Stochastic Nonlinear Model Predictive Control for a Switched Photovoltaic Battery System

Battery systems gain popularity among users in residential household setups. In this setup, currently the main source of profitability is to increase photovoltaic (PV) self-sufficiency which is highly dependent on the battery system efficiency. We present a control approach based on stochastic dynamic programming (SDP) suitable to increase the system efficiency. The optimization framework includes a switched system with standby losses, a nonlinear modeling of the converter losses as well as a stochastic forecast model for household load and PV generation. We show in a simulation of a typical benchmark case that our approach can in fact reduce overall system losses and costs of operation. Then, the applicability in a real-world scenario is shown using a commercially available battery system in a field test.