GAVE – Municipality Großschönau as virtual Energy Storage

GAVEFor the first time in Austria , GAVE analyzes the effectiveness and user acceptance of automated electrical load management in Austria. Private, public and commercial electricity customers in a municipality in Lower Austria are equipped with appropriate technology and participate in an experiment. The goal is to show that effective load management and cost savings are possible without restricting user comfort.

The GAVE project deals with the user acceptance and implementation of technologies for consumer energy management (demand side management, demand response, load management). This technology can be regarded as one of the key instruments for intelligent power networks of the future. Demand side energy management is especially important because in the future the supply side energy management will not be so effective due to the increased penetration of renewable energy sources, which are more unreliable. In order to ensure the profitability of renewable energy sources it is vital to convert as much energy as possible into electric energy and feed it in the grid.

Demand side management affects the consumption side, and therefore the people. The control of power generation, although it leads to loss of earnings, it is still easily accomplished. In contrast, the control of electric power loads is much more complicated. During this process, the user is restricted in his free decision about the time, duration and sequence of his electrical consumption. This situation, which is generally not economically clear, is largely unexplored. There are very few findings on the user acceptance of automatic load balancing in Europe. Due to cultural dependencies of the effects strong regional differences are to be expected.

For this reason, the present project aims to find, for the first time, valid statements on the question of the feasibility of the implementation and the user acceptance for automated load management by means of a model region, the municipality of Grossschönau in Lower Austria. The electrical energy consumption of the municipality is modeled on the basis of measured data. Particularly accurate models are produced by sliding loads, such as water pumps, air conditioning systems, heat pumps and sewage sludge pumps. Some of the private, public and commercial electricity customers are equipped with sensors and actuators, which allow real load shifts to be carried out. Consumers participate in a community-wide experiment. Therefore, the processes are measured and the measured data are fed to a simulation. In a simulation environment, the load shifts, which is only implemented for a few consumer and afterwards are scaled to the entire municipality in order to obtain a statement about the effectiveness of the measures. The goal is to determine how much the load displacement potential of the municipality is, without the user comfort is significantly reduced. In the project, a “best practice” catalog is drawn up on how the integration of flexible loads is to be carried out optimally under the aspects of user comfort and user acceptance.



GAVE – Municipality Großschönau as virtual Energy Storage


About Lampros Fotiadis

Lampros Fotiadis MEng, MBA, was born in 1980 in Greece. His passion for engineering led him to receive his Engineer’s degree (MEng equivalent) from the Electrical and Computer Engineering school of the Aristotle University (Greece) in 2004. During his studies, he specialised in Electronics and Computer Engineering. In his diploma thesis, he simulated and implemented a multi-zone fuzzy-logic heating system using a real-time reconfigurable System-on-Chip. Pursuing a holistic approach to solving engineering problems, he successfully earned an MBA degree from the University of Macedonia (Greece) in 2006 and his master thesis examined the relation between European environmental policies and the European Energy market. He worked as an expert IT and Physical security consultant for more than 10 years and his expertise include system design and requirement analysis, system integration and product management. His recent areas of interests are Data Science, Machine Learning, Autonomous Driving and Smart Grids. Since February 2017 he is working as project member at the Institute of Computer Technology in the Energy&IT Group, where he is especially contributing know-how as IT and physical security consultant in the areas of smart grids and industry 4.0.
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