A demand side management (DSM) scheme is proposed in this work to schedule Heating, Ventilating, and Air Conditioning (HVAC) loads, using forward dynamic programming in order to maintain consumer's thermal comfort while avoiding demand peaks at the distribution transformer. The motivation is to analyze the impact of different control signal frequencies i.e. per 15, 30, 45 and 60 minute control, from both the utility and consumer perspective. The analysis parameters are percentage reduction in peak demand, energy violation, number of violations, sustained duration of violation from utility perspective, and total deviation duration and sustained deviation duration from the preferred thermostat settings from consumer's perspective. The comparison of results is based upon permissible limits of temperature drift for each frequency as mentioned in ASHRAE 55 standards for thermal comfort. Since dynamic programming approach is used, the impact of number of states to be saved per stage is also analyzed. In an attempt to imitate a real system and test the algorithm, a simple intuition based household load profile model is first developed. The equivalent thermal parameter (ETP) model is used to for the HVAC system with its parameters tuned to reflect ideal conditions. The algorithm then utilizes day-ahead forecast of price and outdoor temperature data to solve the scheduling problem. The constraint signal for the distribution transformer serving a group of households is generated using transformer rating and price signal from the utility. The day-ahead forecast of price signal used is downloaded from ComEd, Illinois and both the price and weather data used are for the duration 123 days from May 1st to August 31st, 2012.