Presentation at the IRES 2017, March 2017
Due to high feed-in tariffs in the past, residential PV systems are widespread in Germany. Recent reductions of these tariffs, as well as the temporal limitation of EEG funding, lead to a decline of the profitability of such systems. Self-consumption of the generated solar energy can help to maintain or increase this profitability. Besides demand side management measures, the market availability of residential battery storage systems allows to increase the amount of self-consumed energy.
A simulation of the interaction of PV generation, energy consumption and the potential battery system can support the purchase decision. It can be used to evaluate the effect of additional storage for different battery types and sizes and therefore determine the optimal configuration for a specific customer. In order to achieve this, measured consumption data of this customer is necessary. In case of available smart meters, this data can be easily acquired. Otherwise, measurements over a short period of time, i. e. some weeks, can be extrapolated to approximate the yearly consumption profile. Simulation of expected PV generation is another important component. Due to power limitations of the batteries, small deviations of the generation profile can already cause wrong results.
The presented simulation tool combines these components in a usable and applicable way. Validation computations show that simulations based on measured individual consumption data lead to far more reliable results than use of generic load profiles. PV generation and battery properties can be simulated with sufficient accuracy, while maintaining low execution time of the tool. This allows for easy and fast application for and by customers which aim to buy an accompanying battery system for their PV plant.