An analytical approach and a control strategy are proposed in Part I of this two-part paper for leveraging the aggregate demand of a population of Thermostatically-Controlled Loads (TCLs) to deliver contingency-type reserve capacity. Further, a metric is introduced to quantify the TCL users' comfort satisfaction in response to a control signal. In Part II, we address the validation of the concepts put forth in the first part of the paper. To do so, we develop an extensive set of case studies based upon a population of 10 000 electric water heaters (EWH). Here, a physically-based model is first derived for the calculation of EWHs on-time statistics. The model is then extended to calculate the probability of EWH users' comfort satisfaction. The analytical approach and control strategy presented in Part I are validated using the EWH model against Monte Carlo simulations. Further, the trade-off between demand response capacity and EWH users' comfort satisfaction is investigated.