Paradigm and paradox in power networks

Well known in the theory of network flows, Braess paradox states that adding path(s) to a congested road network may increase overall journey time. In transportation networks, the phenomenon results from selfish routing. In power systems, an analogous increase in congestion can arise as a consequence of Kirchhoff's laws, suggesting opportunities to optimize grid topology. The thesis starts with the discussion of Braess-like congestion phenomena in linear circuits. We prove that adding electrical path(s) always increases congestion in networks powered by voltage sources, while the opposite in networks driven by current sources. Although such predictability is not present in networks controlled by a mixture of voltage and current sources, our results offer a clean decomposition that completely separates the effect of current sources and voltage sources on total loss. The culmination of this research is a set of four equivalent methods of computing I^2R loss in mixed-source networks. We go on to explore network decomposition in combination with greedy sequential line switching heuristics to address the NP-hardness of power grid topology control. By means of some low order examples, it is shown that within a reasonably large class of greedy heuristics, none can be found that perform better than the others across all grid topologies. Despite this cautionary tale, statistical evidence indicates that, among three most representative heuristics, the global greedy heuristic is most computationally intensive but has the best chance of reducing generation cost while enforcing connectivity. The final part of the thesis presents a new approach to grid decomposition using vertex cut sets. We show that each vertex cut set and corresponding grid decomposition establishes a natural upper bound on the interactions between subgrids as nodal injections are regulated within each. Using such decomposition, it becomes possible to isolate congestion effects to a relatively small subgrid. A fast grid decomposition heuristic based on vertex cut sets and locational marginal prices is then proposed and studied through simulations on IEEE 118-bus system. On average, the computational cost is significantly reduced and the generation cost saving is similar to what is obtained with a global greedy algorithm

Human-building interaction towards a sustainable built environment: A review

Human Building Interaction (HBI), a recently introduced emerging area, can be used for various purposes, including the development of better designs, constructions, and operations, as well as the support of building managers and occupants in meeting their goals. The expanding community of HBI researchers seeks to investigate the future of HBI research and design for an interactive built environment. Building managers and owners strive for energy-efficient, sustainable, and more livable buildings to improve and become 'smart.' Diverse buildings and urban spaces are individually designed and outfitted with various systems, components, and accessories. With the advent of the Internet of Things (IoT), these devices form a network of internet-connected 'things' that generate massive amounts of data. We can collect vast volumes of data in unprecedented numbers, providing critical insights that allow buildings to care for us by learning from acquired data and adjusting to our requirements. This paper contributes to HBI by surveying various efforts to interact with buildings using IoT sensors and interconnected things to gain useful insights. Buildings, in our perspective, have distinct personalities and obligations to achieve their objectives. So, we are trying to incorporate them into reality. Considering a building to be a bio-inspired living architecture, we compare human anatomy to building anatomy to understand better the functions and operations that buildings can perform in their built environment. Thinking from this outlook allows us to investigate how sensors can help us achieve such building sustainability standards and what operations they perform to create an interactive built environment. This review paper aims to investigate the role of sensors in particular and to what extent they can provide various useful insights to building occupants and users to meet sustainability standards. We examine the most recent work on how people engage with and interact with buildings via various interfaces to achieve sustainability goals. Finally, some domain-specific challenges that limit human engagement and interactions with the built environment are discussed

An SoS Conceptual Model, LVC Simulation Framework, and a Prototypical Implementation of Unmanned System Interventions for Nuclear Power Plant Disaster Preparedness, Response, and Mitigation

Nuclear power plant disasters can have severe and far-reaching consequences, thus emergency managers and first responders from utility owners to the DoD must be prepared to respond to and mitigate effects protecting the public and environment from further damage. Rapidly emerging unmanned systems promise significant improvement in response and mitigation of nuclear disasters. Models and simulations (M&S) may play a significant role in improving readiness and reducing risks through its use in planning, analysis, preparation training, and mitigation rehearsal for a wide spectrum of derivate scenarios. Legacy nuclear reactor M&S lack interoperability between themselves and avatar or agent-based simulations of emergent unmanned systems. Bridging the gap between past and the evolving future, we propose a conceptual model (CM) using a System of System (SoS) approach, a simulation federation framework capable of supporting concurrent and interoperating live, virtual and constructive simulation (LVC), and demonstrate a prototypical implementation of an unmanned system intervention for nuclear power plant disaster using the constructive simulation component. The SoS CM, LVC simulation framework, and prototypical implementation are generalizable to other preparedness, response, and mitigation scenarios. The SoS CM broadens the current stovepipe reactor-based simulations to a system-of-system perspective. The framework enables distributed interoperating simulations with a network of legacy and emergent avatar and agent simulations. The unmanned system implementation demonstrates feasibility of the SoS CM and LVC framework through replication of selective Fukushima events. Further, the system-of-systems approach advances life cycle stages including concept exploration, system design, engineering, training, and mission rehearsal. Live, virtual, and constructive component subsystems of the CM are described along with an explanation of input/output requirements. Finally, applications to analysis and training, an evaluation of the SoS CM based on recently proposed criteria found in the literature, and suggestions for future research are discussed

