Wind power generation does, on the one hand, contribute to a less polluting and more sustainable electric power generation mix. On the other hand, the uncertainty and the variability of the power output do challenge the operation of the power system: hourly variations in wind power generation are hardly predictable in a precise way. To decrease the need for balancing power, it might be beneficial from the overall system-perspective to subject power generating companies to stricter balancing incentives/rules. The way the market is designed has become crucial to exploit the existing flexibility in the power system and to increase the efficiency in its operation: inappropriate market designs can counteract all technical achievements. The work conducted for this thesis is embedded in a project on wind power integration and electricity market design following the aim to develop a simulation tool to analyse the consequences of changes in specific market rules. This thesis analyses wind power variations and forecast errors in the Swedish power system and explores the question whether internal ex-ante self-balancing can efficiently reduce the need for balancing power. Applying internal ex-ante self-balancing, every power generating company re-schedules its own power plants in order to balance its commitments towards other market actors with its newest production forecast. This is done shortly before the hour of delivery. To assess the value of this self-balancing, possible trading and scheduling decisions for power generating companies are modelled based on a hydro-thermal generation portfolio within the framework of the Nordic electricity market design. The model is based on a sequence of mixed-integer linear optimisation problems for the clearing of the different sub-markets. Both the data and the model have an hourly time resolution. In a case study, the model is applied on a simplified test-system. The need of real-time balancing by the transmission system operator, the total variable generation cost of the system, as well as the extent to which the power generating companies re-scheduled their production are then used as indicators to evaluate self-balancing. / <p>QC 20121017</p> / Short-term hydro power planning in power systems with large amounts of wind power / Elektra 36141: Korttidsplanering av vatten-värmekraftsystem vid stora mängder vindkraft: System-perspektivet

The use of automated procedures has recently become popular in the causal inference literature. Naive implementations of automatic procedures stand in contrast to the perspective advocated in Imbens and Rubin's Causal Inference. Imbens and Rubin suggest that researchers should make modelling decisions informed by subjective knowledge. We make use of simulated data to compare Imbens and Rubin's approach to naive implementations of two automatic procedures: Genetic Matching and Entropy Balancing. In addition we perform a small Monte Carlo simulation, based on one of the simulated data sets. Using the simulated data sets and the Monte Carlo simulations, we illustrate and explore benefits and drawbacks of the different approaches. We argue that there are benefits to make use of design-decisions grounded in subjective knowledge.

In recent years, routing research concerning wired networks has focused on minimizing the maximum utilization of the links which is equivalent to reducing the number of bottlenecks while supporting the same traffic demands. This can be achieved using multipath routing with load balancing instead of single path routing using of routing optimizers. However, in the domain of ad hoc networks multipath routing has not been investigated in depth. We would like to develop an analogy between wired and wireless networks, but before that we need to identify the major differences between these two in the case of multipath routing. First, in order to increase the network throughput, the multiple paths have to be independent so they don't share the same bottlenecks. Then, due to radio propagation properties the link capacity is not constant. So using the maximum utilization metric for wireless networks is not suitable. Based on the research done in wired networks, which has shown that using multiple paths with load balancing policies between sourcedestination pairs can minimize the maximum utilization of the links, we investigate if this is applicable to ad hoc networks. This paper proposes a multipath routing algorithm with a load balancing policy. The results obtained from an indoor 802.11g network highlight two major points. The maximum throughput is not achieved with multipath routing, but with single path routing. However, the results on the delivery ratio are encouraging, indeed we observe a real improvement thanks to our multipath routing algorithm. / På senare år har routning forskningen angående trådnätverken focusen på att minska den maximala användingen av länkar vilket motsvarar än reducering av flaskhalsar medan man stöder samma trafikkrav. Det här kan åstadkommas genom att av multiväg routning med lasta balansering I stället för använder enkelvägrouting med routing optimizers. Emellertid har inom ad hoc nätverken multiväg routning har inte blivit undersökts på djupet. Vi skulle vilja utveckla en analogy emellan trådnätverk och trådlösnätverken.men främföre det behöver identifiera de store differenserna mellan dessa två vid multiväg routning. För det första måste de flerfaldiga vägarna vara oberoende för att öka nätverkens throughput så de inte delar samma flaskhalsar. Sedan är länkkapaciteten inte constant på grund av radiospridningsegenskaperna. Så den maximal användningsmetric för trådlös nätverken passar inte. Den här arbetetet föreslår en multiväg routning algoritm med lasta balanseringen. Resultaten få från en indoor 802.11g nätverk framhåller ger två store meningen. Den maximala throughput är inte åstadkoms med multiväg routing, men med enkelväg routning. Emellertid är resultaten på den leveransförhållande uppmuntrande; vi observera en verklig förbättring tack vare vår multiväg routning algoritmen.

