The increasing operational complexity of power systems considering the higher renewable energy penetration and changing load characteristics, together with the recent developments in the ICT field have led to more research and implementation efforts related to the activation of the demand side. In this manner, different direct load control (DLC) and indirect load control concepts have been developed and DLC strategies are considered as an effective tool for load serving entities (LSEs) with several real-world application examples. In this study, a new DLC strategy tailored for residential air-conditioners (ACs) participating in the day-ahead planning, based on offering energy credits to the enrolled end-users is proposed. The mentioned energy credits are then used by residential end-users to lower their energy procurement costs during peak-price periods. The strategy is formulated as a stochastic mixed-integer linear programming (MILP) model considering uncertainties related to weather conditions. The outcomes regarding the end-user comfort level and economic benefits are also analyzed.