solution to Computer Integrated Manufacturing (ClM) Architecture and Systems Design. The current approaches are shown to be difficult to understand and use, over complex. In spite of their complexity of approach they lack comprehensiveness and omit many factors and dimensions considered essential for success in today's competitive and often global market place. A new approach to ClM Architecture and Systems Design is presented which offers a simpler, more flexible and more robust format for defining a particular ClM System within a general architectural framework. At the same time this new approach is designed to offer a comprehensive and holistic solution. The research work involved the investigation of current approaches and research and development initiatives focusing particularly on the CIM-OSA and GRAI Integrated methodologies in the field of ClM Architecture. The strengths and weaknesses of the various approaches are examined. Developments in other related fields including manufacturing systems, manufacturing management, information technology and systems generally have been investigated regarding their relevance and possible contribution to an improved solution. The author has built on his practical experience in creating, designing and managing the implementation of a global CIM system. The authors work on several publicly funded collaborative research and development projects relevant to the problem area is described. These include CIM-OSA, IMOCIM and TIQS projects. In the latter two projects the author was instrumental in developing the methodological approach based on a systems approach to business processes in connection with the design of quality and manufacturing systems. Both of these projects have contributed to this work. The author has also participated in the global IMS programme as a rapporteur for the European Commission and this helped to provide a global perspective on the problems of manufacturing companies as they attempt to compete in a world wide market place. The results of this work provide the basis for a radically improved approach to ClM Architecture and Systems Design based on the holistic view of an enterprise. The approach developed supports the business process view of an enterprise; addresses the people and organisational aspects; leads to ClM solutions focused on meeting enterprise goals; and is able to deal with a significantly increased scope and complexity compared with existing methods yet is easily understood and more simple to simple to apply than current approaches

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/

Dynamic stability with artificial intelligence in smart grids

Environmental concerns are among the main drives of the energy transition in power systems. Smart grids are the natural evolution of power systems to become more efficient and sustainable. This modernization coincides with the vast and wide integration of energy generation and storage systems dependent on power electronics. At the same time, the low inertia power electronics, introduce new challenges in power system dynamics. In fact, the synchronisation capabilities of power systems are threatened by the emergence of new oscillations and the displacement of conventional solutions for ensuring the stability of power systems. This necessitates an equal modernization of the methods to maintain the rotor angle stability in the future smart grids. The applications of artificial intelligence in power systems are constantly increasing. The thesis reviews the most relevant works for monitoring, predicting, and controlling the rotor angle stability of power systems and presents a novel controller for power oscillation damping

Dynamic Stability with Artificial Intelligence in Smart Grids

Environmental concerns are among the main drives of the energy transition in power systems. Smart grids are the natural evolution of power systems to become more efficient and sustainable. This modernization coincides with the vast and wide integration of energy generation and storage systems dependent on power electronics. At the same time, the low inertia power electronics, introduce new challenges in power system dynamics. In fact, the synchronisation capabilities of power systems are threatened by the emergence of new oscillations and the displacement of conventional solutions for ensuring the stability of power systems. This necessitates an equal modernization of the methods to maintain the rotor angle stability in the future smart grids. The applications of artificial intelligence in power systems are constantly increasing. The thesis reviews the most relevant works for monitoring, predicting, and controlling the rotor angle stability of power systems and presents a novel controller for power oscillation damping

Multi Agent Systems

Research on multi-agent systems is enlarging our future technical capabilities as humans and as an intelligent society. During recent years many effective applications have been implemented and are part of our daily life. These applications have agent-based models and methods as an important ingredient. Markets, finance world, robotics, medical technology, social negotiation, video games, big-data science, etc. are some of the branches where the knowledge gained through multi-agent simulations is necessary and where new software engineering tools are continuously created and tested in order to reach an effective technology transfer to impact our lives. This book brings together researchers working in several fields that cover the techniques, the challenges and the applications of multi-agent systems in a wide variety of aspects related to learning algorithms for different devices such as vehicles, robots and drones, computational optimization to reach a more efficient energy distribution in power grids and the use of social networks and decision strategies applied to the smart learning and education environments in emergent countries. We hope that this book can be useful and become a guide or reference to an audience interested in the developments and applications of multi-agent systems

Towards a new methodology for design, modelling, and verification of reconfigurable distributed control systems based on a new extension to the IEC 61499 standard

In order to meet user requirements and system environment changes, reconfigurable control systems must dynamically adapt their structure and behaviour without disrupting system operation. IEC 61499 standard provides limited support for the design and verification of such systems. In fact, handling different reconfiguration scenarios at runtime is difficult since function blocks in IEC 61499 cannot be changed at run-time. Hence, this thesis promotes an IEC 61499 extension called reconfigurable function block (RFB) that increases design readability and smoothly switches to the most appropriate behaviour when a reconfiguration event occurs. To ensure system feasibility after reconfiguration, in addition to the qualitative verification, quantitative verification based on probabilistic model checking is addressed in a new RFBA approach. The latter aims to transform the designed RFB model automatically into a generalised reconfigurable timed net condition/event system model (GRTNCES) using a newly developed environment called RFBTool. The GR-TNCES fits well with RFB and preserves its semantic. Using the probabilistic model checker PRISM, the generated GR-TNCES model is checked using defined properties specified in computation tree logic. As a result, an evaluation of system performance and an estimation of reconfiguration risks are obtained. The RFBA methodology is applied on a distributed power system case study.Dynamische Anforderungen und Umgebungen erfordern rekonfigurierbare Anlagen und Steuerungssysteme. Rekonfiguration ermöglicht es einem System, seine Struktur und sein Verhalten an interne oder externe Änderungen anzupassen. Die Norm IEC 61499 wurde entwickelt, um (verteilte) Steuerungssysteme auf Basis von Funktionsbausteinen zu entwickeln. Sie bietet jedoch wenig Unterstützung für Entwurf und Verifikation. Die Tatsache, dass eine Rekonfiguration das System-Ausführungsmodell verändert, erschwert die Entwicklung in IEC 61499 zusätzlich. Daher schlägt diese Dissertation rekonfigurierbare Funktionsbausteine (RFBs) als Erweiterung der Norm vor. Ein RFB verarbeitet über einen Master-Slave-Automaten Rekonfigurationsereignisse und löst das entsprechende Verhalten aus. Diese Hierarchie trennt das Rekonfigurationsmodell vom Steuerungsmodell und vereinfacht so den Entwurf. Die Funktionalität des Entwurfs muss verifiziert werden, damit die Ausführbarkeit des Systems nach einer Rekonfiguration gewährleistet ist. Hierzu wird das entworfene RFB-Modell automatisch in ein generalised reconfigurable timed net condition/event system übersetzt. Dieses wird mit dem Model-Checker PRISM auf qualitative und quantitative Eigenschaften überprüft. Somit wird eine Bewertung der Systemperformanz und eine Einschätzung der Rekonfigurationsrisiken erreicht. Die RFB-Methodik wurde in einem Softwarewerkzeug umgesetzt und in einer Fallstudie auf ein dezentrales Stromnetz angewendet