Demand-Side Flexibility through Real-Time Control of Heating Systems using Digital Twin

In the scope of energy transition, the increasing penetration of intermittent renewable energy generation has put the electrical system against a great challenge: real-time power balance between supply and demand. In this context, heating systems stand out as one of the most decisive controllable loads in commercial buildings and residential households. Managing peak load consumption by controlling electric heaters has excellent potential in demand-side management. This paper presents a method to reduce peak load consumption using a fuzzy-logic-based real-time control of heating systems while minimizing the rebound effect. The proposed solution is evaluated based on a digital twin of a real low-voltage distribution network containing 50 houses under different conditions of desired power exchange. This technique falls within the framework of the smart grid concept in order to make load consumption more active and intelligent, thereby increasing flexibility on the demand side.