ENERGY CONSUMPTION OF MOBILE PHONES

Battery consumption in mobile applications development is a very important aspect and has to be considered by all the developers in their applications. This study will present an analysis of different relevant concepts and parameters that may have an impact on energy consumption of Windows Phone applications. This operating system was chosen because limited research related thereto has been conducted, even though there are related studies for Android and iOS operating systems. Furthermore, another reason is the increasing number of Windows Phone users. The objective of this research is to categorise the energy consumption parameters (e.g. use of one thread or several threads for the same output). The result for each group of experiments will be analysed and a rule will be derived. The set of derived rules will serve as a guide for developers who intend to develop energy efficient Windows Phone applications. For each experiment, one application is created for each concept and the results are presented in two ways; a table and a chart. The table presents the duration of the experiment, the battery consumed in the experiment, the expected battery lifetime, and the energy consumption, while the charts display the energy distribution based on the main threads: UI thread, application thread, and network thread

A WEB-BASED ENVIRONMENTAL TOOLKIT TO SUPPORT SMES IN THE IMPLEMENTATION OF AN ENVIRONMENTAL MANAGEMENT SYSTEM

With small and medium sized-enterprises (SMEs) taking up the majority of the global businesses, it is important they act in an environmentally responsible manner. Environmental management systems (EMS) help companies evaluate and improve their environmental impact but they often require human, financial, and temporary resources that not all SMEs can afford. This research encompasses interviews with representatives of two small enterprises in Germany to provide insights into their understanding, and knowledge of an EMS and how they perceive their responsibility towards the environment. Furthermore, it presents a toolkit created especially for small and medium-sized enterprises. It serves as a simplified version of an EMS based on the ISO 14001 standard and is evaluated by target users and appropriate representatives. Some of the findings are: while open to the idea of improving their environmental impact, SMEs do not always feel it is their responsibility to do so; they seem to lack the means to fully implement an EMS. The developed toolkit is considered useful and usable and recommendations are drawn for its future enhancement

CPS Data Streams Analytics based on Machine Learning for Cloud and Fog Computing: A Survey

Cloud and Fog computing has emerged as a promising paradigm for the Internet of things (IoT) and cyber-physical systems (CPS). One characteristic of CPS is the reciprocal feedback loops between physical processes and cyber elements (computation, software and networking), which implies that data stream analytics is one of the core components of CPS. The reasons for this are: (i) it extracts the insights and the knowledge from the data streams generated by various sensors and other monitoring components embedded in the physical systems; (ii) it supports informed decision making; (iii) it enables feedback from the physical processes to the cyber counterparts; (iv) it eventually facilitates the integration of cyber and physical systems. There have been many successful applications of data streams analytics, powered by machine learning techniques, to CPS systems. Thus, it is necessary to have a survey on the particularities of the application of machine learning techniques to the CPS domain. In particular, we explore how machine learning methods should be deployed and integrated in cloud and fog architectures for better fulfilment of the requirements, e.g. mission criticality and time criticality, arising in CPS domains. To the best of our knowledge, this paper is the first to systematically study machine learning techniques for CPS data stream analytics from various perspectives, especially from a perspective that leads to the discussion and guidance of how the CPS machine learning methods should be deployed in a cloud and fog architecture

