Dissertation/Thesis Abstract

A Model Predictive Control Approach to Economic Scheduling for a Building Microgrid
by Sanchez, Edward, M.S., California State University, Long Beach, 2018, 106; 10784182
Abstract (Summary)

This thesis presents a model predictive control (MPC) approach to economic scheduling for a building microgrid at California State University, Long Beach. First, components of the microgrid relevant to operational costs are modeled. Next, a peak demand cost model to extend MPC-based microgrid energy scheduling is proposed. The corresponding objective function is then formulated as a mixed-integer linear programming (MILP) problem. The MPC framework is implemented onto MILP optimization to construct MPC-MILP, which is formulated to compensate for uncertainties in day-ahead demand, photovoltaic (PV) power forecasts and system modeling. Next, the forecast modeling for demand and PV power to improve the accuracy of MPC-MILP is provided. The simulation results show that the MPC-MILP optimization approach provides superior cost minimization over other strategies such as MILP, which controls the microgrid subject to only one calculation using day-ahead forecasts.

Indexing (document details)
Advisor: Nazari, Masoud H.
Commitee: Mozumdar, Mohammad, Yeh, Hen-Geul (Henry)
School: California State University, Long Beach
Department: Electrical Engineering
School Location: United States -- California
Source: MAI 58/01M(E), Masters Abstracts International
Subjects: Electrical engineering
Keywords: Energy management systems, Microgrids, Mixed integer linear programming, Model predictive control
Publication Number: 10784182
ISBN: 978-0-438-20899-5
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