It is expected that the grid of the future differs from the current system by the increased integration of distributed generation, distributed storage, demand response, power electronics, and communications and sensing technologies. The consequence is that the physical structure of the system becomes significantly more distributed. The existing centralized control structure is not suitable any more to operate such a highly distributed system. This thesis is dedicated to providing a promising solution to a class of energy management problems in power systems with a high penetration of distributed resources. This class includes optimal dispatch problems such as optimal power flow, security constrained optimal dispatch, optimal power flow control and coordinated plug-in electric vehicles charging. Our fully distributed algorithm not only handles the computational complexity of the problem, but also provides a more practical solution for these problems in the emerging smart grid environment. This distributed framework is based on iteratively solving in a distributed fashion the first order optimality conditions associated with the optimization formulations. A multi-agent viewpoint of the power system is adopted, in which at each iteration, every network agent updates a few local variables through simple computations, and exchanges information with neighboring agents. Our proposed distributed solution is based on the consensus+innovations framework, in which the consensus term enforces agreement among agents while the innovations updates ensure that local constraints are satisfied.

Flood events have become more frequent in Europe, and the adaptation to the increasing flood risks is needed. The Flood Directive set up a series of measures to increase European resilience, establishing Flood Risk Management Plans (FRMPs) at the level of the river basin district as one relevant action. In order to efficiently fulfil this objective, the involvement of stakeholders as well as the analysis of their roles, responsibilities, and demands has been considered to be crucial to develop FRMPs. As a result, the hypothesis tested in this paper is that a consensus solution for the 2021 update Austrian Flood Risk Management Plan is feasible. To demonstrate this, both in-depth interviews and questionnaires to key Austrian stakeholders are implemented. The information collected in both participatory techniques are then used to run a conflict prevention analysis. The results show that (a) improving the coordination among regions and including better land-use planning approaches are preferable to a hypothetical business as usual scenario; and (b) a consensus solution for the 2021 update Austrian FRMP might be achievable on the basis of both a deep discussion on the state-of-the art and green infrastructure development.

Traditional clustering algorithms have different criteria and biases, and there is no single algorithm that can be the best solution for a wide range of data sets. This problem often presents a significant obstacle to analysts in revealing meaningful information buried among the huge amount of data. Ensemble Clustering has been proposed as a way to avoid the biases and improve the accuracy of clustering. The difficulty in developing Ensemble Clustering methods is to combine external information (provided by input clusterings) with internal information (i.e. characteristics of given data) effectively to improve the accuracy of clustering. The work presented in this thesis focuses on enhancing the clustering accuracy of Ensemble Clustering by employing heuristic optimisation techniques to achieve a robust combination of relevant information during the consensus clustering stage. Two novel heuristic optimisation-based Ensemble Clustering methods, Multi-Optimisation Consensus Clustering (MOCC) and K-Ants Consensus Clustering (KACC), are developed and introduced in this thesis. These methods utilise two heuristic optimisation algorithms (Simulated Annealing and Ant Colony Optimisation) for their Ensemble Clustering frameworks, and have been proved to outperform other methods in the area. The extensive experimental results, together with a detailed analysis, will be presented in this thesis.

Modern power systems are characterized by an increasing penetration of renewable energy generating units. These aim to reduce the carbon emissions in the environment by replacing conventional energy generating units which rely on fossil fuels. In this new power systems composition, wind generators (WGs) dominate, being one of the largest and fastest-growing sources of renewable energy production. Nevertheless, their unpredictable and highly volatile power output hinders their efficient and secure large-scale deployment, and poses challenges for the transient stability of power systems. Given that, we identify two challenges in the operation of modern power systems: rendering WGs capable of reguating their power output while securing transient stabilization of conventional synchronous generators (SGs). This dissertation makes several contributions for effectively dealing with these major challenges by introducing new distributed control techniques for SGs, storage devices and state-of-the-art (SoA) WGs. Initially, this dissertation introduces a novel nonlinear control design which is able to coordinate a storage device and a SG to attain transient stabilization and concurrent voltage regulation on their terminal bus. Thereafter, it proposes control designs that SoA WGs can adopt to effectively regulate their power out- put to meet local or group objectives. In this context, the rst control design is a decentralized nonlinear energy-based control design, that can be employed by a wind double-fed induction generator (DFIG) with an incorporated energy storage device (namely a SoA WG) to regulate its power output by harnessing stored energy, with guaranteed performance for a wide-range of operating conditions. Recognizing that, today, albeit wind farms (WFs) are comprised of numerous WGs which are sparsely located in large geographical areas, they are required to respond rapidly and provide services to the grid in an efficient, reliable and timely fashion. To this end, this dissertation proposes distributed control methods for power output regulation of WFs comprised of SoA WGs. In particular, a novel distributed control design is proposed, which can be adopted by SoA WGs to continuously, dynamically and distributively self-organize and control their power outputs by leveraging limited peer-to-peer communication. By employing the proposed control design, WGs can exploit their storage devices in a fair load-sharing manner so that their total power output tracks a total power reference under highly dynamical conditions. Finally, this dissertation proposes a distributed control design for wind DFIGs without a storage device, the most common type of WGs deployed today. With this control design, wind DFIGs can dynamically, distributively and fairly self-dispatch and adjust the power they extract from the wind for the purpose of their total power tracking a dynamic reference. The effectiveness of the control designs proposed in this dissertation is illustrated through several case studies on a 3-bus power system and the IEEE 24-bus Reliability Test System.

