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Robust rapid prototyping system for model predictive control of single zone residential buildings
Harris, Maxwell Thomas
Harris, Maxwell Thomas
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2016
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2017-07-17
Abstract
Buildings in the United States are responsible for around 75% of total electric energy usage. Advanced controls are one way to minimize the energy use and cost; however, they require co-simulation platforms to study the effects on buildings and occupants. This thesis develops a platform to simulate advanced air conditioning controllers using model predictive controls (MPCs). MPCs require the use of co-simulation software which includes building energy simulation (EnergyPlus), optimization (AMPL), and MATLAB software used for simulation and investigation. MPCs require fast energy models as MPCs might require thousands of iterations to find an optimal solution. Thus, the platform uses an autoregressive statistical reduced order model (ROM) that quickly predicts building cooling energy use. Nine case studies test the newly developed platform with a residential building in Austin, Texas, under three different variable electric rates, along with three baseline temperature controllers. Results show that the developed MPC can save upwards of 29% energy while, at the same time, reducing cost by upwards of 45%.
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