Demand Side Management in the Smart Grid

Résumée L'objectif du présent projet est de développer des solutions pour améliorer l'efficacité énergétique dans les réseaux électriques. L'approche adoptée dans cette recherche est basée sur un concept nouveau dans le Smart Grids (réseaux électriques intelligents), l’optimisation du Demand/Response, qui permet la mise en œuvre de la gestion autonome de la demande de énergie pour une grande variété de consommateurs, des les maisons à les bâtiments, usines, centres commerciaux, les campus, les bases militaires, et même les micro-réseaux. La première partie de cette thèse présente le thème de la Smart Grid et évalue l'état de l'art par rapport aux portées du projet. Ensuite, nous introduisons une architecture pour la gestion autonome de la charge du côté de la demande. Cette architecture est composée par trois couches principales, dont deux, l’ordonnancement en ligne et l'ordonnancement au moindre coût, sont pleinement pris en compte, tandis que la troisième couche, la Demande/Response, est laissé comme une extension future. Une telle architecture tire profit de la séparation des des échelles de temps de la consommation d'énergie, et elle est évolutif et flexible. La deuxième partie de ce projet est axé sur la mise en œuvre de l'architecture proposée dans Matlab/Simulink, après une preuve de concept est donnée par des simulations et résultats expérimentaux. Mots-clés: programmation optimale de la charge, la charge de pointe de rasage, autonome Demand-Side Management (DSM), bâtiments intelligents, la demande / réponse, l'efficacité énergétique.----------ABSTRACT The objective of the present project is to develop solutions to improve energy eciency in electric grids. The basic approach adopted in this research is based on a new concept in the Smart Grid, namely Demand/Response Optimization, which enables the implementation of the autonomous demand side energy management for a big variety of consumers, ranging from homes to buildings, factories, commercial centers, campuses, military bases, and even micro-grids. The rst part of this thesis presents the topic of the Smart Grid and assesses the state of the art with respect to the scopes of the project. Afterward, we introduce an architecture for autonomous demand side load management composed of three main layers, of which two, online scheduling and minimum-cost scheduling, are fully addressed, while the third layer, Demand/Response, is left as future extension. Such architecture takes advantage of time-scale separation of energy consumption. It is scalable and exible. The second part of this project is focused on the implementation of the proposed architecture in Matlab/Simulink and a proof of concept is given through simulations and experimental results. Keywords: Optimal load scheduling, Peak-load shaving, Autonomous Demand-Side Man- agement (DSM), Smart Buildings, Demand/Response, Energy eciency

Towards BIM/GIS interoperability: A theoretical framework and practical generation of spaces to support infrastructure Asset Management

The past ten years have seen the widespread adoption of Building Information Modelling (BIM) among both the Architectural, Engineering and Construction (AEC) and the Asset Management/ Facilities Management (AM/FM) communities. This has been driven by the use of digital information to support collaborative working and a vision for more efficient reuse of data. Within this context, spatial information is either held in a Geographic Information Systems (GIS) or as Computer-Aided Design (CAD) models in a Common Data Environment (CDE). However, these being heterogeneous systems, there are inevitable interoperability issues that result in poor integration. For this thesis, the interoperability challenges were investigated within a case study to ask: Can a better understanding of the conceptual and technical challenges to the integration of BIM and GIS provide improved support for the management of asset information in the context of a major infrastructure project? Within their respective fields, the terms BIM and GIS have acquired a range of accepted meanings, that do not align well with each other. A seven-level socio-technical framework is developed to harmonise concepts in spatial information systems. This framework is used to explore the interoperability gaps that must be resolved to enable design and construction information to be joined up with operational asset information. The Crossrail GIS and BIM systems were used to investigate some of the interoperability challenges that arise during the design, construction and operation of an infrastructure asset. One particular challenge concerns a missing link between AM-based information and CAD-based geometry which hinders engineering assets from being located within the geometric model and preventing geospatial analysis. A process is developed to link these CAD-based elements with AM-based assets using defined 3D spaces to locate assets. However, other interoperability challenges must first be overcome; firstly, the extraction, transformation and loading of geometry from CAD to GIS; secondly, the creation of an explicit representation of each 3D space from the implicit enclosing geometry. This thesis develops an implementation of the watershed transform algorithm to use real-world Crossrail geometry to generate voxelated interior spaces that can then be converted into a B-Rep mesh for use in 3D GIS. The issues faced at the technical level in this case study provide insight into the differences that must also be addressed at the conceptual level. With this in mind, this thesis develops a Spatial Information System Framework to classify the nature of differences between BIM, GIS and other spatial information systems