2,795 research outputs found

    Multi Agent Systems

    Get PDF
    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

    Modelling and Co-simulation of Multi-Energy Systems: Distributed Software Methods and Platforms

    Get PDF
    L'abstract è presente nell'allegato / the abstract is in the attachmen

    Application of service composition mechanisms to Future Networks architectures and Smart Grids

    Get PDF
    Aquesta tesi gira entorn de la hipòtesi de la metodologia i mecanismes de composició de serveis i com es poden aplicar a diferents camps d'aplicació per a orquestrar de manera eficient comunicacions i processos flexibles i sensibles al context. Més concretament, se centra en dos camps d'aplicació: la distribució eficient i sensible al context de contingut multimèdia i els serveis d'una xarxa elèctrica intel·ligent. En aquest últim camp es centra en la gestió de la infraestructura, cap a la definició d'una Software Defined Utility (SDU), que proposa una nova manera de gestionar la Smart Grid amb un enfocament basat en programari, que permeti un funcionament molt més flexible de la infraestructura de xarxa elèctrica. Per tant, revisa el context, els requisits i els reptes, així com els enfocaments de la composició de serveis per a aquests camps. Fa especial èmfasi en la combinació de la composició de serveis amb arquitectures Future Network (FN), presentant una proposta de FN orientada a serveis per crear comunicacions adaptades i sota demanda. També es presenten metodologies i mecanismes de composició de serveis per operar sobre aquesta arquitectura, i posteriorment, es proposa el seu ús (en conjunció o no amb l'arquitectura FN) en els dos camps d'estudi. Finalment, es presenta la investigació i desenvolupament realitzat en l'àmbit de les xarxes intel·ligents, proposant diverses parts de la infraestructura SDU amb exemples d'aplicació de composició de serveis per dissenyar seguretat dinàmica i flexible o l'orquestració i gestió de serveis i recursos dins la infraestructura de l'empresa elèctrica.Esta tesis gira en torno a la hipótesis de la metodología y mecanismos de composición de servicios y cómo se pueden aplicar a diferentes campos de aplicación para orquestar de manera eficiente comunicaciones y procesos flexibles y sensibles al contexto. Más concretamente, se centra en dos campos de aplicación: la distribución eficiente y sensible al contexto de contenido multimedia y los servicios de una red eléctrica inteligente. En este último campo se centra en la gestión de la infraestructura, hacia la definición de una Software Defined Utility (SDU), que propone una nueva forma de gestionar la Smart Grid con un enfoque basado en software, que permita un funcionamiento mucho más flexible de la infraestructura de red eléctrica. Por lo tanto, revisa el contexto, los requisitos y los retos, así como los enfoques de la composición de servicios para estos campos. Hace especial hincapié en la combinación de la composición de servicios con arquitecturas Future Network (FN), presentando una propuesta de FN orientada a servicios para crear comunicaciones adaptadas y bajo demanda. También se presentan metodologías y mecanismos de composición de servicios para operar sobre esta arquitectura, y posteriormente, se propone su uso (en conjunción o no con la arquitectura FN) en los dos campos de estudio. Por último, se presenta la investigación y desarrollo realizado en el ámbito de las redes inteligentes, proponiendo varias partes de la infraestructura SDU con ejemplos de aplicación de composición de servicios para diseñar seguridad dinámica y flexible o la orquestación y gestión de servicios y recursos dentro de la infraestructura de la empresa eléctrica.This thesis revolves around the hypothesis the service composition methodology and mechanisms and how they can be applied to different fields of application in order to efficiently orchestrate flexible and context-aware communications and processes. More concretely, it focuses on two fields of application that are the context-aware media distribution and smart grid services and infrastructure management, towards a definition of a Software-Defined Utility (SDU), which proposes a new way of managing the Smart Grid following a software-based approach that enable a much more flexible operation of the power infrastructure. Hence, it reviews the context, requirements and challenges of these fields, as well as the service composition approaches. It makes special emphasis on the combination of service composition with Future Network (FN) architectures, presenting a service-oriented FN proposal for creating context-aware on-demand communication services. Service composition methodology and mechanisms are also presented in order to operate over this architecture, and afterwards, proposed for their usage (in conjunction or not with the FN architecture) in the deployment of context-aware media distribution and Smart Grids. Finally, the research and development done in the field of Smart Grids is depicted, proposing several parts of the SDU infrastructure, with examples of service composition application for designing dynamic and flexible security for smart metering or the orchestration and management of services and data resources within the utility infrastructure