As global investments in renewable energy technologies continue to grow, their effects on electricity markets are a challenge for regulators and policymakers. The thesis examines the effects of forecast errors of Czech and German renew- able energy sources on the size and volatility of the system imbalance of the Czech balancing market. Using a quantile regression and ARFIMA-GARCH models on hourly data, I found that higher solar and wind forecast errors in- crease the system imbalance in absolute terms and affect the volatility. The results show that the Czech solar and wind forecast errors have significantly higher effect than the German forecast errors on the size and volatility of the system imbalance. The strongest effect on the size and volatility of the system imbalance have the Czech solar forecast errors. Therefore, the Czech govern- ment should insist on improving the accuracy and availability of renewable energy forecasts from the transmission system operator ČEPS. Klasifikace JEL C14, C50, Q42 Klíčová slova renewable sources, forecast errors, balanc- ing market, system imbalance

Mobile learning (m-learning) is a relatively new technology that helps students learn and gain knowledge using the Internet and Cloud computing technologies. Cloud computing is one of the recent advancements in the computing field that makes Internet access easy to end users. Many Cloud services rely on Cloud users for mapping Cloud software using virtualization techniques. Usually, the Cloud users' requests from various terminals will cause heavy traffic or unbalanced loads at the Cloud data centers and associated Cloud servers. Thus, a Cloud load balancer that uses an efficient load balancing technique is needed in all the cloud servers. We propose a new meta-heuristic algorithm, named the dominant firefly algorithm, which optimizes load balancing of tasks among the multiple virtual machines in the Cloud server, thereby improving the response efficiency of Cloud servers that concomitantly enhances the accuracy of m-learning systems. Our methods and findings used to solve load imbalance issues in Cloud servers, which will enhance the experiences of m-learning users. Specifically, our findings such as Cloud-Structured Query Language (SQL), querying mechanism in mobile devices will ensure users receive their m-learning content without delay; additionally, our method will demonstrate that by applying an effective load balancing technique would improve the throughput and the response time in mobile and cloud environments.

Small states tend to use different security strategies to increase and gain influence over their own level of security. Sweden is a small Nordic state with a long history of proclaimed neutrality when it comes to security policy. But in the last couple of decades the country has increased its contributions to, and participations in, numerous EU and NATO security projects and exercises. In 2009, Sweden adopted a declaration of solidarity towards the member countries of the EU. In 2014, Sweden also signed a memorandum of understanding with NATO. This has ignited bothan internal and an external debate among political scientists and security experts about what the Swedish security strategy is. This paper seeks to describe and clarify the Swedish security strategy by analyzing documents on security policy from the Swedish government. The study also examines the level of continuity in the Swedish security strategy. Based on a theoretical framework of security strategies of small states, the study utilizes three ideal types of the small state security strategies balancing , bandwagoning and hedging to analyze and describe the Swedish security strategy. The study concludes that the Swedish security strategy as it is presented in two official documents on security policy ranging from 2009 to 2015 mostly indicates balancing . The willingness to strengthen the Swedish military capacity and theeagerness for cooperation with the EU, NATO and USA clearly indicates balancing towardsRussia, a state which is described as a security threat in both documents. However, there are also tendencies towards hedging due to the insistence of armed neutrality in both documents. The study also shows that while there is a high degree of continuity in Sweden’s security strategy there has been a small shift in strategy towards more balancing from 2009 to 2015.

