Temperature control is a widely researched topic and a common application is in heating systems such as buildings. A temperature control method that is central in ensuring comfort and reduction of energy consumption in modern buildings and other heating systems is based on model predictive control (MPC). Traditionally, the MPC optimal control problem is to track a target, but there are other examples of optimization problems besides tracking problems and one such optimization problem is the economical optimization problem, an optimization based on economical objectives. A heating system with electrical supply may be controlled by an economic MPC such that the economical objective is to consider time-varying prices of electricity.  This thesis studies how time-varying prices of electricity can be utilized as an economical objective in an economical MPC to reduce electricity costs for a double-heater system. This is done using an available model of the double-heater system and an MPC to construct an economical MPC. The performance of the economical MPC is then investigated and compared to the existing MPC.  In the thesis it is found, through a test with six different cost profiles and a test with historical data of forecasts of electricity prices, that the economical MPC can reduce total electricity costs when compared to the existing MPC. Furthermore it is found that the performance of the economic MPC is acceptable when it is compared with and without prediction of setpoint changes, prediction of price changes and an isolating layer between the heaters. The thesis concludes that satisfactory results are attained, as the economical MPC leads to decreased total electricity costs for the double-heater system and notes that the economic MPC is versatile by accepting both user-defined and historical cost profiles.