Improving energy efficiency in residential space heating has a key role to play for achieving the goal of carbon-neutrality. Condensing boilers for providing heating can achieve significantly higher efficiency than conventional ones due to possibility to recover latent heat of vaporization from the flue gas. But it can be achieved when return temperature of heating system is sufficiently low (below the dew temperature of the flue gas), which directly depends on real thermal modes of the heating system. So, development of methods and tools that can use data under real operating conditions and have possibilities to find the most efficient modes is crucial for improving performance of such system. Implementation of these methods should be based on mathematical modeling or simulation. The model should be automatically fitted to current measurements. The paper presents development of a digital twin-based smart heating system, which includes a condensing boiler. The proposed framework of a digital twin (DT) takes advantage of the latest technologies in information technology, which could be applied for real-time information interchange between the physical system and its virtual copy to achieve energy efficient operation modes. A methodology and a user-friendly interface, which are easy to use and navigate, have been developed for estimation of energy efficient solutions in the studied system. It has been demonstrated that the biggest increase in boiler efficiency (by 6.6 %) can be achieved by switching to low-temperature heating systems. Applying intermittent heating is in second place in terms of the possibility of increasing boiler efficiency (up to 1.5 %).
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