597 research outputs found

    Organization of Multi-Agent Systems: An Overview

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    In complex, open, and heterogeneous environments, agents must be able to reorganize towards the most appropriate organizations to adapt unpredictable environment changes within Multi-Agent Systems (MAS). Types of reorganization can be seen from two different levels. The individual agents level (micro-level) in which an agent changes its behaviors and interactions with other agents to adapt its local environment. And the organizational level (macro-level) in which the whole system changes it structure by adding or removing agents. This chapter is dedicated to overview different aspects of what is called MAS Organization including its motivations, paradigms, models, and techniques adopted for statically or dynamically organizing agents in MAS.Comment: 12 page

    Multi-Agent Systems and Complex Networks: Review and Applications in Systems Engineering

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    Systems engineering is an ubiquitous discipline of Engineering overlapping industrial, chemical, mechanical, manufacturing, control, software, electrical, and civil engineering. It provides tools for dealing with the complexity and dynamics related to the optimisation of physical, natural, and virtual systems management. This paper presents a review of how multi-agent systems and complex networks theory are brought together to address systems engineering and management problems. The review also encompasses current and future research directions both for theoretical fundamentals and applications in the industry. This is made by considering trends such as mesoscale, multiscale, and multilayer networks along with the state-of-art analysis on network dynamics and intelligent networks. Critical and smart infrastructure, manufacturing processes, and supply chain networks are instances of research topics for which this literature review is highly relevant

    Practical applications of multi-agent systems in electric power systems

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    The transformation of energy networks from passive to active systems requires the embedding of intelligence within the network. One suitable approach to integrating distributed intelligent systems is multi-agent systems technology, where components of functionality run as autonomous agents capable of interaction through messaging. This provides loose coupling between components that can benefit the complex systems envisioned for the smart grid. This paper reviews the key milestones of demonstrated agent systems in the power industry and considers which aspects of agent design must still be addressed for widespread application of agent technology to occur

    Self-organising smart grid architectures for cyber-security

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    PhD ThesisCurrent conventional power systems consist of large-scale centralised generation and unidirectional power flow from generation to demand. This vision for power system design is being challenged by the need to satisfy the energy trilemma, as the system is required to be sustainable, available and secure. Emerging technologies are restructuring the power system; the addition of distributed generation, energy storage and active participation of customers are changing the roles and requirements of the distribution network. Increased controllability and monitoring requirements combined with an increase in controllable technologies has played a pivotal role in the transition towards smart grids. The smart grid concept features a large amount of sensing and monitoring equipment sharing large volumes of information. This increased reliance on the ICT infrastructure, raises the importance of cyber-security due to the number of vulnerabilities which can be exploited by an adversary. The aim of this research was to address the issue of cyber-security within a smart grid context through the application of self-organising communication architectures. The work examined the relevance and potential for self-organisation when performing voltage control in the presence of a denial of service attack event. The devised self-organising architecture used techniques adapted from a range of research domains including underwater sensor networks, wireless communications and smart-vehicle tracking applications. These components were redesigned for a smart grid application and supported by the development of a fuzzy based decision making engine. A multi-agent system was selected as the source platform for delivering the self-organising architecture The application of self-organisation for cyber-security within a smart grid context is a novel research area and one which presents a wide range of potential benefits for a future power system. The results indicated that the developed self-organising architecture was able to avoid control deterioration during an attack event involving up to 24% of the customer population. Furthermore, the system also reduces the communication load on the agents involved in the architecture and demonstrated wider reaching benefits beyond performing voltage control

    The blessings of explainable AI in operations & maintenance of wind turbines

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    Wind turbines play an integral role in generating clean energy, but regularly suffer from operational inconsistencies and failures leading to unexpected downtimes and significant Operations & Maintenance (O&M) costs. Condition-Based Monitoring (CBM) has been utilised in the past to monitor operational inconsistencies in turbines by applying signal processing techniques to vibration data. The last decade has witnessed growing interest in leveraging Supervisory Control & Acquisition (SCADA) data from turbine sensors towards CBM. Machine Learning (ML) techniques have been utilised to predict incipient faults in turbines and forecast vital operational parameters with high accuracy by leveraging SCADA data and alarm logs. More recently, Deep Learning (DL) methods have outperformed conventional ML techniques, particularly for anomaly prediction. Despite demonstrating immense promise in transitioning to Artificial Intelligence (AI), such models are generally black-boxes that cannot provide rationales behind their predictions, hampering the ability of turbine operators to rely on automated decision making. We aim to help combat this challenge by providing a novel perspective on Explainable AI (XAI) for trustworthy decision support.This thesis revolves around three key strands of XAI – DL, Natural Language Generation (NLG) and Knowledge Graphs (KGs), which are investigated by utilising data from an operational turbine. We leverage DL and NLG to predict incipient faults and alarm events in the turbine in natural language as well as generate human-intelligible O&M strategies to assist engineers in fixing/averting the faults. We also propose specialised DL models which can predict causal relationships in SCADA features as well as quantify the importance of vital parameters leading to failures. The thesis finally culminates with an interactive Question- Answering (QA) system for automated reasoning that leverages multimodal domain-specific information from a KG, facilitating engineers to retrieve O&M strategies with natural language questions. By helping make turbines more reliable, we envisage wider adoption of wind energy sources towards tackling climate change

    Design, modelling, simulation and integration of cyber physical systems: Methods and applications

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    The main drivers for the development and evolution of Cyber Physical Systems (CPS) are the reduction of development costs and time along with the enhancement of the designed products. The aim of this survey paper is to provide an overview of different types of system and the associated transition process from mechatronics to CPS and cloud-based (IoT) systems. It will further consider the requirement that methodologies for CPS-design should be part of a multi-disciplinary development process within which designers should focus not only on the separate physical and computational components, but also on their integration and interaction. Challenges related to CPS-design are therefore considered in the paper from the perspectives of the physical processes, computation and integration respectively. Illustrative case studies are selected from different system levels starting with the description of the overlaying concept of Cyber Physical Production Systems (CPPSs). The analysis and evaluation of the specific properties of a sub-system using a condition monitoring system, important for the maintenance purposes, is then given for a wind turbine
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