11:45 - 12:20 | Wed 24 Apr | Fauna | WeS2
09:00 - 10:20 | Thu 25 Apr | Hallway | ThSS
This study presents a Filtered Model-based Predictive Control method for the Fault- Tolerant Energy Management of a sugarcane microgrid; such plant has several renewable sources (solar, wind and biomass power), being subject to different operational constraints and load demands. The proposed control policy ensures that these demands are met at every iteration, despite the presence of faults, coordinating which energy source to use, maximizing the use the renewables according to contract rules. The proposed predictive controller is synthesized with a fault-free model of the plant and coupled with a feedback low-pass Linear Parameter Varying (LPV) filter that is scheduled according to the level of faults detected upon the system. Such system is compared to a standard predictive controller, displaying much improved behavior.
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