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Methodology to determine the impact of simplified building models on model-predictive-control morning start optimization performance

The current article introduces a method of quantifying the losses in a model predictive control scheme for morning start optimization by using a simplified statistical building model compared to a detailed engineering building model. A new concept of “emulated” model predictive control is introduced using a detailed EnergyPlus model as a baseline for expected savings to which the simplified model predictive control results can be compared. The examples provided with the methodology shows that the simplified model predictive control captures a minimum 84% of the savings that are achieved using the detailed emulated model predictive control, with a minimal increase in the number of thermal comfort violations when the building has not reached set-point during the occupied period. A comparison between different building types and climates is also conducted to determine the influence these have on simplified model predictive control performance. It shows that both climate and building type do influence the level of performance for the simplified modeling employed in the current article. Other areas for the application of emulated model predictive control are also introduced, such as evaluating objective functions and other model predictive control parameters (horizon length, timestep, etc.).