Autonomous observer of hydrogen storage to enhance a model predictive control structure for building microgrids

Hydrogen energy storage has emerged as a promising technology to improve the integration of renewable sources in building microgrids. However, inaccuracies modelling fuel cells and electrolysers reduce performance microgrids' management system. To flexibility microgrids, this paper proposes associate two-level hierarchical model predictive controller empowered with an Autonomous Observer Storage (AOHS). This novel observer evaluates hydrogen production consumption rates, storing little past data needing no tuning parameters. Relying only on instantaneous measurement, algorithm can estimate tank's level average relative error inferior 2 %, even under measurement noise. A case-study based microgrid currently construction serves basis for all simulations. The AOHS is evaluated by comparing self-consumption rates when governed system: one using fixed parameters other equipped proposed algorithm. Results show that associated better compared parameters, well robustness regarding noise error. Furthermore, demonstrates planning function it facilitates from aggregator's point view external grid management.