Two practical steps for digitalising your district heating operations in 2024  

4 min read

Facing the challenge of enhanced operational efficiency, district heating companies are taking their first steps to embrace digitalisation. To ensure digital is not running behind while going through decarbonisation, heating providers can take two practical first steps: leverage their existing data and connect data across teams and tools to build future-proof district heating systems. 

To achieve an efficient day-to-day operation, district heating companies need to develop a new degree of understanding of their current system. Many companies have installed smart heat meters and sensors in their grids and are now facing a wave of data coming from production, networks, and substations. 

However, extracting tangible business value from the data is difficult. Where to get started with your data?  

Gartner’s maturity framework for data analytics shows that it’s a step-by-step approach, where each following step builds on capabilities acquired in the previous one.

Keep reading to discover the two first steps a district heating company can take to get started on its digitalisation journey. 

But first, what does each level mean for a heating company? 

4 levels of digitalisation in district heating 

1. Descriptive analytics 

The first level is descriptive analytics, which provides an opportunity to draw insights from statistical information based on historical data such as exports from in-field IoT devices or SCADA systems. 

2. Diagnostic analytics 

Diagnostic analytics adds sophisticated analytics to descriptive data to discover the cause of specific events, for instance by analysing tens of thousands of smart heat meters. 

3. Predictive analytics  

Predictive analytics uses data, statistical algorithms, models, and machine learning approaches to forecast future events based on past data. Common applications include weather forecasts driving heat demand and temperature estimates for production schedules.  

4. Prescriptive analytics 

The final stage, prescriptive analytics, presents choice alternatives for how to capitalise on a future opportunity (e-sales) or manage future risks regarding operational stability. 

4a. Decision support 

This sublevel enables a company to decide the best course of action to take. It can provide direct advice on the best next step or offer multiple possibilities or scenarios for operation, planning, and maintenance. 

4b. Autopilot 

As systems become more difficult to operate and labour availability shrinks, some form of automated control will play a more important role in helping district heating companies achieve business goals. In this mode, a digital solution controls the heating system for direct optimisation and management. 

For a more detailed overview, check out the DHC+ Report on Digitalisation in DHC Systems to which Gradyent has contributed. 

All of this sounds great, but where do you get started to start unlocking value from your data right now? 

2 practical steps to start your digitalisation journey 

Step 1: Start immediately, from whichever point you’re at

Looking at higher levels of data analytics, such as predictive or prescriptive, might feel intimidating. But just because your heating system isn’t ready for full autopilot mode, it doesn’t mean you should abandon data analytics altogether. 

The best first step to digitalisation is to start with the data you currently have.  

Many district heating leaders mistakenly believe that they require a large amount of data before using it for analysis and decision-making support. Even a small data set from a SCADA system or IoT sensors may give you insights for predicting the future or prescribing what should be done when processed by a modern digital solution.  

As a result, district heating companies may reap the benefits of insights and automation immediately after connecting the agreed-upon list of data and sensor tags to a solution like a Digital Twin.

Step 2: Connect your data to avoid silos 

District heating providers need flexibility in the capacity of their heating systems to store heat in accumulators, networks, and even buildings to balance production and for e-trading in multiple markets.  

However, unconnected tooling and data prevent them from realising the maximum value potential across such scenarios. Traditionally, tools were dedicated to a specific part of the system and were only used by a specific team. However, this results in limited insights into how the entire system is working together. 

It’s in your best interest to start combating fragmentation of insight as soon as possible. Linking data from multiple sensors, systems, and tools across the heating system is essential. Having a comprehensive perspective of the entire grid enables flexibility and the exploration of future scenarios, leading to informed decision-making and effective cost minimisation. 

Wrap up

District heating providers need to start their digitalisation journeys now and operate in parallel to data analytics initiatives by using their existing data and preventing its fragmentation. This is the quickest path to commercial value and the safest choice for building a robust, future-proof district heating system.  

Do you want to discover how industry leaders are planning to address industry trends such as increasing system complexity, rising fuel prices, or sector coupling?  

Read our Market Research Report for actionable advice supported by real-life case studies based on interviews with 17 Nordic district heating leaders.
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