Fault-tolerant energy management for an industrial microgrid: A compact optimization method

• Published in: International journal of electrical power & energy systems Vol. 124; p. 106342
• Main Authors: Bernardi, Emanuel, Morato, Marcelo M., Mendes, Paulo R.C., Normey-Rico, Julio E., Adam, Eduardo J.
• Format: Journal Article
• Language: English
• Published: Elsevier Ltd 01.01.2021
• Subjects: Fault estimation; Fault tolerant control; Microgrid; Model predictive control; Moving horizon estimation; Model predictive control; Fault estimation; Microgrid; Moving horizon estimation; Fault tolerant control
• ISSN: 0142-0615; 1879-3517
• DOI: 10.1016/j.ijepes.2020.106342

•A Moving Horizon Fault Estimation method is proposed for renewable microgrids.•A Fault Tolerant Model Predictive Control is proposed as an Energy Management System.•A fault reconfiguration mechanism coordinates both QPs.•Realistic numerical simulation scenarios are presented, showing the effectiveness of the method. This work presents an optimization-based control method for the fault-tolerant energy management task of an industrial energy microgrid, based on a sugarcane power plant. The studied microgrid has several renewable energy sources, such as photovoltaic panels, wind turbines and biomass power generation, being subject to different operational constraints and load demands. The proposed management policy guarantees that these demands are met at every sampling instant, despite eventual faults. This law is derived from the solution of an optimization problem that combines the formalism of a Moving Horizon Estimation (MHE) scheme (to estimate faults) and a Model Predictive Control (MPC) loop (for fault-tolerant control goals); it chooses which energy source to use, seeking maximal profit and increased sustainability. The predictive controller part of the scheme is based on a linear time-varying model of the process, which is scheduled with respect to the fault estimation brought up by the MHE. Via numerical simulations, it is demonstrated that the proposed method, when compared to other MPC strategies, exhibits enhanced performances.