This paper evaluates the impact of modeling accuracy on the model-based closed-loop predictive optimal control of both passive building thermal capacitance and active thermal energy storage (TES) systems to minimize utility cost. The following guidelines have been derived: for an internal heat gain-dominated commercial building, the deviation of building geometry and zoning from the reference building only marginally affects the optimal control strategy; reasonable simplifications are acceptable without loss of cost savings potential. Building construction characteristics determine the building passive thermal storage capacity. Zone temperature setpoints are affected more than TES operation by this construction mismatch, and a loss of cost savings potential is found in some cases. It is advisable to make sure the construction material is well modeled. Zone temperature setpoint profiles and TES performance are strongly affected by mismatches in internal heat gains, especially when they are underestimated. Since they are a key factor determining the building cooling load, efforts should be invested to keep the internal gain mismatch as small as possible. Efficiencies of the building energy systems have no direct impact on building cooling load, but they affect both zone temperature setpoints and active TES operation because of the coupling of the base chiller and the TES chiller. Relative efficiencies of the base and TES chillers will determine the balance of operation of the two chillers. Mismatch in this category may be significant. To avoid critical modeling mismatch, system identification techniques may be useful in improving the modeling process.

Units: SI