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In this paper, a two-stage cost and energy efficient HVAC load control strategy under a dynamic price setting is developed and proposed for residential buildings. In the first stage, the proposed model generates efficient mappings between electricity price ranges and temperature set points for all hours of the day within a predetermined thermal comfort interval. The second stage further improves the cost and energy efficiency by employing pre-cooling and pre-floating procedures between two consecutive time intervals with price changes based on a thermal transition formula. The proposed model incorporates consumer utility for thermal comfort using a tolerance index that basically measures the consumer's preference trade-off between cost savings and thermal comfort. The proposed model is illustrated using a numerical analysis based on real-life data. The results indicate that the proposed strategy can provide a better overall comfort while reducing the electricity cost to consumers and energy usage at peaks.