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This paper presents a Model Predictive Controller (MPC) for electrical heaters' predictive power consumption including maximizing the use of local generation (e.g. solar power) in an intelligent building. The MPC is based on dynamic power price and weather forecast, considering users' comfort settings to meet an optimization objective such as minimum cost and minimum reference temperature error. It demonstrates that this MPC strategy can realize load shifting, and maximize the PV self-consumption in the residential sector. With this demand side control study, it is expected that MPC strategy for Active Demand Side Management (ADSM) can dramatically save energy and improve grid reliability, when there is a high penetration of Renewable Energy Sources (RESs) in the power system.