    Control Architecture Modeling for Future Power Systems

    Get PDF
    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/

    Staging urban emergence through collective creativity: Devising an outdoor mobile augmented reality tool

    Get PDF
    The unpredictability of global geopolitical conflicts, economic trends, and impacts of climate change, coupled with an increasing urban population, necessitates a more profound commitment to resilience thinking in urban planning and design. In contrast to top-down planning and designing for sustainability, allowing for emergence to take place seems to contribute to a capacity to better deal with this complex unpredictability, by allowing incremental changes through bottom-up, self-organized adaptation made by diverse actors in the proximity of various social, economical and functional entities in the urban context.The present thesis looks into the processes of creating urban emergence from both theoretical and practical perspectives. The theoretical section of the thesis first looks into the relationship between the processes and the qualities of a compact city. The Japanese city of Tokyo is used as an example of a resilient compact city that continuously emerges through incremental micro-adaptations by individual actors guided by urban rules that ‘let it happen’ without much central control or top-down design of the individual outcomes. The thesis then connects such rule-based emergent processes and the qualities of a compact city to complex adaptive system’s (CAS) theory, emphasizing the value of incremental and individual multiple-stakeholder input. The latter part of the thesis focuses on how to create a platform that can combine the bottom-up, emergent, rule-based planning approaches, and collective creativity based on individual participation and input from the public. This section is dedicated to developing a tool for a collaborative urban design using outdoor mobile augmented reality (MAR) by research-through-design method.The thesis thus has three parts addressing the topics: 1. urban planning processes and resulting urban qualities concerning compact city – i.e., density and diversity; 2. the processes of urban emergence, which generates complexity that renders urban resilience from the urban planning theory perspective; 3. developing a tool for non-expert citizens and other stakeholders to design and visualize an urban neighborhood by simulating the rule-based urban emergence using outdoor MAR. The results include a proposal for a complementary hybrid planning approaches that might approximate the CAS in urban systems with qualities that contribute to urban resiliency. Thereafter, the results describe specifications and design criteria for a tool as a public collaborative design platform using outdoor MAR to promote public participation: Urban CoBuilder. The processes of developing and prototyping such a tool to test various urban concepts concerning identified adaptive urban planning approaches are also presented with an assessment of the MAR tool based on focus group user tests. Future studies need to better include the potential of crowdsourcing public creativity through mass participation using the collaborative design tool and actual integration of these participatory design results in urban policies

    High Energy Physics Forum for Computational Excellence: Working Group Reports (I. Applications Software II. Software Libraries and Tools III. Systems)

    Full text link
    Computing plays an essential role in all aspects of high energy physics. As computational technology evolves rapidly in new directions, and data throughput and volume continue to follow a steep trend-line, it is important for the HEP community to develop an effective response to a series of expected challenges. In order to help shape the desired response, the HEP Forum for Computational Excellence (HEP-FCE) initiated a roadmap planning activity with two key overlapping drivers -- 1) software effectiveness, and 2) infrastructure and expertise advancement. The HEP-FCE formed three working groups, 1) Applications Software, 2) Software Libraries and Tools, and 3) Systems (including systems software), to provide an overview of the current status of HEP computing and to present findings and opportunities for the desired HEP computational roadmap. The final versions of the reports are combined in this document, and are presented along with introductory material.Comment: 72 page

    Transitioning power distribution grid into nanostructured ecosystem : prosumer-centric sovereignty

