Impairment-Aware QoS Routing in Translucent Optical Networks

Wavelength-division-multiplexed (WDM) optical networks are commonly used to trans- port huge amount of tra±c in long-haul and metro/regional networks. In these networks, the optical signals deteriorate due to the physical impairments they encounter as they traverse multiple links. This necessitates regeneration of the signals at the intermediate nodes so that the signals will reach the destination with an acceptable level of quality. In translucent optical networks, the regenerators are sparsely placed in the network. Some applications that are transported over these networks require a guaranteed end-to-end quality of service (QoS). The QoS routing in these networks involves two tasks: guaran- teeing the end-to-end QoS requirement, and making sure that the signal quality will be acceptable at the destination by considering the physical impairments. In this thesis, we present physical impairment-aware QoS routing algorithms in translucent optical networks. We have proposed exact and heuristic algorithms that aim at optimally satisfying the QoS requirements, and minimizing the number of regenerators used along the selected path. The attractive feature of our algorithms is that they incorporate both the physical impairments and the regenerator assignment into the path computation process. As a result, the paths are computed efficiently. The experimental results show that each of our algorithms has its own aspect of fitness where it should be the best choice over the others.Computer EngineeringElectrical Engineering, Mathematics and Computer Scienc

Smart Power Grid: A Holonic Approach

The electrical power system provides vital support for the functioning of modern so- cieties. Driven by the growing interest in clean, reliable and affordable energy, the electrical power system is facing transitions. The share of renewable energy sources in electricity supply is growing. In addition, the end customers of electricity, such as households, are transforming into “prosumers” that can generate, store, and export elec- tricity. Moreover, the demand for active participation of the end customers in electricity market is rising. Furthermore, the increasing electrification of the transportation sector is foreseen to bring about large wave of electric vehicles into neighborhoods. The future electricity grid, referred to as the smart grid, is expected to conveniently accommodate all the transitions to deliver clean, reliable and affordable energy. Unfortunately, at the moment there is no clear recipe for constructing the smart grid. The objective of this thesis is to find solutions for some of the challenges to be addressed to construct the smart grid. As more and more end customers become prosumers, the electrical power system will shift from the old paradigm in which electricity is centrally generated at few large scale power plants and supplied to distributed consumers, to a new decentralized paradigm where different kinds of prosumers exchange power on the grid. Thus, the rather old power system that was designed for centralized power supply needs to be restructured since it is not convenient to accommodate the new paradigm. To this end, this thesis proposes a new architecture of the smart grid based on the concept of holons. In the proposed holonic architecture of the smart grid, prosumers are recursively organized as systems of systems to eventually constitute the overall smart grid holarchy. The attrac- tive attributes of the holonic architecture include its provision of sufficient autonomy to the prosumers to manage their energy resources, its recursive structure that orga- nizes prosumers as systems of systems at various aggregation layers, and the dynamic reconfiguration capability of the prosumers to adapt to the changes in the environment. The benefits of the holonic control architecture are providing convenience for active participation of prosumers in the energy market, enabling scalable distributed control of myriad of energy resources, and increasing the reliability, efficiency, self-healing, and dynamic recovery of the smart grid. In the new paradigm, managing the load profile of the prosumers becomes a major challenge due to various factors. The energy production of the renewable sources, such as solar panels, are highly intermittent depending on the weather conditions. Besides, the large amount of energy consumed in charging the electric vehicles could introduce peak loads. Moreover, the autonomous prosumers might exploit the flexibility of their energy resources to achieve load profiles that maximize their individual benefits, which could add up to volatile aggregate load profile of the energy community. The volatility may result in undesirable peak loads, hence it needs to be minimized. In this thesis, a suitable load management strategy is developed to cope with this challenge. Our load management strategy employs a pricing incentive to coordinate the prosumers in the energy community so that a desirable aggregate load shape is achieved while the autonomous prosumers selfishly strive to minimize their individual costs. The pric- ing incentive adjusts to the intermittence of the renewable energy sources and the price-responsiveness of the prosumers, thereby effectively persuading the autonomous prosumers to a desirable aggregate load shape. In the classical electrical power system, the low voltage (LV) grid delivers energy in one direction, top-down, from controlled supply side to passive end consumers with moderate loads. Thus, the voltage and current dynamics can easily be maintained within the required operational boundaries. But this is changing. As more distributed energy sources and electric vehicles become widely available at the end customers, the energy produced from the distributed energy sources and the large energy consumption of electric vehicles could lead to undesirable voltage and current dynamics that could violate the operational boundaries of the LV grid. In this thesis, we assess how the physical structure of the LV grid influences its ability to maintain safe operational condition in the new paradigm. Using this assessment, we identified the key structural features of the LV grid that influence its operational performance, based on which we propose an algorithm to design the LV grid structure that can cope with the new paradigm. Clearly, improving the structure of the LV grid is not enough by itself. It is commonly understood that intelligence of the future smart grid is provided by the support of ICT networks. Yet, the interdependence between the power grid and the ICT network might affect the reliability of the power grid. After assessing the impact of the interdependence between the LV grid and its supporting ICT network on the reliability of the LV grid, this thesis provides valuable insights for optimal design of the interdependence between the two. As prosumers increasingly dominate the power system, the performance of the sys- tem can be significantly influenced by the performance of the individual prosumers. Whereas, the performances of the individual prosumers depend on the composition of their energy resources, since different energy resources make different contributions to a prosumer. Hence, understanding the value added by an energy resource to the perfor- mance of a prosumer is crucial. In this thesis, a model that assesses the value an energy resource adds to a prosumer is presented. The developed valuation model assesses how addition of an energy resource affects a comprehensive set of performance indicators of a prosumer that incorporate economic, environmental and social dimensions. Using the valuation model, certain energy resources can be added to or removed from a prosumer to improve the desirable performance indicators of the prosumer. The solutions developed in this thesis play important roles in overcoming different challenges facing the smart grid, thereby facilitating the transition to clean, reliable and affordable energy.Intelligent SystemsElectrical Engineering, Mathematics and Computer Scienc

