The future success of chargeable vehicles will, among other factors, depend on their charging costs and their ability to charge with minimal disturbances to the national, local and household electrical grid. To be able to minimize costs and schedule charging sessions, there has to be knowledge of how the charging power varies with time. This is called charging profile. A number of charging profiles for a Volvo V60 plug‑in hybrid electric vehicle have been recorded. For charging currents above 10 A they prove to be more complex than are assumed in most current research papers.   The charging profiles are used together with historical electricity prices to calculate charging costs for 2013 and 2014. Charging is assumed to take place during the night, between 18:00 and 07:00, with the battery being totally depleted at 18:00. By using a timer to have the charging start at 01:00, instead of immediately at 18:00, annual charging costs are reduced by approximately 7 to 8%. By using dynamic programming to optimize the charging sessions, annual charging costs are reduced by approximately 10 to 11%. An interesting issue regarding dynamic programming was identified, namely when using a limited set of predetermined discrete control signals, interpolation returns unrealizable cost-to-go values. This occurs specifically for instances crossing the zero cost-to-go area boundary.   It is concluded that the mentioned savings are realizable, via implementing timers or optimization algorithms into consumer charging stations. Finally, by using these decentralized charging planning tools and seen from a power usage perspective, at least 30% of the Swedish vehicle fleet could be chargeable and powered by the electrical grid.

The aim of this thesis is to analyze the costs of the chosen company and through the analysis suggest provisions which will lead to costs optimization. The practical part starts with introducing the company, which was chosen for this thesis. Then the analysis of operating and financial cost is made. The optimization suggestions of selected costs are based on this analysis.

The rapid growth of Cloud based services on the Internet invited many critical security attacks. Consumers and corporations who use the Cloud to store their data encounter a difficult trade-off of accepting and bearing the security, reliability, and privacy risks as well as costs in order to reap the benefits of Cloud storage. The primary goal of this thesis is to resolve this trade-off while minimizing total costs. This thesis presents a system framework that solves this problem by using erasure codes to add redundancy and security to users’ data, and by optimally choosing Cloud storage providers to minimize risks and total storage costs. Detailed comparative analysis of the security and algorithmic properties of 7 different erasure codes is presented, showing codes with better data security comes with a higher cost in computational time complexity. The codes which granted the highest configuration flexibility bested their peers, as the flexibility directly corresponded to the level of customizability for data security and storage costs. In-depth analysis of the risks, benefits, and costs of Cloud storage is presented, and analyzed to provide cost-based and security-based optimal selection criteria for choosing appropriate Cloud storage providers. A brief historical introduction to Cloud Computing and security principles is provided as well for those unfamiliar with the field. The analysis results show that the framework can resolve the trade-off problem by mitigating and eliminating the risks while preserving and enhancing the benefits of using Cloud storage. However, it requires higher total storage space due to the redundancy added by the erasure codes. The storage provider selection criteria will minimize the total storage costs even with the added redundancies, and minimize risks.

The selection of sites for biodiversity conservation is best done if it anticipates future challenges and efficiently accomplishes targets, given limited funding for such efforts. The first chapter of this thesis discusses how conservation practitioners might manage and enhance long-term survival for species whose ranges must shift as climate changes, across regions that present significant mobility barriers. I describe recommendations highlighting connectivity, refugia from climate change, adaptation, and restoration within agricultural landscapes in North America, but these recommendations are transferable elsewhere. The second chapter examines patterns of change in agricultural intensity and land price within Canada’s species-rich farmland between 1986 and 2011, and creates sequential cost-efficient plans to conserve resident species-at-risk within that time period, to determine how environmental and cost changes erode the efficiency of conservation plans. While sites initially selected as cost-efficient remained so through time, total plan costs increased, decreasing each plan’s ability to represent all species for a given budget. This emphasizes the urgent need for conservation within Canada’s farmland.

