The goal of my study is to quantify the flexibility of electrical heat supply in German households as a function of the various influencing factors like outside temperature, building insulation, heating technologies used and comfort level of the residents. For achieving this aim a model of a single building and of a residential area will be set up. This flexibility – together with data-driven supply forecasts – will be used to react to times when an oversupply of power produced by the volatile renewable energy sources is observable in the grid. By doing so we can estimate how much flexibility is necessary in order to avoid oversupply in certain areas in Germany (e.g. Schleswig-Holstein). Moreover, we aim to calculate the required macroeconomic investments to avoid excess energy in Germany by using different power-to-heat-systems. Those numbers will then be compared to the ones of other flexibility options like electric vehicles or batteries.
- Operations Research and Optimisation
- Energy System Analysis
- Application of Data Mining and Machine Learning