Two ways to manage complexity in a transforming heating system: Part 1
In this two-part series, we explore four best practices employed by Nordic district heating leaders to address the increasing complexity of district heating systems. This article emphasises the first two: staying in control of costs and the use of digital solutions for better system understanding.
District heating leaders are facing a new reality where fuel availability is unpredictable, prices are volatile, and the energy transition to green sources for decarbonisation is underway. Many respond to these challenges by betting on multiple fuels for resilience and incorporating more geographically distributed renewable sources to decarbonise their production.
As a result, the operating complexity of heating systems is bound to increase. Where does the complexity come from? Here are a few causes:
To reduce heat loss and allow renewable sources, heating grids will need to run at lower temperatures without exceeding flow and pressure limits.
Systems that generate heat from various sources distributed across the network are more difficult to operate.
More sophisticated energy storage solutions will boost network flexibility, but also increase complexity.
System integrations with industry, electricity, and cooling networks will generate even more interdependencies.
What can district heating leaders do today to remain in control during uncertain operational conditions?
In this and the next article, we present four practical measures for addressing system complexity shared by the leaders of District Heating companies in the Nordics.
Best practice 1: Prevent system complexity from driving costs
As system complexity grows, district heating companies will be forced to handle more uncertainty about whether the system performs as predicted and maintains supply security. Many companies decide to use safety margins during their operations to be sure they're in control. However, this brings in issues such as having too much capacity on various aspects: too large pipes, too much pumping capacity, or too high temperatures across the network.
How can leaders control costs while managing system complexity? Here are three approaches:
Creating a realistic and dynamic model of the entire heating system - by simulating a longer time rather than a "snapshot" of a peak or baseload condition, companies gain a better chance of knowing when and how frequently a given issue occurs.
Using historical system operation for building models during expansions - instead of relying on the "theoretical" historic parameter model dating to when the system was created, companies should use existing system data from sensors, heat sources, and smart meters.
Considering the future control systems carefully - peak requirements often determine the cost and size of systems, but a smart approach to shaving peaks is using dedicated buffers or frontloading the system (temporarily increasing temperatures). It’s worth considering these methods during the design process as they reduce system peak capacity requirements.
Best practice 2: Understand your current system better with digital solutions
Following European regulations, companies have been adding heat meters and other sensors to their networks, and data is perceived as a critical enabler for managing more complex district heating systems.
As more data is collected from the production, network, and substations, it will open the doors to improving the system and its efficiency.
Data coming from a smart meter can give insights into the performance of individual users. Astrid Birnbaum, Director at Høje Taastrup: “Our investments in smart meters have paid off. It allowed us to identify and engage with customers who create unnecessarily high return temperatures.''
Installing smart meters for a steady data flow is, however, just the first step. To extract business value from data and reduce costs or achieve higher levels of decarbonisation, companies need the right tools. That’s especially because large data volumes present two challenges for DH leaders looking to extract value from data:
Data is frequently stored in separate silos: departments, servers, or even machines that are inaccessible to the rest of the organisation.
Data doesn’t immediately lead to business value, so higher levels of automation in data analytics is key for unlocking insights to feed decision-making processes.
Turku Energia - Investing in data to create a deeper understanding of its heating grid
In the past six years, Turku Energia has increased its efficiency by 100 GWh, setting a record for heat losses of less than 7.5% in 2022. The company achieved this thanks to automated meter readings and consolidation of their operations, gaining complete visibility and control over their system.
One thing is certain: district heating systems will become more difficult to develop, manage, and maintain. DH companies can prepare for the new reality by building a greater understanding of their systems even as their complexity increases and using digital solutions to extract value from all the collected data.
We’ll soon share an article with two more tactics for DH leaders looking to solve the growing complexity of their systems.
Are you curious to learn how industry experts are planning for other known certainties, such as increasing fuel pricing volatility or sector coupling?
Read our Market Research Report for practical tips backed up by real-life case studies based on interviews with 17 Nordic district heating leaders.