Dynamic Energy Management Needs in Energy Efficient Buildings Imposed by Stochastic Solar Resources

Justin Hughes with adviser
A. Domínguez-García
Frequency regulation is becoming increasingly important with deeper penetration of variable generation resources. Flexible loads have been proposed as a low-cost provider of frequency regulation. For example, the flexibility of loads with inherent thermal energy storage resides in their ability to vary their electricity consumption without compromising their end function. In this context, the aggregate flexibility of a collection of diverse residential air-conditioning loads has previously been shown to be well modeled as a virtual battery using first principles load models. That analytical method will not scale to more complex flexible loads such as commercial HVAC systems. This work presents a method to identify virtual battery model parameters for these more complex flexible loads. The method extracts the parameters of the virtual battery model by stress-testing a detailed software model of the physical system. Synthetic examples have been used to develop an appropriate control strategy and determine appropriate test inputs to be used during the identification procedure. The University of Illinois Willard Airport was used as a case study. While performing the study, numerous improvements were made to the procedure to make it more robust to noisy or time-varying data and to make it applicable to a wider variety of loads including additional types of buildings, industrial processes, and electric vehicle charging. With these developments, the effectiveness of the proposed identification technique to real systems was verified. Figure 39 shows the 3D model on which the simulations were based. Figure 40

Figure 39: 3D model of the University of Illinois Willard Airport

Figure 39: 3D model of the University of Illinois Willard Airport

shows that the identified virtual battery models and the underlying building models give

Figure 40: Virtual battery models and underlying building models

Figure 40: Virtual battery models and underlying building models

nearly identical results when predicting how much regulation can be provided.
This work was supported in part by Stanford (GCEP) and the Power Systems Engineering Research Center (PSERC).