<p>Nowadays, methods of intelligent management of electricity consumption remain a key issue due to, among other things, the variable, almost unpredictable performance of solar and wind power generators and the varying load levels on electric lines demanded by end users. It is becoming necessary to minimize the cost of consumed electricity. Fuzzy control can be one of the solutions to the aforementioned challenge. This paper presents simulation results of applying fuzzy sets to control the electric heater of a water tank according to daily changes in the price of electricity and the variable heat load of the water system. The presented concept provides economic savings, optimization of the use of renewable energy during periods of overproduction, and thermal comfort for users. This type of control can be easily implemented into smart electric heater modules and can provide a more sustainable use of electricity, determined by current production and demand levels. This can be an excellent extension of the functionality of Internet of Things heating devices. The effectiveness of the method has been tested with a number of simulations, and the statistical effects are described and discussed. Overall, this fuzzy control technique achieves about 15% savings per month with typical hour-by-hour changes in electricity prices. The solution can be easily customized to meet the smart power requirements of various non-critical electrical devices.</p>