Quantifying cumulative effects of stochastic forecast errors of renewable energy generation on energy storage SOC and application of Hybrid-MPC approach to microgrid

Abstract Energy storage system (ESS) is crucial for microgrid to mitigate adverse impacts of renewable energy generation by participating in primary frequency regulation. In previous studies, research on evaluating the cumulative impacts of stochastic forecast errors (SFE) of renewable energy generation on the variance of SOC (state of charge) of ESS is lacking. This paper presents quantification models of the impacts of SFE on the variance of SOC of ESS. Novel SFE propagation and accumulation models are introduced. The effects of dispatch control and droop control on ESS at different time scales are comprehensively considered. The mechanism of ESS working from a stable state to an unstable state owing to SOC deviation is demonstrated. Then aiming at solving the problem that ESS is forced to quit operation owing to SOC deviation, an online hybrid model predictive control (Hybrid-MPC) based strategy is proposed. Hybrid-MPC consists of two hierarchies: one is decreasing horizon rolling optimization which is specially for handling small SFE and the other is heuristic cooperative control which is designed to tackle large SFE. Besides, feedback correction is applied to change the real-time operation status of microgrid in time. Finally, the strategy is tested in a self-developed program named microgrid real operation simulation (MG-ROS).