Le travail de recherche mené dans cette thèse consiste à développer de nouveaux algorithmes de répartition de charge pour les systèmes de traitement de données massives. Le premier algorithme mis au point, nommé "WACA" (Workload and Cache Aware Algorithm) améliore le temps d’exécution des traitements en se basant sur des résumés de contenus. Le second algorithme, appelé "CAWA" (Cost Aware Algorithm) tire partie de l’information de coût disponible dans les plateformes de type "Cloud Computing" en étudiant l’historique d’exécution des services.L’évaluation de ces algorithmes a nécessité le développement d’un simulateur d’infrastructures de "Cloud" nommé Simizer, afin de permettre leur test avant le déploiement en conditions réelles. Ce déploiement peut se faire de manière transparente grâce au système de distribution et de surveillance de service web nommé "Cloudizer", développé aussi dans le cadre de cette thèse. Ces travaux s’inscrivent dans le cadredu projet de plateforme de traitement de données Multimédia for Machine to Machine (MCUBE), dans le lequel le canevas Cloudizer est mis en oeuvre. / The research work carried out in this thesis consists in the development of new load balancing algorithms aimed at big data computing. The first algorithm, called « WACA » (Workload and Cache Aware Algorithm), enhances response times by locating data efficiently through content summaries. The second algorithm, called CAWA (Cost AWare Algorithm) takes advantage of the cost information available on Cloud Computing platforms by studying the workload history.Evaluation of these algorithms required the development of a cloud infrastructure simulator named Simizer, to enable testing of these policies prior to their deployment. This deployment can be transparently done thanks to the Cloudizer web service distribution and monitoring system, also developed during this thesis. These works are included in the Multimedia for Machine to Machine (MCUBE) project, where the Cloudizer Framework is deployed.

Traditional electric vehicle and stationary battery systems use series-connected battery packs that employ centralized battery management and power processing architecture. Though, these systems meet the basic safety and power requirements with a simple hard- ware structure, the approach results in a battery pack that is energy and power limited by weak cells throughout life and most importantly at end-of-life. The applications of battery systems can benefit significantly from modular, scalable battery systems capable of advanced cell balancing, efficient power processing, and cost gains via reuse beyond first-use application. The design of modular battery systems has unique requirements for the power electronics designer, including architecture, design, modeling and control of power processing converters, and battery balancing methods. This dissertation considers the requirements imposed by electric vehicle and stationary applications and presents design and control of modular battery systems to overcome challenges associated with conventional systems. The modular battery system uses cell or substring-level power converters to combine battery balancing and power processing functionality and opens the door to new opportunities for advanced cell balancing methods. This approach enables balancing control to act on cell-level information, reroute power around weaker cells in a string of cells to optimally deploy the stored energy, and achieve performance gains throughout the life of the battery pack. With this approach, the integrated balancing power converters can achieve system cost and efficiency gains by replacing or eliminating some of the conventional components inside battery systems such as passive balancing circuits and high-voltage, high-power converters. In addition, when coupled with life prognostic based cell balancing control, the modular system can extend the lifetime of a battery pack by up to 40%. The modular architecture design and control concepts developed in this dissertation can be applied to designs of large battery packs and improve battery pack performance, lifetime, size, and cost.

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This research first identifies some of the key concerns about the techniques and algorithms developed for distributed and parallel model checking; specifically, the inherent problem with load balancing and large queue sizes resultant in a static partition algorithm. This research then presents a load balancing algorithm to improve the run time performance in distributed model checking, reduce maximum queue size, and reduce the number of states expanded before error discovery. The load balancing algorithm is based on Generalized Dimension Exchange (GDE). This research presents an empirical analysis of the GDE based load balancing algorithm on three different supercomputing architectures---distributed memory clusters, Networks of Workstations (NOW) and shared memory machines. The analysis shows increased speedup, lower maximum queue sizes and fewer total states explored before error discovery on each of the architectures. Finally, this research presents a study of the communication overhead incurred by using the load balancing algorithm, which although significant, does not offset performance gains.