Within the field of multi-agent systems theory, we study the problems of consensus and pursuit-evasion. In our study of the consensus problem, we first provide some theoretical results and then consider the problem of consensus on SO(3) or attitude synchronization. In Chapter 2, for agents with states in R^m, we present two theorems along the lines of Lyapunov’s second method that, under different conditions, guarantee asymptotic state consensus in multi-agent systems where the interconnection topologies are switching. The first theorem is formulated by using the states of the agents in the multi-agent system, whereas the second theorem is formulated by using the pairwise states for pairs of agents in the multi-agent system. In Chapter 3, the problem of consensus on SO(3) for a multi-agent system with directed and switching interconnection topologies is addressed. We provide two different types of kinematic control laws for a broad class of local representations of SO(3). The first control law consists of a weighted sum of pairwise differences between positions of neighboring agents, expressed as coordinates in a local representation. The structure of the control law is well known in the consensus community for being used in systems of agents in the Euclidean space, and here we show that the same type of control law can be used in the context of consensus on SO(3). In a later part of this chapter, based on the kinematic control laws, we introduce torque control laws for a system of rigid bodies in space and show that the system reaches consensus when these control laws are used. Chapter 4 addresses the problem of consensus on SO(3) for networks of uncalibrated cameras. Under the assumption that each agent uses a camera in order to measure its rotation, we prove convergence to the consensus set for two types of kinematic control laws, where only conjugate rotation matrices are available for the agents. In these conjugate rotations, the rotation matrix can be seen as distorted by the (unknown) intrinsic parameters of the camera. For the conjugate rotations we introduce distorted versions of well known local parameterizations of SO(3) and show consensus by using control laws that are similar to the ones in Chapter 3, with the difference that the distorted local representations are used instead. In Chapter 5, we study the output consensus problem for homogeneous systems of agents with linear continuous time-invariant dynamics. We derive control laws that solve the problem, while minimizing a cost functional of the control signal. Instead of considering a fixed communication topology for the system, we derive the optimal control law without any restrictions on the topology. We show that for all linear output controllable homogeneous systems, the optimal control law uses only relative information but requires the connectivity graph to be complete and in general requires measurements of the state errors. We identify cases where the optimal control law is only based on output errors. In Chapter 6, we address the multi-pursuer version of the visibility pursuit-evasion problem in polygonal environments. By discretizing the problem and applying a Mixed Integer Linear Programming (MILP) framework, we are able to address problems requiring so called recontamination and also impose additional constraints, such as connectivity between the pursuers. The proposed MILP formulation is less conservative than solutions based on graph discretizations of the environment, but still somewhat more conservative than the original underlying problem. It is well known that MILPs, as well as multi-pursuer pursuit-evasion problems, are NP-hard. Therefore we apply an iterative Receding Horizon Control (RHC) scheme, where a number of smaller MILPs are solved over shorter planning horizons. The proposed approach is illustrated by a number of solved examples. / <p>QC 20140327</p>

This thesis provides an implementation of consensus of multi-agent networked systems. Consensus problem is an important issue of distributed computing and has various algorithms and applications in the field of electronical and computer science. The consensus requests all nodes of a network reach an agreement over a certain measurement. An algorithm of convergent consensus problem is implemented through a small network of Bluetooth communication in the thesis. The connections of the Bluetooth devices are wireless, and the device nodes of the network are driven by C++ software and Winsock API. The simulation results show that the implementation completes all the requirements of the distributed consensus algorithm.

Mémoire numérisé par la Division de la gestion de documents et des archives de l'Université de Montréal.

This thesis presents an ethnography of public discourse in postcolonial, decolonial, queer, and multimedia contexts, as part of a critical analysis of imperialism in the digital age. In mixing experiences with theory and social practice, I draw on the work of activists who have already begun to mold these theories into everyday practice, paying particular attention to Occupy Wall Street, the Zapatistas of Mexico, and Southerners on New Ground (SONG)—a regionally focused non-profit organization based in the southern United States. I develop techno-seduction as a term to deconstruct the lure of technological determinism promoting static interpretations of democracy, consensus, and participation, and to describe the impact these interpretations have on intrapersonal and group identity formation.

Thèse numérisée par la Direction des bibliothèques de l'Université de Montréal.

Thèse numérisée par la Direction des bibliothèques de l'Université de Montréal.