HOT|COOL NO. 3/2019 - "Big Markets: China and Poland


A general challenge with model-based approaches is their reliance on quality input data, or as the computer science saying goes: “Garbage in, garbage out”. Equally important to the quality of the data is the ability to effectively implement the output from the model. It is therefore clear that for enabling efficient digital solutions then high-quality control components need to be installed in the system. An example of a smart enabling component is the smart and high-accuracy actuator NovoCon, see Figure 6. To facilitate smart control the actuator can be used not only for regulating the flow, but also to supply flow estimates and to collect and forward signals to and from external sensors or devices. In a combination with a well- defined pressure independent valve it can act precisely on the outputs from the smart controller and significantly improve the quality of the input data.

Danfoss Leanheat is an example of how digitalization can pave the way for utilities to advance their business model. The solution applies Artificial Intelligence to automatically and continuously optimize the substation control parameters to ensure stable and desired room temperatures within the building, see Figure 4. The approach is a perfect fit to the fixed payment based Chinese district heating system, where the aim is to supply the residents enough heat to achieve indoor temperature within the interval of 18-20°C. The solution is running in multiple pilot installations in China, with energy savings exceeding 20% being documented.

Figure 4. The move from manual configuration to automatic configuration of parameters.

In an addition to optimizing the substation control parameters the solution learns the thermodynamic behavior of the building and can utilize that information to efficiently shift the building heat demand from peak demand periods with either pre- heating of the building or cooling the building within a pre- defined building comfort temperature level. Up to 9 % daily peak load reduction has e.g been demonstrated in multiple buildings in Copenhagen, see Figure 5.

Figure 6. NovaCon® actuator mounted on an AB-QM control valve.

CONCLUSION The development dynamics of the Chinese district heating systems is changing, going from rapid expansion towards more streamlined and energy efficient operation. The modernization process is inspired by the enormous energy savings that have been realized when European DH system went through similar process. The rapidly advancing digital technology will however give opportunities for the Chinese district heating sector to incorporate smart functionality into the new and modernized system structure. To be efficient and able to achieve maximum energy savings the digital solutions however must rely on high quality and reliable components.

For further information please contact: Oddgeir Gudmundsson,

Figure 5. Load shifting in Copenhagen multi-apartment buildings using Leanheat.

A further logical step in fixed payment markets like China would be to apply the Artificial Intelligence to the flat level, where each flat is controlled to achieve and maintain a desired temperature. This kind of a business model would build on the accepted payment structure and motivate the heat provider to implement energy efficient components. A centrally operated flat control would further maximize the system supply and demand flexibility, leading towards lower cost and reduced emissions.

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