Coordination Mechanisms for Agent-Based Smart Grids
dc.contributor.author | Mihailescu, Radu-Casian | |
dc.date.accessioned | 2014-04-29T08:00:59Z | |
dc.date.available | 2014-04-29T08:00:59Z | |
dc.date.issued | 2013 | |
dc.identifier.uri | http://hdl.handle.net/10115/12312 | |
dc.description | Tesis Doctoral leída en la Universidad Rey Juan Carlos de Madrid en 2013. Director de la Tesis: Sascha Ossowski | es |
dc.description.abstract | Governments around the globe are heavily investing in upgrading the ageing infrastructure of the electricity grid. The imperative for this is driven primarily by regulatory requirements and the high cost of inefficiently delivering energy. The infrastructure is continuously improving, as more and more smart meters are installed, coupled with the proliferation of controllable loads and distributed generation. However, network operators, utilities, as well as end-consumers and small-scale producers are struggling to extract value from such systems and are exploring new ways for optimizing the performance of their deployed assets. This thesis introduces a multiagent approach for modelling the emerging complexity of the energy industry. The multiagent system paradigm is an ideal candidate for delivering a framework that captures the inherent distributed and dynamic nature of smart grids. While the traditionally centralized management of the system becomes less viable in the context of distributed generation and controllable loads, the underlying thread of this thesis advocates the design and implementation of coordination mechanisms capable to integrate and manage a large-scale integration of such devices via agent-based control. We begin by proposing dynamic micro-grids, a new conceptual organization of the network, adequate to integrate today¿s traditional users into an interactive, internetlike system, in the sense that power flow will become bidirectional and energy management will become distributed in the grid due to the many actors involved in the operation of the system. The mechanisms proposed for micro-grid formation are oriented towards producing sub-systems of the grid that are exhibiting reduced transmission losses and an efficient utilization of renewables, as well as endowing the system with self-adaptation techniques for coping with dynamic environments. We further aim to enhance the operation of the micro-grid formations by mainly focusing on two aspects. On one hand (supply-side) we are concerned with seamlessly integrating distributed generation to ensure a reliable service of energy supply comparable to what a large power plant delivers today. We first address the economic benefits of virtual power plants in a game-like setting and then go on to propose a DCOP-based formalism for solving the schedule generation problem, while accounting for the stochastic behavior of intermittent supply. On the other hand (consumer-side), we apply the use of game mechanics to drive the behaviour of prosumers towards efficient grid-wise use of energy. In order to cope with the challenges faced by current electricity networks, we propose a game layer on top of the electricity grid infrastructure and the use coordination mechanisms as a catalyst for change, encouraging participation of prosumers in the energy field towards reduced costs, lower carbon generation and increased grid resilience in the form of demand response and demandside management solutions. Finally, we propose a collusion detection mechanism that complements the above-mentioned solutions in the sense of inspecting for patterns where agents tacitly cooperate through illicit monopoly tactics to manipulate energy markets. | es |
dc.language.iso | eng | es |
dc.publisher | Universidad Rey Juan Carlos | es |
dc.subject | Informática | es |
dc.title | Coordination Mechanisms for Agent-Based Smart Grids | es |
dc.type | info:eu-repo/semantics/doctoralThesis | es |
dc.rights.accessRights | info:eu-repo/semantics/openAccess | es |
dc.subject.unesco | 3304.06 Arquitectura de Ordenadores | es |
dc.subject.unesco | 1203.04 Inteligencia Artificial | es |
dc.description.departamento | Arquitectura de Computadores y Ciencias de la Computación e Inteligencia Artificial |
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