#5 use cases for a Digital Twin in existing heat networks

For heat network operators, the Hysopt software can be used to model the existing network and use this “digital twin” to optimise the network.
Ruben Vos - Hysopt

Ruben Vos

An article by Ruben Vos

The hysopt software is a science-based HVAC calculation and simulation tool, to optimise heating and cooling installations. Hysopt’s unique design and simulation software helps heat network developers to design, build and commission more efficient heat networks and assure that the asset they have invested in will perform “first time right”.


For heat network operators, the Hysopt software can be used to model the existing network and use this “digital twin” to optimise the network.

Use case 1: Network extensions

Use case 1: Network Extensions

Network extensions are an opportunity to connect additional load at the right conditions. Getting this wrong however, results in adopting bad loads. Certainly with new- build developments, this can be quite disastrous as loads are very low but high flow rates will constraint future extensions. Within this process, the Hysopt software can also be used to objectify discussions between the stakeholders of this extension in terms of the real performance and behaviour of the design on the table.

Use case 2: Optimising critical loads

Use case 2: Optimising critical loads

Increased return temperatures are often originating already at the building installation, outside the scope of the heat network. Inefficient building installations will incur additional costs to both the building owner and for heat network operators. Specifically for anchor loads with poor return temperatures, it might be very interesting to reach out to these building owners to optimise the building installation. The Hysopt software can be used to optimise this installation for lower return temperatures and decreased capacity. Simulating the before and after, the Hysopt software can then be used to objectively quantify the impact on the performance on both installations and be used to work out a commercial position.

Use case 3: Decarbonisation

Most existing heat network still heavily rely on fossil fuels, producing heat at high temperatures. As a result, these heat networks have typically been designed for these temperatures. Most renewable heat sources however are available at lower temperatures and are brought to adequate temperature levels, with heat pumps doing most of the heavy lifting. There is a big challenge to drive down temperatures to adopt these low temperature heat sources. And in contrast to fossil fueled heat, renewable heat is often available much more decentralised. Being able to simulate how all these available heat sources can be integrated in a near or far feature as a pathway to reach net-zero is very powerful to assess how future-proof your asset is and to quantify upcoming investments.

Use case 4: Capacity constraints

Heat networks grow organically and the initial network layout design can almost never anticipate the exact development of it for the upcoming decades. Naturally, constraints will appear when growing the network and resolving them is very capital-intensive. Assessing capacity constraints typically very much relies on gut feel as well as static load calculations whilst this is a highly dynamic challenge. The availability of a hydraulic model, loadmatched with operational data can give very valuable insight into the real capacity constraints. Knowing exactly what the constraints are and being able to model how this can be resolved without digging up the road or refusing additional load can save heat network operators significant amounts of avoidable costs.

Use case 5: Digitisation

A hydraulic digital twin of the installation is an asset on itself and is naturally part of a wider digitization of heat networks. It can also be used to soft-test other digital solutions like new control logics, using additional data points as an input to control the installation. But also for more advanced digital solutions like peak-shaving and dynamic load balancing. These so-called smart grid solutions can be soft-tested in the digital twin to evaluate what the impact on the network and the building would be and how to deploy them best. Doing this extra due diligence provides more certainty within the business model of such expensive investments.

Use case 5: Digitisation

Some reflections

These are but five of the many use cases for a digital twin in existing heat networks. It all starts with a good hydraulic model which accurately represents your network such that it can acts as its digital twin. This digital twin can then be used for all sorts of analysis, whether that is to unlock an immediate operational saving or to fast-forward to 2050 to find out if there is a future at all for this heat network in a fossil-free world. We hope there is and would love to help you prepare for that future.

Please reach out to us for more information. We are happy to explore how a digital twin can deliver value to your heat network.

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