Designing reliable and resilient smart low-voltage grids

The electric power grid is a critical infrastructure that delivers electricity from power generation sources to consumers. At this time, renewable and distributed sources of electricity as well as new technologies that introduce large loads are significantly changing load profiles in low-voltage grids. This trend calls for reassessing the structure of low-voltage grids to examine if they can safely accommodate the new load profiles. The future smart grid will also rely on information and communications networks to support decentralized power distribution. The information and communications network nodes may depend on the grid for power supply, leading to bidirectional interdependence between the two types of networks that could affect the reliability of the power grid.This paper focuses on the problem of enhancing the reliability of future low-voltage grids by improving their structure and dealing with their interdependence with information and communications networks. The paper investigates the structural features of a low-voltage grid and assesses their influence on the ability of the grid to handle new load profiles. Concepts from complex networks theory are used to derive relevant structural metrics that characterize the structural properties of low-voltage grids and performance metrics are proposed to assess their operational performance. Several low-voltage networks are analyzed under various loading scenarios to observe the influence of structural metrics of a low-voltage grid on its operational metrics. Based on this analysis, a constraint programming formulation is proposed for the cost-optimal and robust structural design of a low-voltage grid. In addition, a design algorithm is proposed that considers the interdependence of information and communications network nodes on power grid nodes to increase the reliability of the grid.Network Architectures and Service

Holonic architecture of the smart grid

With the growing concerns about sustainable energy, energy efficiency and energy security, the electrical power system is undergoing major changes. Distributed energy sources are becoming widely available at the lower parts of the grid. As a result, more and more end consumers are transforming from passive consumers to active “prosumers” that can autonomously generate, store, import and/or export power. As prosumers increasingly dominate the power system, the system demands capability that allows enormous number of stakeholders with heterogeneous types to exchange power on the grid. Unfortunately, the classical power system cannot efficiently handle this scenario since it was designed for centralized power distribution. Thus, restructuring the rather old power system is indispensable. In this paper, we apply the holonic approach to structure the smart grid as a system that is bottom-up organized from autonomous prosumers that are recursively clustered at various aggregation layers. Based on this, we present a control architecture of the smart grid using holonic concepts. Our control architecture is characterized by autonomy of the prosumers, distributed control, recursive self-similar control structures at different aggregation levels. Further, we present a service oriented architec-ture (SOA) framework that models the control functions that make up the holonic control architecture. Our proposed control architecture is tested using a simulation set-up.Intelligent SystemsElectrical Engineering, Mathematics and Computer Scienc

Valuation Model for Adding Energy Resource into Autonomous Energy Cluster

With the availability of distributed generation (DG), clusters that can autonomously manage their energy profile are emerging in the power grid. These autonomous clusters manage their load profiles by orchestrating their energy resources, such as DG, storage, flexible energy consuming appliances, etc. The performance of such an autonomous cluster depends on the composition of its energy resources. In this paper, we study how the performance of a cluster is affected by adding energy resources such as generating units, storage systems or consuming appliances. First, we characterize the energy resources by parameters that describe their relevant properties. Afterwards, we describe a comprehensive set of performance indicators of a cluster that capture the economical, environmental, and social aspects. We present a model that shows how the energy resources influence the performance indicators of the cluster. We have tested our model with a case study, revealing its effectiveness to evaluate the value added by an energy resource to a cluster.Intelligent SystemsElectrical Engineering, Mathematics and Computer Scienc