The deployment of Demand Response in private households poses complex issues in terms of fulfilling both restrictions of the grid and flexibility constraints of the households. Researchers at Fraunhofer IWES have developed stochastic optimizations based on probabilistic forecasts, which consider these restrictions. This innovative optimization approach is implemented in the virtual power plant from Fraunhofer IWES (IWES.vpp) used in SEMIAH.
Flexibility levels ensured
In SEMIAH, households that enable an appliance to operate in “Demand Response mode” offer a particular level of flexibility towards the grid. Moreover, the households allow the SEMIAH back-end system based on IWES.vpp to take control over and schedule the run of the appliance. To ensure that the level of flexibility offered by the households are fully utilized, schedules are generated based on probabilistic flexibility forecasts. In addition, restrictions from DSOs are taken into account.
Another issue arises from the ability of the households to shift between modes in real time. With this ability, there is a need for the optimization to occur continuously and to satisfy both the flexibility constraints of the households and the needs or offers of the DSOs in real time. To solve this issue combined with the enclosed uncertainty of consumption and generation forecasts, a stochastic optimization method based on probabilistic flexibility forecast is used in SEMIAH.
Learn more about the back-end system of SEMIAH here