The automotive sector has been the most happening industry in terms of development ever since its creation. With markets emerging across the globe in the automotive sector there are newer challenges in terms of providing new products at lesser cost but without compromising on quality. Testing cost of electromechanical components (HMI) is high and which in turn has a direct impact on the final price of the product, which they are selling it to their customers. One way to counter this issue is to outsource. The aim of this thesis is to actually provide business intelligence where by the midsize segmented automotive suppliers are benefited and the cost of testing can be reduced. The product in focus here is an electromechanical component (HMI) for commercial vehicles. The main contribution in this thesis has been the analysis & implementation of the outsourcing strategy. There were two approaches one being a theoretical approach where a market research was done to get an overview of the current trend and studying the demands of different customer for testing. The second half has been practicality implementing this data collected. Here no assumptions have been taken and the data collected has been obtained purely based on interaction with various test vendors across Europe. Cost optimization analysis was further done in order to arrive at a conclusion of preferred suppliers. Also another strategy used was by investigating possibilities for making some test in house and defining standardized test plan procedures for them. Thereby providing an overall strategy for testing with cost optimization as the main focus also leading to an edge over their competitors and increasing their market share.

Aujourd’hui les réseaux électriques sont exploités dans un marché dérégulé. Les gestionnaires des réseaux électriques sont tenus d’assurer un certain nombre de critères de fiabilité et de continuité du service, tout en minimisant le coût total consacré aux efforts effectués pour maintenir la fiabilité des installations. Il s’agit de trouver une stratégie, qui répond à plusieurs exigences, comme : le coût, les performances, la législation, les exigences du régulateur, etc. Cependant, le processus de prise de décision est subjectif, car chaque participant ramène sa contribution sur base de sa propre expérience. Bien que ce processus permette de trouver la « meilleure » stratégie, cette dernière n’est pas forcément la stratégie « optimale ». Ce compromis technico-économique a sensibilisé les gestionnaires des réseaux électriques à la nécessité d’un recours à des outils d’aide à la décision, qui doivent se baser sur des nouvelles approches quantitatives et une modélisation plus proches de la réalité physique. Cette thèse rentre dans le cadre d’un projet de recherche lancé par ELIA, et dénommé COMPRIMa (Cost-Optimization Models for the Planning of the Renewal, Inspection, and Maintenance of Belgian power system facilities). Ce projet vise à développer une méthodologie qui permet de modéliser une partie du réseau électrique de transport (par les réseaux de Petri stochastiques) et de simuler son comportement dynamique sur un horizon donné (simulation de Monte Carlo). L’évaluation des indices de fiabilité permet de comparer les différents scénarios qui tentent d’améliorer les performances de l’installation. L’approche proposée est basée sur la stratégie RCM (Reliability-Centered Maintenance). La méthodologie développée dans cette thèse permet une modélisation plus réaliste du réseau qui tient compte, entre autres, des aspects suivants : - La corrélation quantitative entre le processus de maintenance et le processus de vieillissement des composants (par un modèle d’âge virtuel) ; - Les dépendances liées à l’aspect multi-composant du système, qui tient compte des modes de défaillance spécifiques des systèmes de protection ; - L’aspect économique lié à la stratégie de maintenance (inspection, entretien, réparation, remplacement), aux coupures (programmées et forcées) et aux événements à risque (refus disjoncteur, perte d’un client, perte d’un jeu de barres, perte d’une sous-station, etc.).

A unique approach is developed for evaluating Human Capital (workforce) requirements. With this approach, new ways of measuring personnel availability are proposed and available to ensure that an organization remains ready to provide timely, relevant, and accurate products and services in support of its strategic objectives over its planning horizon. The development of this analysis and methodology was established as an alternative approach to existing studies for determining appropriate hiring and attrition rates and to maintain appropriate personnel levels of effectiveness to support existing and future missions. The contribution of this research is a prescribed method for the strategic analyst to incorporate a personnel and cost simulation model within the framework of Human Resources Human Capital forecasting which can be used to project personnel requirements and evaluate workforce sustainment, at least cost, through time. This will allow various personnel managers to evaluate multiple resource strategies, present and future, maintaining near “perfect” hiring and attrition policies to support its future Human Capital assets.