    Get PDF
    PhD ThesisGrowing acceptance for in-house Distributed Energy Resource (DER) installations at lowvoltage level have gained much significance in recent years due to electricity market liberalisations and opportunities in reduced energy billings through personalised utilisation management for targeted business model. In consequence, modelling of passive customers’ electric power system are progressively transitioned into Prosumer-based settings where presidency for Transactive Energy (TE) system framework is favoured. It amplifies Prosumers’ commitments into annexing TE values during market participations and optimised energy management to earn larger rebates and incentives from TE programs. However, when dealing with mass Behind-The-Meter DER administrations, Utility foresee managerial challenges when dealing with distribution network analysis, planning, protection, and power quality security based on Prosumers’ flexibility in optimising their energy needs. This dissertation contributes prepositions into modelling Distributed Energy Resources Management System (DERMS) as an aggregator designed for Prosumer-centered cooperation, interoperating TE control and coordination as key parameters to market for both optimised energy trading and ancillary services in a Community setting. However, Prosumers are primarily driven to create a profitable business model when modelling their DERMS aggregator. Greedy-optimisation exploitations are negative concerns when decisions made resulted in detrimental-uncoordinated outcomes on Demand-Side Response (DSR) and capacity market engagements. This calls for policy decision makers to contract safe (i.e. cooperative yet competitive tendency) business models for Prosumers to maximise TE values while enhancing network’s power quality metrics and reliability performances. Firstly, digitalisation and nanostructuring of distribution network is suggested to identify Prosumer as a sole energy citizen while extending bilateral trading between Prosumer-to- Prosumer (PtP) with the involvements of other grid operators−TE system. Modelling of Nanogrid environment for DER integrations and establishment of local area network infrastructure for IoT security (i.e. personal computing solutions and data protection) are committed for communal engagements in a decentralise setting. Secondly, a multi-layered Distributed Control Framework (DCF) is proposed using Microsoft Azure cloud-edge platform that cascades energy actors into respective layers of TE control and coordination. Furthermore, modelling of flexi-edge computing architecture is proposed, comprising of Contract-Oriented Sensor-based Application Platform (COSAP) employing Multi-Agent System (MAS) to enhance data-sharing privacy and contract coalition agreements during PtP engagements. Lastly, the Agents of MAS are programmed with cooperative yet competitive intelligences attributed to Reinforcement Learning (RL) and Neural Networks (NN) algorithms to solve multimodal socio-economical and uncertainty problems that corresponded to Prosumers’ dynamic energy priorities within the TE framework. To verify the DERMS aggregator operations, three business models were proposed (i.e. greedy-profit margin, collegial-peak demand, reserved-standalone) to analyse comparative technical/physical and economic/social dimensions. Results showed that the proposed TE-valued DERMS aggregator provides participation versatility in the electricity market that enables competitive edginess when utilising Behind-The-Meter DERs in view of Prosumer’s asset scheduling, bidding strategy, and corroborative ancillary services. Performance metrics were evaluated on both domestic and industrial NG environments against IEEE Standard 2030.7-2017 & 2030.8-2018 compliances to ensure deployment practicability. Subsequently, proposed in-house protection system for DER installation serves as an add-on monitoring service which can be incorporated into existing Advance Distribution Management System (ADMS) for Distribution Service Operator (DSO) and field engineers use, ADMS aggregator. It provides early fault detections and isolation processes from allowing fault current to propagate upstream causing cascading power quality issues across the feeder line. In addition, ADMS aggregator also serves as islanding indicator that distinguishes Nanogrid’s islanding state from unintentional or intentional operations. Therefore, a Overcurrent Current Relay (OCR) is proposed using Fuzzy Logic (FL) algorithm to detect, profile, and provide decisional isolation processes using specified OCRs. Moreover, the proposed expert knowledge in FL is programmed to detect fault crises despite insufficient fault current level contributed by DER (i.e. solar PV system) which conventional OCR fails to trigger

    Artificial Intelligence and Machine Learning Approaches to Energy Demand-Side Response: A Systematic Review

    Get PDF
    Recent years have seen an increasing interest in Demand Response (DR) as a means to provide flexibility, and hence improve the reliability of energy systems in a cost-effective way. Yet, the high complexity of the tasks associated with DR, combined with their use of large-scale data and the frequent need for near real-time de-cisions, means that Artificial Intelligence (AI) and Machine Learning (ML) — a branch of AI — have recently emerged as key technologies for enabling demand-side response. AI methods can be used to tackle various challenges, ranging from selecting the optimal set of consumers to respond, learning their attributes and pref-erences, dynamic pricing, scheduling and control of devices, learning how to incentivise participants in the DR schemes and how to reward them in a fair and economically efficient way. This work provides an overview of AI methods utilised for DR applications, based on a systematic review of over 160 papers, 40 companies and commercial initiatives, and 21 large-scale projects. The papers are classified with regards to both the AI/ML algorithm(s) used and the application area in energy DR. Next, commercial initiatives are presented (including both start-ups and established companies) and large-scale innovation projects, where AI methods have been used for energy DR. The paper concludes with a discussion of advantages and potential limitations of reviewed AI techniques for different DR tasks, and outlines directions for future research in this fast-growing area
    corecore