?url_ver=Z39.88-2004&rft_val_fmt=info%3Aofi%2Ffmt%3Akev%3Amtx%3Adc&rft.title=Learning-based+MPC+with+uncertainty+estimation+for+resilient+microgrid+energy+management&rft.creator=Casagrande%2C+V&rft.creator=Ferianc%2C+M&rft.creator=Rodrigues%2C+M&rft.creator=Boem%2C+F&rft.description=To+enhance+fault+resilience+in+microgrid+systems+at+the+energy+management+level%2C+this+paper+introduces+a+novel+proactive+scheduling+algorithm%2C+based+on+uncertainty+modelling+thanks+to+a+specifically+designed+neural+network.+The+algorithm+is+trained+and+deployed+online+and+it+estimates+uncertainties+in+predicting+future+load+demands+and+other+relevant+profiles.+We+integrate+the+novel+learning+algorithm+with+a+stochastic+model+predictive+control%2C+enabling+the+microgrid+to+store+sufficient+energy+to+adaptively+deal+with+possible+faults.+Experimental+results+show+that+a+reliable+estimation+of+the+unknown+profiles'+mean+and+variance+is+obtained%2C+improving+the+robustness+of+proactive+scheduling+strategies+against+uncertainties.&rft.subject=Energy+Management+Systems%2C+Microgrid%2C+Model+Predictive+Control%2C+Online%0D%0ALearning%2C+Uncertainty+Estimation&rft.publisher=Elsevier+BV&rft.date=2024&rft.type=Proceedings+paper&rft.language=eng&rft.source=+++++In%3A++IFAC-PapersOnLine.++(pp.+pp.+556-561).++Elsevier+BV+(2024)+++++&rft.format=text&rft.identifier=https%3A%2F%2Fdiscovery.ucl.ac.uk%2Fid%2Feprint%2F10197014%2F2%2FCasagrande_1-s2.0-S2405896324003616-main.pdf&rft.identifier=https%3A%2F%2Fdiscovery.ucl.ac.uk%2Fid%2Feprint%2F10197014%2F&rft.rights=open