Robust Multi-Objective Model Predictive Control for PV–BESS Energy Scheduling Under Uncertainty

Abstract

In order to solve problems in modern grids caused by the increasing use of renewable energy sources, ESSs (Energy Storage Systems) are being investigated.To ensure that ESS offers maximum benefits, integration of ESS should be complemented with an ideal energy management system. When utilized with PV systems, conventional battery energy management maximizes self-consumption but ignores degradation of batteries and grid congestion. MPC (Model predictive control) maximizes self-consumption while reducing congestion and degradation. Therefore, utilizing simulations of one-year system behavior, studies will be conducted in this research to demonstrate the advantages of MPC-based energy management over traditional methods.Since MPC adopts decisions based on prediction data, the impact of prediction uncertainties will be evaluated, and a proposal for tightening constraints to address them will be made.It has been found that MPC improves system behavior across a number of performance metrics.