Coronal Mass Ejections (CMEs) and solar flares are energetic events taking place at the Sun that can affect the space weather or the near-Earth environment by the release of vast quantities of electromagnetic radiation and charged particles. Solar active regions are the areas where most flares and CMEs originate. Studying the associations among sunspot groups, flares, filaments, and CMEs is helpful in understanding the possible cause and effect relationships between these events and features. Forecasting space weather in a timely manner is important for protecting technological systems and human life on earth and in space. The research presented in this thesis introduces novel, fully computerised, machine learning-based decision rules and models that can be used within a system design for automated space weather forecasting. The system design in this work consists of three stages: (1) designing computer tools to find the associations among sunspot groups, flares, filaments, and CMEs (2) applying machine learning algorithms to the associations¿ datasets and (3) studying the evolution patterns of sunspot groups using time-series methods. Machine learning algorithms are used to provide computerised learning rules and models that enable the system to provide automated prediction of CMEs, flares, and evolution patterns of sunspot groups. These numerical rules are extracted from the characteristics, associations, and time-series analysis of the available historical solar data. The training of machine learning algorithms is based on data sets created by investigating the associations among sunspots, filaments, flares, and CMEs. Evolution patterns of sunspot areas and McIntosh classifications are analysed using a statistical machine learning method, namely the Hidden Markov Model (HMM).

1 ABSTRACT This thesis is named Linguistic Analysis of weather forecasts and is divided into two parts, theoretical and practical. In the first part of this thesis readers can find general knowledge of field of media: the term media communication is defined, specifics are described, it is talked about a media product, content and meaning. After that we mention media audience with respect to the pupil as a special type of recipient. The following is a characteristic of television weather forecasts within the media communication and analysis of its typical means of expression. The last part of this section is the description of the school curriculum, especially the media education, because the research was made in the schools and the main goals of this thesis were based on requirements of curricula of the Czech Republic. The second part presents the motivation of investigation and the method of the action research that was chosen. The largest part of this section is the part containing the whole evaluation and interpretation of the results of particular activities, both propaedeutic and proactive with the media product. The main goals of this thesis are the development and subsequent application of an action plan with projected activities for the Czech language teachers at primary school, especially in the...

The thesis consists of 95 pages and 41 pages of enclosure. Pictures, charts and colour graphs are included. The thesis and the enclosure contain data presented in charts and from the charts graphs have been made. Also, internal material provided by the Czech Hydrometeorological Institute, České Budějovice 7, Antala Staška 1177/32 is incorporated, as well as data from two amateur weather-stations situated in České Budějovice and Hluboká nad Vltavou. The objective of this work is to explain and describe measuring apparatus and methods used in meteorology. The work also compares results gained from a professional weather-station with those from an amateur one.

Le contexte de nos travaux de thèse est l'intégration de l'énergie éolienne sur les réseaux insulaires. Ces travaux sont soutenus par EDF SEI, l'opérateur électrique des îles françaises. Nous étudions un système éolien-stockage où un système de stockage d'énergie doit aider un producteur éolien à tenir, vis-à-vis du réseau, un engagement de production pris un jour à l'avance. Dans ce contexte, nous proposons une démarche pour l'optimisation du dimensionnement et du contrôle du système de stockage (gestion d'énergie). Comme les erreurs de prévision J+1 de production éolienne sont fortement incertaines, la gestion d'énergie du stockage est un problème d'optimisation stochastique (contrôle optimal stochastique). Pour le résoudre, nous étudions tout d'abord la modélisation des composants du système (modélisation énergétique du stockage par batterie Li-ion ou Sodium-Soufre) ainsi que des entrées (modélisation temporelle stochastique des entrées incertaines). Nous discutons également de la modélisation du vieillissement du stockage, sous une forme adaptée à l'optimisation de la gestion. Ces modèles nous permettent d'optimiser la gestion de l'énergie par la méthode de la programmation dynamique stochastique (SDP). Nous discutons à la fois de l'algorithme et de ses résultats, en particulier de l'effet de la forme des pénalisations sur la loi de gestion. Nous présentons également l'application de la SDP sur des problèmes complémentaires de gestion d'énergie (lissage de la production d'un houlogénérateur, limitation des rampes de production éolienne). Cette étude de l'optimisation de la gestion permet d'aborder l'optimisation du dimensionnement (choix de la capacité énergétique). Des simulations temporelles stochastiques mettent en évidence le fort impact de la structure temporelle (autocorrélation) des erreurs de prévision sur le besoin en capacité de stockage pour atteindre un niveau de performance donné. La prise en compte de paramètres de coût permet ensuite l'optimisation du dimensionnement d'un point de vue économique, en considérant les coûts de l'investissement, des pertes ainsi que du vieillissement. Nous étudions également le dimensionnement du stockage lorsque la pénalisation des écarts à l'engagement comporte un seuil de tolérance. Nous terminons ce manuscrit en abordant la question structurelle de l'interaction entre l'optimisation du dimensionnement et celle du contrôle d'un système de stockage, car ces deux problèmes d'optimisation sont couplés. / The context of this PhD thesis is the integration of wind power into the electricity grid of small islands. This work is supported by EDF SEI, the system operator for French islands. We study a wind-storage system where an energy storage is meant to help a wind farm operator fulfill a day-ahead production commitment to the grid. Within this context, we propose an approach for the optimization of the sizing and the control of the energy storage system (energy management). Because day-ahead wind power forecast errors are a major source of uncertainty, the energy management of the storage is a stochastic optimization problem (stochastic optimal control). To solve this problem, we first study the modeling of the components of the system. This include energy-based models of the storage system, with a focus on Lithium-ion and Sodium-Sulfur battery technologies. We then model the system inputs and in particular the stochastic time series like day-ahead forecast errors. We also discuss the modeling of storage aging, using a formulation which is adapted to the control optimization. Assembling all these models enables us to optimize the energy management of the storage system using the stochastic dynamic programming (SDP) method. We introduce the SDP algorithms and present our optimization results, with a special interest for the effect of the shape of the penalty function on the energy control law. We also present additional energy management applications with SDP (mitigation of wind power ramps and smoothing of ocean wave power). Having optimized the storage energy management, we address the optimization of the storage sizing (choice of the rated energy). Stochastic time series simulations show that the temporal structure (autocorrelation) of wind power forecast errors have a major impact on the need for storage capacity to reach a given performance level. Then we combine simulation results with cost parameters, including investment, losses and aging costs, to build a economic cost function for sizing. We also study storage sizing when the penalization of commitment deviations includes a tolerance threshold. We finish this manuscript with a structural study of the interaction between the optimizations of the sizing and the control of an energy storage system, because these two optimization problems are coupled.

Diplomová práce shrnuje nejdůležitější informace o letectví, jako například základní používané termíny, popis letových fází apod. V této práci je popsán flight management system, jeho funkce a schopnosti vytvořit cenově příznivý a současně absolutně spolehlivý letový plán. V další části práce je nastíněna důležitost předpovědi počasí pro bezpečnou a současně cenově příznivou leteckou dopravu. Tato práce je vytvořena v programu Matlab a všechny bloky jsou naprogramovány jako m-funkce. Důležité části kódu jsou z důvodu názornosti zobrazeny jako vývojové diagramy. Praktická část práce je rozdělena do několika podkapitol, kde každá podkapitola popisuje jeden blok z blokového schématu pro výpočet nejistoty odhadované doby příletu. Současně je zde vysvětlena funkce ostatních bloků pro plánování letu, předpověď počasí, kombinování větrů a výpočet odhadnuté doby příletu a její nejistoty.