Large-scale simulation-based parametric analysis of an optimal precooling strategy for demand flexibility in a commercial office building

Grid -interactive efficient buildings (GEBs) optimize their operations by using flexible load techniques, such as precooling, to reduce peak electricity demand. However, precooling effectiveness depends on factors like building properties, weather, and utility rates. Therefore, investigating the impacts of these condition -specific factors is crucial, especially when considering precooling strategies that utilize thermal mass in commercial buildings. In this paper, we first devised a novel heuristic control approach that incorporates parameterized optimal precooling thermostat schedules to enhance demand flexibility in a commercial office building. Subsequently, we conducted a thorough performance evaluation of this control strategy. Utilizing the DOE medium-sized office building as the virtual testbed, we showed that the parameterized schedule effectively approximates model predictive control and requires drastically reduced computational overhead. On top of that, we investigated the impact of building thermal mass, outdoor air conditions, and energy price profiles on the optimal precooling strategy. Our results show substantial cost savings and peak load reduction potential in buildings with heavy thermal mass, with some energy penalty. Although the potential for cost savings is lower in buildings with low and medium thermal mass, the energy penalty remains consistent in all three thermal mass scenarios. Furthermore, the results highlight that while outdoor air conditions play a role in cost and energy performance, the cooling load exerts a more immediate and substantial influence on cost savings in precooling strategies. In addition, the duration of peak pricing and the ratio between peak and off-peak times exhibit clear correlations with cost savings, peak load reduction, and energy consumption, aligning with intuitive expectations. These findings offer valuable insights for optimizing precooling strategies in office buildings.