Semi-Automatic Classification of Weather Maps

In this paper we analyze weather maps to distinguish between the three main circulation forms which are essential factors for weather composition and are fundamental for weather forecasters. We propose a set of features specifically tailored for the classification of these circulation forms in General Weather Situations and use these to train a support vector machine for classification. Additionally, we propose a semi-automatic algorithm to extract the necessary data directly from the weather maps itself. This enables us to also analyze historic map material for which the original data is not available anymore. In order to reconstruct the weather data, we extract and analyze the isolines from the weather maps based on color and line thickness as well as symbolic and numerical features using template matching techniques. We reconstruct the dense wind alignment field and air velocity field from these sparse data and extract expressive feature vectors to classify the presented main circulation forms. Our algorithm shows an overall classification success rate of 61% for the three main circulation forms zonal, meridional and mixed

Globale Optimierung netzgekoppelter PV-Batteriesysteme unter besonderer Berücksichtigung der Batteriealterung

Within this work a simulation based tool for design optimization of PV battery systems is developed. The component models of the power electronic converters, the PV generator and the household electric load are implemented. Special attention has been paid to the model implementation of the lithium ion battery, which is based on intensive laboratory measurements. The single component models have been assembled to form an overall system model. This allows for a detailed analysis of the system states as well as of characteristic values like self-consumption and self-sufficiency. Finally the simulation model has been integrated into an optimization framework, using a genetic algorithm. Based on exemplary scenarios it is demonstrated how the tool can be used to support the design process of PV battery systems

Photovoltaic Self-consumption in Germany : Using Lithium-ion storage to Increase Self-Consumed Photovoltaic Energy

The new German Renewable Energy Sources Act (EEG) for the year 2009 provides a new tariff option: self-consumption (EEG §33,2). By economically favouring the local consumption of PV energy, the EEG incentivises the owners of PV systems to either shift their consumption to the time of production by load management or use storage options. Massive deployment of such energy management approaches may reduce the impact of PV energy in the grid and thus pave the way for a further rise of the number of installations. For maximizing locally consumed PV energy, a storage system based on lithium-ion batteries is developed in the French-German project Sol-ion. Fraunhofer IWES, INES, ISEA and ZSW developed models to analyse the energy flows in residential PV-battery systems installed in Germany and in France. The models are used to calculate the increase of PV self-consumption. Energy flow simulations show that PV battery systems as developed in the Sol-ion project increase the local consumption of PV energy at the point of common coupling without constraining the user in his consumption habits. Target battery costs were calculated in an economical assessment. The installation of a Sol-ion system will become economically interesting with specific battery costs below 350 €/kWh as expected by the manufacturers in the medium term. The integration of additional functionalities (e.g. backup power and grid support) can improve the benefit of the Sol-ion system significantly