This thesis recounts the study of contour blasting practices in the Appalachia coal region. Contour blasting practices vary widely and problems are often encountered. Several different sites were visited and contour blasting practices at each were studied. Based on the information gathered, a comprehensive plan was developed for blasting operations to follow and then was tested and compared to an example of blasting practices without use of the plan. The blasting practices were compared by examining monthly production rates as well as a time study to measure the efficiency a contour blast could be loaded and hauled away and a cost per cubic yard of material determined. The plan was found to be successful in keeping safety while increasing profitability. However, the plan will need to be backed and understood by management in order to achieve the same success.

Cloud Computing represents a recent paradigm shift that enables users to share and remotely access high-powered computing resources (both infrastructure and software/services) contained in off-site data centers thereby allowing a more efficient use of hardware and software infrastructures. This growing trend in cloud computing, combined with the demands for Big Data and Big Data analytics, is driving the rapid evolution of datacenter technologies towards more cost-effective, consumer-driven, more privacy conscious and technology agnostic solutions. This dissertation is dedicated to taking a systematic approach to develop system-level techniques and algorithms to tackle the challenges of large-scale data processing in the Cloud and scaling and delivering privacy-aware services with anytime-anywhere availability. We analyze the key challenges in effective provisioning of Cloud services in the context of MapReduce-based parallel data processing considering the concerns of cost-effectiveness, performance guarantees and user-privacy and we develop a suite of solution techniques, architectures and models to support cost-optimized and privacy-preserving service provisioning in the Cloud. At the cloud resource provisioning tier, we develop a utility-driven MapReduce Cloud resource planning and management system called Cura for cost-optimally allocating resources to jobs. While existing services require users to select a number of complex cluster and job parameters and use those potentially sub-optimal per-job configurations, the Cura resource management achieves global resource optimization in the cloud by minimizing cost and maximizing resource utilization. We also address the challenges of resource management and job scheduling for large-scale parallel data processing in the Cloud in the presence of networking and storage bottlenecks commonly experienced in Cloud data centers. We develop Purlieus, a self-configurable locality-based data and virtual machine management framework that enables MapReduce jobs to access their data either locally or from close-by nodes including all input, output and intermediate data achieving significant improvements in job response time. We then extend our cloud resource management framework to support privacy-preserving data access and efficient privacy-conscious query processing. Concretely, we propose and implement VNCache: an efficient solution for MapReduce analysis of cloud-archived log data for privacy-conscious enterprises. Through a seamless data streaming and prefetching model in VNCache, Hadoop jobs begin execution as soon as they are launched without requiring any apriori downloading. At the cloud consumer tier, we develop mix-zone based techniques for delivering anonymous cloud services to mobile users on the move through Mobimix, a novel road-network mix-zone based framework that enables real time, location based service delivery without disclosing content or location privacy of the consumers.

[pt] Planejar a expansão de sistemas de transmissão de energia elétrica constitui uma tarefa complexa dentro do planejamento do setor elétrico. De acordo com os critérios vigentes, hoje no Brasil, procura-se abordar o problema através de um enfoque de programação matemática. É feito um estudo das técnicas em uso e dos modelos de análise de redes de transmissão. Em seguida é proposta uma nova metodologia para resolver o problema, levando em conta a cultura dos planejadores que podem, assim, interagir com os programas, aperfeiçoando o planejamento. Foi elaborado um modelo de programação inteira, capaz de gerar inúmeras alternativas de planejamento para um dado ano. Estas alternativas são analisadas e concatenadas, obtendo-se o planejamento ao longo do tempo. Apresenta-se um caso real, do planejamento da expansão do sistema sul do Brasil, comparando-se os resultados obtidos com os de outras metodologias. / [en] The plannification of the transmission system expansion is a very complex problem. In this work it is proposed a mathematical programming model to solve it, taking in account the restrictions established by the brazilian electric sector. It is shown the characteristics of some technics for solving the problem and a brief description of the transmission network analysis methods is also presented. It is proposed a new methodology to solve the planning problem, taking in account the planners experience. They are able to interfere on the process interacting with the program looking fot better solutions. An integer programming model was developped to obtain Several distinct expanded configurations for every year of the planning horizon. These configurations are analysed and then linked year, to obtain an expansion policy of the transmission sistem. It is presented the actual planning of the southern brazilian system, and the result obtained by this model are compared with those obtained by other methodologies.