A Model Predictive Control Approach to Microgrid Operation Optimization
Alessandra Parisioa b, Evangelos Rikosc, Luigi Glielmod
- aACCESS Linnaeus Center and the Automatic Control Laboratory, School of Electrical Engineering, KTH Royal Institute of Technology, Stockholm, Sweden
- b[ACCESS Linnaeus Center and the Automatic Control Laboratory, School of Electrical Engineering, KTH Royal Institute of Technology, Stockholm, Sweden]
- cDepartment of PVs and DER systems, Center for Renewable Energy Sources and Saving, Athens, Greece
- dDepartment of Engineering, Universitàdegli Studi del Sannio, Benevento, Italy
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Abstract
Microgrids are subsystems of the distribution grid, which comprises generation capacities, storage devices, and controllable loads, operating as a single controllable system either connected or isolated from the utility grid. In this paper, we present a study on applying a model predictive control approach to the problem of efficiently optimizing microgrid operations while satisfying a time-varying request and operation constraints. The overall problem is formulated using mixed-integer linear programming (MILP), which can be solved in an efficient way by using commercial solvers without resorting to complex heuristics or decompositions techniques. Then, the MILP formulation leads to significant improvements in solution quality and computational burden. A case study of a microgrid is employed to assess the performance of the online optimization-based control strategy and the simulation results are discussed. The method is applied to an experimental microgrid located in Athens, Greece. The experimental results show the feasibility and the effectiveness of the proposed approach.