Electric utility companies (EUCs) play an intermediary role of retailers between wholesale market and end-users, maximizing their profits. Retail pricing can be well deployed with the support of EUCs to promote demand response (DR) programs for heating, ventilating, and air-conditioning (HVAC) systems in commercial buildings. This paper proposes a pricing strategy to help EUCs and building operators achieve an optimal DR of price-elastic HVAC systems, considering peak load reduction. The proposed strategy is implemented by adopting a bi-level decision model. The nonlinear thermal response of an experimental building room is modeled using piecewise linear equations, which helps convert the bi-level model to the single-level model. The pricing strategy is implemented considering a time-of-use (TOU) pricing scheme, leading to low price volatility. Case studies are conducted for two types of load curves and the results demonstrate that the proposed strategy helps EUC promote the price-based DR of the commercial buildings for conventional load curves. However, EUC cannot reduce the peak load on duck curve caused by the large introduction of photovoltaic generators, even with price-sensitive HVAC systems in commercial building. This will be addressed in future studies by inducing DR participation of HVAC systems in residential buildings.

This paper presents a new method on fault distribution modeling for stochastic prediction study of voltage sags in the distribution system. Two-dimensional stochastic models for fault modeling make it possible to obtain the fault performance for the whole system of interest, which helps obtaining not only sag performance at individual locations but also system sag performance through system indices of voltage sag. By using bivariate normal distribution for fault distribution modeling, the paper estimates the influence of model parameters on system voltage sag performance. The paper also develops the modified SARFI X regarding phase loads that creates better estimation for voltage sag performance for distribution system.Index Terms--distribution system, power quality, voltage sag frequency, stochastic prediction, fault distribution modeling, bivariate normal distribution, phase loads.