Stochastic Modelling and Simulation of Energy Flows for Residential Areas

Conference: VDE-Kongress 2014 - Smart Cities – Intelligente Lösungen für das Leben in der Zukunft
10/20/2014 - 10/21/2014 at Frankfurt am Main, Deutschland

Proceedings: VDE-Kongress 2014 – Smart Cities

Pages: 6Language: englishTyp: PDF

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Authors:
Fischer, David; Scherer, Johannes; Haertl, Andreas; Byskov Lindberg, Karen; Elci, Mehmet; Wille-Haussmann, Bernhard (Fraunhofer ISE, Freiburg, Deutschland)

Abstract:
With the introduction of on-site PV production, electric cars, and more energy efficient buildings, planning and operation of energy systems are becoming more challenging as the electricity flows both to and from each customer, acting as so-called prosumers. In this context, high resolution forecasting models for both on-site production, and energy loads of the buildings and electric cars are needed in order to ensure a reliable power supply and optimal utilisation of energy resources. When modelling load profiles, it is important to use consistent data which properly reflects the coupling of energy demands for electricity and heating. Additionally, the impact of user-behaviour of the residents, their electrical device stock, and the technical standard of the houses plays an important role. The method introduced is based on a stochastic bottom-up modelling approach, which has the advantage that the load profiles for each demand type can be explained, and the influence of different users, building characteristics and number of electric devices can be studied in detail. It is shown that the general characteristics as well as the annual energy demand and peak values of the model are in line with the values of the VDI standard reference load profiles for an individual building. The strengths of the model can be seen in the total load profile of an area as each household is modelled individually and through the stochastic feature of the model makes the total peak loads more realistic as compared to only aggregation of the reference load profile.