How to reduce peak boiler usage with a real-time Digital Twin Platform

3 min read

Many district heating companies use peak boilers to meet demand spikes. However, they are often placed across the entire network. Thus, when operated decentrally, it is difficult to understand when you need them and how you can reduce their use. Also, these boilers are often based on fossil fuels and hence are quite expensive and polluting.

Find out how you can get real insights into when the peak boilers are exactly needed and how to phase them out using a real-time Digital Twin Platform in this article.

Peak boilers are widely used in district heating

Most heating grids have multiple sources at different locations. There is a base load supply that has a lower CO2 intensity (e.g., geothermal, residual heat, etc.), and in addition, heat-only peak boilers are used to supplement that base load in times of high demand.  

Despite the fact that these boilers only supply a few percentages of the total grid demand, they are very expensive and pollutive as they are fossil-fueled – hence utilities and operators aim to reduce their use to save costs and CO2.  

Reducing the usage of peak boilers is a challenge 

Utilities and operators are aiming to use the peak boilers as little as possible through scheduling and experience. Nevertheless, the complexity of combining vast amounts of sensor data, travel time, and other grid dynamics makes optimisation of this very challenging. 

Since there is a large travel time of the hot water between supply and demand in these grids (typically it takes multiple hours), it is difficult to understand when you actually need peak boilers. 

Advanced forecasting by a real-time Digital Twin provides valuable insights 

A real-time Digital Twin provides a pipe-by-pipe model supplemented with real-time-series data (smart meters, source sensors, etc.) indicating where and how demand will occur. This full grid model makes it also visible how the heat travels through the network, and when the heat is consumed over time. This makes it possible to forecast with high granularity where to produce heat in the next hours and days.    

This way, the Digital Twin comes up with smarter alternatives for the peak boilers; for instance, by initiating the base load power earlier or for longer to cover the forecasted peak demand.

As a result of this integration, less CO2 will be emitted and the costs for heat production will be lower.

The benefits of a real-time Digital Twin for one of our clients

  • Significant CO2 reduction - for one of our clients it turned out to be a saving of 500+ tons per month.

  • Significant reduction of production costs and reduced heat losses.

  • Insight into network dynamics directly applicable to the operation.

  • The starting point to automate the control of the peak sources.

Would you like to know more?

To learn more about how our real-time Digital Twin Platform can help optimise, decarbonise, and grow your district heating grid, visit the Digital Twin page.

We've successfully applied our Digital Twin and its 6 modules to heating grids across Europe, amongst others Wien Energie GmbHE.ON, and Eneco - read more about it in Customer Stories.

Our real-time Digital Twin platform puts you in control with six solutions that matter. Check all six of them, including temperature and pressure control, in the Solutions Overview.

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