Using Probabilistic Forecasts in Stochastic Optimization

Stochastic Nonlinear Model Predictive Control for a Switched Photovoltaic Battery System

“…In this, optimization-based and especially stochastic MPC approaches perform better than heuristics. This has been shown in previous publications [18], [19] for a setup with a feed-in limit. These results can be observed with the switched system as well.…”

“…Therein, the parameter τ ∈ [0, 1] holds information on how much a current state is valued as a short-term forecast over the external information. The parameter σ > 0 denotes the uncertainty of the external model and can be determined from probabilistic forecasts as described in [19].…”

“…The value for σ was obtained from forecast uncertainty of the PV forecast and previous errors of the load forecast using a method presented in [19]. Subsequently, the parameter R was determined corresponding to the expected standard deviation of model ( 14) to be…”

“…Here, the complexity of the system modeling is reduced to linear approximations to allow for a consideration of forecast uncertainties. In previous publications [18], [19], we have combined a nonlinear efficiency modeling with a stochastic forecast albeit without a discrete switched state of the system. Both, mitigating forecast uncertainty and increasing overall efficiency of battery usage have implications This work is licensed under a Creative Commons Attribution 4.0 License.…”