Candidate: Carlos Ceja Espinosa
Title: Energy Management Systems for Multi-Microgrid Networks Under Uncertainties
Date: May 15, 2023
Time: 3:00 PM
Place: EIT 3142
Supervisor(s): Canizares, Claudio - Pirnia, Mehrdad
Abstract:
Environmental concerns have motivated a gradual transformation of power systems in recent years, mainly focused on replacing fossil fuel-based energy sources with Renewable Energy Sources (RESs). Microgrids (MGs) are an attractive option to effectively integrate RESs into existing grids, which requires an Energy Management System (EMS) that considers the variability of demand and RESs to adequately dispatch the MG resources.
The coordinated operation of multiple MGs as a multi-microgrid (MMG) system has recently attracted attention due to the advantages of a distributed structure, and the benefits that originate from a coordinated operation, as opposed to the independent operation of each MG. The collective operation enables power exchanges among MGs and the main grid, which can mitigate the unpredictability of RESs and reduce the overall operational costs.
In this seminar, a centralized MMG EMS model will be presented, which minimizes the operational cost of all MGs while considering their interactions among each other and the main grid. A decomposition procedure is then applied to obtain subproblems corresponding to each MG, which can be solved independently using a distributed optimization algorithm, thus preserving the privacy of each MG.
Then, the proposed centralized MMG EMS model is reformulated using an Affine Arithmetic (AA) optimization framework to consider uncertainties associated with demand and renewable generation. The AA model is robust under a range of possible realizations of the uncertain parameters and can be solved with lower computational burden with respect to a Monte Carlo simulation approach, which is one the main advantages of the proposed AA model.